Are you struggling to decide between a cloud VPN vs. traditional VPN for your business?
You’re not alone. Many companies grapple with this decision, still determining which option best meets their needs.
The pain of making the wrong choice is real. Opt for a solution that doesn’t align with your business needs, and you could face slow connection speeds, increased security risks, or even inflated costs. Worse, you might be locked into a solution that doesn’t scale with your business, leading to even more headaches.
The world of VPNs can be complex and confusing, with each type boasting its features, benefits, and drawbacks. It’s easy to feel overwhelmed, unsure of which path to take.
In this article, we’ll demystify the differences between cloud VPN vs. traditional VPN, providing you with the information you need to make an informed decision. We’ll explore how each type works, its advantages, and its key differences.
What is a Cloud VPN?
A Cloud VPN is a service that provides secure and private internet access to users. Cloud VPNs are hosted in the cloud, meaning they can be accessed from anywhere worldwide, making them an ideal choice for businesses with a remote workforce or multiple office locations.
Cloud VPNs are more scalable, flexible, and efficient than their traditional counterparts. They can quickly adapt to the needs of businesses, whether it’s accommodating growth, supporting mobile devices, or providing global accessibility.
This adaptability makes Cloud VPNs popular for companies looking to secure their data without sacrificing convenience or performance.
How Do Cloud VPNs Work?
Cloud VPNs create a secure pathway, an encrypted tunnel, between the user’s device and the internet. This tunnel acts as a safe conduit for data to travel, ensuring that all information passing through it’s protected from external threats such as hackers or malware.
When users connect to a Cloud VPN, their device communicates with the VPN server in the cloud. The server then encrypts the user’s data before it’s sent over the internet. This encryption makes the data unreadable to anyone who might intercept it, ensuring its security.
A Cloud VPN also masks the user’s IP address, replacing it with the IP address of the VPN server. This provides an additional layer of privacy, preventing third parties from tracking the user’s online activities or determining their physical location.
Types of Cloud VPNs
Businesses come in all shapes and sizes, and so do their networking needs. That’s why Cloud VPNs are versatile, offering different types to suit various requirements. Here are the two main types of Cloud VPNs:
Remote Access VPNs
Designed for the modern workforce, these VPNs allow individual users to securely access a private network from anywhere. Ideal for remote workers or teams spread across multiple locations, they ensure secure access to company resources.
Site-to-Site Connection VPNs
Site-to-site connection VPNs connect entire networks, providing a secure bridge for data to travel between different office locations or between a business and its partners or clients. Ideal for companies with multiple office locations.
The Main Benefits of Cloud VPNs
Cloud VPNs offer several advantages over traditional VPNs. These include:
Direct Cloud Access
Cloud VPNs provide direct access to cloud services, reducing latency and improving performance.
Global Accessibility
They are hosted in the cloud and can be accessed from anywhere worldwide.
Flexibility
They can be easily scaled up or down based on the needs of the business.
Scalability
They can support many users without the need for significant hardware investment.
Mobile Support
They are designed to work well with mobile devices, supporting the modern mobile workforce.
Cost Efficiency
They eliminate the need for expensive hardware and maintenance costs associated with traditional VPNs.
What is a Traditional VPN (remote VPN)?
A traditional VPN, also known as a remote VPN, is a technology that creates a secure connection over a less secure network between the user’s computer and a private network.
Remote workers widely use this technology to access company resources they wouldn’t otherwise be able to reach. It’s also used by individuals who want to ensure their online activity is private and secure.
How Do Remote VPNs Work?
A cloud VPN vs. traditional VPN comparison reveals how remote VPNs function. These systems create a secure tunnel between the user’s device and the VPN server. The data traveling through this tunnel is encrypted, offering a safe method for transmitting information between the remote user and the company network.
The VPN server, acting as a go-between, conceals your IP address and gives the impression that your traffic originates from its IP address. This covers your online activities from your ISP and creates the illusion that you’re located where the VPN server is. This can be particularly useful for accessing content that is region-restricted.
In a hosted VPN service, the server is maintained by a third-party provider, reducing the burden on your IT resources.
Advantages of Traditional VPNs
Traditional VPNs offer several benefits, including:
Security: Traditional VPNs use advanced encryption protocols to secure your data, protecting your information from hackers and other cyber threats.
Privacy: By masking your IP address, a VPN ensures that your online activities remain private.
Remote access: VPNs allow remote workers to securely access their company’s network from anywhere in the world.
Bypassing geo-restrictions: VPNs can make it appear as though you’re browsing from a different location, allowing you to access content that may be region-locked.
Cost-effective: Many VPN services are available at a relatively low cost, and the security benefits they provide can save businesses money in the long run by preventing data breaches.
Cloud VPN vs. Traditional VPN: the Main Differences
Regarding cloud VPN vs. traditional VPN, it’s essential to understand that both have strengths and weaknesses. However, the transition from traditional VPN to cloud VPN has really underscored how good the cloud is at addressing the limitations of traditional VPN technologies.
Cloud VPNs eliminate network choke points by allowing users to connect directly to the required network, whether cloud-based or on-premises. This direct connection reduces bandwidth consumption and latency, enhancing user experience.
Also, cloud VPNs centralize remote access security, simplifying setting up and maintaining security policies across all cloud platforms.
Unlike traditional VPNs, which have hard limits on bandwidth and user numbers, cloud VPNs can scale to meet changing business requirements. Still, as we delve deeper into the differences, you’ll see that the choice between cloud and traditional VPNs depends on your business’s needs.
Features
Cloud VPNs are known for their scalability, cost-efficiency, and enhanced security features. They’re implemented as cloud-based services, making them more flexible and globally accessible. On the other hand, traditional VPNs are network appliances that provide secure, remote access to company networks but may lack the flexibility and scalability of their cloud counterparts.
Performance
Performance is a key differentiator. Cloud VPNs, running in data centers, offer high-speed connections not limited by network speed, unlike hardware VPNs. They also eliminate backhaul, allowing users to connect directly to cloud-based networks, improving network performance and reducing latency.
Support
In terms of support, Cloud VPNs have an edge. They can quickly adopt new security features and vulnerability patches, making them more secure than on-premise VPNs. Traditional VPNs, however, may require more time and resources to implement such updates.
Pricing
Pricing is a significant factor in cloud VPN vs. traditional VPN. Cloud VPNs are generally more affordable, with usage-based VPN-as-a-Service (VPNaaS) fees being more cost-effective than the expenses associated with deploying, maintaining, and upgrading VPN hardware.
So, Which Should You Choose: A Cloud Vpn or a Traditional Vpn?
Choosing between a cloud VPN vs. a traditional VPN for your business largely depends on your specific needs and circumstances. However, it’s crucial to consider the evolution of technology and the increasing demand for robust, flexible, and secure networking solutions.
Cloud VPNs offer a more flexible and scalable solution than traditional VPNs. On the other hand, traditional VPNs have been a staple in the security landscape for decades.
However, as businesses adapt to an increasingly digital landscape, the demand for secure, remote access to resources is rising. This has led to the emergence of alternatives to both cloud VPN and traditional VPN.
Two such alternatives are:
Zero Trust Network Access (ZTNA): This modern approach to network access enhances security by verifying every connection attempt and limiting access privileges to only what users need to perform their tasks. This reduces the risk of data breaches and ensures a secure network environment.
Software-Defined Perimeter (SDP): Offering a flexible, scalable, and secure solution, the SDP model creates a dynamic, individualized perimeter for each user. This adaptability ensures robust security without compromising user experience, making it an attractive business option.
We offer a comprehensive solution that implements the Zero Trust model, providing businesses with a secure, flexible, and scalable alternative to both Cloud VPN and Traditional VPN. This solution combines the strengths of both ZTNA and SDP, ensuring that your business is equipped with the most robust and adaptable network security measures available today.
Ready to secure your business’s digital infrastructure and enhance your network’s performance? Want to benefit from a solution that aligns with your specific needs? Book a demo today!
By: Greg Young – Trendmicro August 03, 2023 Read time: 4 min (1014 words)
The US Securities and Exchange Commission (SEC) recently adopted rules regarding mandatory cybersecurity disclosure. Explore what this announcement means for you and your organization.
On July 26, 2023, the US Securities and Exchange Commission (SEC) adopted rules regarding mandatory cybersecurity disclosure. What does this mean for you and your organization? As I understand them, here are the major takeaways that cybersecurity and business leaders need to know:
Who does this apply to?
The rules announced apply only to registrants of the SEC i.e., companies filing documents with the US SEC. Not surprisingly, this isn’t limited to attacks on assets located within the US, so incidents concerning SEC registrant companies’ assets in other countries are in scope. This scope also, not surprisingly, does not include the government, companies not subject to SEC reporting (i.e., privately held companies), and other organizations.
Breach notification for these others will be the subject of separate compliance regimes, which will hopefully, at some point in time, be harmonized and/or unified to some degree with the SEC reporting.
Advice for security leaders: be aware that these new rules could require “double reporting,” such as for publicly traded critical infrastructure companies. Having multiple compliance regimes, however, is not new for cybersecurity.
What are the general disclosure requirements?
Some pundits have said “four days after an incident” but that’s not quite correct. The SEC says that “material breaches” must be reported “four business days after a registrant determines that a cybersecurity incident is material.”
We’ve hit the first squishy bit: materiality. Directing companies to disclose material events shouldn’t be necessary before there’s a mixed record of companies making materiality for public company operation. But what kind of cybersecurity incident would be likely to be important to a reasonable investor?
We’ve seen giant breaches that paradoxically did not move stock prices, and minor breaches that did the opposite. I’m clearly on the side of compliance and disclosure, but I recognize it is a gray area. Recently we saw some companies that had the MOVEit vulnerability exploited but had no data loss. Should they report? But in some cases, their response to the vulnerability was in the millions: how about then? I expect and hope there will be further guidance.
Advice for security leaders: monitor the breach investigation and monitor the analysis of materiality. Security leaders won’t often make that call but should give guidance and continuous updates to the CxO who are responsible.
The second squishy bit is that the requirement is the reporting should be made four days after determining the incident is material. So not four days after the incident, but after the materiality determination. I understand why it was structured this way, as a small indicator of compromise must be followed up before understanding the scope and nature of a breach, including whether a breach has occurred at all. But this does give a window to some of the foot-dragging for disclosure we’ve unfortunately seen, including product companies with vulnerabilities.
Advice for security leaders: make management aware of the four-day reporting requirement and monitor the clock once the material line is crossed or identified.
Are there extensions?
There are, but not because you need more time. Instead “The disclosure may be delayed if the United States Attorney General determines that immediate disclosure would pose a substantial risk to national security or public safety and notifies the Commission of such determination in writing.” Note that it specifically states that the Attorney General (AG) makes that determination, and the AG communicates this to the SEC. There could be some delegation of this authority within the Department of Justice in the future, but today it is the AG.
How does it compare to other countries and compliance regimes?
Breach and incident reporting and disclosure is not new, and the concept of reporting material events is already commonplace around the world. GDPR breach reporting is 72 hours, HHS HIPAA requires notice not later than 60 days and 90 days to individuals affected, and the UK Financial Conduct Authority (FCA) has breach reporting requirements. Canada has draft legislation in Bill C-26 that looks at mandatory reporting through the lens of critical industries, which includes verticals such as banking and telecoms but not public companies. Many of the world’s financial oversight bodies do not require breach notification for public companies in the exchanges they are responsible for.
