Alert (AA22-277A) Impacket and Exfiltration Tool Used to Steal Sensitive Information from Defense Industrial Base Organization

Summary

Actions to Help Protect Against APT Cyber Activity:

• Enforce multifactor authentication (MFA) on all user accounts.
• Implement network segmentation to separate network segments based on role and functionality.
• Update software, including operating systems, applications, and firmware, on network assets.
• Audit account usage.

From November 2021 through January 2022, the Cybersecurity and Infrastructure Security Agency (CISA) responded to advanced persistent threat (APT) activity on a Defense Industrial Base (DIB) Sector organization’s enterprise network. During incident response activities, CISA uncovered that likely multiple APT groups compromised the organization’s network, and some APT actors had long-term access to the environment. APT actors used an open-source toolkit called Impacket to gain their foothold within the environment and further compromise the network, and also used a custom data exfiltration tool, CovalentStealer, to steal the victim’s sensitive data.

This joint Cybersecurity Advisory (CSA) provides APT actors tactics, techniques, and procedures (TTPs) and indicators of compromise (IOCs) identified during the incident response activities by CISA and a third-party incident response organization. The CSA includes detection and mitigation actions to help organizations detect and prevent related APT activity. CISA, the Federal Bureau of Investigation (FBI), and the National Security Agency (NSA) recommend DIB sector and other critical infrastructure organizations implement the mitigations in this CSA to ensure they are managing and reducing the impact of cyber threats to their networks.

Download the PDF version of this report: pdf, 692 KB

For a downloadable copy of IOCs, see the following files:

Technical Details

Threat Actor Activity

NoteThis advisory uses the MITRE ATT&CK® for Enterprise framework, version 11. See the MITRE ATT&CK Tactics and Techniques section for a table of the APT cyber activity mapped to MITRE ATT&CK for Enterprise framework.

From November 2021 through January 2022, CISA conducted an incident response engagement on a DIB Sector organization’s enterprise network. The victim organization also engaged a third-party incident response organization for assistance. During incident response activities, CISA and the trusted –third-party identified APT activity on the victim’s network.

Some APT actors gained initial access to the organization’s Microsoft Exchange Server as early as mid-January 2021. The initial access vector is unknown. Based on log analysis, the actors gathered information about the exchange environment and performed mailbox searches within a four-hour period after gaining access. In the same period, these actors used a compromised administrator account (“Admin 1”) to access the EWS Application Programming Interface (API). In early February 2021, the actors returned to the network and used Admin 1 to access EWS API again. In both instances, the actors used a virtual private network (VPN).

Four days later, the APT actors used Windows Command Shell over a three-day period to interact with the victim’s network. The actors used Command Shell to learn about the organization’s environment and to collect sensitive data, including sensitive contract-related information from shared drives, for eventual exfiltration. The actors manually collected files using the command-line tool, WinRAR. These files were split into approximately 3MB chunks located on the Microsoft Exchange server within the CU2\he\debug directory. See Appendix: Windows Command Shell Activity for additional information, including specific commands used.

During the same period, APT actors implanted Impacket, a Python toolkit for programmatically constructing and manipulating network protocols, on another system. The actors used Impacket to attempt to move laterally to another system.

In early March 2021, APT actors exploited CVE-2021-26855, CVE-2021-26857, CVE-2021-26858, and CVE-2021-27065 to install 17 China Chopper webshells on the Exchange Server. Later in March, APT actors installed HyperBro on the Exchange Server and two other systems. For more information on the HyperBro and webshell samples, see CISA MAR-10365227-2 and -3.

In April 2021, APT actors used Impacket for network exploitation activities. See the Use of Impacket section for additional information. From late July through mid-October 2021, APT actors employed a custom exfiltration tool, CovalentStealer, to exfiltrate the remaining sensitive files. See the Use of Custom Exfiltration Tool: CovalentStealer section for additional information.

APT actors maintained access through mid-January 2022, likely by relying on legitimate credentials.

Use of Impacket

CISA discovered activity indicating the use of two Impacket tools: wmiexec.py and smbexec.py. These tools use Windows Management Instrumentation (WMI) and Server Message Block (SMB) protocol, respectively, for creating a semi-interactive shell with the target device. Through the Command Shell, an Impacket user with credentials can run commands on the remote device using the Windows management protocols required to support an enterprise network.

The APT cyber actors used existing, compromised credentials with Impacket to access a higher privileged service account used by the organization’s multifunctional devices. The threat actors first used the service account to remotely access the organization’s Microsoft Exchange server via Outlook Web Access (OWA) from multiple external IP addresses; shortly afterwards, the actors assigned the Application Impersonation role to the service account by running the following PowerShell command for managing Exchange:

powershell add-pssnapin *exchange*;New-ManagementRoleAssignment – name:”Journaling-Logs” -Role:ApplicationImpersonation -User:<account>

This command gave the service account the ability to access other users’ mailboxes.

The APT cyber actors used virtual private network (VPN) and virtual private server (VPS) providers, M247 and SurfShark, as part of their techniques to remotely access the Microsoft Exchange server. Use of these hosting providers, which serves to conceal interaction with victim networks, are common for these threat actors. According to CISA’s analysis of the victim’s Microsoft Exchange server Internet Information Services (IIS) logs, the actors used the account of a former employee to access the EWS. EWS enables access to mailbox items such as email messages, meetings, and contacts. The source IP address for these connections is mostly from the VPS hosting provider, M247.

Use of Custom Exfiltration Tool: CovalentStealer

The threat actors employed a custom exfiltration tool, CovalentStealer, to exfiltrate sensitive files.

CovalentStealer is designed to identify file shares on a system, categorize the files, and upload the files to a remote server. CovalentStealer includes two configurations that specifically target the victim’s documents using predetermined files paths and user credentials. CovalentStealer stores the collected files on a Microsoft OneDrive cloud folder, includes a configuration file to specify the types of files to collect at specified times and uses a 256-bit AES key for encryption. See CISA MAR-10365227-1 for additional technical details, including IOCs and detection signatures.

MITRE ATT&CK Tactics and Techniques

MITRE ATT&CK is a globally accessible knowledge base of adversary tactics and techniques based on real-world observations. CISA uses the ATT&CK Framework as a foundation for the development of specific threat models and methodologies. Table 1 lists the ATT&CK techniques employed by the APT actors.

Initial Access
Technique TitleIDUse
Valid AccountsT1078Actors obtained and abused credentials of existing accounts as a means of gaining Initial Access, Persistence, Privilege Escalation, or Defense Evasion. In this case, they exploited an organization’s multifunctional device domain account used to access the organization’s Microsoft Exchange server via OWA.
Execution
Technique TitleIDUse
Windows Management InstrumentationT1047Actors used Impacket tools wmiexec.py and smbexec.py to leverage Windows Management Instrumentation and execute malicious commands.
Command and Scripting InterpreterT1059Actors abused command and script interpreters to execute commands.
Command and Scripting Interpreter: PowerShellT1059.001Actors abused PowerShell commands and scripts to map shared drives by specifying a path to one location and retrieving the items from another. See Appendix: Windows Command Shell Activity for additional information.
Command and Scripting Interpreter: Windows Command ShellT1059.003Actors abused the Windows Command Shell to learn about the organization’s environment and to collect sensitive data. See Appendix: Windows Command Shell Activity for additional information, including specific commands used.The actors used Impacket tools, which enable a user with credentials to run commands on the remote device through the Command Shell.
Command and Scripting Interpreter: PythonT1059.006The actors used two Impacket tools: wmiexec.py and smbexec.py.
Shared ModulesT1129Actors executed malicious payloads via loading shared modules. The Windows module loader can be instructed to load DLLs from arbitrary local paths and arbitrary Universal Naming Convention (UNC) network paths.
System ServicesT1569Actors abused system services to execute commands or programs on the victim’s network.
Persistence
Technique TitleIDUse
Valid AccountsT1078Actors obtained and abused credentials of existing accounts as a means of gaining Initial Access, Persistence, Privilege Escalation, or Defense Evasion.
Create or Modify System ProcessT1543Actors were observed creating or modifying system processes.
Privilege Escalation
Technique TitleIDUse
Valid AccountsT1078Actors obtained and abused credentials of existing accounts as a means of gaining Initial Access, Persistence, Privilege Escalation, or Defense Evasion. In this case, they exploited an organization’s multifunctional device domain account used to access the organization’s Microsoft Exchange server via OWA.
Defense Evasion
Technique TitleIDUse
Masquerading: Match Legitimate Name or LocationT1036.005Actors masqueraded the archive utility WinRAR.exe by renaming it VMware.exe to evade defenses and observation.
Indicator Removal on HostT1070Actors deleted or modified artifacts generated on a host system to remove evidence of their presence or hinder defenses.
Indicator Removal on Host: File DeletionT1070.004Actors used the del.exe command with the /f parameter to force the deletion of read-only files with the *.rar and tempg* wildcards.
Valid AccountsT1078Actors obtained and abused credentials of existing accounts as a means of gaining Initial Access, Persistence, Privilege Escalation, or Defense Evasion. In this case, they exploited an organization’s multifunctional device domain account used to access the organization’s Microsoft Exchange server via OWA.
Virtualization/Sandbox Evasion: System ChecksT1497.001Actors used Windows command shell commands to detect and avoid virtualization and analysis environments. See Appendix: Windows Command Shell Activity for additional information.
Impair Defenses: Disable or Modify ToolsT1562.001Actors used the taskkill command to probably disable security features. CISA was unable to determine which application was associated with the Process ID.
Hijack Execution FlowT1574Actors were observed using hijack execution flow.
Discovery
Technique TitleIDUse
System Network Configuration DiscoveryT1016Actors used the systeminfo command to look for details about the network configurations and settings and determine if the system was a VMware virtual machine.The threat actor used route print to display the entries in the local IP routing table.
System Network Configuration Discovery: Internet Connection DiscoveryT1016.001Actors checked for internet connectivity on compromised systems. This may be performed during automated discovery and can be accomplished in numerous ways.
System Owner/User DiscoveryT1033Actors attempted to identify the primary user, currently logged in user, set of users that commonly use a system, or whether a user is actively using the system.
System Network Connections DiscoveryT1049Actors used the netstat command to display TCP connections, prevent hostname determination of foreign IP addresses, and specify the protocol for TCP.
Process DiscoveryT1057Actors used the tasklist command to get information about running processes on a system and determine if the system was a VMware virtual machine.The actors used tasklist.exe and find.exe to display a list of applications and services with their PIDs for all tasks running on the computer matching the string “powers.”
System Information DiscoveryT1082Actors used the ipconfig command to get detailed information about the operating system and hardware and determine if the system was a VMware virtual machine.
File and Directory DiscoveryT1083Actors enumerated files and directories or may search in specific locations of a host or network share for certain information within a file system.
Virtualization/Sandbox Evasion: System ChecksT1497.001Actors used Windows command shellcommands to detect and avoid virtualization and analysis environments.
Lateral Movement
Technique TitleIDUse
Remote Services: SMB/Windows Admin SharesT1021.002Actors used Valid Accounts to interact with a remote network share using Server Message Block (SMB) and then perform actions as the logged-on user.
Collection
Technique TitleIDUse
Archive Collected Data: Archive via UtilityT1560.001Actor used PowerShell commands and WinRAR to compress and/or encrypt collected data prior to exfiltration.
Data from Network Shared DriveT1039Actors likely used net share command to display information about shared resources on the local computer and decide which directories to exploit, the powershell dircommand to map shared drives to a specified path and retrieve items from another, and the ntfsinfo command to search network shares on computers they have compromised to find files of interest.The actors used dir.exe to display a list of a directory’s files and subdirectories matching a certain text string.
Data Staged: Remote Data StagingT1074.002The actors split collected files into approximately
3 MB chunks located on the Exchange server within the CU2\he\debug directory.
Command and Control
Technique TitleIDUse
Non-Application Layer ProtocolT1095Actors used a non-application layer protocol for communication between host and Command and Control (C2) server or among infected hosts within a network.
Ingress Tool TransferT1105Actors used the certutil command with three switches to test if they could download files from the internet.The actors employed CovalentStealer to exfiltrate the files.
ProxyT1090Actors are known to use VPN and VPS providers, namely M247 and SurfShark, as part of their techniques to access a network remotely.
Exfiltration
Technique TitleIDUse
Schedule TransferT1029Actors scheduled data exfiltration to be performed only at certain times of day or at certain intervals and blend traffic patterns with normal activity.
Exfiltration Over Web Service: Exfiltration to Cloud StorageT1567.002The actor’s CovalentStealer tool stores collected files on a Microsoft OneDrive cloud folder.

DETECTION

Given the actors’ demonstrated capability to maintain persistent, long-term access in compromised enterprise environments, CISA, FBI, and NSA encourage organizations to:

  • Monitor logs for connections from unusual VPSs and VPNs. Examine connection logs for access from unexpected ranges, particularly from machines hosted by SurfShark and M247.
  • Monitor for suspicious account use (e.g., inappropriate or unauthorized use of administrator accounts, service accounts, or third-party accounts). To detect use of compromised credentials in combination with a VPS, follow the steps below:
    • Review logs for “impossible logins,” such as logins with changing username, user agent strings, and IP address combinations or logins where IP addresses do not align to the expected user’s geographic location.
    • Search for “impossible travel,” which occurs when a user logs in from multiple IP addresses that are a significant geographic distance apart (i.e., a person could not realistically travel between the geographic locations of the two IP addresses in the time between logins). Note: This detection opportunity can result in false positives if legitimate users apply VPN solutions before connecting to networks.
    • Search for one IP used across multiple accounts, excluding expected logins.
      • Take note of any M247-associated IP addresses used along with VPN providers (e.g., SurfShark). Look for successful remote logins (e.g., VPN, OWA) for IPs coming from M247- or using SurfShark-registered IP addresses.
    • Identify suspicious privileged account use after resetting passwords or applying user account mitigations.
    • Search for unusual activity in typically dormant accounts.
    • Search for unusual user agent strings, such as strings not typically associated with normal user activity, which may indicate bot activity.
  • Review the YARA rules provided in MAR-10365227-1 to assist in determining whether malicious activity has been observed.
  • Monitor for the installation of unauthorized software, including Remote Server Administration Tools (e.g., psexec, RdClient, VNC, and ScreenConnect).
  • Monitor for anomalous and known malicious command-line use. See Appendix: Windows Command Shell Activity for commands used by the actors to interact with the victim’s environment.
  • Monitor for unauthorized changes to user accounts (e.g., creation, permission changes, and enabling a previously disabled account).

