Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO
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14
Feb 2019
Originally created by famed French programmer Benjamin Delpy to highlight security flaws in Windows authentication mechanisms, today Mimikatz is a staple post-exploitation module in the arsenal of cyber-criminals, since it facilitates lateral movement across a victim’s network. Mimikatz was a primary feature of the global ransomware attacks NotPetya and BadRabbit, in addition to the alleged Russian hacking of the German parliament in 2015 and 2017.
Among the primary vulnerabilities that Mimikatz exploits is Windows’ Local Security Authority Subsystem Service (LSASS), which is designed to obviate the need for users to reauthenticate every time they seek to access internal resources. Despite its clear utility, LSASS works by keeping a cache of every credential used since the last boot, presenting an obvious security risk in the event the cache is compromised. Broadly speaking, Mimikatz plunders this resource and allows users to access cleartext passwords as well as NTLM hashes. With this data in hand, threat actors are able to conduct the following attacks:
Kerberos Golden Ticket: Provides administrative credentials for the whole domain.
Pass-the-Ticket: Enables a user to pass a Kerberos ticket to a second device and login using this ticket.
Kerberos Silver Ticket: Provides a TGS ticket to log into any network service.
Pass-the-Hash: Allows a user to pass a hash string in order to login.
Dumping LSASS memory is just one method that Mimikatz and its many updated versions employ to harvest credentials. Indeed, once malware such as NotPetya has established itself on single device, the Mimikatz module can exploit a variety of security flaws to obtain the password information for any other users or computers that have logged onto that machine: a key step for both lateral movement and privilege escalation. Like many successful hacker tools, Mimikatz has inspired the creation of other programs with similar aims, which are largely intended to circumvent antivirus controls.
Using AI to end the cat-and-mouse game
At the most basic level, security teams can reduce vulnerability to Mimikatz and to lateral movement more generally by ensuring that each user has the minimum amount of privileges needed for his or her role. But while this measure is certainly prudent, it will not always be effective — especially when dealing with sophisticated threats. Another strategy is to implement endpoint security tools and anti-virus software, which rely on rules and signatures to detect known Mimikatz variants. However, as Mimikatz and its copycats continue to evolve, these traditional tools are locked in a ceaseless cat-and-mouse game, unable to spot unknown variants of Mimikatz that are designed to circumvent them.
As a fundamentally different approach to security, artificially intelligent systems like Darktrace avoid this cat-and-mouse game by learning what constitutes normal behavior for the users and devices they safeguard while “on the job,” rather than using fixed rules and signatures. This approach alerts defenders to any anomalous activity, regardless of whether such activity constitutes a known or unknown threat. Typically, lateral movement involving Mimikatz will involve a spike in unusual SMB activity, as attackers seek to write the tool to target devices. The following recent attack on a Darktrace customer highlights how AI can allow security teams to quickly detect and respond to such lateral movement involving Mimikatz:
Darktrace alerts to a non-domain joined Linux device appearing on the customer’s network and engaging in extensive SMB bruteforce activity against key servers.
Figure 1: Darktrace detects the spike in SMB activity.
Darktrace flags the device successfully logging into a server using administrative credentials via SMBv1, opening the \sect pipe and writing the suspicious and likely malicious file Syssvc.exe to the server’s \temp folder. Immediately after this, Darktrace alerts to the device writing mimikatz.exe to the same folder.
Figure 2: Darktrace flags the device using Mimikatz.
Following this step, multiple .tmp and .txt files appear on the target device, indicating that Mimikatz was proceeding to access passwords and hashes.
The novelty of this AI-powered approach is that it does not rely on a string search for the term “mimikatz.exe”; rather, it highlights the unusual behavior that commonly surrounds Mimikatz’ activity. As shown in the screenshot above, this behavior constitutes “New activity”: Darktrace has not seen this type of SMB activity between the source and the destination before. Moreover, SMBv1 is used — highly unusual for the environment. And finally, it is unusual for devices in the target environment to make SMB network drive writes to Temp folders. All these subtle deviations from the customer’s ‘pattern of life,’ taken together, caused Darktrace to alert on the Mimikatz behavior.