Advice to security leaders: consider the new SEC rules as clarification and amplification of existing reporting requirements for material events rather than a new regime or something that is harsher or different to other geographies.
Is breach reporting the only new rule?
No, I’ve only focused on incident reporting in this post. There’s a few more. The two most noteworthy ones are:
Regulation S-K Item 106, requiring registrants to “describe their processes, if any, for assessing, identifying, and managing material risks from cybersecurity threats, as well as the material effects or reasonably likely material effects of risks from cybersecurity threats and previous cybersecurity incidents.”
Also specified is that annual 10-Ks “describe the board of directors’ oversight of risks from cybersecurity threats and management’s role and expertise in assessing and managing material risks from cybersecurity threats.”
Bottom line
SEC mandatory reporting for material cybersecurity events was already a requirement under the general reporting requirements, however the timelines and nature of the reporting are getting real and have a ticking four-day timer on them.
Stepping back from the rules, the importance of visibility and continuous monitoring are the real takeaways. Time to detection can’t be at the speed of your least experienced analyst. Platform means unified visibility rather than a wall of consoles. Finding and stopping breaches means internal visibility must include a rich array of telemetry, and that it be continuously monitored.
Many SEC registrants have operations outside the US, and that means visibility needs to include threat intelligence that is localized to other geographies. These new SEC rules show more than ever that that cyber risk is business risk.
To learn more about cyber risk management, check out the following resources:
By: Trend Micro August 08, 2023 Read time: 4 min (1020 words)
How generative AI influenced threat trends in 1H 2023
A lot can change in cybersecurity over the course of just six months in criminal marketplaces. In the first half of 2023, the rapid expansion of generative AI tools began to be felt in scams such as virtual kidnapping and tools by cybercriminals. Tools like WormGPT and FraudGPT are being marketed. The use of AI empowers adversaries to carry out more sophisticated attacks and poses a new set of challenges. The good news is that the same technology can also be used to empower security teams to work more effectively.
As we analyze the major events and patterns observed during this time, we uncover critical insights that can help businesses stay ahead of risk and prepare for the challenges that lie ahead in the second half of the year.
AI-Driven Tools in Cybercrime
The adoption of AI in organizations has increased significantly, offering numerous benefits. However, cybercriminals are also harnessing the power of AI to carry out attacks more efficiently.
As detailed in a Trend research report in June, virtual kidnapping is a relatively new and concerning type of imposter scam. The scammer extorts their victims by tricking them into believing they are holding a friend or family member hostage. In reality, it is AI technology known as a “deepfake,” which enables the fraudster to impersonate the real voice of the “hostage” whilst on the phone. Audio harvested from their social media posts will typically be used to train the AI model.
However, it is generative AI that’s playing an increasingly important role earlier on in the attack chain—by accelerating what would otherwise be a time-consuming process of selecting the right victims. To find those most likely to pay up when confronted with traumatic content, threat groups can use generative AI like ChatGPT to filter large quantities of potential victim data, fusing it with geolocation and advertising analytics. The result is a risk-based scoring system that can show scammers at a glance where they should focus their attacks.
This isn’t just theory. Virtual kidnapping scams are already happening. The bad news is that generative AI could be leveraged to make such attacks even more automated and effective in the future. An attacker could generate a script via ChatGPT to then convert to the hostage’s voice using deepfake and a text-to-speech app.
Of course, virtual kidnapping is just one of a growing number of scams that are continually being refined and improved by threat actors. Pig butchering is another type of investment fraud where the victim is befriended online, sometimes on romance sites, and then tricked into depositing their money into fictitious cryptocurrency schemes. It’s feared that these fraudsters could use ChatGPT and similar tools to improve their conversational techniques and perhaps even shortlist victims most likely to fall for the scams.
What to expect
The emergence of generative AI tools enables cybercriminals to automate and improve the efficiency of their attacks. The future may witness the development of AI-driven threats like DDoS attacks, wipers, and more, increasing the sophistication and scale of cyberattacks.
One area of concern is the use of generative AI to select victims based on extensive data analysis. This capability allows cybercriminals to target individuals and organizations with precision, maximizing the impact of their attacks.
Fighting back
Fortunately, security experts like Trend are also developing AI tools to help customers mitigate such threats. Trend pioneered the use of AI and machine learning for cybersecurity—embedding the technology in products as far back as 2005. From those early days of spam filtering, we began developing models designed to detect and block unknown threats more effectively.
Trend’s defense strategy
Most recently, we began leveraging generative AI to enhance security operations. Companion is a cybersecurity assistant designed to automate repetitive tasks and thereby free up time-poor analysts to focus on high-value tasks. It can also help to fill skills gaps by decoding complex scripts, triaging and recommending actions, and explaining and contextualizing alerts for SecOps staff.
What else happened in 1H 2023?
Ransomware: Adapting and Growing
Ransomware attacks are becoming sophisticated, with illegal actors leveraging AI-enabled tools to automate their malicious activities. One new player on the scene, Mimic, has abused legitimate search tools to identify and encrypt specific files for maximum impact. Meanwhile, the Royal ransomware group has expanded its targets to include Linux platforms, signaling an escalation in their capabilities.
According to Trend data, ransomware groups have been targeting finance, IT, and healthcare industries the most in 2023. From January 1 to July 17, 2023, there have been 219, 206, and 178 successful compromises of victims in these industries, respectively.
Our research findings revealed that ransomware groups are collaborating more frequently, leading to lower costs and increased market presence. Some groups are showing a shift in motivation, with recent attacks resembling those of advanced persistent threat (APT) groups. To combat these evolving threats, organizations need to implement a “shift left” strategy, fortifying their defenses to prevent threats from gaining access to their networks in the first place.
Vulnerabilities: Paring Down Cyber Risk Index
While the Cyber Risk Index (CRI) has lowered to a moderate range, the threat landscape remains concerning. Smaller platforms are exploited by threat actors, such as Clop ransomware targeting MOVEIt and compromising government agencies. New top-level domains by Google pose risks for concealing malicious URLs. Connected cars create new avenues for hackers. Proactive cyber risk management is crucial.
Campaigns: Evading Detection and Expanding Targets
Malicious actors are continually updating their tools, techniques and procedures (TTP) to evade detection and cast a wider net for victims. APT34, for instance, used DNS-based communication combined with legitimate SMTP mail traffic to bypass security policies. Meanwhile, Earth Preta has shifted its focus to target critical infrastructure and key institutions using hybrid techniques to deploy malware.
Persistent threats like the APT41 subgroup Earth Longzhi have resurfaced with new techniques, targeting firms in multiple countries. These campaigns require a coordinated approach to cyber espionage, and businesses must remain vigilant against such attacks.
By: Alifiya Sadikali – Trendmicro August 09, 2023 Read time: 4 min (1179 words)
Discover the core principles and frameworks of Zero Trust, NIST 800-207 guidelines, and best practices when implementing CISA’s Zero Trust Maturity Model.
With the growing number of devices connected to the internet, traditional security measures are no longer enough to keep your digital assets safe. To protect your organization from digital threats, it’s crucial to establish strong security protocols and take proactive measures to stay vigilant.
What is Zero Trust?
Zero Trust is a cybersecurity philosophy based on the premise that threats can arise internally and externally. With Zero Trust, no user, system, or service should automatically be trusted, regardless of its location within or outside the network. Providing an added layer of security to protect sensitive data and applications, Zero Trust only grants access to authenticated and authorized users and devices. And in the event of a data breach, compartmentalizing access to individual resources limits potential damage.
Your organization should consider Zero Trust as a proactive security strategy to protect its data and assets better.
The pillars of Zero Trust
At its core, the basis for Zero Trust is comprised of a few fundamental principles:
Verify explicitly. Only grant access once the user or device has been explicitly authenticated and verified. By doing so, you can ensure that only those with a legitimate need to access your organization’s resources can do so.
Least privilege access. Only give users access to the resources they need to do their job and nothing more. Limiting access in this way prevents unauthorized access to your organization’s data and applications.
Assume breach. Act as if a compromise to your organization’s security has occurred. Take steps to minimize the damage, including monitoring for unusual activity, limiting access to sensitive data, and ensuring that backups are up-to-date and secure.
Microsegmentation. Divide your organization’s network into smaller, more manageable segments and apply security controls to each segment individually. This reduces the risk of a breach spreading from one part of your network to another.
Security automation. Use tools and technologies to automate the process of monitoring, detecting, and responding to security threats. This ensures that your organization’s security is always up-to-date and can react quickly to new threats and vulnerabilities.
A Zero Trust approach is a proactive and effective way to protect your organization’s data and assets from cyber-attacks and data breaches. By following these core principles, your organization can minimize the risk of unauthorized access, reduce the impact of a breach, and ensure that your organization’s security is always up-to-date and effective.
The role of NIST 800-207 in Zero Trust
NIST 800-207 is a cybersecurity framework developed by the National Institute of Standards and Technology. It provides guidelines and best practices for organizations to manage and mitigate cybersecurity risks.
Designed to be flexible and adaptable for a variety of organizations and industries, the framework supports the customization of cybersecurity plans to meet their specific needs. Its implementation can help organizations improve their cybersecurity posture and protect against cyber threats.
One of the most important recommendations of NIST 800-207 is to establish a policy engine, policy administrator, and policy enforcement point. This will help ensure consistent policy enforcement and that access is granted only to those who need it.
Another critical recommendation is conducting continuous monitoring and having real-time risk-based decision-making capabilities. This can help you quickly identify and respond to potential threats.
Additionally, it is essential to understand and map dependencies among assets and resources. This will help you ensure your security measures are appropriately targeted based on potential vulnerabilities.
Finally, NIST recommends replacing traditional paradigms, such as implicit trust in assets or entities, with a “trust but verify” methodology. Adopting this approach can better protect your organization’s assets and resources from internal and external threats.
CISA’s Zero Trust Maturity Model
The Zero Trust Maturity Model (ZMM), developed by CISA, provides a comprehensive framework for assessing an organization’s Zero Trust posture. This model covers critical areas including:
Identity management: To implement a Zero Trust strategy, it is important to begin with identity. This involves continuously verifying, authenticating, and authorizing any entity before granting access to corporate resources. To achieve this, comprehensive visibility is necessary.
Devices, networks, applications: To maintain Zero Trust, use endpoint detection and response capabilities to detect threats and keep track of device assets, network connections, application configurations, and vulnerabilities. Continuously assess and score device security posture and implement risk-informed authentication protocols to ensure only trusted devices, networks and applications can access sensitive data and enterprise systems.
Data and governance: To maximize security, implement prevention, detection, and response measures for identity, devices, networks, IoT, and cloud. Monitor legacy protocols and device encryption status. Apply Data Loss Prevention and access control policies based on risk profiles.
Visibility and analytics: Zero Trust strategies cannot succeed within silos. By collecting data from various sources within an organization, organizations can gain a complete view of all entities and resources. This data can be analyzed through threat intelligence, generating reliable and contextualized alerts. By tracking broader incidents connected to the same root cause, organizations can make informed policy decisions and take appropriate response actions.
Automation and orchestration: To effectively automate security responses, it is important to have access to comprehensive data that can inform the orchestration of systems and manage permissions. This includes identifying the types of data being protected and the entities that are accessing it. By doing so, it ensures that there is proper oversight and security throughout the development process of functions, products, and services.
By thoroughly evaluating these areas, your organization can identify potential vulnerabilities in its security measures and take prompt action to improve your overall cybersecurity posture. CISA’s ZMM offers a holistic approach to security that will enable your organization to remain vigilant against potential threats.
