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August 4, 2021

Detecting a Cobalt Strike Attack With Darktrace AI

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04
Aug 2021
See how Darktrace AI was able to detect Cobalt Strike attacks by identifying anomalous connections and performing automated network reconnaissance.

Since its release in 2012, Cobalt Strike has become a popular platform for red teams and ethical hackers. Robust and reliable software combined with innovative features such as DNS tunnelling, lateral movement tools for privilege escalation, and PowerShell support, have made it a desirable option for organizations wanting to test their own cyber defenses. As the framework was previously only available with a commercial license, it gave security teams a distinct advantage over threat actors when preparing for attacks.

That all changed in late 2020, when a GitHub repository appeared hosting a decompiled version of the framework. Users claimed that the leaked platform did indeed function similarly, if not identically, to the commercial version, and even included a commented-out licensing check. This suddenly made the software readily available, and highly appealing for cyber-criminals: rather than requiring a paper trail and licensing, its source code was freely available for customization and use in offensive campaigns.

With sophisticated capabilities of subtle command and control (C2), privilege escalation, and lateral movement, the tools have become a favorite for ransomware gangs. Even prior to the reporting of the leaked version, 66% of ransomware attacks were found to use Cobalt Strike.

Overview of a Cobalt Strike attack

Cobalt Strike has distinctive TTPs (tools, techniques and procedures) and evasive features for each stage of the attack.

Figure 1: Cyber kill chain with Cobalt Strike

Initial compromise can be achieved with a native module for modifying emails. This includes the insertion of malicious links into existing emails or the creation of convincing spear phishing emails.

The initial payload is intentionally lightweight and can be delivered from cheaply hosted infrastructure. The smaller file size is easier to obfuscate and can be implemented in several ways, including injection into libraries or trusted processes, or creating a series of persistence mechanisms (such as turning off anti-virus prior to downloading the full payload). As such, it is remarkably difficult to detect with blocking rules or signatures.

Network reconnaissance can be done through a variety of subtle methods, using commonly used protocols such as DNS and DCE-RPC to interrogate the network. These services are frequently used in legitimate operations, so it is challenging to apply sufficiently strict controls to prevent this stage of the attack.

Lateral movement and privilege escalation are easily accessible with pre-packaged versions of common attack tools such as Mimikatz. They can interrogate an Active Directory (AD) or steal credentials, while also using SMB pipes for peer-to-peer C2. There is little space for perimeter-based security controls to monitor and restrict these abuses, even if sufficiently granular controls could be imposed.

Payload execution is a straightforward matter as Cobalt Strike beacon allows the delivery of effectively arbitrary payloads, including portability for ransomware. As the previous evasive steps can afford the attacker privileged credentials, the deployment of such payloads could look like non-threatening administrative behavior.

AI detections

Initial compromise

Cobalt Strike has utilities for creating spear phishing documents. As email remains a prolific source of perimeter breaches, threat actors will frequently implant the tool through phishes.

One such example was detected by Darktrace’s AI at Canadian manufacturer in June 2021. The compromise started when an end user appeared to open a phishing document, evidenced by connections to Adobe and VeriSign shortly prior to an HTTP connection to a rare external IP address.

A packet capture of the anomalous connection revealed the creation of an object using a base64 encoded string – a common obfuscation technique. If the customer had been using Darktrace/Email, the threat would have been nullified before it hit the mailbox.

Shortly after the HTTP connection, Darktrace identified unusual use of SSL, which appears to have been leveraged to upgrade to HTTPS using self-signed certificates. The endpoint served an executable, which was later confirmed as a Cobalt Strike beacon based on open-source intelligence (OSINT). Such beacons are supported by the framework, with a variety of common C2 protocols available to the attacker.

Figure 2: Event log for ‘Patient Zero’ of a Sodinokibi infection

Darktrace’s detection was based on the anomalous nature of the connection (suspicious violations of standard SSL protocols) and not a pre-defined rule. The initial compromise was detected in a matter of minutes.