Since its introduction to the cyber-threat landscape, Mimikatz has become a highly effective means for cyber-attackers to move laterally inside corporate and government networks. But by empowering security teams to respond before attackers can plunder a network’s entire cache of passwords, AI cyber defenses are thwarting Mimikatz and its copycats alike.
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Unpacking ClickFix: Darktrace’s detection of a prolific social engineering tactic
What is ClickFix and how does it work?
Amid heightened security awareness, threat actors continue to seek stealthy methods to infiltrate target networks, often finding the human end user to be the most vulnerable and easily exploited entry point.
ClickFix baiting is an exploitation of the end user, making use of social engineering techniques masquerading as error messages or routine verification processes, that can result in malicious code execution.
Since March 2024, the simplicity of this technique has drawn attention from a range of threat actors, from individual cybercriminals to Advanced Persistent Threat (APT) groups such as APT28 and MuddyWater, linked to Russia and Iran respectively, introducing security threats on a broader scale [1]. ClickFix campaigns have been observed affecting organizations in across multiple industries, including healthcare, hospitality, automotive and government [2][3].
Actors carrying out these targeted attacks typically utilize similar techniques, tools and procedures (TTPs) to gain initial access. These include spear phishing attacks, drive-by compromises, or exploiting trust in familiar online platforms, such as GitHub, to deliver malicious payloads [2][3]. Often, a hidden link within an email or malvertisements on compromised legitimate websites redirect the end user to a malicious URL [4]. These take the form of ‘Fix It’ or fake CAPTCHA prompts [4].
From there, users are misled into believing they are completing a human verification step, registering a device, or fixing a non-existent issue such as a webpage display error. As a result, they are guided through a three-step process that ultimately enables the execution of malicious PowerShell commands:
Open a Windows Run dialog box [press Windows Key + R]
Automatically or manually copy and paste a malicious PowerShell command into the terminal [press CTRL+V]
And run the prompt [press ‘Enter’] [2]
Once the malicious PowerShell command is executed, threat actors then establish command and control (C2) communication within the targeted environment before moving laterally through the network with the intent of obtaining and stealing sensitive data [4]. Malicious payloads associated with various malware families, such as XWorm, Lumma, and AsyncRAT, are often deployed [2][3].
Based on investigations conducted by Darktrace’s Threat Research team in early 2025, this blog highlights Darktrace’s capability to detect ClickFix baiting activity following initial access.
Darktrace’s coverage of a ClickFix attack chain
Darktrace identified multiple ClickFix attacks across customer environments in both Europe, the Middle East, and Africa (EMEA) and the United States. The following incident details a specific attack on a customer network that occurred on April 9, 2025.
Although the initial access phase of this specific attack occurred outside Darktrace’s visibility, other affected networks showed compromise beginning with phishing emails or fake CAPTCHA prompts that led users to execute malicious PowerShell commands.
Darktrace’s visibility into the compromise began when the threat actor initiated external communication with their C2 infrastructure, with Darktrace / NETWORK detecting the use of a new PowerShell user agent, indicating an attempt at remote code execution.
Figure 1: Darktrace / NETWORK's detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for C2 communications.
Download of Malicious Files for Lateral Movement
A few minutes later, the compromised device was observed downloading a numerically named file. Numeric files like this are often intentionally nondescript and associated with malware. In this case, the file name adhered to a specific pattern, matching the regular expression: /174(\d){7}/. Further investigation into the file revealed that it contained additional malicious code designed to further exploit remote services and gather device information.
Figure 2: Darktrace / NETWORK's detection of a numeric file, one minute after the new PowerShell User Agent alert.
The file contained a script that sent system information to a specified IP address using an HTTP POST request, which also processed the response. This process was verified through packet capture (PCAP) analysis conducted by the Darktrace Threat Research team.
By analyzing the body content of the HTTP GET request, it was observed that the command converts the current time to Unix epoch time format (i.e., 9 April 2025 13:26:40 GMT), resulting in an additional numeric file observed in the URI: /1744205200.
Figure 3: PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.
Across Darktrace’s investigations into other customers' affected by ClickFix campaigns, both internal information discovery events and further execution of malicious code were observed.