Implementing Zero Trust with Trend Vision One
Trend Vision One seamlessly integrates with third-party partner ecosystems and aligns to industry frameworks and best practices, including NIST and CISA, offering coverage from prevention to extended detection and response across all pillars of zero trust.
Trend Vision One is an innovative solution that empowers organizations to identify their vulnerabilities, monitor potential threats, and evaluate risks in real-time, enabling them to make informed decisions regarding access control. With its open platform approach, Trend enables seamless integration with third-party partner ecosystems, including IAM, Vulnerability Management, Firewall, BAS, and SIEM/SOAR vendors, providing a comprehensive and unified source of truth for risk assessment within your current security framework. Additionally, Trend Vision One is interoperable with SWG, CASB, and ZTNA and includes Attack Surface Management and XDR, all within a single console.
Conclusion
CISOs today understand that the journey towards achieving Zero Trust is a gradual process that requires careful planning, step-by-step implementation, and a shift in mindset towards proactive security and cyber risk management. By understanding the core principles of Zero Trust and utilizing the guidelines provided by NIST and CISA to operationalize Zero Trust with Trend Vision One, you can ensure that your organization’s cybersecurity measures are strong and can adapt to the constantly changing threat landscape.
To read more thought leadership and research about Zero Trust, click here.
By: William Malik – Trendmicro August 14, 2023 Read time: 4 min (1014 words)
Rethinking learning metrics and fostering critical thinking in the era of generative AI and LLMs
I recently participated in a conversation about artificial intelligence, specifically ChatGPT and its kin, with a group of educators in South Africa. They were concerned that the software would help students cheat.
We discussed two possible alternatives to ChatGPT: First, teachers could require that students submit handwritten homework. This would force students to at least read the material once before submitting it; Second, teachers could grade the paper submissions no higher than 89 percent (or a “B”), but that to get an “A,” the student would have to stand in front of the class and verbally discuss the material, their research, their conclusion, and answer any questions the teacher or other classmates might ask. (With that verbal defense of the ideas, the teacher might even waive the requirement for paper submission at all!)
The fundamental problem is that the grading system depends on homework. If education aims to teach an individual both a) a body of knowledge and b) the techniques of reasoning with that knowledge, then the metrics proving that achievement is misaligned.
One of the most quoted management scientists is Fredrick W. Taylor. He is most known for saying, “If you can’t measure it, you can’t manage it.” Interestingly, he never said that – which is fortunate because it is entirely wrong. People always manage things without metrics – from driving a car to raising children. He said: “If you measure it, you’ll manage it” – and he intended that as a warning. Whenever you adopt a metric, you will adjust your assessment of the underlying process in terms of your chosen metric. His warning is to be very careful about which metrics you choose.
Sometime in the past forty years, we decided that the purpose of education is to do well on tests. Unfortunately, that is also wrong. The purpose of education is to teach people to gather evidence and to think clearly about it. Students should learn how to judge various forms of evidence. They should understand rhetorical techniques (in the classical sense – how to render ideas clearly). They should be aware of common errors in thinking – the cognitive pitfalls we all fall into when rushed or distracted and logical fallacies which rob our arguments of their validity.
Large Language Models (LLMs) aggregate vast troves of text. Those data sources are not curated, so LLMs reflect the biases, logical limitations, and cognitive distortions in so much of what’s online. We are all familiar with early chatbots that were easily corrupted – the Microsoft chatbot Tay was perverted into being a racist resonator. (See “Twitter taught Microsoft’s AI Chatbot to be a Racist A**hole in Less than a Day” from The Verge, March 24, 2016, at https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist accessed Aug 2023.)
LLMs do not think. They scan as much material as possible, then build a set of probabilities about which word is most likely to follow another word. If the word “pterodactyl” occurs in a text, then the next most likely word might be “soaring,” and “flying” might be in second place. If ChatGPT gets the word “pterodactyl” as input, it will put “soaring” next to it. This may look plausible to a person reading the output, but it cannot be correct. Correctness implies some kind of comprehension and judgment. ChatGPT does neither. It merely arranges words based on their statistical likelihood in the LLM’s database. We are now learning that LLMs that ingest computer-generated content become even more skewed – augmenting the likelihood of one word following another by rescanning the previous output. Over time, LLMs fed AI-generated content will drift farther and farther from actual human writing. The oft-mentioned hallucinations that LLMs generate will become more common as the distillation and amplification of the more likely subset of words leads to a contracted pool of possible machine-generated responses. Eventually – if we are not able to prevent LLMs from ingesting already-processed content – the output of ChatGPT will become more and more constrained, which, taken to the extreme, will yield one plot, one answer, one painting, and one outcome regardless of the specific input. Long before then, people will have abandoned LLM-based efforts for any activity that requires creativity.
Where can LLMs help? By sorting through bounded sets of information. That means an LLM trained on protein sequences could rapidly develop a most likely model for a protein that could attack a particular disease or interrupt an allergic reaction. In that case, the issue isn’t seeking creativity but rapidly scanning a set of nearly identical data overreactions to find the few that stand out enough to make a difference. A human doing this kind of work would quickly grow bored and likely make errors. LLMs can help science move quickly through vast quantities of data in closed domains. But when looking at an unbounded domain (art, poetry, fiction, movies, music, and the like), LLMs can only build average content, filling in the space between works. Artists seek to reach beyond the space their prior work defined.
The core problem with LLMs may be unsolvable. At this point, various organizations are exploring ways to tag AI-generated content (written and graphic) so humans can spend a moment assessing the accuracy and validity of the material. Of course, message digests can be corrupted and watermarks forged. A bad actor might maliciously tag authentic content as AI-generated. Recent developments include malicious ChatGPT variants designed to create BEC and phishing email content,
Students will always look for a shortcut, and that habit is difficult to overcome. In business, it will also be tempting for bureaucrats to use tools to simplify their tasks. How will your firm incorporate LLMs safely into your business processes? Organizations should consider how they will audit their internal procedures to ensure that LLM outputs are incorporated appropriately into communications. Imagine the potential for harm if some publicly traded company was found to have used an LLM to develop its annual financial report!
What do you think? Let me know in the comments below, or contact me @wjmalik@noc.social
By: Kazuhisa Tagaya – Trendmicro August 14, 2023 Read time: 2 min (638 words)
The latest study said that OT security is less mature in several capabilities than IT security, but most organizations are improving it.
e asked participants whether OT security for cybersecurity capabilities is less mature or more mature than IT in their organizations with reference to the NIST CSF.
As an average of all items, 39.5% answered that OT has a lower level of maturity. (18% answered OT security is more mature, and 36.4% at the same level)
Categorizing security capabilities into the five cores of the NIST CSF and aggregating them for each core, the most was that Detect is lower maturity in OT security than in IT. (42%)
Figure1: What security capabilities in OT are lower than IT (NIST CSF 5 Core)
Furthermore, looking at the specific security capabilities, the score of “Cyber event detection” is the most(45.7%).
Figure2: What security capabilities in OT are lower than IT (detail)
The OT environment has more diverse legacy assets, and protocol stacks dedicated to ICS/OT, making it difficult to implement sensors to detect malicious behavior or apply the patches on the assets. The inability to implement uniform measures in the same way as IT security is an obstacle to increasing the maturity level.
Detection in OT: Endpoint and Network
The survey asked respondents about their Endpoint Detection and Response (EDR) and Network Security Monitoring (NSM) implementations to measure their visibility in their OT environments. They answered whether EDR (including antivirus) was implemented in the following three places.
Server assets running commercial OS (Windows, Linux, Unix): 41%
Engineering (engineering workstations, instrumentation laptops, calibration and test equipment) assets running commercial OS (Windows, Unix, Linux): 34%
In addition, 76% of organizations that have already deployed EDR said they plan to expand their deployment within 24 months.
Figure3: EDR deployment
We also asked whether NSM (including IDS) was implemented at the following levels referring to the Purdue model.
Purdue Level 4 (Enterprise): 30%
Purdue Level 3.5 (DMZ): 36%
Purdue Level 3 (Site or SCADA-wide): 38%
Purdue Level 2 (Control): 20%
Purdue Levels 1/0 (Sensors and Actuators): 8%
Like EDR, 70% of organizations that have already implemented NSM said they have plans to expand implementation within 24 months.
Figure4: NSM deployment
In this survey, EDR implementation rates tended to vary depending on the respondent’s industry and size of organization. The implementation rate of NSM was relatively high in DMZ and Level 3, and the implementation rate decreased according to the lower layers. But I think it is not appropriate to conclude the decisive trend from the average value in the questions, because there are variations in the places where they are implemented EDR and NSM depending on the organization. The implementation rate shown here is just a rough standard. Where and how much to invest depends on the environment and decision-making of the organization. Asset owners can use the result as a reference to see where to implement EDR and NSM and evaluate their implementation plans.
By: Trend Micro August 15, 2023 Read time: 4 min (1157 words)
The unveiling of the first-ever Open Worldwide Application Security Project (OWASP) risk list for large language model AI chatbots was yet another sign of generative AI’s rush into the mainstream—and a crucial step toward protecting enterprises from AI-related threats.
For more than 20 years, the Open Worldwide Application Security Project (OWASP) top 10 risk list has been a go-to reference in the fight to make software more secure. So it’s no surprise developers and cybersecurity professionals paid close attention earlier this spring when OWASP published an all-new list focused on large language model AI vulnerabilities.
OWASP’s move is yet more proof of how quickly AI chatbots have swept into the mainstream. Nearly half (48%) of corporate respondents to one survey said that by February 2023 they had already replaced workers with ChatGPT—just three months after its public launch. With many observers expressing concern that AI adoption has rushed ahead without understanding of the risks involved, the OWASP top 10 AI risk list is both timely and essential.
Large language model vulnerabilities at a glance
OWASP has released two draft versions of its AI vulnerability list so far: one in May 2023 and a July 1 update with refined classifications and definitions, examples, scenarios, and links to additional references. The most recent is labeled ‘version 0.5’, and a formal version 1 is reported to be in the works.
We did some analysis and found the vulnerabilities identified by OWASP fall broadly into three categories:
Access risks associated with exploited privileges and unauthorized actions.
Data risks such as data manipulation or loss of services.
Reputational and business risks resulting from bad AI outputs or actions.
In this blog, we take a closer look at the specific risks in each case and offer some suggestions about how to handle them.
1. Access risks
Of the 10 vulnerabilities listed by OWASP, four are specific to access and misuse of privileges: insecure plugins, insecure output handling, permissions issues, and excessive agency.
According to OWASP, any large language model that uses insecure plugins to receive “free-form text” inputs could be exposed to malicious requests, resulting in unwanted behaviors or the execution of unauthorized remote code. On the flipside, plugins or applications that handle large language model outputs insecurely—without evaluating them—could be susceptible to cross-site and server-side request forgeries, unauthorized privilege escalations, hijack attacks, and more.
Similarly, when authorizations aren’t tracked between plugins, permissions issues can arise that open the way for indirect prompt injections or malicious plugin usage.
Finally, because AI chatbots are ‘actors’ able to make and implement decisions, it matters how much free reign (i.e., agency) they’re given. As OWASP explains, “When LLMs interface with other systems, unrestricted agency may lead to undesirable operations and actions.” Examples include personal mail reader assistants being exploited to propagate spam or customer service AI chatbots manipulated into issuing undeserved refunds.
In all of these cases, the large language model becomes a conduit for bad actors to infiltrate systems.