CONTAINMENT AND REMEDIATION

Organizations affected by active or recently active threat actors in their environment can take the following initial steps to aid in eviction efforts and prevent re-entry:

  • Report the incident. Report the incident to U.S. Government authorities and follow your organization’s incident response plan.
  • Reset all login accounts. Reset all accounts used for authentication since it is possible that the threat actors have additional stolen credentials. Password resets should also include accounts outside of Microsoft Active Directory, such as network infrastructure devices and other non-domain joined devices (e.g., IoT devices).
  • Monitor SIEM logs and build detections. Create signatures based on the threat actor TTPs and use these signatures to monitor security logs for any signs of threat actor re-entry.
  • Enforce MFA on all user accounts. Enforce phishing-resistant MFA on all accounts without exception to the greatest extent possible.
  • Follow Microsoft’s security guidance for Active DirectoryBest Practices for Securing Active Directory.
  • Audit accounts and permissions. Audit all accounts to ensure all unused accounts are disabled or removed and active accounts do not have excessive privileges. Monitor SIEM logs for any changes to accounts, such as permission changes or enabling a previously disabled account, as this might indicate a threat actor using these accounts.
  • Harden and monitor PowerShell by reviewing guidance in the joint Cybersecurity Information Sheet—Keeping PowerShell: Security Measures to Use and Embrace.

Mitigations

Mitigation recommendations are usually longer-term efforts that take place before a compromise as part of risk management efforts, or after the threat actors have been evicted from the environment and the immediate response actions are complete. While some may be tailored to the TTPs used by the threat actor, recovery recommendations are largely general best practices and industry standards aimed at bolstering overall cybersecurity posture.

Segment Networks Based on Function

  • Implement network segmentation to separate network segments based on role and functionality. Proper network segmentation significantly reduces the ability for ransomware and other threat actor lateral movement by controlling traffic flows between—and access to—various subnetworks. (See CISA’s Infographic on Layering Network Security Through Segmentation and NSA’s Segment Networks and Deploy Application-Aware Defenses.)
  • Isolate similar systems and implement micro-segmentation with granular access and policy restrictions to modernize cybersecurity and adopt Zero Trust (ZT) principles for both network perimeter and internal devices. Logical and physical segmentation are critical to limiting and preventing lateral movement, privilege escalation, and exfiltration.

Manage Vulnerabilities and Configurations

  • Update softwareincluding operating systemsapplicationsand firmwareon network assets. Prioritize patching known exploited vulnerabilities and critical and high vulnerabilities that allow for remote code execution or denial-of-service on internet-facing equipment.
  • Implement a configuration change control process that securely creates device configuration backups to detect unauthorized modifications. When a configuration change is needed, document the change, and include the authorization, purpose, and mission justification. Periodically verify that modifications have not been applied by comparing current device configurations with the most recent backups. If suspicious changes are observed, verify the change was authorized.

Search for Anomalous Behavior

  • Use cybersecurity visibility and analytics tools to improve detection of anomalous behavior and enable dynamic changes to policy and other response actions. Visibility tools include network monitoring tools and host-based logs and monitoring tools, such as an endpoint detection and response (EDR) tool. EDR tools are particularly useful for detecting lateral connections as they have insight into common and uncommon network connections for each host.
  • Monitor the use of scripting languages (e.g., Python, Powershell) by authorized and unauthorized users. Anomalous use by either group may be indicative of malicious activity, intentional or otherwise.

Restrict and Secure Use of Remote Admin Tools

  • Limit the number of remote access tools as well as who and what can be accessed using them. Reducing the number of remote admin tools and their allowed access will increase visibility of unauthorized use of these tools.
  • Use encrypted services to protect network communications and disable all clear text administration services(e.g., Telnet, HTTP, FTP, SNMP 1/2c). This ensures that sensitive information cannot be easily obtained by a threat actor capturing network traffic.

Implement a Mandatory Access Control Model

  • Implement stringent access controls to sensitive data and resources. Access should be restricted to those users who require access and to the minimal level of access needed.

Audit Account Usage

  • Monitor VPN logins to look for suspicious access (e.g., logins from unusual geo locations, remote logins from accounts not normally used for remote access, concurrent logins for the same account from different locations, unusual times of the day).
  • Closely monitor the use of administrative accounts. Admin accounts should be used sparingly and only when necessary, such as installing new software or patches. Any use of admin accounts should be reviewed to determine if the activity is legitimate.
  • Ensure standard user accounts do not have elevated privileges Any attempt to increase permissions on standard user accounts should be investigated as a potential compromise.

VALIDATE SECURITY CONTROLS

In addition to applying mitigations, CISA, FBI, and NSA recommend exercising, testing, and validating your organization’s security program against threat behaviors mapped to the MITRE ATT&CK for Enterprise framework in this advisory. CISA, FBI, and NSA recommend testing your existing security controls inventory to assess how they perform against the ATT&CK techniques described in this advisory.

To get started:

  1. Select an ATT&CK technique described in this advisory (see Table 1).
  2. Align your security technologies against the technique.
  3. Test your technologies against the technique.
  4. Analyze the performance of your detection and prevention technologies.
  5. Repeat the process for all security technologies to obtain a set of comprehensive performance data.
  6. Tune your security program, including people, processes, and technologies, based on the data generated by this process.

CISA, FBI, and NSA recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&CK techniques identified in this advisory.

RESOURCES

CISA offers several no-cost scanning and testing services to help organizations reduce their exposure to threats by taking a proactive approach to mitigating attack vectors. See cisa.gov/cyber-hygiene-services.

U.S. DIB sector organizations may consider signing up for the NSA Cybersecurity Collaboration Center’s DIB Cybersecurity Service Offerings, including Protective Domain Name System (PDNS) services, vulnerability scanning, and threat intelligence collaboration for eligible organizations. For more information on how to enroll in these services, email dib_defense@cyber.nsa.gov.

ACKNOWLEDGEMENTS

CISA, FBI, and NSA acknowledge Mandiant for its contributions to this CSA.

APPENDIX: WINDOWS COMMAND SHELL ACTIVITY

Over a three-day period in February 2021, APT cyber actors used Windows Command Shell to interact with the victim’s environment. When interacting with the victim’s system and executing commands, the threat actors used /q and /c parameters to turn the echo off, carry out the command specified by a string, and stop its execution once completed.

On the first day, the threat actors consecutively executed many commands within the Windows Command Shell to learn about the organization’s environment and to collect sensitive data for eventual exfiltration (see Table 2).

CommandDescription / Use
net shareUsed to create, configure, and delete network shares from the command-line.[1] The threat actor likely used this command to display information about shared resources on the local computer and decide which directories to exploit.
powershell dirAn alias (shorthand) for the PowerShell Get-ChildItem cmdlet. This command maps shared drives by specifying a path to one location and retrieving the items from another.[2] The threat actor added additional switches (aka options, parameters, or flags) to form a “one liner,” an expression to describe commonly used commands used in exploitation: powershell dir -recurse -path e:\<redacted>|select fullname,length|export-csv c:\windows\temp\temp.txt. This particular command lists subdirectories of the target environment when.
systeminfoDisplays detailed configuration information [3], tasklist – lists currently running processes [4], and ipconfig – displays all current Transmission Control Protocol (TCP)/IP network configuration values and refreshes Dynamic Host Configuration Protocol (DHCP) and Domain Name System (DNS) settings, respectively [5]. The threat actor used these commands with specific switches to determine if the system was a VMware virtual machine: systeminfo > vmware & date /T, tasklist /v > vmware & date /T, and ipconfig /all >> vmware & date /.
route printUsed to display and modify the entries in the local IP routing table. [6] The threat actor used this command to display the entries in the local IP routing table.
netstatUsed to display active TCP connections, ports on which the computer is listening, Ethernet statistics, the IP routing table, IPv4 statistics, and IPv6 statistics.[7] The threat actor used this command with three switches to display TCP connections, prevent hostname determination of foreign IP addresses, and specify the protocol for TCP: netstat -anp tcp.
certutilUsed to dump and display certification authority (CA) configuration information, configure Certificate Services, backup and restore CA components, and verify certificates, key pairs, and certificate chains.[8] The threat actor used this command with three switches to test if they could download files from the internet: certutil -urlcache -split -f https://microsoft.com temp.html.
pingSends Internet Control Message Protocol (ICMP) echoes to verify connectivity to another TCP/IP computer.[9] The threat actor used ping -n 2 apple.com to either test their internet connection or to detect and avoid virtualization and analysis environments or network restrictions.
taskkillUsed to end tasks or processes.[10] The threat actor used taskkill /F /PID 8952 to probably disable security features. CISA was unable to determine what this process was as the process identifier (PID) numbers are dynamic.
PowerShell Compress-Archive cmdletUsed to create a compressed archive or to zip files from specified files and directories.[11] The threat actor used parameters indicating shared drives as file and folder sources and the destination archive as zipped files. Specifically, they collected sensitive contract-related information from the shared drives.

On the second day, the APT cyber actors executed the commands in Table 3 to perform discovery as well as collect and archive data.

CommandDescription / Use
ntfsinfo.exeUsed to obtain volume information from the New Technology File System (NTFS) and to print it along with a directory dump of NTFS meta-data files.[12]
WinRAR.exeUsed to compress files and subsequently masqueraded WinRAR.exe by renaming it VMware.exe.[13]

On the third day, the APT cyber actors returned to the organization’s network and executed the commands in Table 4.

CommandDescription / Use
powershell -ep bypass import-module .\vmware.ps1;export-mft -volume eThreat actors ran a PowerShell command with parameters to change the execution mode and bypass the Execution Policy to run the script from PowerShell and add a module to the current section: powershell -ep bypass import-module .\vmware.ps1;export-mft -volume e. This module appears to acquire and export the Master File Table (MFT) for volume E for further analysis by the cyber actor.[14]
set.exeUsed to display the current environment variable settings.[15] (An environment variable is a dynamic value pointing to system or user environments (folders) of the system. System environment variables are defined by the system and used globally by all users, while user environment variables are only used by the user who declared that variable and they override the system environment variables (even if the variables are named the same).
dir.exeUsed to display a list of a directory’s files and subdirectories matching the eagx* text string, likely to confirm the existence of such file.
tasklist.exe and find.exeUsed to display a list of applications and services with their PIDs for all tasks running on the computer matching the string “powers”.[16][17][18]
ping.exeUsed to send two ICMP echos to amazon.com. This could have been to detect or avoid virtualization and analysis environments, circumvent network restrictions, or test their internet connection.[19]
del.exe with the /f parameterUsed to force the deletion of read-only files with the *.rar and tempg* wildcards.[20]

References

[1] Microsoft Net Share

[2] Microsoft Get-ChildItem

[3] Microsoft systeminfo

[4] Microsoft tasklist

[5] Microsoft ipconfig

[6] Microsoft Route

[7] Microsoft netstat

[8] Microsoft certutil

[9] Microsoft ping

[10] Microsoft taskkill

[11] Microsoft Compress-Archive

[12] NTFSInfo v1.2

[13] rarlab

[14] Microsoft Import-Module

[15] Microsoft set (environment variable)

[16] Microsoft tasklist

[17] Mitre ATT&CK – Sofware: TaskList

[18] Microsoft find

[19] Microsoft ping

[20] Microsoft del

Revisions

October 4, 2022: Initial version

Source :
https://www.cisa.gov/uscert/ncas/alerts/aa22-277a

Why Continuous Security Testing is a Must for Organizations Today

The global cybersecurity market is flourishing. Experts at Gartner predict that the end-user spending for the information security and risk management market will grow from $172.5 billion in 2022 to $267.3 billion in 2026.

One big area of spending includes the art of putting cybersecurity defenses under pressure, commonly known as security testing. MarketsandMarkets forecasts the global penetration testing (pentesting) market size is expected to grow at a Compound Annual Growth Rate (CAGR) of 13.7% from 2022 to 2027. However, the costs and limitations involved in carrying out a penetration test are already hindering the market growth, and consequently, many cybersecurity professionals are making moves to find an alternative solution.

Pentests aren’t solving cybersecurity pain points

Pentesting can serve specific and important purposes for businesses. For example, prospective customers may ask for the results of one as proof of compliance. However, for certain challenges, this type of security testing methodology isn’t always the best fit.

1 — Continuously changing environments

Securing constantly changing environments within rapidly evolving threat landscapes is particularly difficult. This challenge becomes even more complicated when aligning and managing the business risk of new projects or releases. Since penetration tests focus on one moment in time, the result won’t necessarily be the same the next time you make an update.

2 — Rapid growth

It would be unusual for fast-growing businesses not to experience growing pains. For CISOs, maintaining visibility of their organization’s expanding attack surface can be particularly painful.

According to HelpNetSecurity, 45% of respondents conduct pentests only once or twice per year and 27% do it once per quarter, which is woefully insufficient given how quickly infrastructure and applications change.

3 — Cybersecurity skills shortages

As well as limitations in budgets and resources, finding the available skillsets for internal cybersecurity teams is an ongoing battle. As a result, organizations don’t have the dexterity to spot and promptly remediate specific security vulnerabilities.

While pentests can offer an outsider perspective, often it is just one person performing the test. For some organizations, there is also an issue on trust when relying on the work of just one or two people. Sándor Incze, CISO at CM.com, gives his perspective:

“Not all pentesters are equal. It’s very hard to determine if the pentester you’re hiring is good.”

4 — Cyber threats are evolving

The constant struggle to stay up to date with the latest cyberattack techniques and trends puts media organizations at risk. Hiring specialist skills for every new cyber threat type would be unrealistic and unsustainable.

HelpNetSecurity reported that it takes 71 percent of pentesters one week to one month to conduct a pentest. Then, more than 26 percent of organizations must wait between one to two weeks to get the test results, and 13 percent wait even longer than that. Given the fast pace of threat evolution, this waiting period can leave companies unaware of potential security issues and open to exploitation.