Data Exfiltration
By following the HTTP stream in the same PCAP, the Darktrace Threat Research Team assessed the activity as indicative of data exfiltration involving system and device information to the same command-and-control (C2) endpoint, , 193.36.38[.]237. This endpoint was flagged as malicious by multiple open-source intelligence (OSINT) vendors [5].
Figure 4: PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.
Further analysis of Darktrace’s Advanced Search logs showed that the attacker’s malicious code scanned for internal system information, which was then sent to a C2 server via an HTTP POST request, indicating data exfiltration
Figure 5: Advanced Search further highlights Darktrace's observation of the HTTP POST request, with the second numeric file representing data exfiltration.
Actions on objectives
Around ten minutes after the initial C2 communications, the compromised device was observed connecting to an additional rare endpoint, 188.34.195[.]44. Further analysis of this endpoint confirmed its association with ClickFix campaigns, with several OSINT vendors linking it to previously reported attacks [6].
In the final HTTP POST request made by the device, Darktrace detected a file at the URI /init1234 in the connection logs to the malicious endpoint 188.34.195[.]44, likely depicting the successful completion of the attack’s objective, automated data egress to a ClickFix C2 server.
Darktrace / NETWORK grouped together the observed indicators of compromise (IoCs) on the compromised device and triggered an Enhanced Monitoring model alert, a high-priority detection model designed to identify activity indicative of the early stages of an attack. These models are monitored and triaged 24/7 by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection service, ensuring customers are promptly notified of malicious activity as soon as it emerges.
Figure 6: Darktrace correlated the separate malicious connections that pertained to a single campaign.
Darktrace Autonomous Response
In the incident outlined above, Darktrace was not configured in Autonomous Response mode. As a result, while actions to block specific connections were suggested, they had to be manually implemented by the customer’s security team. Due to the speed of the attack, this need for manual intervention allowed the threat to escalate without interruption.
However, in a different example, Autonomous Response was fully enabled, allowing Darktrace to immediately block connections to the malicious endpoint (138.199.156[.]22) just one second after the initial connection in which a numerically named file was downloaded [7].
Figure 7: Darktrace Autonomous Response blocked connections to a suspicious endpoint following the observation of the numeric file download.
This customer was also subscribed to our Managed Detection and Response service, Darktrace’s SOC extended a ‘Quarantine Device’ action that had already been autonomously applied in order to buy their security team additional time for remediation.
Figure 8: Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.
Conclusion
ClickFix baiting is a widely used tactic in which threat actors exploit human error to bypass security defenses. By tricking end point users into performing seemingly harmless, everyday actions, attackers gain initial access to systems where they can access and exfiltrate sensitive data.
Darktrace’s anomaly-based approach to threat detection identifies early indicators of targeted attacks without relying on prior knowledge or IoCs. By continuously learning each device’s unique pattern of life, Darktrace detects subtle deviations that may signal a compromise. In this case, Darktrace's Autonomous Response, when operating in a fully autonomous mode, was able to swiftly contain the threat before it could progress further along the attack lifecycle.
Credit to Keanna Grelicha (Cyber Analyst) and Jennifer Beckett (Cyber Analyst)
Appendices
NETWORK Models
Device / New PowerShell User Agent
Anomalous Connection / New User Agent to IP Without Hostname
Anomalous Connection / Posting HTTP to IP Without Hostname
Anomalous Connection / Powershell to Rare External
Device / Suspicious Domain
Device / New User Agent and New IP
Anomalous File / New User Agent Followed By Numeric File Download (Enhanced Monitoring Model)
Security teams are drowning in vulnerability alerts, but only a fraction of those issues pose a real threat. The new Exploit Prediction Assessment feature in Darktrace / Attack Surface Management helps teams cut through the noise by validating which vulnerabilities on their external attack surface can be actively exploited.
Instead of relying solely on CVSS scores or waiting for patch cycles, Exploit Prediction Assessment uses safe, targeted simulations to test whether exposed systems can be compromised, delivering fast, evidence-based results in under 72 hours.
This capability augments traditional pen testing and complements existing ASM workflows by transforming passive discovery into actionable insight. With EPA, security teams move from reacting to long lists of potential vulnerabilities to making confident, risk-based decisions on what actually matters.