2. Data risks
Poisoned training data, supply chain vulnerabilities, prompt injection vulnerabilities and denials of serviceare all data-specific AI risks.
Data can be poisoned deliberately by bad actors who want to harm an organization. It can also be distorted inadvertently when an AI system learns from unreliable or unvetted sources. Both types of poisoning can occur within an active AI chatbot application or emerge from the large language model supply chain, where reliance on pre-trained models, crowdsourced data, and insecure plugin extensions may produce biased data outputs, security breaches, or system failures.
With prompt injections, ill-meaning inputs may cause a large language model AI chatbot to expose data that should be kept private or perform other actions that lead to data compromises.
AI denial of service attacks are similar to classic DOS attacks. They may aim to overwhelm a large language model and deprive users of access to data and apps, or—because many AI chatbots rely on pay-as-you-go IT infrastructure—force the system to consume excessive resources and rack up massive costs.
3. Reputational and business risks
The final OWASP vulnerability (according to our buckets) is already reaping consequences around the world today:overreliance on AI. There’s no shortage of stories about large language models generating false or inappropriate outputs from fabricated citations and legal precedents to racist and sexist language.
OWASP points out that depending on AI chatbots without proper oversight can make organizations vulnerable to publishing misinformation or offensive content that results in reputational damage or even legal action. Given all these various risks, the question becomes, “What can we do about it?” Fortunately, there are some protective steps organizations can take.
What enterprises can do about large language model vulnerabilities
From our perspective at Trend Micro, defending against AI access risks requires a zero-trust security stance with disciplined separation of systems (sandboxing). Even though generative AI has the ability to challenge zero-trust defenses in ways that other IT systems don’t—because it can mimic trusted entities—a zero-trust posture still adds checks and balances that make it easier to identify and contain unwanted activity. OWASP also advises that large language models “should not self-police” and calls for controls to be embedded in application programming interfaces (APIs).
Sandboxing is also key to protecting data privacy and integrity: keeping confidential information fully separated from shareable data and making it inaccessible to AI chatbots and other public-facing systems. (See our recent blog on AI cybersecurity policies for more.)
Good separation of data prevents large language models from including private or personally identifiable information in public outputs, and from being publicly prompted to interact with secure applications such as payment systems in inappropriate ways.
On the reputational front, the simplest remedies are to not rely solely on AI-generated content or code, and to never publish or use AI outputs without first verifying they are true, accurate, and reliable.
Many of these defensive measures can—and should—be embedded in corporate policies. Once an appropriate policy foundation is in place, security technologies such as endpoint detection and response (EDR), extended detection and response (XDR), and security information and event management (SIEM) can be used for enforcement and to monitor for potentially harmful activity.
Large language model AI chatbots are here to stay
OWASP’s initial work cataloguing AI risks proves that concerns about the rush to embrace AI are well justified. At the same time, AI clearly isn’t going anywhere, so understanding the risks and taking responsible steps to mitigate them is critically important.
Setting up the right policies to manage AI use and implementing those policies with the help of cybersecurity solutions is a good first step. So is staying informed. The way we see it at Trend Micro, OWASP’s top 10 AI risk list is bound to become as much of an annual must-read as its original application security list has been since 2003.
Next steps
For more Trend Micro thought leadership on AI chatbot security, check out these resources:
By: Trend Micro August 18, 2023 Read time: 3 min (931 words)
Private 5G networks offer businesses enhanced security, reliability, and scalability. Learn more about why private 5G could be the future of secure networking.
Private 5G networks offer businesses enhanced security, reliability, and scalability. Learn more about why private 5G could be the future of secure networking.
By: Trend Micro Research August 09, 2023 Read time: 7 min (1966 words)
Updated on August 9, 2023, 9:30 a.m. EDT: We updated the entry to include an analysis of current Rhysida ransomware samples’ encryption routine. Updated on August 14, 2023, 6:00 a.m. EDT: We updated the entry to include Trend XDR workbench alerts for Rhysida and its components.
Introduction
On August 4, 2023, the HHS’ Health Sector Cybersecurity Coordination Center (HC3) released a security alert about a relatively new ransomware called Rhysida (detected as Ransom.PS1.RHYSIDA.SM), which has been active since May 2023. In this blog entry, we will provide details on Rhysida, including its targets and what we know about its infection chain.
Who is behind the Rhysida ransomware?
Not much is currently known about the threat actors behind Rhysida in terms of origin or affiliations. According to the HC3 alert, Rhysida poses itself as a “cybersecurity team” that offers to assist victims in finding security weaknesses within their networks and system. In fact, the group’s first appearance involved the use of a victim chat support portal.
Who are Rhysida’s targets?
As mentioned earlier, Rhysida, which was previously known for targeting the education, government, manufacturing, and tech industries, among others — has begun conducting attacks on healthcare and public health organizations. The healthcare industry has seen an increasing number of ransomware attacks over the past five years. This includes a recent incident involving Prospect Medical Holdings, a California-based healthcare system, that occurred in early August (although the group behind the attack has yet to be named as of writing).
Data from Trend Micro™ Smart Protection Network™ (SPN) shows a similar trend, where detections from May to August 2023 show that its operators are targeting multiple industries rather than focusing on just a single sector.
The threat actor also targets organizations around the world, with SPN data showing several countries where Rhysida binaries were detected, including Indonesia, Germany, and the United States.
Figure 1. The industry and country detection count for Rhysida ransomware based on Trend SPN data from May to August 2023
How does a Rhysida attack proceed?
Figure 2. The Rhysida ransomware infection chain
Rhysida ransomware usually arrives on a victim’s machine via phishing lures, after which Cobalt Strike is used for lateral movement within the system.
Additionally, our telemetry shows that the threat actors execute PsExec to deploy PowerShell scripts and the Rhysida ransomware payload itself. The PowerShell script (g.ps1), detected as Trojan.PS1.SILENTKILL.A, is used by the threat actors to terminate antivirus-related processes and services, delete shadow copies, modify remote desktop protocol (RDP) configurations, and change the active directory (AD) password.
Interestingly, it appears that the script (g.ps1) was updated by the threat actors during execution, eventually leading us to a PowerShell version of the Rhysida ransomware.
Rhysida ransomware employs a 4096-bit RSA key and AES-CTR for file encryption, which we discuss in detail in a succeeding section. After successful encryption, it appends the .rhysida extension and drops the ransom note CriticalBreachDetected.pdf.
This ransom note is fairly unusual — instead of an outright ransom demand as seen in most ransom notes from other ransomware families, the Rhysida ransom note is presented as an alert from the Rhysida “cybersecurity team” notifying victims that their system has been compromised and their files encrypted. The ransom demand comes in the form of a “unique key” designed to restore encrypted files, which must be paid for by the victim.
Summary of malware and tools used by Rhysida
Malware: RHYSIDA, SILENTKILL, Cobalt Strike
Tools: PsExec
Initial Access
Phishing
Based on external reports, Rhysida uses phishing lures for initial access
Lateral Movement
PsExec
Microsoft tool used for remote execution
Cobalt Strike
3rd party tool abused for lateral movement
Defense Evasion
SILENTKILL
Malware deployed to terminate security-related processes and services, delete shadow copies, modify RDP configurations, and change the AD password
Impact
Rhysida ransomware
Ransomware encryption
Table 1. A summary of the malware, tools, and exploits used by Rhysida
A closer look at Rhysida’s encryption routine After analyzing current Rhysida samples, we observed that the ransomware uses LibTomCrypt, an open-source cryptographic library, to implement its encryption routine. Figure 3 shows the procedures Rhysida follows when initializing its encryption parameters.
Figure 3. Rhysida’s parameters for encryption
Rhysida uses LibTomCrypt’s pseudorandom number generator (PRNG) functionalities for key and initialization vector (IV) generation. The init_prng function is used to initialize PRNG functionalities as shown in Figure 4. The same screenshot also shows how the ransomware uses the library’s ChaCha20 PRNG functionality.
Figure 4. Rhysida’s use of the “init_prng” function
After the PRNG is initialized, Rhysida then proceeds to import the embedded RSA key and declares the encryption algorithm it will use for file encryption:
It will use the register_cipher function to “register” the algorithm (in this case, aes), to its table of usable ciphers.
It will use the find_cipher function to store the algorithm to be used (still aes), in the variable CIPHER.
Afterward, it will proceed to also register and declare aes for its Cipher Hash Construction (CHC) functionalities.
Based on our analysis, Rhysida’s encryption routine follows these steps:
After it reads file contents for encryption, it will use the initialized PRNG’s function, chacha20_prng_read, to generate both a key and an IV that are unique for each file.
It will use the ctr_start function to initialize the cipher that will be used, which is aes (from the variable CIPHER), in counter or CTR mode.
The generated key and IV are then encrypted with the rsa_encrypt_key_ex function.
Once the key and IV are encrypted, Rhysida will proceed to encrypt the file using LibTomCrypt’s ctr_encrypt function.
Figure 5. Rhysida’s encryption routine
Unfortunately, since each encrypted file has a unique key and IV — and only the attackers have a copy of the associated private key — decryption is currently not feasible.
How can organizations protect themselves from Rhysida and other ransomware families?
Although we are still in the process of fully analyzing Rhysida ransomware and its tools, tactics, and procedures (TTPs), the best practices for defending against ransomware attacks still holds true for Rhysida and other ransomware families.
Here are several recommended measures that organizations implement to safeguard their systems from ransomware attacks:
Create an inventory of assets and data
Review event and incident logs
Manage hardware and software configurations.
Grant administrative privileges and access only when relevant to an employee’s role and responsibilities.
Enforce security configurations on network infrastructure devices like firewalls and routers.
Establish a software whitelist permitting only legitimate applications
Perform routine vulnerability assessments
Apply patches or virtual patches for operating systems and applications
Keep software and applications up to date using their latest versions
Integrate data protection, backup, and recovery protocols
Utilize sandbox analysis to intercept malicious emails
Regularly educate and evaluate employees’ security aptitude
Deploy security tools (such as XDR) which are capable of detecting abuse of legitimate applications
Indicators of compromise
Hashes
The indicators of compromise for this entry can be found here.
MITRE ATT&CK Matrix
Initial Access
T1566 Phishing
Based on external reports, Rhysida uses phishing lures for initial access.
Execution
T1059.003 Command and Scripting Interpreter: Windows Command Shell
It uses cmd.exe to execute commands for execution.
T1059.001 Command and Scripting Interpreter: PowerShell
It uses PowerShell to create scheduled task named Rhsd pointing to the ransomware.
Persistence
T1053.005 Scheduled Task/Job: Scheduled Task
When executed with the argument -S, it will create a scheduled task named Rhsd that will execute the ransomware
Defense Evasion
T1070.004 Indicator Removal: File Deletion
Rhysida ransomware deletes itself after execution. The scheduled task (Rhsd) created would also be deleted after execution.
T1070.001 Indicator Removal: Clear Windows Event Logs
It uses wevtutil.exe to clear Windows event logs.
Discovery
T1083 File and Directory Discovery
It enumerates and looks for files to encrypt in all local drives.