Network reconnaissance

In another example at a Swiss telecommunications company in April 2021, Darktrace alerted the security team that a device – normally used for data collection – was engaging in suspicious lateral movement activity.

The host was abusing privileged credentials to perform AD reconnaissance and SMB enumeration. The alert then prompted a broader investigation, revealing that multiple devices, including domain controllers, were compromised with IoCs related to Cobalt Strike.

Thanks to Darktrace’s deep understanding of the business and recognition that this behavior was anomalous, the security team were able to remediate the infection before file encryption or large data exfiltration had occurred.

Privilege escalation and ransomware deployment

In a ransomware attack against a South African insurance company in May 2021, where a phishing email resulted in the deployment of ransomware, Darktrace first identified the creation of new administrative credentials. The devices which used the credentials were then seen making anomalous connections to various C2 endpoints associated with Cobalt Strike beacons.

Darktrace enabled the rapid identification of compromised hosts, which in turn allowed for a faster remediation and mitigated fears of a resurgent infection.

Cyber AI Analyst performed a machine-speed investigation of the activity, and automatically produced a report highlighting unusual connections on TCP port 4444 as well as other mail related ports. Port 4444 is the default port for Metasploit, another hacking platform which is often seen in conjunction with Cobalt Strike beacon. It then presented the human analysts with a full list of compromised hosts.

Figure 3: Cyber AI Analyst summary of an affected host using non-standard ports for C2 and subsequently scanning the network

Cobalt Strike malware

As it appears that a cheaply accessible analog of Cobalt Strike has been leaked, detection of the framework is critical to defend against active attackers. Signatures and rule-based restrictions prove ineffective in this regard, as the framework was designed specifically to evade such tools.

Darktrace offers the capability to detect malicious activity in its earliest stages, to triage at the speed of AI, and to autonomously block the proliferation of active threats.

Thanks to Darktrace analyst Roberto Romeu for his insights on the above threat find.

Learn how Darktrace caught APT41 leveraging Cobalt Strike

Inside the SOC
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.
Author
Brianna Leddy
Director of Analyst Operations

Based in San Francisco, Brianna is Director of Analyst Operations at Darktrace. She joined the analyst team in 2016 and has since advised a wide range of enterprise customers on advanced threat hunting and leveraging Self-Learning AI for detection and response. Brianna works closely with the Darktrace SOC team to proactively alert customers to emerging threats and investigate unusual behavior in enterprise environments. Brianna holds a Bachelor’s degree in Chemical Engineering from Carnegie Mellon University.

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March 11, 2025

Survey findings: AI Cyber Threats are a Reality, the People are Acting Now

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Artificial intelligence is changing the cybersecurity field as fast as any other, both on the offensive and defensive side. We surveyed over 1,500 cybersecurity professionals from around the world to uncover their attitudes, understanding, and priorities when it comes to AI cybersecurity in 2025. Our full report, unearthing some telling trends, is out now.

Download the full report to explore these findings in depth

How is AI impacting the threat landscape?

state of ai in cybersecurity report graphic showing ai powered cyber threats having an impact on organizations

Nearly 74% of participants say AI-powered threats are a major challenge for their organization and 90% expect these threats to have a significant impact over the next one to two years, a slight increase from last year. These statistics highlight that AI is not just an emerging risk but a present and evolving one.

As attackers harness AI to automate and scale their operations, security teams must adapt just as quickly. Organizations that fail to prioritize AI-specific security measures risk falling behind, making proactive defense strategies more critical than ever.

Some of the most pressing AI-driven cyber threats include:

  • AI-powered social engineering: Attackers are leveraging AI to craft highly personalized and convincing phishing emails, making them harder to detect and more likely to bypass traditional defenses.
  • More advanced attacks at speed and scale: AI lowers the barrier for less skilled threat actors, allowing them to launch sophisticated attacks with minimal effort.
  • Attacks targeting AI systems: Cybercriminals are increasingly going after AI itself, compromising machine learning models, tampering with training data, and exploiting vulnerabilities in AI-driven applications and APIs.