Key highlights of Exploit Prediction Assessment
Simulated attacks to validate real risk
Exploit Prediction Assessment conducts safe, simulated attacks on assets with potential security vulnerabilities that have been identified by Darktrace / Attack Surface Management. This real-time testing validates your systems' susceptibility to compromise by confirming which vulnerabilities are present and exploitable on your attack surface.
Prioritize what matters most
Confirmed security risks can be prioritized for mitigation, ensuring that the most critical threats are promptly addressed. This takes the existing letter ranking system and brings it a step further by drilling down to yet another level. Even in the most overwhelming situations, teams will be able to act on a pragmatic, clear-cut plan.
Fast results, tailored to your environment
Customers set the scope of the Exploit Prediction Assessment within Darktrace / Attack Surface Management and receive the results of the surgical vulnerability testing within 72 hours. Users will see 1 of 2 shields:
1. A green shield with a check mark: Meaning no vulnerabilities were found on scanned CVEs for the asset.
2. A red shield with a red x: Meaning at least one vulnerability was found on scanned CVEs for the asset.
Why it's a game changer
Traditionally, attack surface management tools have focused on identifying exposed assets and vulnerabilities but lacked the context to determine which issues posed the greatest risk. Without context on what’s exploitable, security teams are left triaging long lists of potential risks, operating in isolation from broader business objectives. This misalignment ultimately leads to both weakened risk posture and cross team communication and execution.
This is where Continuous Threat Exposure Management (CTEM) becomes essential. Introduced by Gartner, CTEM is a framework that helps organizations continuously assess, validate, and improve their exposure to real-world threats. The goal isn’t just visibility, it’s to understand how an attacker could move through your environment today, and what to fix first to stop them.
Exploit Prediction Assessment brings this philosophy to life within Darktrace / Attack Surface Management. By safely simulating exploit attempts against identified vulnerabilities, it validates which exposures are truly at risk—transforming ASM from a discovery tool into a risk-based decision engine.
This capability directly supports the validation and prioritization phases of CTEM, helping teams focus on exploitable vulnerabilities rather than theoretical ones. This shift from visibility to action reduces the risk of critical vulnerabilities in the technology stack being overlooked, turning overwhelming vulnerability data into focused, clear actionable insights.
As attack surfaces continue to grow and change, organizations need more than static scans they need continuous, contextual insight. Exploit Prediction Assessment ensures your ASM efforts evolve with the threat landscape, making CTEM a practical reality, not just a strategy.
Exploit Prediction Assessment in action
With Darktrace / Attack Surface Management organizations can get Exploit Prediction Assessment, and the cyber risk team no longer guesses which vulnerabilities matter most. Instead, they identify several externally exposed areas of their attack surface, then use the feature to surgically test for exploitability across these exposed endpoints. Within 72 hours, they receive a report:
Positive outcome: Based on information in the html or the headers it seems that a vulnerable software version is running on an externally exposed infrastructure. By running a targeted attack on this infrastructure, we can confirm that it cannot be abused.
Negative outcome: Based on information in the html or the headers it seems that a vulnerable software version is running on an externally exposed infrastructure. By running a targeted attack on this infrastructure, we can confirm that it can be exploited, so we can predict it being exploited.
This second outcome changes everything. The team immediately prioritizes the exploitable asset for patching and takes the necessary adjustments to mitigate exposure until the fix is deployed.
Instead of spreading their resources thin across dozens of alerts, they focus on what poses a real threat, saving time, reducing risk, and demonstrating actionable results to stakeholders.
Conclusion
Exploit Predication Assessment bolsters Darktrace’s commitment to proactive cybersecurity. It supports intelligent prioritization of vulnerabilities, keeping organizations ahead of emerging threats. With this new addition to / Attack Surface Management, teams have another tool to empower a more efficient approach to addressing security gaps in real-time.
Stay tuned for more updates and insights on how Darktrace continues to develop a culture of proactive security across the entire ActiveAI Security Platform.
![PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/684068fac1b4368f672c17cc_Screenshot%202025-06-04%20at%208.40.32%E2%80%AFAM.png)
![PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6840694509d92b6220ccf5f1_Screenshot%202025-06-04%20at%208.41.48%E2%80%AFAM.png)
![Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68406a1f723c9d6fda9c5268_Screenshot%202025-06-04%20at%208.45.23%E2%80%AFAM.png)