T1082 System Information Discovery
Obtains the following information:Number of processorsSystem information
Impact
T1490 Inhibit System Recovery
It executes uses vssadmin to remove volume shadow copies
T1486 Data Encrypted for Impact
It uses a 4096-bit RSA key and Cha-cha20 for file encryption.It avoids encrypting files with the following strings in their file name:.bat.bin.cab.cmd.com.cur.diagcab.diagcfg.diagpkg.drv.dll.exe.hlp.hta.ico.msi.ocx.ps1.psm1.scr.sys.ini.Thumbs.db.url.isoIt avoids encrypting files found in the following folders:$Recycle.BinBootDocuments and SettingsPerfLogsProgramDataRecoverySystem Volume InformationWindows$RECYCLE.BINApzDataIt appends the following extension to the file name of the encrypted files:.rhysidaIt encrypts all system drives from A to Z.It drops the following ransom note:{Encrypted Directory}\CriticalBreachDetected.pdf
T1491.001 Defacement: Internal Defacement
It changes the desktop wallpaper after encryption and prevents the user from changing it back by modifying the NoChangingWallpaper registry value.
As ransomware attacks continue to grow in number and sophistication, threat actors can quickly impact business operations if organizations are not well prepared. In a recent investigation by Microsoft Incident Response (previously known as Microsoft Detection and Response Team – DART) of an intrusion, we found that the threat actor progressed through the full attack chain, from initial access to impact, in less than five days, causing significant business disruption for the victim organization.
Our investigation found that within those five days, the threat actor employed a range of tools and techniques, culminating in the deployment of BlackByte 2.0 ransomware, to achieve their objectives. These techniques included:
Exploitation of unpatched internet-exposed Microsoft Exchange Servers
Web shell deployment facilitating remote access
Use of living-off-the-land tools for persistence and reconnaissance
Deployment of Cobalt Strike beacons for command and control (C2)
Process hollowing and the use of vulnerable drivers for defense evasion
Deployment of custom-developed backdoors to facilitate persistence
Deployment of a custom-developed data collection and exfiltration tool
Figure 1. BlackByte 2.0 ransomware attack chain
In this blog, we share details of our investigation into the end-to-end attack chain, exposing security weaknesses that the threat actor exploited to advance their attack. As we learned from Microsoft’s tracking of ransomware attacks and the cybercriminal economy that enables them, disrupting common attack patterns could stop many of the attacker activities that precede ransomware deployment. This case highlights that common security hygiene practices go a long way in preventing, identifying, and responding to malicious activity as early as possible to mitigate the impact of ransomware attacks. We encourage organizations to follow the outlined mitigation steps, including ensuring that internet-facing assets are up to date and configured securely. We also share indicators of compromise, detection details, and hunting guidance to help organizations identify and respond to these attacks in their environments.
Forensic analysis
Initial access and privilege escalation
To obtain initial access into the victim’s environment, the threat actor was observed exploiting the ProxyShell vulnerabilities CVE-2021-34473, CVE-2021-34523, and CVE-2021-31207 on unpatched Microsoft Exchange Servers. The exploitation of these vulnerabilities allowed the threat actor to:
Attain system-level privileges on the compromised Exchange host
Enumerate LegacyDN of users by sending Autodiscover requests, including SIDs of users
Construct a valid authentication token and use it against the Exchange PowerShell backend
Impersonate domain admin users and create a web shell by using the New-MailboxExportRequest cmdlet
Create web shells to obtain remote control on affected servers
The threat actor was observed operating from the following IP to exploit ProxyShell and access the web shell:
185.225.73[.]244
Persistence
Backdoor
After gaining access to a device, the threat actor created the following registry run keys to run a payload each time a user signs in:
The file api-msvc.dll (SHA-256: 4a066569113a569a6feb8f44257ac8764ee8f2011765009fdfd82fe3f4b92d3e) was determined to be a backdoor capable of collecting system information, such as the installed antivirus products, device name, and IP address. This information is then sent via HTTP POST request to the following C2 channel:
hxxps://myvisit[.]alteksecurity[.]org/t
The organization was not using Microsoft Defender Antivirus, which detects this malware as Trojan:Win32/Kovter!MSR, as the primary antivirus solution, and the backdoor was allowed to run.
An additional file, api-system.png, was identified to have similarities to api-msvc.dll. This file behaved like a DLL, had the same default export function, and also leveraged run keys for persistence.
Cobalt Strike Beacon
The threat actor leveraged Cobalt Strike to achieve persistence. The file sys.exe (SHA-256: 5f37b85687780c089607670040dbb3da2749b91b8adc0aa411fd6280b5fa7103), detected by Microsoft Defender Antivirus as Trojan:Win64/CobaltStrike!MSR, was determined to be a Cobalt Strike Beacon and was downloaded directly from the file sharing service temp[.]sh:
hxxps://temp[.]sh/szAyn/sys.exe
This beacon was configured to communicate with the following C2 channel:
109.206.243[.]59:443
AnyDesk
Threat actors leverage legitimate remote access tools during intrusions to blend into a victim network. In this case, the threat actor utilized the remote administration tool AnyDesk, to maintain persistence and move laterally within the network. AnyDesk was installed as a service and was run from the following paths:
C:\systemtest\anydesk\AnyDesk.exe
C:\Program Files (x86)\AnyDesk\AnyDesk.exe
C:\Scripts\AnyDesk.exe
Successful connections were observed in the AnyDesk log file ad_svc.trace involving anonymizer service IP addresses linked to TOR and MULLVAD VPN, a common technique that threat actors employ to obscure their source IP ranges.
Reconnaissance
We found the presence and execution of the network discovery tool NetScan being used by the threat actor to perform network enumeration using the following file names:
Additionally, execution of AdFind (SHA-256: f157090fd3ccd4220298c06ce8734361b724d80459592b10ac632acc624f455e), an Active Directory reconnaissance tool, was observed in the environment.
Credential access
Evidence of likely usage of the credential theft tool Mimikatzwas also uncovered through the presence of a related log file mimikatz.log. Microsoft IR assesses that Mimikatz was likely used to attain credentials for privileged accounts.
Lateral movement
Using compromised domain admin credentials, the threat actor used Remote Desktop Protocol (RDP) and PowerShell remoting to obtain access to other servers in the environment, including domain controllers.
Data staging and exfiltration
In one server where Microsoft Defender Antivirus was installed, a suspicious file named explorer.exe was identified, detected as Trojan:Win64/WinGoObfusc.LK!MT, and quarantined. However, because tamper protection wasn’t enabled on this server, the threat actor was able to disable the Microsoft Defender Antivirus service, enabling the threat actor to run the file using the following command:
explorer.exe P@$$w0rd
After reverse engineering explorer.exe, we determined it to be ExByte, a GoLang-based tool developed and commonly used in BlackByte ransomware attacks for collection and exfiltration of files from victim networks. This tool is capable of enumerating files of interest across the network and, upon execution, creates a log file containing a list of files and associated metadata. Multiple log files were uncovered during the investigation in the path:
C:\Exchange\MSExchLog.log
Analysis of the binary revealed a list of file extensions that are targeted for enumeration.
Figure 2. Binary analysis showing file extensions enumerated by explorer.exe
Forensic analysis identified a file named data.txt that was created and later deleted after ExByte execution. This file contained obfuscated credentials that ExByte leveraged to authenticate to the popular file sharing platform Mega NZ using the platform’s API at:
hxxps://g.api.mega.co[.]nz
Figure 3. Binary analysis showing explorer.exe functionality for connecting to file sharing service MEGA NZ
We also determined that this version of Exbyte was crafted specifically for the victim, as it contained a hardcoded device name belonging to the victim and an internal IP address.
ExByte execution flow
Upon execution, ExByte decodes several strings and checks if the process is running with privileged access by reading \\.\PHYSICALDRIVE0:
If this check fails, ShellExecuteW is invoked with the IpOperation parameter RunAs, which runs explorer.exe with elevated privileges.
After this access check, explorer.exe attempts to read the data.txt file in the current location:
If the text file doesn’t exist, it invokes a command for self-deletion and exits from memory:
If data.txt exists, explorer.exe reads the file, passes the buffer to Base64 decode function, and then decrypts the data using the key provided in the command line. The decrypted data is then parsed as JSON below and fed for login function:
{“a”:”us0”,“user”:”<CONTENT FROM data.txt>”}
Finally, it forms a URL for sign-in to the API of the service MEGA NZ:
hxxps://g.api.mega.co[.]nz/cs?id=1674017543
Data encryption and destruction
On devices where files were successfully encrypted, we identified suspicious executables, detected by Microsoft Defender Antivirus as Trojan:Win64/BlackByte!MSR, with the following names:
wEFT.exe
schillerized.exe
The files were analyzed and determined to be BlackByte 2.0 binaries responsible for encryption across the environment. The binaries require an 8-digit key number to encrypt files.
Two modes of execution were identified:
When the -s parameter is provided, the ransomware self-deletes and encrypts the machine it was executed on.
When the -a parameter is provided, the ransomware conducts enumeration and uses an Ultimate Packer Executable (UPX) packed version of PsExec to deploy across the network. Several domain admin credentials were hardcoded in the binary, facilitating the deployment of the binary across the network.
Depending on the switch (-s or -a), execution may create the following files:
C:\SystemData\M8yl89s7.exe (UPX-packed PsExec with a random name; SHA-256: ba3ec3f445683d0d0407157fda0c26fd669c0b8cc03f21770285a20b3133098f)
C:\SystemData\rENEgOtiAtES (A vulnerable (CVE-2019-16098) driver RtCore64.sys used to evade detection by installed antivirus software; SHA-256: 01aa278b07b58dc46c84bd0b1b5c8e9ee4e62ea0bf7a695862444af32e87f1fd)
C:\SystemData\iHu6c4.ico (Random name – BlackBytes icon)
Some capabilities identified for the BlackByte 2.0 ransomware were:
Antivirus bypass
The file rENEgOtiAtES created matches RTCore64.sys, a vulnerable driver (CVE-2049-16098) that allows any authenticated user to read or write to arbitrary memory
The BlackByte binary then creates and starts a service named RABAsSaa calling rENEgOtiAtES, and exploits this service to evade detection by installed antivirus software
Process hollowing
Invokes svchost.exe, injects to it to complete device encryption, and self-deletes by executing the following command:
Ability to terminate running services and processes
Ability to enumerate and mount volumes and network shares for encryption
Perform anti-forensics technique timestomping (sets the file time of encrypted and ReadMe file to 2000-01-01 00:00:00)
Ability to perform anti-debugging techniques
Recommendations
To guard against BlackByte ransomware attacks, Microsoft recommends the following:
Ensure that you have a patch management process in place and that patching for internet-exposed devices is prioritized; Understand and assess your cyber exposure with advanced vulnerability and configuration assessment tools like Microsoft Defender Vulnerability Management
Implement an endpoint detection and response (EDR) solution like Microsoft Defender for Endpoint to gain visibility into malicious activity in real time across your network
Ensure antivirus protections are updated regularly by turning on cloud-based protection and that your antivirus solution is configured to block threats
Enable tamper protection to prevent components of Microsoft Defender Antivirus from being disabled
Block inbound traffic from IPs specified in the indicators of compromise section of this report
Block inbound traffic from TOR exit nodes
Block inbound access from unauthorized public VPN services
Restrict administrative privileges to prevent authorized system changes
Conclusion
BlackByte ransomware attacks target organizations that have infrastructure with unpatched vulnerabilities. As outlined in the Microsoft Digital Defense Report, common security hygiene practices, including keeping systems up to date, could protect against 98% of attacks.
As new tools are being developed by threat actors, a modern threat protection solution like Microsoft 365 Defender is necessary to prevent and detect the multiple techniques used in the attack chain, especially where the threat actor attempts to evade or disable specific defense mechanisms. Hunting for malicious behavior should be performed regularly in order to detect potential attacks that could evade detections, as a complementary activity for continuous monitoring from security tools alerts and incidents.