Safe and secure use of AI

AI is having an effect on the cyber-threat landscape, but it also is starting to impact every aspect of a business – from marketing to HR to operations. The accessibility of AI tools for employees improves workflows, but also poses risks like data privacy violations, shadow AI, and violation of industry regulations.

How are security practitioners accommodating for this uptick in AI use across business?

Among survey participants 45% of security practitioners say they had already established a policy on the safe and secure use of AI and around 50% are in discussions to do so.

While almost all participants acknowledge that this is a topic that needs to be addressed, the gap between discussion and execution could underscore a need for greater insight, stronger leadership commitment, and adaptable security frameworks to keep pace with AI advancements in the workplace. The most popular actions taken are:

  1. Implemented security controls to prevent unwanted exposure of corporate data when using AI technology (67%)
  2. Implemented security controls to protect against other threats/risks associated with using AI technology (62%)

This year specifically, we see further action being taken with the implementation of security controls, training, and oversight.

For a more detailed breakdown that includes results based on industry and organizational size, download the full report here.

AI threats are rising, but security teams still face major challenges

78% of CISOs say AI-powered cyber-threats are already having a significant impact on their organization, a 5% increase from last year.

While cyber professionals feel more prepared for AI powered threats than they did 12 months ago, 45% still say their organization is not adequately prepared—down from 60% last year.

Despite this optimism, key challenges remain, including:

  • A shortage of personnel to manage tools and alerts
  • Gaps in knowledge and skills related to AI-driven countermeasures

Confidence in traditional security tools vs. new AI based tools

This year, 73% of survey participants expressed confidence in their security team’s proficiency in using AI within their tool stack, marking an increase from the previous year.

However, only 50% of participants have confidence in traditional cybersecurity tools to detect and block AI-powered threats. In contrast, 75% of participants are confident in AI-powered security solutions for detecting and blocking such threats and attacks.

As leading organizations continue to implement and optimize their use of AI, they are incorporating it into an increasing number of workflows. This growing familiarity with AI is likely to boost the confidence levels of practitioners even further.

The data indicates a clear trend towards greater reliance on AI-powered security solutions over traditional tools. As organizations become more adept at integrating AI into their operations, their confidence in these advanced technologies grows.

This shift underscores the importance of staying current with AI advancements and ensuring that security teams are well-trained in utilizing these tools effectively. The increasing confidence in AI-driven solutions reflects their potential to enhance cybersecurity measures and better protect against sophisticated threats.

State of AI report

Download the full report to explore these findings in depth

The full report for Darktrace’s State of AI Cybersecurity is out now. Download the paper to dig deeper into these trends, and see how results differ by industry, region, organization size, and job title.  

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March 11, 2025

Darktrace's Early Detection of the Latest Ivanti Exploits

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As reported in Darktrace’s 2024 Annual Threat Report, the exploitation of Common Vulnerabilities and Exposures (CVEs) in edge infrastructure has consistently been a significant concern across the threat landscape, with internet-facing assets remaining highly attractive to various threat actors.

Back in January 2024, the Darktrace Threat Research team investigated a surge of malicious activity from zero-day vulnerabilities such as those at the time on Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances. These vulnerabilities were disclosed by Ivanti in January 2024 as CVE-2023-46805 (Authentication bypass vulnerability) and CVE-2024-21887 (Command injection vulnerability), where these two together allowed for unauthenticated, remote code execution (RCE) on vulnerable Ivanti systems.

What are the latest vulnerabilities in Ivanti products?

In early January 2025, two new vulnerabilities were disclosed in Ivanti CS and PS, as well as their Zero Trust Access (ZTA) gateway products.

  • CVE-2025-0282: A stack-based buffer overflow vulnerability. Successful exploitation could lead to unauthenticated remote code execution, allowing attackers to execute arbitrary code on the affected system [1]
  • CVE-2025-0283: When combined with CVE-2025-0282, this vulnerability could allow a local authenticated attacker to escalate privileges, gaining higher-level access on the affected system [1]

Ivanti also released a statement noting they are currently not aware of any exploitation of CVE-2025-0283 at the time of disclosure [1].