5 — Poor-fitting security testing solutions for agile environments

Continuous development lifecycles don’t align with penetration testing cycles (often performed annually.) Therefore, vulnerabilities mistakenly created during long security testing gaps can remain undiscovered for some time.

Bringing security testing into the 21st-century Impact

Cybersecurity Testing

A proven solution to these challenges is to utilize ethical hacker communities in addition to a standard penetration test. Businesses can rely on the power of these crowds to assist them in their security testing on a continuous basis. A bug bounty program is one of the most common ways to work with ethical hacker communities.

What is a bug bounty program?

Bug bounty programs allow businesses to proactively work with independent security researchers to report bugs through incentivization. Often companies will launch and manage their program through a bug bounty platform, such as Intigriti.

Organizations with high-security maturity may leave their bug bounty program open for all ethical hackers in the platform’s community to contribute to (known as a public program.) However, most businesses begin by working with a smaller pool of security talent through a private program.

How bug bounty programs support continuous security testing structures

While you’ll receive a certificate to say you’re secure at the end of a penetration test, it won’t necessarily mean that’s still the case the next time you make an update. This is where bug bounty programs work well as a follow-up to pentests and enable a continuous security testing program.

The impact of bug bounty program on cybersecurity

By launching a bug bounty program, organizations experience:

  1. More robust protection: Company data, brand, and reputation have additional protection through continuous security testing.
  2. Enabled business goals: Enhanced security posture, leading to a more secure platform for innovation and growth.
  3. Improved productivity: Increased workflow with fewer disruptions to the availability of services. More strategic IT projects that executives have prioritized, with fewer security “fires” to put out.
  4. Increased skills availability: Internal security team’s time is freed by using a community for security testing and triage.
  5. Clearer budget justification: Ability to provide more significant insights into the organization’s security posture to justify and motivate for an adequate security budget.
  6. Improved relationships: Project delays significantly decrease without the reliance on traditional pentests.

Want to know more about setting up and launching a bug bounty program?

Intigriti is the leading European-based platform for bug bounty and ethical hacking. The platform enables organizations to reduce the risk of a cyberattack by allowing Intigriti’s network of security researchers to test their digital assets for vulnerabilities continuously.

If you’re intrigued by what you’ve read and want to know about bug bounty programs, simply schedule a meeting today with one of our experts.

www.intigriti.com

Source :
https://thehackernews.com/2022/09/why-continuous-security-testing-is-must.html

Record DDoS Attack with 25.3 Billion Requests Abused HTTP/2 Multiplexing

Cybersecurity company Imperva has disclosed that it mitigated a distributed denial-of-service (DDoS) attack with a total of over 25.3 billion requests on June 27, 2022.

The “strong attack,” which targeted an unnamed Chinese telecommunications company, is said to have lasted for four hours and peaked at 3.9 million requests per second (RPS).

“Attackers used HTTP/2 multiplexing, or combining multiple packets into one, to send multiple requests at once over individual connections,” Imperva said in a report published on September 19.

The attack was launched from a botnet that comprised nearly 170,000 different IP addresses spanning routers, security cameras, and compromised servers located in more than 180 countries, primarily the U.S., Indonesia, and Brazil.

CyberSecurity

The disclosure also comes as web infrastructure provider Akamai said it fielded a new DDoS assault aimed at a customer based in Eastern Europe on September 12, with attack traffic spiking at 704.8 million packets per second (pps).

The same victim was previously targeted on July 21, 2022, in a similar fashion in which the attack volume ramped up to 853.7 gigabits per second (Gbps) and 659.6 million pps over a period of 14 hours.

Akamai’s Craig Sparling said the company has been “bombarded relentlessly with sophisticated distributed denial-of-service (DDoS) attacks,” indicating that the offensives could be politically motivated in the face of Russia’s ongoing war against Ukraine.

Both the disruptive attempts were UDP flood attacks where the attacker targets and overwhelms arbitrary ports on the target host with User Datagram Protocol (UDP) packets.

CyberSecurity

UDP, being both connectionless and session-less, makes it an ideal networking protocol for handling VoIP traffic. But these same traits can also render it more susceptible to exploitation.

“Without an initial handshake to ensure a legitimate connection, UDP channels can be used to send a large volume of traffic to any host,” NETSCOUT says.

“There are no internal protections that can limit the rate of a UDP flood. As a result, UDP flood DoS attacks are exceptionally dangerous because they can be executed with a limited amount of resources.”

Source :
https://thehackernews.com/2022/09/record-ddos-attack-with-253-billion.html

Hackers Exploited Zero-Day RCE Vulnerability in Sophos Firewall — Patch Released

Security software company Sophos has released a patch update for its firewall product after it was discovered that attackers were exploiting a new critical zero-day vulnerability to attack its customers’ network.

The issue, tracked as CVE-2022-3236 (CVSS score: 9.8), impacts Sophos Firewall v19.0 MR1 (19.0.1) and older and concerns a code injection vulnerability in the User Portal and Webadmin components that could result in remote code execution.

The company said it “has observed this vulnerability being used to target a small set of specific organizations, primarily in the South Asia region,” adding it directly notified these entities.

CyberSecurity

As a workaround, Sophos is recommending that users take steps to ensure that the User Portal and Webadmin are not exposed to WAN. Alternatively, users can update to the latest supported version –

  • v19.5 GA
  • v19.0 MR2 (19.0.2)
  • v19.0 GA, MR1, and MR1-1
  • v18.5 MR5 (18.5.5)
  • v18.5 GA, MR1, MR1-1, MR2, MR3, and MR4
  • v18.0 MR3, MR4, MR5, and MR6
  • v17.5 MR12, MR13, MR14, MR15, MR16, and MR17
  • v17.0 MR10

Users running older versions of Sophos Firewall are required to upgrade to receive the latest protections and the relevant fixes.

The development marks the second time a Sophos Firewall vulnerability has come under active attacks within a year. Earlier this March, another flaw (CVE-2022-1040) was used to target organizations in the South Asia region.

CyberSecurity

Then in June 2022, cybersecurity firm Volexity shared more details of the attack campaign, pinning the intrusions on a Chinese advanced persistent threat (APT) known as DriftingCloud.

Sophos firewall appliances have also previously come under attack to deploy what’s called the Asnarök trojan in an attempt to siphon sensitive information.

Source :
https://thehackernews.com/2022/09/hackers-actively-exploiting-new-sophos.html

IT threat evolution in Q2 2022. Mobile statistics

These statistics are based on detection verdicts of Kaspersky products received from users who consented to providing statistical data.

Quarterly figures

According to Kaspersky Security Network, in Q2 2022:

  • 5,520,908 mobile malware, adware and riskware attacks were blocked.
  • The most common threat to mobile devices was adware: 25.28% of all threats detected.
  • 405,684 malicious installation packages were detected, of which:
    • 55,614 packages were related to mobile banking Trojans;
    • 3,821 packages were mobile ransomware Trojans.

Quarterly highlights

In the second quarter of 2022, cybercriminal activity continued to decline — if the number of attacks on mobile devices is any indication.

https://e.infogram.com/_/kUJZ2IuFyVL5rs1NUqoG?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Number of attacks targeting users of Kaspersky mobile solutions, Q1 2020 — Q2 2022 (download)

As in the previous quarter, fraudulent apps occupied seven out of twenty leading positions in the malware rankings. That said, the total number of attacks by these apps started to decrease.

Interestingly enough, some fraudulent app creators were targeting users from several countries at once. For instance, J-Lightning Application purported to help users to invest into a Polish oil refinery, a Russian energy company, a Chinese cryptocurrency exchange and an American investment fund.

On the contrary, the number of attacks by the RiskTool.AndroidOS.SpyLoan riskware family (loan apps that request access to users’ text messages, contact list and photos) more than quadrupled from the first quarter. The majority of users whose devices were found to be infected with this riskware were based in Mexico: a third of the total number of those attacked. This was followed by India and Colombia. The ten most-affected countries include Kenya, Brazil, Peru, Pakistan, Nigeria, Uganda and the Philippines.

The second quarter was also noteworthy for Europol taking down the infrastructure of the FluBot mobile botnet, also known as Polph and Cabassous. This aggressively spreading banking Trojan attacked mainly users in Europe and Australia.

Mobile threat statistics

In Q2 2022, Kaspersky detected 405,684 malicious installation packages, a reduction of 110,933 from the previous quarter and a year-on-year decline of 480,421.

https://e.infogram.com/_/sggcRCeC8v5IMtDdh0MY?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Number of detected malicious installation packages, Q2 2021 — Q2 2022 (download)

Distribution of detected mobile malware by type

https://e.infogram.com/_/xd4vJYpEUtvNfzYvS1xv?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Distribution of newly detected mobile malware by type, Q1 and Q2 2022 (download)

Adware ranked first among all threats detected in Q2 2022 with 25.28%, exceeding the previous quarter’s figure by 8.36 percentage points. A third of all detected threats of that class were objects of the AdWare.AndroidOS.Ewind family (33.21%). This was followed by the AdWare.AndroidOS.Adlo (22.54%) and AdWare.AndroidOS.HiddenAd (8.88%) families.

The previous leader, the RiskTool riskware, moved to second place with 20.81% of all detected threats, a decline of 27.94 p.p. from the previous quarter. More than half (60.16%) of the discovered apps of that type belonged to the Robtes family.

Various Trojans came close behind with 20.49%, a rise of 5.81 p.p. on the previous quarter. The largest contribution was made by objects belonging to the Mobtes (38.75%), Boogr (21.12%) and Agent (18.98%) families.

Top 20 mobile malware programs

Note that the malware rankings below exclude riskware or PUAs, such as RiskTool or adware.

Verdict%*
1DangerousObject.Multi.Generic21.90
2Trojan-SMS.AndroidOS.Fakeapp.d10.71
3Trojan.AndroidOS.Generic10.55
4Trojan.AndroidOS.GriftHorse.ah6.07
5Trojan-Spy.AndroidOS.Agent.aas5.40
6Trojan.AndroidOS.GriftHorse.l3.43
7DangerousObject.AndroidOS.GenericML3.21
8Trojan-Dropper.AndroidOS.Agent.sl2.82
9Trojan.AndroidOS.Fakemoney.d2.33
10Trojan.AndroidOS.Fakeapp.ed1.82
11Trojan.AndroidOS.Fakeapp.dw1.68
12Trojan.AndroidOS.Fakemoney.i1.62
13Trojan.AndroidOS.Soceng.f1.59
14Trojan-Ransom.AndroidOS.Pigetrl.a1.59
15Trojan.AndroidOS.Boogr.gsh1.56
16Trojan-Downloader.AndroidOS.Necro.d1.56
17Trojan-SMS.AndroidOS.Agent.ado1.54
18Trojan-Dropper.AndroidOS.Hqwar.gen1.54
19Trojan.AndroidOS.Fakemoney.n1.52
20Trojan-Downloader.AndroidOS.Agent.kx1.45

* Unique users attacked by this malware as a percentage of all attacked users of Kaspersky mobile solutions.

First and third places went to DangerousObject.Multi.Generic (21.90%) and Trojan.AndroidOS.Generic (10.55%), respectively, which are verdicts we use for malware detected with cloud technology. Cloud technology is triggered whenever the antivirus databases lack data for detecting a piece of malware, but the antivirus company’s cloud already contains information about the object. This is essentially how the latest malware types are detected.

Trojan-SMS.AndroidOS.Fakeapp.d rose from third to second place with 10.71%. This malware is capable of sending text messages and calling predefined numbers, displaying ads and hiding its icon.

Members of the Trojan.AndroidOS.GriftHorse family took fourth and sixth places with 6.07% and 3.43%, respectively. This family includes fraudulent apps that purchase paid subscriptions on the user’s behalf.

Trojan-Spy.AndroidOS.Agent.aas (5.40%), an evil twin of WhatsApp with a spy module built in, retained fifth position.

The verdict of DangerousObject.AndroidOS.GenericML (3.21%) came seventh. These verdicts are assigned to files recognized as malicious by our machine-learning systems.

Trojan-Dropper.AndroidOS.Agent.sl (2.82%), a dropper that unpacks and runs a banking Trojan on devices, remained in eighth place. Most of the attacked users were based in Russia or Germany.

Trojan.AndroidOS.Fakemoney.d slid from second to ninth place with 2.33%. Other members of the family occupied twelfth and nineteenth places in the rankings. These are fraudulent apps that offer users to fill out fake welfare applications.

Trojan.AndroidOS.Fakeapp.ed dropped to tenth place from sixth with 1.82%; this verdict covers fraudulent apps purporting to help with investing in gas utilities and mostly targeting Russian users.

Trojan.AndroidOS.Fakeapp.dw dropped from tenth place to eleventh with 1.68%. This verdict is assigned to various scammer apps, for example, those offering to make extra income.

Trojan.AndroidOS.Soceng.f (1.59%) dropped from twelfth to thirteenth place. This Trojan sends text messages to people in your contacts list, deletes files on the user’s SD card, and overlays the interfaces of popular apps with its own window.

Trojan-Ransom.AndroidOS.Pigetrl.a dropped from eleventh to fourteenth place with 1.59%. This malware locks the screen, asking to enter an unlock code. The Trojan provides no instructions on how to obtain this code, which is embedded in the body of the malware.

The verdict of Trojan.AndroidOS.Boogr.gsh occupied fifteenth place with 1.56%. Like DangerousObject.AndroidOS.GenericML, this verdict is produced by a machine learning system.

Trojan-Downloader.AndroidOS.Necro.d (1.56%), designed for downloading and running other malware on infected devices, climbed to sixteenth place from seventeenth.

Trojan-SMS.AndroidOS.Agent.ado dropped from fifteenth to seventeenth place with 1.54%. This malware sends text messages to short codes.

Trojan-Dropper.AndroidOS.Hqwar.gen, which unpacks and runs various banking Trojans on a device, kept eighteenth place with 1.54%.

Trojan-Downloader.AndroidOS.Agent.kx (1.45%), which loads adware, dropped to the bottom of the rankings.

Geography of mobile threats

https://e.infogram.com/_/5488dBZS93CY789cAis8?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Map of attempts to infect mobiles with malware, Q2 2022 (download)

TOP 10 countries and territories by share of users attacked by mobile malware

Countries and territories*%**
1Iran26,91
2Yemen17,97
3Saudi Arabia12,63
4Oman12,01
5Algeria11,49
6Egypt10,48
7Morocco7,88
8Kenya7,58
9Ecuador7,19
10Indonesia6,91

* Excluded from the rankings are countries and territories with relatively few (under 10,000) Kaspersky mobile security users.
** Unique users attacked as a percentage of all users of Kaspersky mobile security solutions in the country.