To understand how Microsoft can help you secure your network and respond to network compromise, visit https://aka.ms/MicrosoftIR.
Microsoft 365 Defender detections
Microsoft Defender Antivirus
Microsoft Defender Antivirus detects this threat as the following malware:
Trojan:Win32/Kovter!MSR
Trojan:Win64/WinGoObfusc.LK!MT
Trojan:Win64/BlackByte!MSR
HackTool:Win32/AdFind!MSR
Trojan:Win64/CobaltStrike!MSR
Microsoft Defender for Endpoint
The following alerts might indicate threat activity related to this threat. Note, however, that these alerts can be also triggered by unrelated threat activity.
‘CVE-2021-31207’ exploit malware was detected
An active ‘NetShDisableFireWall’ malware in a command line was prevented from executing.
Suspicious registry modification.
‘Rtcore64’ hacktool was detected
Possible ongoing hands-on-keyboard activity (Cobalt Strike)
A file or network connection related to a ransomware-linked emerging threat activity group detected
Suspicious sequence of exploration activities
A process was injected with potentially malicious code
Suspicious behavior by cmd.exe was observed
‘Blackbyte’ ransomware was detected
Microsoft Defender Vulnerability Management
Microsoft Defender Vulnerability Management surfaces devices that may be affected by the following vulnerabilities used in this threat:
CVE-2021-34473
CVE-2021-34523
CVE-2021-31207
CVE-2019-16098
Hunting queries
Microsoft 365 Defender
Microsoft 365 Defender customers can run the following query to find related activity in their networks:
ProxyShell web shell creation events
DeviceProcessEvents| where ProcessCommandLine has_any ("ExcludeDumpster","New-ExchangeCertificate") and ProcessCommandLine has_any ("-RequestFile","-FilePath")
Suspicious vssadmin events
DeviceProcessEvents| where ProcessCommandLine has_any ("vssadmin","vssadmin.exe") and ProcessCommandLine has "Resize ShadowStorage" and ProcessCommandLine has_any ("MaxSize=401MB"," MaxSize=UNBOUNDED")
Detection for persistence creation using Registry Run keys
DeviceRegistryEvents | where ActionType == "RegistryValueSet" | where (RegistryKey has @"Microsoft\Windows\CurrentVersion\RunOnce" and RegistryValueName == "MsEdgeMsE") or (RegistryKey has @"Microsoft\Windows\CurrentVersion\RunOnceEx" and RegistryValueName == "MsEdgeMsE")or (RegistryKey has @"Microsoft\Windows\CurrentVersion\Run" and RegistryValueName == "MsEdgeMsE")| where RegistryValueData startswith @"rundll32"| where RegistryValueData endswith @".dll,Default"| project Timestamp,DeviceId,DeviceName,ActionType,RegistryKey,RegistryValueName,RegistryValueData
Microsoft Sentinel
Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace. More details on the Content Hub can be found here: https://learn.microsoft.com/azure/sentinel/sentinel-solutions-deploy
Microsoft Sentinel also has a range of detection and threat hunting content that customers can use to detect the post exploitation activity detailed in this blog in addition to Microsoft 365 Defender detections list above.
The table below shows IOCs observed during our investigation. We encourage our customers to investigate these indicators in their environments and implement detections and protections to identify past related activity and prevent future attacks against their systems.
AdFind.exe (Active Directory information gathering tool)
hxxps://myvisit[.]alteksecurity[.]org/t
URL
C2 for backdoor api-msvc.dll
hxxps://temp[.]sh/szAyn/sys.exe
URL
Download URL for sys.exe
109.206.243[.]59
IP Address
C2 for Cobalt Strike Beacon sys.exe
185.225.73[.]244
IP Address
Originating IP address for ProxyShell exploitation and web shell interaction
NOTE: These indicators should not be considered exhaustive for this observed activity.
Appendix
File extensions targeted by BlackByte binary for encryption:
.4dd
.4dl
.accdb
.accdc
.accde
.accdr
.accdt
.accft
.adb
.ade
.adf
.adp
.arc
.ora
.alf
.ask
.btr
.bdf
.cat
.cdb
.ckp
.cma
.cpd
.dacpac
.dad
.dadiagrams
.daschema
.db
.db-shm
.db-wal
.db3
.dbc
.dbf
.dbs
.dbt
.dbv
. dbx
. dcb
. dct
. dcx
. ddl
. dlis
. dp1
. dqy
. dsk
. dsn
. dtsx
. dxl
. eco
. ecx
. edb
. epim
. exb
. fcd
. fdb
. fic
. fmp
. fmp12
. fmpsl
. fol
.fp3
. fp4
. fp5
. fp7
. fpt
. frm
. gdb
. grdb
. gwi
. hdb
. his
. ib
. idb
. ihx
. itdb
. itw
. jet
. jtx
. kdb
. kexi
. kexic
. kexis
. lgc
. lwx
. maf
. maq
. mar
. masmav
. mdb
. mpd
. mrg
. mud
. mwb
. myd
. ndf
. nnt
. nrmlib
. ns2
. ns3
. ns4
. nsf
. nv
. nv2
. nwdb
. nyf
. odb
. ogy
. orx
. owc
. p96
. p97
. pan
. pdb
. pdm
. pnz
. qry
. qvd
. rbf
. rctd
. rod
. rodx
. rpd
. rsd
. sas7bdat
. sbf
. scx
. sdb
. sdc
. sdf
. sis
. spg
. sql
. sqlite
. sqlite3
. sqlitedb
. te
. temx
. tmd
. tps
. trc
. trm
. udb
. udl
. usr
. v12
. vis
. vpd
. vvv
. wdb
. wmdb
. wrk
. xdb
. xld
. xmlff
. abcddb
. abs
. abx
. accdw
. and
. db2
. fm5
. hjt
. icg
. icr
. kdb
. lut
. maw
. mdn
. mdt
Shared folders targeted for encryption (Example: \\[IP address]\Downloads):
Users
Backup
Veeam
homes
home
media
common
Storage Server
Public
Web
Images
Downloads
BackupData
ActiveBackupForBusiness
Backups
NAS-DC
DCBACKUP
DirectorFiles
share
File extensions ignored:
.ini
.url
.msilog
.log
.ldf
.lock
.theme
.msi
.sys
.wpx
.cpl
.adv
.msc
.scr
.key
.ico
.dll
.hta
.deskthemepack
.nomedia
.msu
.rtp
.msp
.idx
.ani
.386
.diagcfg
.bin
.mod
.ics
.com
.hlp
.spl
.nls
.cab
.exe
.diagpkg
.icl
.ocx
.rom
.prf
.thempack
.msstyles
.icns
.mpa
.drv
.cur
.diagcab
.cmd
.shs
Folders ignored:
windows
boot
program files (x86)
windows.old
programdata
intel
bitdefender
trend micro
windowsapps
appdata
application data
system volume information
perflogs
msocache
Files ignored:
bootnxt
ntldr
bootmgr
thumbs.db
ntuser.dat
bootsect.bak
autoexec.bat
iconcache.db
bootfont.bin
Processes terminated:
teracopy
teamviewer
nsservice
nsctrl
uranium
processhacker
procmon
pestudio
procmon64
x32dbg
x64dbg
cff explorer
procexp
pslist
tcpview
tcpvcon
dbgview
rammap
rammap64
vmmap
ollydbg
autoruns
autorunssc
filemon
regmon
idaq
idaq64
immunitydebugger
wireshark
dumpcap
hookexplorer
importrec
petools
lordpe
sysinspector
proc_analyzer
sysanalyzer
sniff_hit
windbg
joeboxcontrol
joeboxserver
resourcehacker
fiddler
httpdebugger
dumpit
rammap
rammap64
vmmap
agntsvc
cntaosmgr
dbeng50
dbsnmp
encsvc
infopath
isqlplussvc
mbamtray
msaccess
msftesql
mspub
mydesktopqos
mydesktopservice
mysqld
mysqld-nt
mysqld-opt
Ntrtscan
ocautoupds
ocomm
ocssd
onenote
oracle
outlook
PccNTMon
powerpnt
sqbcoreservice
sql
sqlagent
sqlbrowser
sqlservr
sqlwriter
steam
synctime
tbirdconfig
thebat
thebat64
thunderbird
tmlisten
visio
winword
wordpad
xfssvccon
zoolz
Services terminated:
CybereasonRansomFree
vnetd
bpcd
SamSs
TeraCopyService
msftesql
nsService
klvssbridge64
vapiendpoint
ShMonitor
Smcinst
SmcService
SntpService
svcGenericHost
Swi_
TmCCSF
tmlisten
TrueKey
TrueKeyScheduler
TrueKeyServiceHelper
WRSVC
McTaskManager
OracleClientCache80
mfefire
wbengine
mfemms
RESvc
mfevtp
sacsvr
SAVAdminService
SepMasterService
PDVFSService
ESHASRV
SDRSVC
FA_Scheduler
KAVFS
KAVFS_KAVFSGT
kavfsslp
klnagent
macmnsvc
masvc
MBAMService
MBEndpointAgent
McShield
audioendpointbuilder
Antivirus
AVP
DCAgent
bedbg
EhttpSrv
MMS
ekrn
EPSecurityService
EPUpdateService
ntrtscan
EsgShKernel
msexchangeadtopology
AcrSch2Svc
MSOLAP$TPSAMA
Intel(R) PROSet Monitoring
msexchangeimap4
ARSM
unistoresvc_1af40a
ReportServer$TPS
MSOLAP$SYSTEM_BGC
W3Svc
MSExchangeSRS