Darktrace coverage of Ivanti

The Darktrace Threat Research team investigated the new Ivanti vulnerabilities across their customer base and discovered suspicious activity on two customer networks. Indicators of Compromise (IoCs) potentially indicative of successful exploitation of CVE-2025-0282 were identified as early as December 2024, 11 days before they had been publicly disclosed by Ivanti.

Case 1: December 2024

Authentication with a Privileged Credential

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024, when a customer device was observed logging into the network via SMB using the credential “svc_negbackups”, before authenticating with the credential “svc_negba” via RDP.

This likely represented a threat actor attempting to identify vulnerabilities within the system or application and escalate their privileges from a basic user account to a more privileged one. Darktrace / NETWORK recognized that the credential “svc_negbackups” was new for this device and therefore deemed it suspicious.

Darktrace / NETWORK’s detection of the unusual use of a new credential.
Figure 1: Darktrace / NETWORK’s detection of the unusual use of a new credential.

Likely Malicious File Download

Shortly after authentication with the privileged credential, Darktrace observed the device performing an SMB write to the C$ share, where a likely malicious executable file, ‘DeElevate64.exe’ was detected. While this is a legitimate Windows file, it can be abused by malicious actors for Dynamic-Link Library (DLL) sideloading, where malicious files are transferred onto other devices before executing malware. There have been external reports indicating that threat actors have utilized this technique when exploiting the Ivanti vulnerabilities [2].

Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.
Figure 2: Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.

Shortly after, a high volume of SMB login failures using the credential “svc_counteract-ext” was observed, suggesting potential brute forcing activity. The suspicious nature of this activity triggered an Enhanced Monitoring model alert that was escalated to Darktrace’s Security Operations Center (SOC) for further investigation and prompt notification, as the customer was subscribed to the Security Operations Support service.  Enhanced Monitoring are high-fidelity models detect activities that are more likely to be indicative of compromise

Suspicious Scanning and Internal Reconnaissance

Darktrace then went on to observe the device carrying out network scanning activity as well as anomalous ITaskScheduler activity. Threat actors can exploit the task scheduler to facilitate the initial or recurring execution of malicious code by a trusted system process, often with elevated permissions. The same device was also seen carrying out uncommon WMI activity.

Darktrace’s detection of a suspicious network scan from the compromised device.
Figure 3: Darktrace’s detection of a suspicious network scan from the compromised device.

Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Figure 4: Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.
Figure 5: Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.

Case 2: January 2025

Suspicious File Downloads

On January 13, 2025, Darktrace began to observe activity related to the exploitation of CVE-2025-0282  on the network of another customer, with one in particular device attempting to download likely malicious files.

Firstly, Darktrace observed the device making a GET request for the file “DeElevator64.dll” hosted on the IP 104.238.130[.]185. The device proceeded to download another file, this time “‘DeElevate64.exe”. from the same IP. This was followed by the download of “DeElevator64.dll”, similar to the case observed in December 2024. External reporting indicates that this DLL has been used by actors exploiting CVE-2025-0282 to sideload backdoor into infected systems [2]

Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.
Figure 6: Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.

Suspicious Internal Activity

Just like the previous case, on January 15, the same device was observed making numerous internal connections consistent with network scanning activity, as well as DCE-RPC requests.

Just a few minutes later, Darktrace again detected the use of a new administrative credential, observing the following details:

  • domain=REDACTED hostname=DESKTOP-1JIMIV3 auth_successful=T result=success ntlm_version=2 .

The hostname observed by Darktrace, “DESKTOP-1JIMIV3,” has also been identified by other external vendors and was associated with a remote computer name seen accessing compromised accounts [2].

Darktrace also observed the device performing an SMB write of an additional file, “to.bat,” which may have represented another malicious file loaded from the DLL files that the device had downloaded earlier. It is possible this represented the threat actor attempting to deploy a remote scheduled task.