Iran remained the leader in terms of the share of infected devices in Q2 2022 with 26.91%; the most widespread threats there as before were the annoying AdWare.AndroidOS.Notifyer and AdWare.AndroidOS.Fyben families. Yemen rose to second place with 17.97%; the Trojan-Spy.AndroidOS.Agent.aas spyware was the threat most often encountered by users in that country. Saudi Arabia came third with 12.63%, the most common malware apps in the country being the AdWare.AndroidOS.Adlo and AdWare.AndroidOS.Fyben adware families.

Mobile banking Trojans

The number of detected mobile banking Trojan installation packages increased slightly compared to the previous quarter: during the reporting period, we found 55,614 of these, an increase of 1,667 on Q1 2022 and a year-on-year increase of 31,010.

Almost half (49.28%) of the detected installation packages belonged to the Trojan-Banker.AndroidOS.Bray family. The Trojan-Banker.AndroidOS.Wroba was second with 5.54%, and Trojan-Banker.AndroidOS.Fakecalls third with 4.83%.

https://e.infogram.com/_/WmVkKmoCinRxAPQXWFha?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Number of installation packages for mobile banking Trojans detected by Kaspersky, Q2 2021 — Q2 2022 (download)

Ten most common mobile bankers

Verdict%*
1Trojan-Banker.AndroidOS.Bian.h23.22
2Trojan-Banker.AndroidOS.Anubis.t10.48
3Trojan-Banker.AndroidOS.Svpeng.q7.88
4Trojan-Banker.AndroidOS.Asacub.ce4.48
5Trojan-Banker.AndroidOS.Sova.g4.32
6Trojan-Banker.AndroidOS.Gustuff.d4.04
7Trojan-Banker.AndroidOS.Ermak.a4.00
8Trojan-Banker.AndroidOS.Agent.ep3.66
9Trojan-Banker.AndroidOS.Agent.eq3.58
10Trojan-Banker.AndroidOS.Faketoken.z2.51

* Unique users attacked by this malware as a percentage of all Kaspersky mobile security solution users who encountered banking threats.

https://e.infogram.com/_/bawulAIMCMSwfujrqAJT?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Geography of mobile banking threats, Q2 2022 (download)

TOP 10 countries and territories by shares of users attacked by mobile banking Trojans

Countries and territories*%**
1Spain1.04
2Turkey0.71
3Australia0.67
4Saudi Arabia0.64
5Switzerland0.38
6UAE0.23
7Japan0.14
8Colombia0.14
9Italy0.10
10Portugal0.09

* Countries and territories with relatively few users of Kaspersky mobile security solutions (under 10,000) have been excluded from the ranking.
** Unique users attacked by mobile banking Trojans as a percentage of all Kaspersky mobile security solution users in the country.

In Q2 2022, Spain still had the largest share of unique users attacked by mobile financial threats: 1.04%. Trojan-Banker.AndroidOS.Bian.h accounted for 89.95% of attacks on Spanish users. Turkey had the second-largest share (0.71%), with attacks on Turkish users dominated by Trojan-Banker.AndroidOS.Ermak.a (41.38%). Australia was third with 0.67%; most attacks in this country were attributed to Trojan-Banker.AndroidOS.Gustuff.d (96,55%).

Mobile ransomware Trojans

The number of mobile ransomware Trojan installation packages we detected in Q2 2022 (3,821) almost doubled from Q1 2022, increasing by 1,879; the figure represented a year-on-year increase of 198.

https://e.infogram.com/_/qgwrjBbIOWRSVBiw4z6r?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Number of installation packages for mobile ransomware Trojans detected by Kaspersky, Q2 2021 — Q2 2022 (download)

Top 10 most common mobile ransomware

Verdict%*
1Trojan-Ransom.AndroidOS.Pigetrl.a76.81
2Trojan-Ransom.AndroidOS.Rkor.ch2.66
3Trojan-Ransom.AndroidOS.Small.as2.51
4Trojan-Ransom.AndroidOS.Rkor.br1.46
5Trojan-Ransom.AndroidOS.Rkor.bi1.40
6Trojan-Ransom.AndroidOS.Svpeng.ah1.29
7Trojan-Ransom.AndroidOS.Congur.cw1.23
8Trojan-Ransom.AndroidOS.Small.cj1.14
9Trojan-Ransom.AndroidOS.Svpeng.ac1.14
10Trojan-Ransom.AndroidOS.Congur.bf1.07

* Unique users attacked by the malware as a percentage of all Kaspersky mobile security solution users attacked by ransomware Trojans.

https://e.infogram.com/_/fLxtf6iaN8E9XJOQQUsF?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-mobile-statistics%2F107123%2F&src=embed#async_embed

Geography of mobile ransomware Trojans, Q2 2022 (download)

TOP 10 countries and territories by share of users attacked by mobile ransomware Trojans

Countries and territories*%**
1Yemen0,30
2Kazakhstan0,19
3Azerbaijan0,06
4Kyrgyzstan0,04
5Switzerland0,04
6Egypt0,03
7Saudi Arabia0,03
8Uzbekistan0,02
9Russian Federation0,02
10Morocco0,02

* Excluded from the rankings are countries and territories with relatively few (under 10,000) Kaspersky mobile security users.
** Unique users attacked by ransomware Trojans as a percentage of all Kaspersky mobile security solution users in the country or territory.

Countries leading by number of users attacked by mobile ransomware Trojans were Yemen (0.30%), Kazakhstan (0.19%) and Azerbaijan (0.06%). Users in Yemen most often encountered Trojan-Ransom.AndroidOS.Pigetrl.a, while users in Kazakhstan and Azerbaijan were attacked mainly by members of the Trojan-Ransom.AndroidOS.Rkor family.

IT threat evolution in Q2 2022. Non-mobile statistics

These statistics are based on detection verdicts of Kaspersky products and services received from users who consented to providing statistical data.

Quarterly figures

According to Kaspersky Security Network, in Q2 2022:

  • Kaspersky solutions blocked 1,164,544,060 attacks from online resources across the globe.
  • Web Anti-Virus recognized 273,033,368 unique URLs as malicious. Attempts to run malware for stealing money from online bank accounts were stopped on the computers of 100,829 unique users.
  • Ransomware attacks were defeated on the computers of 74,377 unique users.
  • Our File Anti-Virus detected 55,314,176 unique malicious and potentially unwanted objects.

Financial threats

Financial threat statistics

In Q2 2022, Kaspersky solutions blocked the launch of malware designed to steal money from bank accounts on the computers of 100,829 unique users.

https://e.infogram.com/_/xVIqEwzQRE40afesiEuD?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Number of unique users attacked by financial malware, Q2 2022 (download)

Geography of financial malware attacks

To evaluate and compare the risk of being infected by banking Trojans and ATM/POS malware worldwide, for each country and territory we calculated the share of Kaspersky users who faced this threat during the reporting period as a percentage of all users of our products in that country or territory.

https://e.infogram.com/_/VAlc8RYhTGIEk24LI7Q3?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Geography of financial malware attacks, Q2 2022 (download)

TOP 10 countries and territories by share of attacked users

Country or territory*%**
1Turkmenistan4.8
2Afghanistan4.3
3Tajikistan3.8
4Paraguay3.1
5China2.4
6Yemen2.4
7Uzbekistan2.2
8Sudan2.1
9Egypt2.0
10Mauritania1.9

* Excluded are countries and territories with relatively few Kaspersky product users (under 10,000).
** Unique users whose computers were targeted by financial malware as a percentage of all unique users of Kaspersky products in the country.

TOP 10 banking malware families

NameVerdicts%*
1Ramnit/NimnulTrojan-Banker.Win32.Ramnit35.5
2Zbot/ZeusTrojan-Banker.Win32.Zbot15.8
3CliptoShufflerTrojan-Banker.Win32.CliptoShuffler6.4
4Trickster/TrickbotTrojan-Banker.Win32.Trickster6
5RTMTrojan-Banker.Win32.RTM2.7
6SpyEyeTrojan-Spy.Win32.SpyEye2.3
7IcedIDTrojan-Banker.Win32.IcedID2.1
8DanabotTrojan-Banker.Win32.Danabot1.9
9BitStealerTrojan-Banker.Win32.BitStealer1.8
10GoziTrojan-Banker.Win32.Gozi1.3

* Unique users who encountered this malware family as a percentage of all users attacked by financial malware.

Ransomware programs

In the second quarter, the Lockbit group launched a bug bounty program. The cybercriminals are promising $1,000 to $1,000,000 for doxing of senior officials, reporting  web service, Tox messenger or ransomware Trojan algorithm vulnerabilities, as well as for ideas on improving the Lockbit website and Trojan. This was the first-ever case of ransomware groups doing a (self-promotion?) campaign like that.

Another well-known group, Conti, said it was shutting down operations. The announcement followed a high-profile attack on Costa Rica’s information systems, which prompted the government to declare a state of emergency. The Conti infrastructure was shut down in late June, but some in the infosec community believe that Conti members are either just rebranding or have split up and joined other ransomware teams, including Hive, AvosLocker and BlackCat.

While some ransomware groups are drifting into oblivion, others seem to be making a comeback. REvil’s website went back online in April, and researchers discovered a newly built specimen of their Trojan. This might have been a test build, as the sample did not encrypt any files, but these events may herald the impending return of REvil.

Kaspersky researchers found a way to recover files encrypted by the Yanluowang ransomware and released a decryptor for all victims. Yanluowang has been spotted in targeted attacks against large businesses in the US, Brazil, Turkey, and other countries.

Number of new modifications

In Q2 2022, we detected 15 new ransomware families and 2355 new modifications of this malware type.

https://e.infogram.com/_/LLQNUsWe0kQuAyykdQ9p?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Number of new ransomware modifications, Q2 2021 — Q2 2022 (download)

Number of users attacked by ransomware Trojans

In Q2 2022, Kaspersky products and technologies protected 74,377 users from ransomware attacks.

https://e.infogram.com/_/YAmZLBPilFKmsbsxFKpJ?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Number of unique users attacked by ransomware Trojans, Q2 2022 (download)

Geography of attacked users

https://e.infogram.com/_/oDrJKQvRPnVf4zT5I0kp?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Geography of attacks by ransomware Trojans, Q2 2022 (download)

TOP 10 countries and territories attacked by ransomware Trojans

Country or territory*%**
1Bangladesh1.81
2Yemen1.24
3South Korea1.11
4Mozambique0.82
5Taiwan0.70
6China0.46
7Pakistan0.40
8Angola0.37
9Venezuela0.33
10Egypt0.32

* Excluded are countries and territories with relatively few Kaspersky users (under 50,000).
** Unique users whose computers were attacked by Trojan encryptors as a percentage of all unique users of Kaspersky products in the country.

TOP 10 most common families of ransomware Trojans

NameVerdicts*Percentage of attacked users**
1Stop/DjvuTrojan-Ransom.Win32.Stop17.91
2WannaCryTrojan-Ransom.Win32.Wanna12.58
3MagniberTrojan-Ransom.Win64.Magni9.80
4(generic verdict)Trojan-Ransom.Win32.Gen7.91
5(generic verdict)Trojan-Ransom.Win32.Phny6.75
6(generic verdict)Trojan-Ransom.Win32.Encoder6.55
7(generic verdict)Trojan-Ransom.Win32.Crypren3.51
8(generic verdict)Trojan-Ransom.MSIL.Encoder3.02
9PolyRansom/VirLockTrojan-Ransom.Win32.PolyRansom / Virus.Win32.PolyRansom2.96
10(generic verdict)Trojan-Ransom.Win32.Instructions2.69

* Statistics are based on detection verdicts of Kaspersky products. The information was provided by Kaspersky product users who consented to provide statistical data.
** Unique Kaspersky users attacked by specific ransomware Trojan families as a percentage of all unique users attacked by ransomware Trojans.

Miners

Number of new miner modifications

In Q2 2022, Kaspersky solutions detected 40,788 new modifications of miners. A vast majority of these (more than 35,000) were detected in June. Thus, the spring depression — in March through May we found a total of no more than 10,000 new modifications — was followed by a record of sorts.

https://e.infogram.com/_/vZm5Z2G3sFuuIAqZGWRA?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Number of new miner modifications, Q2 2022 (download)

Number of users attacked by miners

In Q2, we detected attacks using miners on the computers of 454,385 unique users of Kaspersky products and services worldwide. We are seeing a reverse trend here: miner attacks have gradually declined since the beginning of 2022.

https://e.infogram.com/_/ibd7ASo3u4ZaWhgBgbcF?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Number of unique users attacked by miners, Q2 2022 (download)

Geography of miner attacks

https://e.infogram.com/_/e5HYDOqPpDYZ08UMSsAM?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Geography of miner attacks, Q2 2022 (download)

TOP 10 countries and territories attacked by miners

Country or territory*%**
1Rwanda2.94
2Ethiopia2.67
3Tajikistan2.35
4Tanzania1.98
5Kyrgyzstan1.94
6Uzbekistan1.88
7Kazakhstan1.84
8Venezuela1.80
9Mozambique1.68
10Ukraine1.56

* Excluded are countries and territories with relatively few users of Kaspersky products (under 50,000).
** Unique users attacked by miners as a percentage of all unique users of Kaspersky products in the country.

Vulnerable applications used by criminals during cyberattacks

Quarterly highlights

During Q2 2022, a number of major vulnerabilities were discovered in the Microsoft Windows. For instance, CVE-2022-26809 critical error allows an attacker to remotely execute arbitrary code in a system using a custom RPC request. The Network File System (NFS) driver was found to contain two RCE vulnerabilities: CVE-2022-24491 and CVE-2022-24497. By sending a custom network message via the NFS protocol, an attacker can remotely execute arbitrary code in the system as well. Both vulnerabilities affect server systems with the NFS role activated. The CVE-2022-24521 vulnerability targeting the Common Log File System (CLFS) driver was found in the wild. It allows elevation of local user privileges, although that requires the attacker to have gained a foothold in the system. CVE-2022-26925, also known as LSA Spoofing, was another vulnerability found during live operation of server systems. It allows an unauthenticated attacker to call an LSARPC interface method and get authenticated by Windows domain controller via the NTLM protocol. These vulnerabilities are an enduring testament to the importance of timely OS and software updates.