ReportServer$TPSAMA
Zoolz 2 Service
MSOLAP$TPS
aphidmonitorservice
SstpSvc
MSExchangeMTA
ReportServer$SYSTEM_BGC
Symantec System Recovery
UI0Detect
MSExchangeSA
MSExchangeIS
ReportServer
MsDtsServer110
POP3Svc
MSExchangeMGMT
SMTPSvc
MsDtsServer
IisAdmin
MSExchangeES
EraserSvc11710
Enterprise Client Service
MsDtsServer100
NetMsmqActivator
stc_raw_agent
VSNAPVSS
PDVFSService
AcrSch2Svc
Acronis
CASAD2DWebSvc
CAARCUpdateSvc
McAfee
avpsus
DLPAgentService
mfewc
BMR Boot Service
DefWatch
ccEvtMgr
ccSetMgr
SavRoam
RTVsc screenconnect
ransom
sqltelemetry
msexch
vnc
teamviewer
msolap
veeam
backup
sql
memtas
vss
sophos
svc$
mepocs
wuauserv
Drivers that Blackbyte can bypass:
360avflt.sys
360box.sys
360fsflt.sys
360qpesv.sys
5nine.cbt.sys
a2acc.sys
a2acc64.sys
a2ertpx64.sys
a2ertpx86.sys
a2gffi64.sys
a2gffx64.sys
a2gffx86.sys
aaf.sys
aalprotect.sys
abrpmon.sys
accessvalidator.sys
acdriver.sys
acdrv.sys
adaptivaclientcache32.sys
adaptivaclientcache64.sys
adcvcsnt.sys
adspiderdoc.sys
aefilter.sys
agentrtm64.sys
agfsmon.sys
agseclock.sys
agsyslock.sys
ahkamflt.sys
ahksvpro.sys
ahkusbfw.sys
ahnrghlh.sys
aictracedrv_am.sys
airship-filter.sys
ajfsprot.sys
alcapture.sys
alfaff.sys
altcbt.sys
amfd.sys
amfsm.sys
amm6460.sys
amm8660.sys
amsfilter.sys
amznmon.sys
antileakfilter.sys
antispyfilter.sys
anvfsm.sys
apexsqlfilterdriver.sys
appcheckd.sys
appguard.sys
appvmon.sys
arfmonnt.sys
arta.sys
arwflt.sys
asgard.sys
ashavscan.sys
asiofms.sys
aswfsblk.sys
aswmonflt.sys
aswsnx.sys
aswsp.sys
aszfltnt.sys
atamptnt.sys
atc.sys
atdragent.sys
atdragent64.sys
aternityregistryhook.sys
atflt.sys
atrsdfw.sys
auditflt.sys
aupdrv.sys
avapsfd.sys
avc3.sys
avckf.sys
avfsmn.sys
avgmfi64.sys
avgmfrs.sys
avgmfx64.sys
avgmfx86.sys
avgntflt.sys
avgtpx64.sys
avgtpx86.sys
avipbb.sys
avkmgr.sys
avmf.sys
awarecore.sys
axfltdrv.sys
axfsysmon.sys
ayfilter.sys
b9kernel.sys
backupreader.sys
bamfltr.sys
bapfecpt.sys
bbfilter.sys
bd0003.sys
bddevflt.sys
bdfiledefend.sys
bdfilespy.sys
bdfm.sys
bdfsfltr.sys
bdprivmon.sys
bdrdfolder.sys
bdsdkit.sys
bdsfilter.sys
bdsflt.sys
bdsvm.sys
bdsysmon.sys
bedaisy.sys
bemk.sys
bfaccess.sys
bfilter.sys
bfmon.sys
bhdrvx64.sys
bhdrvx86.sys
bhkavka.sys
bhkavki.sys
bkavautoflt.sys
bkavsdflt.sys
blackbirdfsa.sys
blackcat.sys
bmfsdrv.sys
bmregdrv.sys
boscmflt.sys
bosfsfltr.sys
bouncer.sys
boxifier.sys
brcow_x_x_x_x.sys
brfilter.sys
brnfilelock.sys
brnseclock.sys
browsermon.sys
bsrfsflt.sys
bssaudit.sys
bsyaed.sys
bsyar.sys
bsydf.sys
bsyirmf.sys
bsyrtm.sys
bsysp.sys
bsywl.sys
bwfsdrv.sys
bzsenspdrv.sys
bzsenth.sys
bzsenyaradrv.sys
caadflt.sys
caavfltr.sys
cancelsafe.sys
carbonblackk.sys
catflt.sys
catmf.sys
cbelam.sys
cbfilter20.sys
cbfltfs4.sys
cbfsfilter2017.sys
cbfsfilter2020.sys
cbsampledrv.sys
cdo.sys
cdrrsflt.sys
cdsgfsfilter.sys
centrifyfsf.sys
cfrmd.sys
cfsfdrv
cgwmf.sys
change.sys
changelog.sys
chemometecfilter.sys
ciscoampcefwdriver.sys
ciscoampheurdriver.sys
ciscosam.sys
clumiochangeblockmf.sys
cmdccav.sys
cmdcwagt.sys
cmdguard.sys
cmdmnefs.sys
cmflt.sys
code42filter.sys
codex.sys
conduantfsfltr.sys
containermonitor.sys
cpavfilter.sys
cpavkernel.sys
cpepmon.sys
crexecprev.sys
crncache32.sys
crncache64.sys
crnsysm.sys
cruncopy.sys
csaam.sys
csaav.sys
csacentr.sys
csaenh.sys
csagent.sys
csareg.sys
csascr.sys
csbfilter.sys
csdevicecontrol.sys
csfirmwareanalysis.sys
csflt.sys
csmon.sys
cssdlp.sys
ctamflt.sys
ctifile.sys
ctinet.sys
ctrpamon.sys
ctx.sys
cvcbt.sys
cvofflineflt32.sys
cvofflineflt64.sys
cvsflt.sys
cwdriver.sys
cwmem2k64.sys
cybkerneltracker.sys
cylancedrv64.sys
cyoptics.sys
cyprotectdrv32.sys
cyprotectdrv64.sys
cytmon.sys
cyverak.sys
cyvrfsfd.sys
cyvrlpc.sys
cyvrmtgn.sys
datanow_driver.sys
dattofsf.sys
da_ctl.sys
dcfafilter.sys
dcfsgrd.sys
dcsnaprestore.sys
deepinsfs.sys
delete_flt.sys
devmonminifilter.sys
dfmfilter.sys
dgedriver.sys
dgfilter.sys
dgsafe.sys
dhwatchdog.sys
diflt.sys
diskactmon.sys
dkdrv.sys
dkrtwrt.sys
dktlfsmf.sys
dnafsmonitor.sys
docvmonk.sys
docvmonk64.sys
dpmfilter.sys
drbdlock.sys
drivesentryfilterdriver2lite.sys
drsfile.sys
drvhookcsmf.sys
drvhookcsmf_amd64.sys
drwebfwflt.sys
drwebfwft.sys
dsark.sys
dsdriver.sys
dsfemon.sys
dsflt.sys
dsfltfs.sys
dskmn.sys
dtdsel.sys
dtpl.sys
dwprot.sys
dwshield.sys
dwshield64.sys
eamonm.sys
easeflt.sys
easyanticheat.sys
eaw.sys
ecatdriver.sys
edevmon.sys
ednemfsfilter.sys
edrdrv.sys
edrsensor.sys
edsigk.sys
eectrl.sys
eetd32.sys
eetd64.sys
eeyehv.sys
eeyehv64.sys
egambit.sys
egfilterk.sys
egminflt.sys
egnfsflt.sys
ehdrv.sys
elock2fsctldriver.sys
emxdrv2.sys
enigmafilemondriver.sys
enmon.sys
epdrv.sys
epfw.sys
epfwwfp.sys
epicfilter.sys
epklib.sys
epp64.sys
epregflt.sys
eps.sys
epsmn.sys
equ8_helper.sys
eraser.sys
esensor.sys
esprobe.sys
estprmon.sys
estprp.sys
estregmon.sys
estregp.sys
estrkmon.sys
estrkr.sys
eventmon.sys
evmf.sys
evscase.sys
excfs.sys
exprevdriver.sys
failattach.sys
failmount.sys
fam.sys
fangcloud_autolock_driver.sys
fapmonitor.sys
farflt.sys
farwflt.sys
fasdriver
fcnotify.sys
fcontrol.sys
fdrtrace.sys
fekern.sys
fencry.sys
ffcfilt.sys
ffdriver.sys
fildds.sys
filefilter.sys
fileflt.sys
fileguard.sys
filehubagent.sys
filemon.sys
filemonitor.sys
filenamevalidator.sys
filescan.sys
filesharemon.sys
filesightmf.sys
filesystemcbt.sys
filetrace.sys
file_monitor.sys
file_protector.sys
file_tracker.sys
filrdriver.sys
fim.sys
fiometer.sys
fiopolicyfilter.sys
fjgsdis2.sys
fjseparettifilterredirect.sys
flashaccelfs.sys
flightrecorder.sys
fltrs329.sys
flyfs.sys
fmdrive.sys
fmkkc.sys
fmm.sys
fortiaptfilter.sys
fortimon2.sys
fortirmon.sys
fortishield.sys
fpav_rtp.sys
fpepflt.sys
fsafilter.sys
fsatp.sys
fsfilter.sys
fsgk.sys
fshs.sys
fsmon.sys
fsmonitor.sys
fsnk.sys
fsrfilter.sys
fstrace.sys
fsulgk.sys
fsw31rj1.sys
gagsecurity.sys
gbpkm.sys
gcffilter.sys
gddcv.sys
gefcmp.sys
gemma.sys
geprotection.sys
ggc.sys
gibepcore.sys
gkff.sys
gkff64.sys
gkpfcb.sys
gkpfcb64.sys
gofsmf.sys
gpminifilter.sys
groundling32.sys
groundling64.sys
gtkdrv.sys
gumhfilter.sys
gzflt.sys
hafsnk.sys
hbflt.sys
hbfsfltr.sys
hcp_kernel_acq.sys
hdcorrelatefdrv.sys
hdfilemon.sys
hdransomoffdrv.sys
hdrfs.sys
heimdall.sys
hexisfsmonitor.sys
hfileflt.sys
hiofs.sys
hmpalert.sys
hookcentre.sys
hooksys.sys
hpreg.sys
hsmltmon.sys
hsmltwhl.sys
hssfwhl.sys
hvlminifilter.sys
ibr2fsk.sys
iccfileioad.sys
iccfilteraudit.sys
iccfiltersc.sys
icfclientflt.sys
icrlmonitor.sys
iderafilterdriver.sys
ielcp.sys
ieslp.sys
ifs64.sys
ignis.sys
iguard.sys
iiscache.sys
ikfilesec.sys
im.sys
imffilter.sys
imfilter.sys
imgguard.sys
immflex.sys
immunetprotect.sys
immunetselfprotect.sys
inisbdrv64.sys
ino_fltr.sys
intelcas.sys
intmfs.sys
inuse.sys
invprotectdrv.sys
invprotectdrv64.sys
ionmonwdrv.sys
iothorfs.sys
ipcomfltr.sys
ipfilter.sys
iprotect.sys
iridiumswitch.sys
irongatefd.sys
isafekrnl.sys
isafekrnlmon.sys
isafermon
isecureflt.sys
isedrv.sys
isfpdrv.sys
isirmfmon.sys
isregflt.sys
isregflt64.sys
issfltr.sys
issregistry.sys
it2drv.sys
it2reg.sys
ivappmon.sys
iwdmfs.sys
iwhlp.sys
iwhlp2.sys
iwhlpxp.sys
jdppsf.sys
jdppwf.sys
jkppob.sys
jkppok.sys
jkpppf.sys
jkppxk.sys
k7sentry.sys
kavnsi.sys
kawachfsminifilter.sys
kc3.sys
kconv.sys
kernelagent32.sys
kewf.sys
kfac.sys
kfileflt.sys
kisknl.sys
klam.sys
klbg.sys
klboot.sys
kldback.sys
kldlinf.sys
kldtool.sys
klfdefsf.sys
klflt.sys
klgse.sys
klhk.sys
klif.sys
klifaa.sys
klifks.sys
klifsm.sys
klrsps.sys
klsnsr.sys
klupd_klif_arkmon.sys
kmkuflt.sys
kmnwch.sys