Darktrace’s detection of SMB Write of the suspicious file “to.bat”.
Figure 7: Darktrace’s detection of SMB Write of the suspicious file “to.bat”.

Further investigation revealed that the device was likely a Veeam server, with its MAC address indicating it was a VMware device. It also appeared that the Veeam server was capturing activities referenced from the hostname DESKTOP-1JIMIV3. This may be analogous to the remote computer name reported by external researchers as accessing accounts [2]. However, this activity might also suggest that while the same threat actor and tools could be involved, they may be targeting a different vulnerability in this instance.

Autonomous Response

In this case, the customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device. This action allows a device to make its usual connections while blocking any that deviate from expected behavior. These mitigative actions by Darktrace ensured that the compromise was promptly halted, preventing any further damage to the customer’s environment.

Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.
Figure 8: Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.

Conclusion

If the previous blog in January 2024 was a stark reminder of the threat posed by malicious actors exploiting Internet-facing assets, the recent activities surrounding CVE-2025-0282 and CVE-2025-0283 emphasize this even further.

Based on the telemetry available to Darktrace, a wide range of malicious activities were identified, including the malicious use of administrative credentials, the download of suspicious files, and network scanning in the cases investigated .

These activities included the download of suspicious files such as “DeElevate64.exe” and “DeElevator64.dll” potentially used by attackers to sideload backdoors into infected systems. The suspicious hostname DESKTOP-1JIMIV3 was also observed and appears to be associated with a remote computer name seen accessing compromised accounts. These activities are far from exhaustive, and many more will undoubtedly be uncovered as threat actors evolve.

Fortunately, Darktrace was able to swiftly detect and respond to suspicious network activity linked to the latest Ivanti vulnerabilities, sometimes even before these vulnerabilities were publicly disclosed.

Credit to: Nahisha Nobregas, Senior Cyber Analyst, Emma Foulger, Principle Cyber Analyst, Ryan Trail, Analyst Content Lead and the Darktrace Threat Research Team

Appendices

Darktrace Model Detections

Case 1

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Internal / Unusual SMB Script Write

·      Anomalous File / Multiple EXE from Rare External Locations

·      Anomalous File / Script from Rare External Location

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / Network Range Scan

·      Device / Network Scan

·      Device / New or Uncommon WMI Activity

·      Device / RDP Scan

·      Device / Suspicious Network Scan Activity

·      Device / Suspicious SMB Scanning Activity

·      User / New Admin Credentials on Client

·      User / New Admin Credentials on Server 

Case 2

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous Connection / Unusual Admin RDP Session

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / SMB Lateral Movement

·      Device / Possible SMB/NTLM Brute Force

·      Device / Suspicious SMB Scanning Activity

·      Device / Network Scan

·      Device / RDP Scan

·      Device / Large Number of Model Alerts

·      Device / Anomalous ITaskScheduler Activity

·      Device / Suspicious Network Scan Activity

·      Device / New or Uncommon WMI Activity

List of IoCs Possible IoCs:

·      DeElevator64.dll

·      deelevator64.dll

·      DeElevate64.exe

·      deelevator64.dll

·      deelevate64.exe

·      to.bat

Mid-high confidence IoCs:

-       104.238.130[.]185

-       http://104.238.130[.]185/DeElevate64.exe

-       http://104.238.130[.]185/DeElevator64.dll

-       DESKTOP-1JIMIV3

References:

1.     https://www.ivanti.com/blog/security-update-ivanti-connect-secure-policy-secure-and-neurons-for-zta-gateways

2.     https://unit42.paloaltonetworks.com/threat-brief-ivanti-cve-2025-0282-cve-2025-0283/

3.     https://www.proofpoint.com/uk/blog/identity-threat-defense/privilege-escalation-attack#:~:text=In%20this%20approach%2C%20attackers%20exploit,handing%20over%20their%20login%20credentials

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About the author
Hugh Turnbull
Cyber Analyst
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