Most of the network threats detected in Q2 2022 had been mentioned in previous reports. Most of those were attacks that involved brute-forcing  access to various web services. The most popular protocols and technologies susceptible to these attacks include MS SQL Server, RDP and SMB. Attacks that use the EternalBlue, EternalRomance and similar exploits are still popular. Exploitation of Log4j vulnerability (CVE-2021-44228) is also quite common, as the susceptible Java library is often used in web applications. Besides, the Spring MVC framework, used in many Java-based web applications, was found to contain a new vulnerability CVE-2022-22965 that exploits the data binding functionality and results in remote code execution. Finally, we have observed a rise in attacks that exploit insecure deserialization, which can also result in access to remote systems due to incorrect or missing validation of untrusted user data passed to various applications.

Vulnerability statistics

Exploits targeting Microsoft Office vulnerabilities grew in the second quarter to 82% of the total. Cybercriminals were spreading malicious documents that exploited CVE-2017-11882 and CVE-2018-0802, which are the best-known vulnerabilities in the Equation Editor component. Exploitation involves the component memory being damaged and a specially designed script, run on the target computer. Another vulnerability, CVE-2017-8570, allows downloading and running a malicious script when opening an infected document, to execute various operations in a vulnerable system. The emergence of CVE-2022-30190or Follina vulnerability also increased the number of exploits in this category. An attacker can use a custom malicious document with a link to an external OLE object, and a special URI scheme to have Windows run the MSDT diagnostics tool. This, in turn, combined with a special set of parameters passed to the victim’s computer, can cause an arbitrary command to be executed — even if macros are disabled and the document is opened in Protected Mode.

https://e.infogram.com/_/1dqpsnMqrH26rdzDOOht?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Distribution of exploits used by cybercriminals, by type of attacked application, Q2 2022 (download)

Attempts at exploiting vulnerabilities that affect various script engines and, specifically, browsers, dipped to 5%. In the second quarter, a number of critical RCE vulnerabilities were discovered in various Google Chrome based browsers: CVE-2022-0609CVE-2022-1096, and CVE-2022-1364. The first one was found in the animation component; it exploits a Use-After-Free error, causing memory damage, which is followed by the attacker creating custom objects to execute arbitrary code. The second and third vulnerabilities are Type Confusion errors associated with the V8 script engine; they also can result in arbitrary code being executed on a vulnerable user system. Some of the vulnerabilities discovered were found to have been exploited in targeted attacks, in the wild. Mozilla Firefox was found to contain a high-risk Use-After-Free vulnerability, CVE-2022-1097, which appears when processing NSSToken-type objects from different streams. The browser was also found to contain CVE-2022-28281, a vulnerability that affects the WebAuthn extension. A compromised Firefox content process can write data out of bounds of the parent process memory, thus potentially enabling code execution with elevated privileges. Two further vulnerabilities, CVE-2022-1802 and CVE-2022-1529, were exploited in cybercriminal attacks. The exploitation method, dubbed “prototype pollution”, allows executing arbitrary JavaScript code in the context of a privileged parent browser process.

As in the previous quarter, Android exploits ranked third in our statistics with 4%, followed by exploits of Java applications, the Flash platform, and PDF documents, each with 3%.

Attacks on macOS

The second quarter brought with it a new batch of cross-platform discoveries. For instance, a new APT group Earth Berberoka (GamblingPuppet) that specializes in hacking online casinos, uses malware for Windows, Linux, and macOS. The TraderTraitor campaign targets cryptocurrency and blockchain organizations, attacking with malicious crypto applications for both Windows and macOS.

TOP 20 threats for macOS

Verdict%*
1AdWare.OSX.Amc.e25.61
2AdWare.OSX.Agent.ai12.08
3AdWare.OSX.Pirrit.j7.84
4AdWare.OSX.Pirrit.ac7.58
5AdWare.OSX.Pirrit.o6.48
6Monitor.OSX.HistGrabber.b5.27
7AdWare.OSX.Agent.u4.27
8AdWare.OSX.Bnodlero.at3.99
9Trojan-Downloader.OSX.Shlayer.a3.87
10Downloader.OSX.Agent.k3.67
11AdWare.OSX.Pirrit.aa3.35
12AdWare.OSX.Pirrit.ae3.24
13Backdoor.OSX.Twenbc.e3.16
14AdWare.OSX.Bnodlero.ax3.06
15AdWare.OSX.Agent.q2.73
16Trojan-Downloader.OSX.Agent.h2.52
17AdWare.OSX.Bnodlero.bg2.42
18AdWare.OSX.Cimpli.m2.41
19AdWare.OSX.Pirrit.gen2.08
20AdWare.OSX.Agent.gen2.01

* Unique users who encountered this malware as a percentage of all users of Kaspersky security solutions for macOS who were attacked.

As usual, the TOP 20 ranking for threats detected by Kaspersky security solutions for macOS users is dominated by various adware. AdWare.OSX.Amc.e, also known as Advanced Mac Cleaner, is a newcomer and already a leader, found with a quarter of all attacked users. Members of this family display fake system problem messages, offering to buy the full version to fix those. It was followed by members of the AdWare.OSX.Agent and AdWare.OSX.Pirrit families.

Geography of threats for macOS

https://e.infogram.com/_/sREMxK7Q3GvfvQe7t1Ql?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Geography of threats for macOS, Q2 2022 (download)

TOP 10 countries and territories by share of attacked users

Country or territory*%**
1France2.93
2Canada2.57
3Spain2.51
4United States2.45
5India2.24
6Italy2.21
7Russian Federation2.13
8United Kingdom1.97
9Mexico1.83
10Australia1.82

* Excluded from the rating are countries and territories  with relatively few users of Kaspersky security solutions for macOS (under 10,000).
** Unique users attacked as a percentage of all users of Kaspersky security solutions for macOS in the country.

In Q2 2022, the country where the most users were attacked was again France (2.93%), followed by Canada (2.57%) and Spain (2.51%). AdWare.OSX.Amc.e was the most common adware encountered in these three countries.

IoT attacks

IoT threat statistics

In Q2 2022, most devices that attacked Kaspersky traps did so using the Telnet protocol, as before.

Telnet82,93%
SSH17,07%

Distribution of attacked services by number of unique IP addresses of attacking devices, Q2 2022

The statistics for working sessions with Kaspersky honeypots show similar Telnet dominance.

Telnet93,75%
SSH6,25%

Distribution of cybercriminal working sessions with Kaspersky traps, Q2 2022

TOP 10 threats delivered to IoT devices via Telnet

Verdict%*
1Backdoor.Linux.Mirai.b36.28
2Trojan-Downloader.Linux.NyaDrop.b14.66
3Backdoor.Linux.Mirai.ek9.15
4Backdoor.Linux.Mirai.ba8.82
5Trojan.Linux.Agent.gen4.01
6Trojan.Linux.Enemybot.a2.96
7Backdoor.Linux.Agent.bc2.58
8Trojan-Downloader.Shell.Agent.p2.36
9Trojan.Linux.Agent.mg1.72
10Backdoor.Linux.Mirai.cw1.45

* Share of each threat delivered to infected devices as a result of a successful Telnet attack out of the total number of delivered threats.

Detailed IoT-threat statistics are published in the DDoS report for Q2 2022.

Attacks via web resources

The statistics in this section are based on Web Anti-Virus, which protects users when malicious objects are downloaded from malicious/infected web pages. Cybercriminals create these sites on purpose; they can infect hacked legitimate resources as well as web resources with user-created content, such as forums.

TOP 10 countries and territories that serve as sources of web-based attacks

The following statistics show the distribution by country or territory  of the sources of Internet attacks blocked by Kaspersky products on user computers (web pages with redirects to exploits, sites hosting malicious programs, botnet C&C centers, etc.). Any unique host could be the source of one or more web-based attacks.

To determine the geographic source of web attacks, the GeoIP technique was used to match the domain name to the real IP address at which the domain is hosted.

In Q2 2022, Kaspersky solutions blocked 1,164,544,060 attacks launched from online resources across the globe. A total of 273,033,368 unique URLs were recognized as malicious by Web Anti-Virus components.

https://e.infogram.com/_/Mii35djEPWnjaHq4c2Ve?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Distribution of web-attack sources by country and territory, Q2 2022 (download)

Countries and territories where users faced the greatest risk of online infection

To assess the risk of online infection faced by users around the world, for each country or territory we calculated the percentage of Kaspersky users on whose computers Web Anti-Virus was triggered during the quarter. The resulting data provides an indication of the aggressiveness of the environment in which computers operate in different countries and territories.

Note that these rankings only include attacks by malicious objects that fall under the Malware class; they do not include Web Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.

Country or territory*%**
1Taiwan26.07
2Hong Kong14.60
3Algeria14.40
4Nepal14.00
5Tunisia13.55
6Serbia12.88
7Sri Lanka12.41
8Albania12.21
9Bangladesh11.98
10Greece11.86
11Palestine11.82
12Qatar11.50
13Moldova11.47
14Yemen11.44
15Libya11.34
16Zimbabwe11.15
17Morocco11.03
18Estonia11.01
19Turkey10.75
20Mongolia10.50

* Excluded are countries and territories with relatively few Kaspersky users (under 10,000).
** Unique users targeted by Malware-class attacks as a percentage of all unique users of Kaspersky products in the country.

On average during the quarter, 8.31% of the Internet users’ computers worldwide were subjected to at least one Malware-class web attack.

https://e.infogram.com/_/ZeKtZKpRpQBrBYKAEvcg?parent_url=https%3A%2F%2Fsecurelist.com%2Fit-threat-evolution-in-q2-2022-non-mobile-statistics%2F107133%2F&src=embed#async_embed

Geography of web-based malware attacks, Q2 2022 (download)

Local threats

In this section, we analyze statistical data obtained from the OAS and ODS modules of Kaspersky products. It takes into account malicious programs that were found directly on users’ computers or removable media connected to them (flash drives, camera memory cards, phones, external hard drives), or which initially made their way onto the computer in non-open form (for example, programs in complex installers, encrypted files, etc.).

In Q2 2022, our File Anti-Virus detected 55,314,176 malicious and potentially unwanted objects.

Countries and territories where users faced the highest risk of local infection

For each country, we calculated the percentage of Kaspersky product users on whose computers File Anti-Virus was triggered during the reporting period. These statistics reflect the level of personal computer infection in different countries and territories.

Note that these rankings only include attacks by malicious programs that fall under the Malware class; they do not include File Anti-Virus triggerings in response to potentially dangerous or unwanted programs, such as RiskTool or adware.

Country or territory*%**
1Turkmenistan47.54
2Tajikistan44.91
3Afghanistan43.19
4Yemen43.12
5Cuba42.71
6Ethiopia41.08
7Uzbekistan37.91
8Bangladesh37.90
9Myanmar36.97
10South Sudan36.60
11Syria35.60
12Burundi34.88
13Rwanda33.69
14Algeria33.61
15Benin33.60
16Tanzania32.88
17Malawi32.65
18Venezuela31.79
19Cameroon31.34
20Chad30.92

*  Excluded are countries with relatively few Kaspersky users (under 10,000).
** Unique users on whose computers Malware-class local threats were blocked, as a percentage of all unique users of Kaspersky products in the country.

Source :
https://securelist.com/it-threat-evolution-in-q2-2022-non-mobile-statistics/107133/

IT threat evolution Q2 2022

Targeted attacks

New technique for installing fileless malware

Earlier this year, we discovered a malicious campaign that employed a new technique for installing fileless malware on target machines by injecting a shellcode directly into Windows event logs. The attackers were using this to hide a last-stage Trojan in the file system.

The attack starts by driving targets to a legitimate website and tricking them into downloading a compressed RAR file that is booby-trapped with the network penetration testing tools Cobalt Strike and SilentBreak. The attackers use these tools to inject code into any process of their choosing. They inject the malware directly into the system memory, leaving no artifacts on the local drive that might alert traditional signature-based security and forensics tools. While fileless malware is nothing new, the way the encrypted shellcode containing the malicious payload is embedded into Windows event logs is.

The code is unique, with no similarities to known malware, so it is unclear who is behind the attack.

WinDealer’s man-on-the-side spyware

We recently published our analysis of WinDealer: malware developed by the LuoYu APT threat actor. One of the most interesting aspects of this campaign is the group’s use of a man-on-the-side attack to deliver malware and control compromised computers. A man-on-the-side attack implies that the attacker is able to control the communication channel, allowing them to read the traffic and inject arbitrary messages into normal data exchange. In the case of WinDealer, the attackers intercepted an update request from completely legitimate software and swapped the update file with a weaponized one.

Observed WinDealer infection flow

The malware does not contain the exact address of the C2 (command-and-control) server, making it harder for security researchers to find it. Instead, it tries to access a random IP address from a predefined range. The attackers then intercept the request and respond to it. To do this, they need constant access to the routers of the entire subnet, or to some advanced tools at ISP level.

Geographic distribution of WinDealer victims

The vast majority of WinDealer’s targets are located in China: foreign diplomatic organizations, members of the academic community, or companies active in the defense, logistics or telecoms sectors. Sometimes, though, the LuoYu APT group will infect targets in other countries: Austria, the Czech Republic, Germany, India, Russia and the US. In recent months, they have also become more interested in businesses located in other East Asian countries and their China-based offices.

ToddyCat: previously unknown threat actor attacks high-profile organizations in Europe and Asia

In June, we published our analysis of ToddyCat, a relatively new APT threat actor that we have not been able to link to any other known actors. The first wave of attacks, against a limited number of servers in Taiwan and Vietnam, targeted Microsoft Exchange servers, which the threat actor compromised with Samurai, a sophisticated passive backdoor that typically works via ports 80 and 443. The malware allows arbitrary C# code execution and is used alongside multiple modules that let the attacker administer the remote system and move laterally within the targeted network. In certain cases, the attackers have used the Samurai backdoor to launch another sophisticated malicious program, which we dubbed Ninja. This is probably a component of an unknown post-exploitation toolkit exclusively used by ToddyCat.