kmxagent.sys
kmxfile.sys
kmxsbx.sys
ksfsflt.sys
ktfsfilter.sys
ktsyncfsflt.sys
kubwksp.sys
lafs.sys
lbd.sys
lbprotect.sys
lcgadmon.sys
lcgfile.sys
lcgfilemon.sys
lcmadmon.sys
lcmfile.sys
lcmfilemon.sys
lcmprintmon.sys
ldsecdrv.sys
libwamf.sys
livedrivefilter.sys
llfilter.sys
lmdriver.sys
lnvscenter.sys
locksmith.sys
lragentmf.sys
lrtp.sys
magicbackupmonitor.sys
magicprotect.sys
majoradvapi.sys
marspy.sys
maxcryptmon.sys
maxproc64.sys
maxprotector.sys
mbae64.sys
mbam.sys
mbamchameleon.sys
mbamshuriken.sys
mbamswissarmy.sys
mbamwatchdog.sys
mblmon.sys
mcfilemon32.sys
mcfilemon64.sys
mcstrg.sys
mearwfltdriver.sys
message.sys
mfdriver.sys
mfeaack.sys
mfeaskm.sys
mfeavfk.sys
mfeclnrk.sys
mfeelamk.sys
mfefirek.sys
mfehidk.sys
mfencbdc.sys
mfencfilter.sys
mfencoas.sys
mfencrk.sys
mfeplk.sys
mfewfpk.sys
miniicpt.sys
minispy.sys
minitrc.sys
mlsaff.sys
mmpsy32.sys
mmpsy64.sys
monsterk.sys
mozycorpfilter.sys
mozyenterprisefilter.sys
mozyentfilter.sys
mozyhomefilter.sys
mozynextfilter.sys
mozyoemfilter.sys
mozyprofilter.sys
mpfilter.sys
mpkernel.sys
mpksldrv.sys
mpxmon.sys
mracdrv.sys
mrxgoogle.sys
mscan-rt.sys
msiodrv4.sys
msixpackagingtoolmonitor.sys
msnfsflt.sys
mspy.sys
mssecflt.sys
mtsvcdf.sys
mumdi.sys
mwac.sys
mwatcher.sys
mwfsmfltr.sys
mydlpmf.sys
namechanger.sys
nanoavmf.sys
naswsp.sys
ndgdmk.sys
neokerbyfilter
netaccctrl.sys
netaccctrl64.sys
netguard.sys
netpeeker.sys
ngscan.sys
nlcbhelpi64.sys
nlcbhelpx64.sys
nlcbhelpx86.sys
nlxff.sys
nmlhssrv01.sys
nmpfilter.sys
nntinfo.sys
novashield.sys
nowonmf.sys
npetw.sys
nprosec.sys
npxgd.sys
npxgd64.sys
nravwka.sys
nrcomgrdka.sys
nrcomgrdki.sys
nregsec.sys
nrpmonka.sys
nrpmonki.sys
nsminflt.sys
nsminflt64.sys
ntest.sys
ntfsf.sys
ntguard.sys
ntps_fa.sys
nullfilter.sys
nvcmflt.sys
nvmon.sys
nwedriver.sys
nxfsmon.sys
nxrmflt.sys
oadevice.sys
oavfm.sys
oczminifilter.sys
odfsfilter.sys
odfsfimfilter.sys
odfstokenfilter.sys
offsm.sys
omfltlh.sys
osiris.sys
ospfile_mini.sys
ospmon.sys
parity.sys
passthrough.sys
path8flt.sys
pavdrv.sys
pcpifd.sys
pctcore.sys
pctcore64.sys
pdgenfam.sys
pecfilter.sys
perfectworldanticheatsys.sys
pervac.sys
pfkrnl.sys
pfracdrv.sys
pgpfs.sys
pgpwdefs.sys
phantomd.sys
phdcbtdrv.sys
pkgfilter.sys
pkticpt.sys
plgfltr.sys
plpoffdrv.sys
pointguardvista64f.sys
pointguardvistaf.sys
pointguardvistar32.sys
pointguardvistar64.sys
procmon11.sys
proggerdriver.sys
psacfileaccessfilter.sys
pscff.sys
psgdflt.sys
psgfoctrl.sys
psinfile.sys
psinproc.sys
psisolator.sys
pwipf6.sys
pwprotect.sys
pzdrvxp.sys
qdocumentref.sys
qfapflt.sys
qfilter.sys
qfimdvr.sys
qfmon.sys
qminspec.sys
qmon.sys
qqprotect.sys
qqprotectx64.sys
qqsysmon.sys
qqsysmonx64.sys
qutmdrv.sys
ranpodfs.sys
ransomdefensexxx.sys
ransomdetect.sys
reaqtor.sys
redlight.sys
regguard.sys
reghook.sys
regmonex.sys
repdrv.sys
repmon.sys
revefltmgr.sys
reveprocprotection.sys
revonetdriver.sys
rflog.sys
rgnt.sys
rmdiskmon.sys
rmphvmonitor.sys
rpwatcher.sys
rrmon32.sys
rrmon64.sys
rsfdrv.sys
rsflt.sys
rspcrtw.sys
rsrtw.sys
rswctrl.sys
rswmon.sys
rtologon.sys
rtw.sys
ruaff.sys
rubrikfileaudit.sys
ruidiskfs.sys
ruieye.sys
ruifileaccess.sys
ruimachine.sys
ruiminispy.sys
rvsavd.sys
rvsmon.sys
rw7fsflt.sys
rwchangedrv.sys
ryfilter.sys
ryguard.sys
safe-agent.sys
safsfilter.sys
sagntflt.sys
sahara.sys
sakfile.sys
sakmfile.sys
samflt.sys
samsungrapidfsfltr.sys
sanddriver.sys
santa.sys
sascan.sys
savant.sys
savonaccess.sys
scaegis.sys
scauthfsflt.sys
scauthiodrv.sys
scensemon.sys
scfltr.sys
scifsflt.sys
sciptflt.sys
sconnect.sys
scred.sys
sdactmon.sys
sddrvldr.sys
sdvfilter.sys
se46filter.sys
secdodriver.sys
secone_filemon10.sys
secone_proc10.sys
secone_reg10.sys
secone_usb.sys
secrmm.sys
secufile.sys
secure_os.sys
secure_os_mf.sys
securofsd_x64.sys
sefo.sys
segf.sys
segiraflt.sys
segmd.sys
segmp.sys
sentinelmonitor.sys
serdr.sys
serfs.sys
sfac.sys
sfavflt.sys
sfdfilter.sys
sfpmonitor.sys
sgresflt.sys
shdlpmedia.sys
shdlpsf.sys
sheedantivirusfilterdriver.sys
sheedselfprotection.sys
shldflt.sys
si32_file.sys
si64_file.sys
sieflt.sys
simrep.sys
sisipsfilefilter
sk.sys
skyamdrv.sys
skyrgdrv.sys
skywpdrv.sys
slb_guard.sys
sld.sys
smbresilfilter.sys
smdrvnt.sys
sndacs.sys
snexequota.sys
snilog.sys
snimg.sys
snscore.sys
snsrflt.sys
sodatpfl.sys
softfilterxxx.sys
soidriver.sys
solitkm.sys
sonar.sys
sophosdt2.sys
sophosed.sys
sophosntplwf.sys
sophossupport.sys
spbbcdrv.sys
spellmon.sys
spider3g.sys
spiderg3.sys
spiminifilter.sys
spotlight.sys
sprtdrv.sys
sqlsafefilterdriver.sys
srminifilterdrv.sys
srtsp.sys
srtsp64.sys
srtspit.sys
ssfmonm.sys
ssrfsf.sys
ssvhook.sys
stcvsm.sys
stegoprotect.sys
stest.sys
stflt.sys
stkrnl64.sys
storagedrv.sys
strapvista.sys
strapvista64.sys
svcbt.sys
swcommfltr.sys
swfsfltr.sys
swfsfltrv2.sys
swin.sys
symafr.sys
symefa.sys
symefa64.sys
symefasi.sys
symevent.sys
symevent64x86.sys
symevnt.sys
symevnt32.sys
symhsm.sys
symrg.sys
sysdiag.sys
sysmon.sys
sysmondrv.sys
sysplant.sys
szardrv.sys
szdfmdrv.sys
szdfmdrv_usb.sys
szedrdrv.sys
szpcmdrv.sys
taniumrecorderdrv.sys
taobserveflt.sys
tbfsfilt.sys
tbmninifilter.sys
tbrdrv.sys
tdevflt.sys
tedrdrv.sys
tenrsafe2.sys
tesmon.sys
tesxnginx.sys
tesxporter.sys
tffregnt.sys
tfsflt.sys
tgfsmf.sys
thetta.sys
thfilter.sys
threatstackfim.sys
tkdac2k.sys
tkdacxp.sys
tkdacxp64.sys
tkfsavxp.sys
tkfsavxp64.sys
tkfsft.sys
tkfsft64.sys
tkpcftcb.sys
tkpcftcb64.sys
tkpl2k.sys
tkpl2k64.sys
tksp2k.sys
tkspxp.sys
tkspxp64.sys
tmactmon.sys
tmcomm.sys
tmesflt.sys
tmevtmgr.sys
tmeyes.sys
tmfsdrv2.sys
tmkmsnsr.sys
tmnciesc.sys
tmpreflt.sys
tmumh.sys
tmums.sys
tmusa.sys
tmxpflt.sys
topdogfsfilt.sys
trace.sys
trfsfilter.sys
tritiumfltr.sys
trpmnflt.sys
trufos.sys
trustededgeffd.sys
tsifilemon.sys
tss.sys
tstfilter.sys
tstfsredir.sys
tstregredir.sys
tsyscare.sys
tvdriver.sys
tvfiltr.sys
tvmfltr.sys
tvptfile.sys
tvspfltr.sys
twbdcfilter.sys
txfilefilter.sys
txregmon.sys
uamflt.sys
ucafltdriver.sys
ufdfilter.sys
uncheater.sys
upguardrealtime.sys
usbl_ifsfltr.sys
usbpdh.sys
usbtest.sys
uvmcifsf.sys
uwfreg.sys
uwfs.sys
v3flt2k.sys
v3flu2k.sys
v3ift2k.sys
v3iftmnt.sys
v3mifint.sys
varpffmon.sys
vast.sys
vcdriv.sys
vchle.sys
vcmfilter.sys
vcreg.sys
veeamfct.sys
vfdrv.sys
vfilefilter.sys
vfpd.sys
vfsenc.sys
vhddelta.sys
vhdtrack.sys
vidderfs.sys
vintmfs.sys
virtfile.sys
virtualagent.sys
vk_fsf.sys
vlflt.sys
vmwvvpfsd.sys
vollock.sys
vpdrvnt.sys
vradfil2.sys
vraptdef.sys
vraptflt.sys
vrarnflt.sys
vrbbdflt.sys
vrexpdrv.sys
vrfsftm.sys
vrfsftmx.sys
vrnsfilter.sys
vrsdam.sys
vrsdcore.sys
vrsdetri.sys
vrsdetrix.sys
vrsdfmx.sys
vrvbrfsfilter.sys
vsepflt.sys
vsscanner.sys
vtsysflt.sys
vxfsrep.sys
wats_se.sys
wbfilter.sys
wcsdriver.sys
wdcfilter.sys
wdfilter.sys
wdocsafe.sys
wfp_mrt.sys
wgfile.sys
whiteshield.sys
windbdrv.sys
windd.sys
winfladrv.sys
winflahdrv.sys
winfldrv.sys
winfpdrv.sys
winload.sys
winteonminifilter.sys
wiper.sys
wlminisecmod.sys
wntgpdrv.sys
wraekernel.sys
wrcore.sys
wrcore.x64.sys
wrdwizfileprot.sys
wrdwizregprot.sys
wrdwizscanner.sys
wrdwizsecure64.sys
wrkrn.sys
wrpfv.sys
wsafefilter.sys
wscm.sys
xcpl.sys
xendowflt.sys
xfsgk.sys
xhunter1.sys
xhunter64.sys
xiaobaifs.sys
xiaobaifsr.sys
xkfsfd.sys
xoiv8x64.sys
xomfcbt8x64.sys
yahoostorage.sys
yfsd.sys
yfsd2.sys
yfsdr.sys
yfsrd.sys
zampit_ml.sys
zesfsmf.sys
zqfilter.sys
zsfprt.sys
zwasatom.sys
zwpxesvr.sys
zxfsfilt.sys
zyfm.sys
zzpensys.sys
Further reading
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