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December 16, 2024

Cleo File Transfer Vulnerability: Patch Pitfalls and Darktrace’s Detection of Post-Exploitation Activities

File transfer applications are prime targets for ransomware groups due to their critical role in business operations. Recent vulnerabilities in Cleo's MFT software, namely CVE-2024-50623 and CVE-2024-55956, highlight ongoing risks. Read more about the Darktrace Threat Research team’s investigation into these vulnerabilities.
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.
Written by
Maria Geronikolou
Cyber Analyst
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16
Dec 2024

File transfer applications: A target for ransomware

File transfer applications have been a consistent target, particularly for ransomware groups, in recent years because they are key parts of business operations and have trusted access across different parts of an organization that include potentially confidential and personal information about an organization and its employees.

Recent targets of ransomware criminals includes applications like Acellion, Moveit, and GoAnywhere [1]. This seems to have been the case for Cleo’s managed file transfer (MFT) software solutions and the vulnerability CVE-2024-50623.

Threat overview: Understanding Cleo file transfer vulnerability

This vulnerability was believed to have been patched with the release of version 5.8.0.21 in late October 2024. However, open-source intelligence (OSINT) reported that the Clop ransomware group had managed to bypass the initial patch in late November, leading to the successful exploitation of the previously patched CVE.

In the last few days Cleo has published a new vulnerability, CVE-2024-55956, which is not a patch bypass of the CVE-2024-50623 but rather another vulnerability. This is also an unauthenticated file write vulnerability but while CVE-2024-50623 allows for both reading and writing arbitrary files, the CVE-2024-55956 only allows for writing arbitrary files and was addressed in version 5.8.0.24 [2].

Darktrace Threat Research analysts have already started investigating potential signs of devices running the Cleo software with network traffic supporting this initial hypothesis.

Comparison of CVE-2024-50623 and CVE-2024-55956

While CVE-2024-50623 was initially listed as a cross-site scripting issue, it was updated on December 10 to reflect unrestricted file upload and download. This vulnerability could lead to remote code execution (RCE) in versions of Cleo’s Harmony, VLTrader, and LexiCom products prior to 5.8.0.24. Attackers could leverage the fact that files are placed in the "autorun" sub-directory within the installation folder and are immediately read, interpreted, and evaluated by the susceptible software [3].

CVE-2024-55956, refers to an unauthenticated user who can import and execute arbitrary Bash or PowerShell commands on the host system by leveraging the default settings of the Autorun directory [4]. Both CVEs have occurred due to separate issues in the “/Synchronization” endpoint.

Investigating post exploitation patterns of activity on Cleo software

Proof of exploitation

Darktrace’s Threat Research analysts investigated multiple cases where devices identified as likely running Cleo software were detected engaging in unusual behavior. Analysts also attempted to identify any possible association between publicly available indicators of compromise (IoCs) and the exploitation of the vulnerability, using evidence of anomalous network traffic.

One case involved an Internet-facing device likely running Cleo VLTrader software (based on its hostname) reaching out to the 100% rare Lithuanian IP 181.214.147[.]164 · AS 15440 (UAB Baltnetos komunikacijos).

This activity occurred in the early hours of December 8 on the network of a customer in the energy sector. Darktrace detected a Cleo server transferring around over 500 MB of data over multiple SSL connections via port 443 to the Lithuanian IP. External research reported that this IP appears to be a callback IP observed in post-exploitation activity of vulnerable Cleo devices [3].

While this device was regularly observed sending data to external endpoints, this transfer represented a small increase in data sent to public IPs and coupled with the rarity of the destination, triggered a model alert as well as a Cyber AI Analyst Incident summarizing the transfer. Unfortunately, due to the encrypted connection no further analysis of the transmitted data was possible. However, due to the rarity of the activity, Darktrace’s Autonomous Response intervened and prevented any further connections to the IP.

 Model Alert Event Log show repeated connections to the rare IP, filtered with the rarity metric.
Figure 1: Model Alert Event Log show repeated connections to the rare IP, filtered with the rarity metric.
Shows connections to 181.214.147[.]164 and the amount of data transferred.
Figure 2: Shows connections to 181.214.147[.]164 and the amount of data transferred.

On the same day, external connections were observed to the external IP 45.182.189[.]225, along with inbound SSL connections from the same endpoint. OSINT has also linked this IP to the exploitation of Cleo software vulnerabilities [5].

Outgoing connections from a Cleo server to an anomalous endpoint.
Figure 3: Outgoing connections from a Cleo server to an anomalous endpoint.
 Incoming SSL connections from the external IP 45.182.189[.]225.
Figure 4: Incoming SSL connections from the external IP 45.182.189[.]225.

Hours after the last connection to 181.214.147[.]164, the integration detection tool from CrowdStrike, which the customer had integrated with Darktrace, issued an alert. This alert provided additional visibility into host-level processes and highlighted the following command executed on the Cleo server:

“D:\VLTrader\jre\bin\java.exe" -jar cleo.4889

Figure 5: The executed comand “D:\VLTrader\jre\bin\java.exe" -jar cleo.4889 and the Resource Location: \Device\HarddiskVolume3\VLTrader\jre\bin\java.exe.