The next wave saw a sudden surge in attacks, as the threat actor began abusing the ProxyLogon vulnerability to target organizations in multiple countries, including Iran, India, Malaysia, Slovakia, Russia and the UK.

Subsequently, we observed other variants and campaigns, which we attributed to the same group. In addition to affecting most of the previously mentioned countries, the threat actor targeted military and government organizations in Indonesia, Uzbekistan and Kyrgyzstan. The attack surface in the third wave was extended to desktop systems.

SessionManager IIS backdoor

In 2021, we observed a trend among certain threat actors for deploying a backdoor within IIS after exploiting one of the ProxyLogon-type vulnerabilities in Microsoft Exchange. Dropping an IIS module as a backdoor enables threat actors to maintain persistent, update-resistant and relatively stealthy access to the IT infrastructure of a target organization — to collect emails, update further malicious access or clandestinely manage compromised servers.

We published our analysis of one such IIS backdoor, called Owowa, last year. Early this year, we investigated another, SessionManager. Developed in C++, SessionManager is a malicious native-code IIS module. The attackers’ aim is for it to be loaded by some IIS applications, to process legitimate HTTP requests that are continuously sent to the server. This kind of malicious modules usually expects seemingly legitimate but specifically crafted HTTP requests from their operators, triggers actions based on the operators’ hidden instructions and then transparently passes the request to the server for it to be processed just as any other request.

Figure 1. Malicious IIS module processing requests

As a result, these modules are not easily spotted through common monitoring practices.

SessionManager has been used to target NGOs and government organizations in Africa, South America, Asia, Europe and the Middle East.

We believe that this malicious IIS module may have been used by the GELSEMIUM threat actor, because of similar victim profiles and the use of a common OwlProxy variant.

Other malware

Spring4Shell

Late in March, researchers discovered a critical vulnerability (CVE-2022-22965) in Spring, an open-source framework for the Java platform. This is a Remote Code Execution (RCE) vulnerability, allowing an attacker to execute malicious code remotely on an unpatched computer. The vulnerability affects the Spring MVC and Spring WebFlux applications running under version 9 or later of the Java Development Kit. By analogy with the well-known Log4Shell vulnerability, this one was dubbed “Spring4Shell”.

By the time researchers had reported it to VMware, a proof-of-concept exploit had already appeared on GitHub. It was quickly removed, but it is unlikely that cybercriminals would have failed to notice such a potentially dangerous vulnerability.

You can find more details, including appropriate mitigation steps, in our blog post.

Actively exploited vulnerability in Windows

Among the vulnerabilities fixed in May’s “Patch Tuesday” update was one that has been actively exploited in the wild. The Windows LSA (Local Security Authority) Spoofing Vulnerability (CVE-2022-26925) is not considered critical per se. However, when the vulnerability is used in a New Technology LAN Manager (NTLM) relay attack, the combined CVSSv3 score for the attack-chain is 9.8. The vulnerability, which allows an unauthenticated attacker to force domain controllers to authenticate with an attacker’s server using NTLM, was already being exploited in the wild as a zero-day, making it a priority to patch it.

Follina vulnerability in MSDT

At the end of May, researchers with the nao_sec team reported a new zero-day vulnerability in MSDT (the Microsoft Support Diagnostic Tool) that can be exploited using a malicious Microsoft Office document. The vulnerability, which has been designated as CVE-2022-30190 and has also been dubbed “Follina”, affects all operating systems in the Windows family, both for desktops and servers.

MSDT is used to collect diagnostic information and send it to Microsoft when something goes wrong with Windows. It can be called up from other applications via the special MSDT URL protocol; and an attacker can run arbitrary code with the privileges of the application that called up the MSD: in this case, the permissions of the user who opened the malicious document.

Kaspersky has observed attempts to exploit this vulnerability in the wild; and we would expect to see more in the future, including ransomware attacks and data breaches.

BlackCat: a new ransomware gang

It was only a matter of time before another ransomware group filled the gap left by REvil and BlackMatter shutting down operations. Last December, advertisements for the services of the ALPHV group, also known as BlackCat, appeared on hacker forums, claiming that the group had learned from the errors of their predecessors and created an improved version of the malware.

The BlackCat creators use the ransomware-as-a-service (RaaS) model. They provide other attackers with access to their infrastructure and malicious code in exchange for a cut of the ransom. BlackCat gang members are probably also responsible for negotiating with victims. This is one reason why BlackCat has gained momentum so quickly: all that a “franchisee” has to do is obtain access to the target network.

The group’s arsenal comprises several elements. One is the cryptor. This is written in the Rust language, allowing the attackers to create a cross-platform tool with versions of the malware that work both in Windows and Linux environments. Another is the Fendr utility (also known as ExMatter), used to exfiltrate data from the infected infrastructure. The use of this tool suggests that BlackCat may simply be a re-branding of the BlackMatter faction, since that was the only known gang to use the tool. Other tools include the PsExec tool, used for lateral movement on the victim’s network; Mimikatz, the well-known hacker software; and the Nirsoft software, used to extract network passwords.

Yanluowang ransomware: how to recover encrypted files

The name Yanluowang is a reference to the Chinese deity Yanluo Wang, one of the Ten Kings of Hell. This ransomware is relatively recent. We do not know much about the victims, although data from the Kaspersky Security Network indicates that threat actor has carried out attacks in the US, Brazil, Turkey and a few other countries.

The low number of infections is due to the targeted nature of the ransomware: the threat actor prepares and implements attacks on specific companies only.

Our experts have discovered a vulnerability that allows files to be recovered without the attackers’ key — although only under certain conditions — with the help of a known-plaintext attack. This method overcomes the encryption algorithm if two versions of the same text are available: one clean and one encrypted. If the victim has clean copies of some of the encrypted files, our upgraded Rannoh Decryptor can analyze these and recover the rest of the information.

There is one snag: Yanluowang corrupts files slightly differently depending on their size. It encrypts small (less than 3 GB) files completely, and large ones, partially. So, the decryption requires clean files of different sizes. For files smaller than 3 GB, it is enough to have the original and an encrypted version of the file that are 1024 bytes or more. To recover files larger than 3 GB, however, you need original files of the appropriate size. However, if you find a clean file larger than 3 GB, it will generally be possible to recover both large and small files.

Ransomware TTPs

In June, we carried out an in-depth analysis of the TTPs (tactics, techniques and procedures) (TTPs) of the eight most widespread ransomware families: Conti/Ryuk, Pysa, Clop, Hive, Lockbit2.0, RagnarLocker, BlackByte and BlackCat. Our aim was to help those tasked with defending corporate systems to understand how ransomware groups operate and how to protect against their attacks.

The report includes the following:

  • The TTPs of eight modern ransomware groups.
  • A description of how various groups share more than half of their components and TTPs, with the core attack stages executed identically across groups.
  • A cyber-kill chain diagram that combines the visible intersections and common elements of the selected ransomware groups and makes it possible to predict the threat actors’ next steps.
  • A detailed analysis of each technique with examples of how various groups use them, and a comprehensive list of mitigations.
  • SIGMA rules based on the described TTPs that can be applied to SIEM solutions.

Ahead of the Anti-Ransomware Day on May 12, we took the opportunity to outline the tendencies that have characterized ransomware in 2022. In our report, we highlight several trends that we have observed.

First, we are seeing more widespread development of cross-platform ransomware, as cybercriminals seek to penetrate complex environments running a variety of systems. By using cross-platform languages such as Rust and Golang, attackers are able to port their code, which allows them to encrypt data on more computers.

Second, ransomware gangs continue to industrialize and evolve into real businesses by adopting the techniques and processes used by legitimate software companies.

Third, the developers of ransomware are adopting a political stance, involving themselves in the conflict between Russia and Ukraine.

Finally, we offer best practices that organizations should adopt to help them defend against ransomware attacks:

  • Keep software updated on all your devices.
  • Focus your defense strategy on detecting lateral movements and data exfiltration.
  • Enable ransomware protection for all endpoints.
  • Install anti-APT and EDR solutions, enabling capabilities for advanced threat discovery and detection, investigation and timely remediation of incidents.
  • Provide your SOC team with access to the latest threat intelligence.

Emotet’s return

Emotet has been around for eight years. When it was first discovered in 2014, its main purpose was stealing banking credentials. Subsequently, the malware underwent numerous transformations to become one of the most powerful botnets ever. Emotet made headlines in January 2021, when its operations were disrupted through the joint efforts of law enforcement agencies in several countries. This kind of “takedowns” does not necessarily lead to the demise of a cybercriminal operation. It took the cybercriminals almost ten months to rebuild the infrastructure, but Emotet did return in November 2021. At that time, the Trickbot malware was used to deliver Emotet, but it is now spreading on its own through malicious spam campaigns.

Recent Emotet protocol analysis and C2 responses suggest that Emotet is now capable of downloading sixteen additional modules. We were able to retrieve ten of these, including two different copies of the spam module, used by Emotet for stealing credentials, passwords, accounts and emails, and to spread spam.

You can read our analysis of these modules, as well as statistics on recent Emotet attacks, here.

Emotet infects both corporate and private computers all around the world. Our telemetry indicates that in the first quarter of 2022, targeted: it mostly targeted users in Italy, Russia, Japan, Mexico, Brazil, Indonesia, India, Vietnam, China, Germany and Malaysia.

Moreover, we have seen a significant growth in the number of users attacked by Emotet.

Mobile subscription Trojans

Trojan subscribers are a well-established method of stealing money from people using Android devices. These Trojans masquerade as useful apps but, once installed, silently subscribe to paid services.

The developers of these Trojans make money through commissions: they get a cut of what the person “spends”. Funds are typically deducted from the cellphone account, although in some cases, these may be debited directly to a bank card. We looked at the most notable examples that we have seen in the last twelve months, belonging to the Jocker, MobOk, Vesub and GriftHorse families.

Normally, someone has to actively subscribe to a service; providers often ask subscribers to enter a one-time code sent via SMS, to counter automated subscription attempts. To sidestep this protection, malware can request permission to access text messages; where they do not obtain this, they can steal confirmation codes from pop-up notifications about incoming messages.

Some Trojans can both steal confirmation codes from texts or notifications, and work around CAPTCHA: another means of protection against automated subscriptions. To recognize the code in the picture, the Trojan sends it to a special CAPTCHA recognition service.

Some malware is distributed through dubious sources under the guise of apps that are banned from official stores, for example, masquerading as apps for downloading content from YouTube or other streaming services, or as an unofficial Android version of GTA5. In addition, they can appear in these same sources as free versions of popular, expensive apps, such as Minecraft.

Other mobile subscription Trojans are less sophisticated. When run for the first time, they ask the user to enter their phone number, seemingly for login purposes. The subscription is issued as soon as they enter their number and click the login button, and the amount is debited to their cellphone account.

Other Trojans employ subscriptions with recurring payments. While this requires consent, the person using the phone might not realize they are signing up for regular automatic payments. Moreover, the first payment is often insignificant, with later charges being noticeably higher.

You can read more about this type of mobile Trojan, along with tips on how to avoid falling victim to it, here.

The threat from stalkerware

Over the last four years, we have published annual reports on the stalkerware situation, in particular using data from the Kaspersky Security Network. This year, our report also included the results of a survey on digital abuse commissioned by Kaspersky and several public organizations.

Stalkerware provides the digital means for a person to secretly monitor someone else’s private life and is often used to facilitate psychological and physical violence against intimate partners. The software is commercially available and can access an array of personal data, including device location, browser history, text messages, social media chats, photos and more. It may be legal to market stalkerware, although its use to monitor someone without their consent is not. Developers of stalkerware benefit from a vague legal framework that still exists in many countries.

In 2021, our data indicated that around 33,000 people had been affected by stalkerware.

The numbers were lower than what we had seen for a few years prior to that. However, it is important to remember that the decrease of 2020 and 2021 occurred during successive COVID-19 lockdowns: that is, during conditions that meant abusers did not need digital tools to monitor and control their partners’ personal lives. It is also important to bear in mind that mobile apps represent only one method used by abusers to track someone — others include tracking devices such as AirTags, laptop applications, webcams, smart home systems and fitness trackers. KSN tracks only the use of mobile apps. Finally, KSN data is taken from mobile devices protected by Kaspersky products: many people do not protect their mobile devices.  The Coalition Against Stalkerware, which brings together members of the IT industry and non-profit companies, believes that the overall number of people affected by this threat might be thirty times higher — that is around a million people!

Stalkerware continues to affect people across the world: in 2021, we observed detections in 185 countries or territories.

Just as in 2020, Russia, Brazil, the US and India were the top four countries with the largest numbers of affected individuals. Interestingly, Mexico had fallen from fifth to ninth place. Algeria, Turkey and Egypt entered the top ten, replacing Italy, the UK and Saudi Arabia, which were no longer in the top ten.

We would recommend the following to reduce your risk of being targeted:

  • Use a unique, complex password on your phone and do not share it with anyone.
  • Try not to leave your phone unattended; and if you have to, lock it.
  • Download apps only from official stores.
  • Protect your mobile device with trustworthy security software and make sure it is able to detect stalkerware.

Remember also that if you discover stalkerware on your phone, dealing with the problem is not as simple as just removing the stalkerware app. This will alert the abuser to the fact that you have become aware of their activities and may precipitate physical abuse. Instead, seek help:  you can find a list or organizations that can provide help and support on the Coalition Against Stalkerware site.

Source :
https://securelist.com/it-threat-evolution-q2-2022/107099/

Threat landscape for industrial automation systems for H1 2022

H1 2022 in numbers

Geography

  • In H1 2022, malicious objects were blocked at least once on 31.8% of ICS computers globally.Percentage of ICS computers on which malicious objects were blocked
  • For the first time in five years of observations, the lowest percentage in the ‎first half of the year was observed in March.‎ During the period from January to March, the percentage of attacked ICS computers decreased by 1.7 p.p.Percentage of ICS computers on which malicious objects were blocked, January – June 2020, 2021, and 2022
  • Among regions, the highest percentage of ICS computers on which malicious objects were blocked was observed in Africa (41.5%). The lowest percentage (12.8%) was recorded in Northern Europe.Percentage of ICS computers on which malicious objects were blocked, in global regions
  • Among countries, the highest percentage of ICS computers on which malicious objects were blocked was recorded in Ethiopia (54.8%) and the lowest (6.8%) in Luxembourg.15 countries and territories with the highest percentage of ICS computers on which malicious objects were blocked, H1 202210 countries and territories with the lowest percentage of ICS computers on which malicious objects were blocked, H1 2022

Threat sources

  • The main sources of threats to computers in the operational technology infrastructure of organizations are internet (16.5%), removable media (3.5%), and email (7.0%).Percentage of ICS computers on which malicious objects from different sources were blocked

Regions

  • Among global regions, Africa ranked highest based on the percentage of ICS computers on which malware was blocked when removable media was connected.Regions ranked by percentage of ICS computers on which malware was blocked when removable media was connected, H1 2022
  • Southern Europe leads the ranking of regions by percentage of ICS computers on which malicious email attachments and phishing links were blocked.Regions ranked by percentage of ICS computers on which malicious email attachments and phishing links were blocked, H1 2022

Industry specifics

  • In the Building Automation industry, the percentage of ICS computers on which malicious email attachments and phishing links were blocked (14.4%) was twice the average value for the entire world (7%).Percentage of ICS computers on which malicious email attachments and phishing links were blocked, in selected industries
  • In the Oil and Gas industry, the percentage of ICS computers on which threats were blocked when removable media was connected (10.4%) was 3 times the average percentage for the entire world (3.5%).Percentage of ICS computers on which threats were blocked when removable media was connected
  • In the Oil and Gas industry, the percentage of ICS computers on which malware was blocked in network folders (1.2%) was twice the world average (0.6%).Percentage of ICS computers on which threats were blocked in network folders

Diversity of malware

  • Malware of different types from 7,219 families was blocked on ICS computers in H1 2022.Percentage of ICS computers on which the activity of malicious objects from different categories was prevented

Ransomware

  • In H1 2022, ransomware was blocked on 0.65% of ICS computers. This is the highest percentage for any six-month reporting period since 2020.Percentage of ICS computers on which ransomware was blocked
  • The highest percentage of ICS computers on which ransomware was blocked was recorded in February (0.27%) and the lowest in March (0.11%). The percentage observed in February was the highest in 2.5 years of observations.Percentage of ICS computers on which ransomware was blocked, January – June 2022
  • East Asia (0.95%) and the Middle East (0.89%) lead the ransomware-based ranking of regions. In the Middle East, the percentage of ICS computers on which ransomware was blocked per six-month reporting period has increased by a factor of 2.5 since 2020.Regions ranked by percentage of ICS computers on which ransomware was blocked, H1 2022
  • Building Automation leads the ranking of industries based on the percentage of ICS computers attacked by ransomware (1%).Percentage of ICS computers on which ransomware was blocked, in selected regions, H1 2022

Malicious documents

  • Malicious documents (MSOffice+PDF) were blocked on 5.5% of ICS computers. This is 2.2 times the percentage recorded in H2 2021. Threat actors distribute malicious documents via phishing emails and actively use such emails as the vector of initial computer infections.Percentage of ICS computers on which malicious documents (MSOffice+PDF) were blocked
  • In the Building Automation industry, the percentage of ICS computers on which malicious office documents were blocked (10.5%) is almost twice the global average.Percentage of ICS computers on which malicious office documents (MSOffice+PDF) were blocked, in selected industries

Spyware

  • Spyware was blocked on 6% of ICS computers. This percentage has been growing since 2020.Percentage of ICS computers on which spyware was blocked
  • Building Automation leads the ranking of industries based on the percentage of ICS computers on which spyware was blocked (12.9%).Percentage of ICS computers on which spyware was blocked, in selected industries

Malware for covert cryptocurrency mining

  • The percentage of ICS computers on which malicious cryptocurrency miners were blocked continued to rise gradually.Percentage of ICS computers on which malicious cryptocurrency miners were blocked
  • Building Automation also leads the ranking of selected industries by percentage of ICS computers on which malicious cryptocurrency miners were blocked.Percentage of ICS computers on which malicious cryptocurrency miners were blocked, in selected industries

The full text of the report has been published on the Kaspersky ICS CERT website.

Source :
https://securelist.com/threat-landscape-for-industrial-automation-systems-for-h1-2022/107373/

Akamai’s Insights on DNS in Q2 2022

by Or Katz and Jim Black
Data analysis by Gal Kochner and Moshe Cohen

Executive summary

  • Akamai researchers have analyzed malicious DNS traffic from millions of devices to determine how corporate and personal devices are interacting with malicious domains, including phishing attacks, malware, ransomware, and command and control (C2).
  • Akamai researchers saw that 12.3% of devices used by home and corporate users communicated at least once to domains associated with malware or ransomware.
  • 63% of those users’ devices communicated with malware or ransomware domains, 32% communicated with phishing domains, and 5% communicated with C2 domains.
  • Digging further into phishing attacks, researchers found that users of financial services and high tech are the most frequent targets of phishing campaigns, with 47% and 36% of the victims, respectively.
  • Consumer accounts are the most affected by phishing, with 80.7% of the attack campaigns.
  • Tracking 290 different phishing toolkits being reused in the wild, and counting the number of distinct days each kit was reused over Q2 2022, shows that 1.9% of the tracked kits were reactivated on at least 72 days. In addition, 49.6% of the kits were reused for at least five days, demonstrating how many users are being revictimized multiple times. This shows how realistic-looking and dangerous these kits can be, even to knowledgeable users. 
  • The most used phishing toolkit in Q2 2022 (Kr3pto, a phishing campaign that targeted banking customers in the United Kingdom, which evades multi-factor authentication [MFA]) was hosted on more than 500 distinct domains.

Introduction

“It’s always DNS.” Although that is a bit of a tongue-in-cheek phrase in our industry, DNS can give us a lot of information about the threat landscape that exists today. By analyzing information from Akamai’s massive infrastructure, we are able to gain some significant insights on how the internet behaves. In this blog, we will explore these insights into traffic patterns, and how they affect people on the other end of the internet connection. 

Akamai traffic insights

Attacks by category

Based on Akamai’s range of visibility across different industries and geographies, we can see that 12.3% of protected devices attempted to reach out to domains that were associated with malware at least once during Q2 2022. This indicates that these devices might have been compromised. On the phishing and C2 front, we can see that 6.2% of devices accessed phishing domains and 0.8% of the devices accessed C2-associated domains. Although these numbers may seem insignificant, the scale here is in the millions of devices. When this is considered, along with the knowledge that C2 is the most malignant of threats, these numbers are not only significant, they’re cardinal.

Comparing 2022 Q2 results with 2022 Q1 results (Figure 1), we can see a minor increase in all categories in Q2. We attribute those increases to seasonal changes that are not associated with a significant change in the threat landscape.

Fig. 1: Devices exposed to threats — Q1 vs. Q2 Fig. 1: Devices exposed to threats — Q1 vs. Q2

In Figure 2, we can see that of the 12.3% potentially compromised devices, 63% were exposed to threats associated with malware activity, 32% with phishing, and 5% with C2. Access to malware-associated domains does not guarantee that these devices were actually compromised, but provides a strong indication of increased potential risk if the threat wasn’t properly mitigated. However, access to C2-associated domains indicates that the device is most likely compromised and is communicating with the C2 server. This can often explain why the incidence of C2 is lower when compared with malware numbers.

Fig. 2: Potentially compromised devices by category Fig. 2: Potentially compromised devices by category

Phishing attack campaigns 

By looking into the brands that are being abused and mimicked by phishing scams in Q2 2022, categorized by brand industry and number of victims, we can see that high tech and financial brands led with 36% and 47%, respectively (Figure 3). These leading phishing industry categories are consistent with Q1 2022 results, in which high tech and financial brands were the leading categories, with 32% and 31%, respectively. 

Fig. 3: Phishing victims and phishing campaigns by abused brands Fig. 3: Phishing victims and phishing campaigns by abused brands

When taking a different view on the phishing landscape–targeted industries by counting the number of attack campaigns being launched over Q2 2022, we can see that high tech and financial brands are still leading, with 36% and 41%, respectively (Figure 3). The correlation between leading targeted brands when it comes to number of attacks and number of victims is evidence that threat actors’ efforts and resources are, unfortunately, effectively working to achieve their desired outcome.

Akamai’s research does not have any visibility into the distribution channels used to deliver the monitored phishing attacks that led to victims clicking on a malicious link and ending up on the phishing landing page. Yet the strong correlation between different brand segments by number of attack campaigns and the number of victims seems to indicate that the volume of attacks is effective and leads to a similar trend in the number of victims. The correlation might also indicate that the distribution channels used have minimal effect on attack outcome, and it is all about the volume of attacks that lead to the desired success rates.

Taking a closer look at phishing attacks by categorization of attack campaigns — consumers vs. business targeted accounts— we can see that consumer attacks are the most dominant, with 80.7% of the attack campaigns (Figure 4). This domination is driven by the massive demand for consumers’ compromised accounts in dark markets that are then used to launch fraud-related second-phase attacks. However, even with only 19.3% of the attack campaigns, attacks against business accounts should not be considered marginal, as these kinds of attacks are usually more targeted and have greater potential for significant damage. Attacks that target business accounts may lead to a company’s network being compromised with malware or ransomware, or to confidential information being leaked. An attack that begins with an employee clicking a link in a phishing email can end up with the business suffering significant financial and reputational damages.

Fig. 4: Phishing targeted accounts — consumers vs. business  Fig. 4: Phishing targeted accounts — consumers vs. business

Phishing toolkits 

Phishing attacks are an extremely common vector that have been used for many years. The potential impacts and risks involved are well-known to most internet users. However, phishing is still a highly relevant and dangerous attack vector that affects thousands of people and businesses daily. Research conducted by Akamai explains some of the reasons for this phenomenon, and focuses on the phishing toolkits and their role in making phishing attacks effective and relevant. 

Phishing toolkits enable rapid and easy creation of fake websites that mimic known brands. Phishing toolkits enable even non–technically gifted scammers to run phishing scams, and in many cases are being used to create distributed and large-scale attack campaigns. The low cost and availability of these toolkits explains the increasing numbers of phishing attacks that have been seen in the past few years. 

According to Akamai’s research that tracked 290 different phishing toolkits being used in the wild, 1.9% of the tracked kits were reused on at least 72 distinct days over Q2 2022 (Figure 5). Further, 49.6% of the kits were reused for at least five days, and when looking into all the tracked kits, we can see that all of them were reused no fewer than three distinct days over Q2 2022.

Fig. 5: Phishing toolkits by number of reused days Q2 2022 Fig. 5: Phishing toolkits by number of reused days Q2 2022

The numbers showing the heavy reuse phenomenon of the observed phishing kits shed some light on the phishing threat landscape and the scale involved, creating an overwhelming challenge to defenders. Behind the reuse of phishing kits are factories and economic forces that drive the phishing landscape. Those forces include developers who create phishing kits that mimic known brands, later to be sold or shared among threat actors to be reused over and over again with very minimal effort.

Further analysis on the most reused kits in Q2 2022, counting the number of different domains used to deliver each kit, shows that the Kr3pto toolkit was the one most frequently used and was associated with more than 500 domains (Figure 6). The tracked kits are labeled by the name of the brand being abused or by a generic name representing the kit developer signature or kit functionality.

In the case of Kr3pto, the actor behind the phishing kit is a developer who builds and sells unique kits that target financial institutions and other brands. In some cases, these kits target financial firms in the United Kingdom, and they bypass MFA. This evidence also shows that this phishing kit that was initially created more than three years ago is still highly active and effective and being used intensively in the wild.

Fig. 6: Top 10 reused phishing toolkits  Fig. 6: Top 10 reused phishing toolkits

The phishing economy is growing, kits are becoming easier to develop and deploy, and the web is full of abandoned, ready-to-be-abused websites and vulnerable servers and services. Criminals capitalize on these weaknesses to establish a foothold that enables them to victimize thousands of people and businesses daily.

The growing industrial nature of phishing kit development and sales (in which new kits are developed and released within hours) and the clear split between creators and users means this threat isn’t going anywhere anytime soon. The threat posed by phishing factories isn’t just focused on the victims who risk having valuable accounts compromised and their personal information sold to criminals — phishing is also a threat to brands and their stakeholders.

The life span of a typical phishing domain is measured in hours, not days. Yet new techniques and developments by the phishing kit creators are expanding these life spans little by little, and it’s enough to keep the victims coming and the phishing economy moving. 

Summary

This type of research is necessary in the fight to keep our customers safer online. We will continue to monitor these threats and report on them to keep the industry informed.

The best way to stay up to date on this and other research pieces from the Akamai team is to follow Akamai Security Research on Twitter.

Source :
https://www.akamai.com/blog/security-research/q2-dns-akamai-insights

Mitigating Log4j Abuse Using Akamai Guardicore Segmentation

Executive summary

A critical remote code-execution vulnerability (CVE-2021-44228) has been publicly disclosed in Log4j, an open-source logging utility that’s used widely in applications, including many utilized by large enterprise organizations.

The vulnerability allows threat actors to exfiltrate information from, and execute malicious code on, systems running applications that utilize the library by manipulating log messages. There already are reports of servers performing internet-wide scans in attempts to locate vulnerable servers, and our threat intelligence teams are seeing attempts to exploit this vulnerability at alarming volumes. Log4j is incorporated into many popular frameworks and many Java applications, making the impact widespread.

Akamai Guardicore Segmentation is well positioned to address this vulnerability in different ways. It’s highly recommended that organizations update Log4j to its latest version- 2.16.0. Due to the rapidly escalating nature of this vulnerability, Akamai teams will continue to develop and deploy mitigation measures in order to support our customers.

As a follow up to Akamai’s recent post we wanted to provide more detail on how organizations can leverage  Akamai Guardicore Segmentation features to help address log4j exposure.

Log4j vulnerability: scope and impact

Log4j is a Java-based open-source logging library. On December 9, 2021, a critical vulnerability involving unauthenticated remote code execution (CVE-2021-44228) in Log4j was reported, causing concern due to how commonly Log4j is used. In addition to being used directly in a large multitude of applications, Log4j is also incorporated into a host of popular frameworks, including Apache Struts2, Apache Solr, Apache Druid, and Apache Flink.