Three days later, on December 11, another CrowdStrike integration alert was generated, this time following encoded PowerShell command activity on the server. This is consistent with post-exploitation activity where arbitrary PowerShell commands are executed on compromised systems leveraging the default settings of the Autorun directory, as highlighted by Cleo support [6]. According to external researchers , this process initiates connections to an external IP to retrieve JAR files with webshell-like functionality for continued post-exploitation [3]. The IP embedded in both commands observed by Darktrace was 38.180.242[.]122, hosted on ASN 58061(Scalaxy B.V.). There is no OSINT associating this IP with Cleo vulnerability exploitation at the time of writing.

Another device within the same customer network exhibited similar data transfer and command execution activity around the same time, suggesting it had also been compromised through this vulnerability. However, this second device contacted a different external IP, 5.45.74[.]137, hosted on AS 58061 (Scalaxy B.V.).

Like the first device, multiple connections to this IP were detected, with almost 600 MB of data transferred over the SSL protocol.

The Security Integration Detection Model that was triggered  and the PowerShell command observed
Figure 6: The Security Integration Detection Model that was triggered  and the PowerShell command observed
 Incoming connections from the external IP 38.180.242[.]122.
Figure 7: Incoming connections from the external IP 38.180.242[.]122.
Connections to the external IP 5.45.74[.]137.
Figure 8: Connections to the external IP 5.45.74[.]137.
Figure 9: Autonomous Response Actions triggered during the suspicious activities

While investigating potential Cleo servers involved in similar outgoing data activity, Darktrace’s Threat Research team identified two additional instances of likely Cleo vulnerability exploitation used to exfiltrate data outside the network. In those two instances, unusual outgoing data transfers were observed to the IP 176.123.4[.]22 (AS 200019, AlexHost SRL), with around 500 MB of data being exfiltrated over port 443 in one case (the exact volume could not be confirmed in the other instance). This IP was found embedded in encoded PowerShell commands examined by external researchers in the context of Cleo vulnerability exploitation investigations.

Conclusion

Overall, Cleo software represents a critical component of many business operations, being utilized by over 4,000 organizations worldwide. This renders the software an attractive target for threat actors who aim at exploiting internet-facing devices that could be used to compromise the software’s direct users but also other dependent industries resulting in supply chain attacks.

Darktrace / NETWORK was able to capture traffic linked to exploitation of CVE-2024-50623 within models that triggered such as Unusual Activity / Unusual External Data to New Endpoint while its Autonomous Response capability successfully blocked the anomalous connections and exfiltration attempts.

Information on new CVEs, how they're being exploited, and whether they've been patched can be fast-changing, sometimes limited and often confusing. Regardless, Darktrace is able to identify and alert to unusual behavior on these systems, indicating exploitation.

Credit to Maria Geronikolou, Alexandra Sentenac, Emma Fougler, Signe Zaharka and the Darktrace Threat Research team

Get the latest insights on emerging cyber threats

Attackers are adapting, are you ready? This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025.

  • Identity-based attacks: How attackers are bypassing traditional defenses
  • Zero-day exploitation: The rise of previously unknown vulnerabilities
  • AI-driven threats: How adversaries are leveraging AI to outmaneuver security controls

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Appendices

References

[1] https://blog.httpcs.com/en/file-sharing-and-transfer-software-the-new-target-of-hackers/

[2] https://attackerkb.com/topics/geR0H8dgrE/cve-2024-55956/rapid7-analysis

[3] https://www.huntress.com/blog/threat-advisory-oh-no-cleo-cleo-software-actively-being-exploited-in-the-wild

[4] https://nvd.nist.gov/vuln/detail/CVE-2024-55956

[5] https://arcticwolf.com/resources/blog/cleopatras-shadow-a-mass-exploitation-campaign/

[6] https://support.cleo.com/hc/en-us/articles/28408134019735-Cleo-Product-Security-Advisory-CVE-Pending

[7] https://support.cleo.com/hc/en-us/articles/360034260293-Local-HTTP-Users-Configuration

Darktrace Model Alerts

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data to New Endpoint

Unusual Activity / Unusual External Data Transfer

Device / Internet Facing Device with High Priority Alert

Anomalous Server Activity / Rare External from Server

Anomalous Connection / New User Agent to IP Without Hostname

Security Integration / High Severity Integration Incident

Security Integration / Low Severity Integration Detection

Autonomous Response Model Detections

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

Cyber AI Analyst Incidents

Unusual External Data Transfer

MITRE ATT&CK Mapping

Tactic – Technique

INITIAL ACCESS – Exploit Public-Facing Application

COMMAND AND CONTROL – Application Layer Protocol (Web Protocols)

COMMAND AND CONTROL – Encrypted Channel

PERSISTENCE – Web Shell

EXFILTRATION - Exfiltration Over C2 Channel

IoC List

IoC       Type    Description + Probability

181.214.147[.]164      IP Address       Likely C2 Infrastructure

176.123.4[.]22            IP Address       Likely C2 Infrastructure

5.45.74[.]137               IP Address           Possible C2 Infrastructure

38.180.242[.]122        IP Address       Possible C2 Infrastructure

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.
Written by
Maria Geronikolou
Cyber Analyst

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April 24, 2025

The Importance of NDR in Resilient XDR

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As threat actors become more adept at targeting and disabling EDR agents, relying solely on endpoint detection leaves critical blind spots.