Although Akamai first observed exploit attempts on the Log4j vulnerability on December 9th, following the widespread publication of the incident, we are now seeing evidence suggesting it could have been around for months. Since widespread publication of the vulnerability, we have seen multiple variants seeking to exploit this vulnerability, at a sustained volume of attack traffic at around 2M exploit requests per hour. The speed at which the variants are evolving is unprecedented.

A compromised machine would allow a threat actor to remotely provide a set of commands which Log4j executes. An attacker would have the ability to run arbitrary commands inside a server. This can allow an attacker to compromise a vulnerable system – including those that might be secured deep inside of a network with no direct access to the internet.

Akamai’s security teams have been monitoring attackers attempting to use Log4j in recent days. Other than the increase in attempted exploitation, Akamai researchers are also seeing attackers using a multitude of tools and attack techniques to get vulnerable components to log malicious content, in order to get remote code execution. This is indicative of threat actors’ ability to exploit a new vulnerability, and the worse the vulnerability is, the quicker they will act.

Mitigating Log4j abuse using Akamai Guardicore Segmentation

Customers using Akamai Guardicore Segmentation can leverage its deep, process level visibility to identify vulnerable applications and potential security risks in the environment. They can then use it to enact precise control over network traffic in order to stop attempted attacks on vulnerable systems, without disruptions to normal business operations. 

Guardicore Hunt customers have their environments monitored and investigated continuously by a dedicated team of security researchers. Alerts on security risks and suggested mitigation steps are immediately sent.

If you’d like to hear more about Akamai Guardicore Segmentation, read more or contact us.

What’s under threat: identify vulnerable Java processes and Log4j abuse

In order to protect against potential Log4j abuse, it is necessary to first identify potentially exploitable processes. This requires deep visibility into network traffic at the process level, which is provided by the Reveal and Insight features of Akamai Guardicore Segmentation. Precise visibility into internet connections and traffic at the process level allows us to see clearly what mitigation steps need to be taken, and visibility tools with historical data are pivotal in helping to prevent disruption to business operations.

Identify internet connected Java applications: using Reveal Explore Map, create a map for the previous week, and filter by java applications- such as tomcat, elastic, logstash- and by applications that have connections to/from the internet. Using this map, you can now see which assets are under potential threat. While this won’t yet identify Log4j applications, this can give you an idea of which machines to prioritize in your mitigation process.

Create a historical map to analyze normal communication patterns: using Reveal Explore Map, create a historical map of previous weeks (excluding the time since Log4j was reported) to view and learn normal communication patterns. Use this information to identify legitimate communications, and respond without disrupting the business. For example, a historical map might indicate what network connections exist under normal circumstances, those could be allowed, while other connections blocked or alerted on. Additionally, compare and contrast with a more recent map to identify anomalies.

Use reveal explore map to identify legitimate communications, and respond without disrupting the business.

Identify applications vulnerable to Log4j abuse: in the query section below, use Query 1 with Insight queries to identify assets that are running Java applications which have Log4j jar files in their directories. This query should return all Log4j packages in your environment, allowing you to assess and address any mitigation steps needed. To better prioritize exposed machines, cross reference the information with the Reveal Explore Map described previously.

Note that this query identifies Log4j packages that exist in the Java process current working directory or sub-directories.

Detect potential exploitation attempts in Linux logs: run an Insight query using YARA signature rule (Query 2, provided below in the query section) to search for known Log4j IoCs in the logs of linux machines. This can help you identify whether you’ve been attacked.

Note, a negative result does not necessarily mean that no attack exists, as this is only one of many indicators.

Stopping the attack: using Guardicore Segmentation to block malicious IoCs and attack vectors

It is imperative to be able to take action, once vulnerable applications have been identified. While patching is underway, Akamai Guardicore Segmentation offers a multitude of options for alerting on, stopping and preventing potential attacks. Critically, a solution with detailed and precise control over network communication and traffic is required to be able to surgically block or isolate attack vectors, with minimal to no disruption to normal business functions.

Automatically block IoC’s with Threat Intelligence Firewall (TIFW) and DNS Security: Akamai security teams are working around the clock to identify IPs and Domains used for Log4j exploitation. Customers who have these features turned on can expect a constantly updated list of IoCs to be blocked, preventing Log4j being used to download malicious payloads. Note that TIFW can be set to alert or block, please ensure it’s configured correctly. DNS Security is available from V41 onwards. The IoCs are also available on the Guardicore Threat Intel Repository and Guardicore Reputation Service.

Fully quarantine compromised servers: if compromised machines are identified during your investigation, use Akamai Guardicore Segmentation to isolate attacked/vulnerable servers from the rest of your network. Leverage built-in templates to easily enable deployment of segmentation policy to mitigate attacks.

Block inbound and outbound traffic to vulnerable assets: as a precautionary measure, you may also choose to block traffic to all machines identified with an unpatched version of Log4j, until patching is completed. Using a historical map of network traffic can help you limit the impact on business operations.

Create block rules for outgoing traffic from Java applications to the internet: if necessary, all internet-connected Java applications revealed in previous steps can be blocked from accessing the internet, as an additional precaution, until patching is complete.

Search queries

Query 1: To Identify assets that are running Java applications, which also have a Log4j jar file under their directories, run the following Insight query:

This query identifies assets that are running Java applications, which also have a Log4j jar file under their directories.

Query 2: To detect potential exploitation attempts, run an Insight query using YARA signature rules (our thanks to Florian Roth who published the original rule): 

SELECT path, count FROM yara WHERE path LIKE '/var/log/%%' AND sigrule = "rule EXPL_Log4j_CallBackDomain_IOCs_Dec21_1 {
strings:
$xr1 = /\b(ldap|rmi):\/\/([a-z0-9\.]{1,16}\.bingsearchlib\.com|[a-z0-9\.]{1,40}\.interact\.sh|[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}):[0-9]{2,5}\/([aZ]|ua|Exploit|callback|[0-9]{10}|http443useragent|http80useragent)\b/
condition:
1 of them
}
rule EXPL_JNDI_Exploit_Patterns_Dec21_1 {
strings:
$ = {22 2F 42 61 73 69 63 2F 43 6F 6D 6D 61 6E 64 2F 42 61 73 65 36 34 2F 22}
$ = {22 2F 42 61 73 69 63 2F 52 65 76 65 72 73 65 53 68 65 6C 6C 2F 22}
$ = {22 2F 42 61 73 69 63 2F 54 6F 6D 63 61 74 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 42 61 73 69 63 2F 4A 65 74 74 79 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 42 61 73 69 63 2F 57 65 62 6C 6F 67 69 63 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 42 61 73 69 63 2F 4A 42 6F 73 73 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 42 61 73 69 63 2F 57 65 62 73 70 68 65 72 65 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 42 61 73 69 63 2F 53 70 72 69 6E 67 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 44 65 73 65 72 69 61 6C 69 7A 61 74 69 6F 6E 2F 55 52 4C 44 4E 53 2F 22}
$ = {22 2F 44 65 73 65 72 69 61 6C 69 7A 61 74 69 6F 6E 2F 43 6F 6D 6D 6F 6E 73 43 6F 6C 6C 65 63 74 69 6F 6E 73 31 2F 44 6E 73 6C 6F 67 2F 22}
$ = {22 2F 44 65 73 65 72 69 61 6C 69 7A 61 74 69 6F 6E 2F 43 6F 6D 6D 6F 6E 73 43 6F 6C 6C 65 63 74 69 6F 6E 73 32 2F 43 6F 6D 6D 61 6E 64 2F 42 61 73 65 36 34 2F 22}
$ = {22 2F 44 65 73 65 72 69 61 6C 69 7A 61 74 69 6F 6E 2F 43 6F 6D 6D 6F 6E 73 42 65 61 6E 75 74 69 6C 73 31 2F 52 65 76 65 72 73 65 53 68 65 6C 6C 2F 22}
$ = {22 2F 44 65 73 65 72 69 61 6C 69 7A 61 74 69 6F 6E 2F 4A 72 65 38 75 32 30 2F 54 6F 6D 63 61 74 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 54 6F 6D 63 61 74 42 79 70 61 73 73 2F 44 6E 73 6C 6F 67 2F 22}
$ = {22 2F 54 6F 6D 63 61 74 42 79 70 61 73 73 2F 43 6F 6D 6D 61 6E 64 2F 22}
$ = {22 2F 54 6F 6D 63 61 74 42 79 70 61 73 73 2F 52 65 76 65 72 73 65 53 68 65 6C 6C 2F 22}
$ = {22 2F 54 6F 6D 63 61 74 42 79 70 61 73 73 2F 54 6F 6D 63 61 74 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 54 6F 6D 63 61 74 42 79 70 61 73 73 2F 53 70 72 69 6E 67 4D 65 6D 73 68 65 6C 6C 22}
$ = {22 2F 47 72 6F 6F 76 79 42 79 70 61 73 73 2F 43 6F 6D 6D 61 6E 64 2F 22}
$ = {22 2F 57 65 62 73 70 68 65 72 65 42 79 70 61 73 73 2F 55 70 6C 6F 61 64 2F 22}
condition:
1 of them
}
rule EXPL_Log4j_CVE_2021_44228_JAVA_Exception_Dec21_1 {
strings:
$xa1 = {22 68 65 61 64 65 72 20 77 69 74 68 20 76 61 6C 75 65 20 6F 66 20 42 61 64 41 74 74 72 69 62 75 74 65 56 61 6C 75 65 45 78 63 65 70 74 69 6F 6E 3A 20 22}
$sa1 = {22 2E 6C 6F 67 34 6A 2E 63 6F 72 65 2E 6E 65 74 2E 4A 6E 64 69 4D 61 6E 61 67 65 72 2E 6C 6F 6F 6B 75 70 28 4A 6E 64 69 4D 61 6E 61 67 65 72 22}
$sa2 = {22 45 72 72 6F 72 20 6C 6F 6F 6B 69 6E 67 20 75 70 20 4A 4E 44 49 20 72 65 73 6F 75 72 63 65 22}
condition:
$xa1 or all of ($sa*)
}
rule EXPL_Log4j_CVE_2021_44228_Dec21_Soft {
strings:
$ = {22 24 7B 6A 6E 64 69 3A 6C 64 61 70 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 72 6D 69 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 6C 64 61 70 73 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 64 6E 73 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 69 69 6F 70 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 68 74 74 70 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 6E 69 73 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 6E 64 73 3A 2F 22}
$ = {22 24 7B 6A 6E 64 69 3A 63 6F 72 62 61 3A 2F 22}
condition:
1 of them
}
rule EXPL_Log4j_CVE_2021_44228_Dec21_OBFUSC {
strings:
$x1 = {22 24 25 37 42 6A 6E 64 69 3A 22}
$x2 = {22 25 32 35 32 34 25 32 35 37 42 6A 6E 64 69 22}
$x3 = {22 25 32 46 25 32 35 32 35 32 34 25 32 35 32 35 37 42 6A 6E 64 69 25 33 41 22}
$x4 = {22 24 7B 6A 6E 64 69 3A 24 7B 6C 6F 77 65 72 3A 22}
$x5 = {22 24 7B 3A 3A 2D 6A 7D 24 7B 22}
condition:
1 of them
}
rule EXPL_Log4j_CVE_2021_44228_Dec21_Hard {
strings:
$x1 = /\$\{jndi:(ldap|ldaps|rmi|dns|iiop|http|nis|nds|corba):\/[\/]?[a-z-\.0-9]{3,120}:[0-9]{2,5}\/[a-zA-Z\.]{1,32}\}/
$fp1r = /(ldap|rmi|ldaps|dns):\/[\/]?(127\.0\.0\.1|192\.168\.|172\.[1-3][0-9]\.|10\.)/
condition:
$x1 and not 1 of ($fp*)
}
rule SUSP_Base64_Encoded_Exploit_Indicators_Dec21 {
strings:
/* curl -s */
$sa1 = {22 59 33 56 79 62 43 41 74 63 79 22}
$sa2 = {22 4E 31 63 6D 77 67 4C 58 4D 67 22}
$sa3 = {22 6A 64 58 4A 73 49 43 31 7A 49 22}
/* |wget -q -O- */
$sb1 = {22 66 48 64 6E 5A 58 51 67 4C 58 45 67 4C 55 38 74 49 22}
$sb2 = {22 78 33 5A 32 56 30 49 43 31 78 49 43 31 50 4C 53 22}
$sb3 = {22 38 64 32 64 6C 64 43 41 74 63 53 41 74 54 79 30 67 22}
condition:
1 of ($sa*) and 1 of ($sb*)
}
rule SUSP_JDNIExploit_Indicators_Dec21 {
strings:
$xr1 = /(ldap|ldaps|rmi|dns|iiop|http|nis|nds|corba):\/\/[a-zA-Z0-9\.]{7,80}:[0-9]{2,5}\/(Basic\/Command\/Base64|Basic\/ReverseShell|Basic\/TomcatMemshell|Basic\/JBossMemshell|Basic\/WebsphereMemshell|Basic\/SpringMemshell|Basic\/Command|Deserialization\/CommonsCollectionsK|Deserialization\/CommonsBeanutils|Deserialization\/Jre8u20\/TomcatMemshell|Deserialization\/CVE_2020_2555\/WeblogicMemshell|TomcatBypass|GroovyBypass|WebsphereBypass)\//
condition:
filesize < 100MB and $xr1
}
rule SUSP_EXPL_OBFUSC_Dec21_1{
strings:
/* ${lower:X} - single character match */
$ = { 24 7B 6C 6F 77 65 72 3A ?? 7D }
/* ${upper:X} - single character match */
$ = { 24 7B 75 70 70 65 72 3A ?? 7D }
/* URL encoded lower - obfuscation in URL */
$ = {22 24 25 37 62 6C 6F 77 65 72 3A 22}
$ = {22 24 25 37 62 75 70 70 65 72 3A 22}
$ = {22 25 32 34 25 37 62 6A 6E 64 69 3A 22}
$ = {22 24 25 37 42 6C 6F 77 65 72 3A 22}
$ = {22 24 25 37 42 75 70 70 65 72 3A 22}
$ = {22 25 32 34 25 37 42 6A 6E 64 69 3A 22}
condition:
1 of them
}"
AND count > 0 AND path NOT LIKE "/var/log/gc%"

Source :
https://www.akamai.com/blog/security/recommendations-for-log4j-mitigation