Network detection and response (NDR) offers the visibility and resilience needed to catch what EDR can’t especially in environments with unmanaged devices or advanced threats that evade local controls.

This blog explores how threat actors can disable or bypass EDR-based XDR solutions and demonstrates how Darktrace’s approach to NDR closes the resulting security gaps with Self-Learning AI that enables autonomous, real-time detection and response.

Threat actors see local security agents as targets

Recent research by security firms has highlighted ‘EDR killers’: tools that deliberately target EDR agents to disable or damage them. These include the known malicious tool EDRKillShifter, the open source EDRSilencer, EDRSandblast and variants of Terminator, and even the legitimate business application HRSword.

The attack surface of any endpoint agent is inevitably large, whether the software is challenged directly, by contesting its local visibility and access mechanisms, or by targeting the Operating System it relies upon. Additionally, threat actors can readily access and analyze EDR tools, and due to their uniformity across environments an exploit proven in a lab setting will likely succeed elsewhere.

Sophos have performed deep research into the EDRShiftKiller tool, which ESET have separately shown became accessible to multiple threat actor groups. Cisco Talos have reported via TheRegister observing significant success rates when an EDR kill was attempted by ransomware actors.

With the local EDR agent silently disabled or evaded, how will the threat be discovered?

What are the limitations of relying solely on EDR?

Cyber attackers will inevitably break through boundary defences, through innovation or trickery or exploiting zero-days. Preventive measures can reduce but not completely stop this. The attackers will always then want to expand beyond their initial access point to achieve persistence and discover and reach high value targets within the business. This is the primary domain of network activity monitoring and NDR, which includes responsibility for securing the many devices that cannot run endpoint agents.

In the insights from a CISA Red Team assessment of a US CNI organization, the Red Team was able to maintain access over the course of months and achieve their target outcomes. The top lesson learned in the report was:

“The assessed organization had insufficient technical controls to prevent and detect malicious activity. The organization relied too heavily on host-based endpoint detection and response (EDR) solutions and did not implement sufficient network layer protections.”

This proves that partial, isolated viewpoints are not sufficient to track and analyze what is fundamentally a connected problem – and without the added visibility and detection capabilities of NDR, any downstream SIEM or MDR services also still have nothing to work with.

Why is network detection & response (NDR) critical?

An effective NDR finds threats that disable or can’t be seen by local security agents and generally operates out-of-band, acquiring data from infrastructure such as traffic mirroring from physical or virtual switches. This means that the security system is extremely inaccessible to a threat actor at any stage.

An advanced NDR such as Darktrace / NETWORK is fully capable of detecting even high-end novel and unknown threats.

Detecting exploitation of Ivanti CS/PS with Darktrace / NETWORK

On January 9th 2025, two new vulnerabilities were disclosed in Ivanti Connect Secure and Policy Secure appliances that were under malicious exploitation. Perimeter devices, like Ivanti VPNs, are designed to keep threat actors out of a network, so it's quite serious when these devices are vulnerable.

An NDR solution is critical because it provides network-wide visibility for detecting lateral movement and threats that an EDR might miss, such as identifying command and control sessions (C2) and data exfiltration, even when hidden within encrypted traffic and which an EDR alone may not detect.

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024 – 11 days before the public disclosure of the vulnerability, this early detection highlights the benefits of an anomaly-based network detection method.

Throughout the campaign and based on the network 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.

Darktrace / NETWORK’s autonomous response capabilities played a critical role in containment by autonomously blocking suspicious connections and enforcing normal behavior patterns. At the same time, Darktrace Cyber AI Analyst™ automatically investigated and correlated the anomalous activity into cohesive incidents, revealing the full scope of the compromise.

This case highlights the importance of real-time, AI-driven network monitoring to detect and disrupt stealthy post-exploitation techniques targeting unmanaged or unprotected systems.

Unlocking adaptive protection for evolving cyber risks

Darktrace / NETWORK uses unique AI engines that learn what is normal behavior for an organization’s entire network, continuously analyzing, mapping and modeling every connection to create a full picture of your devices, identities, connections, and potential attack paths.

With its ability to uncover previously unknown threats as well as detect known threats using signatures and threat intelligence, Darktrace is an essential layer of the security stack. Darktrace has helped secure customers against attacks including 2024 threat actor campaigns against Fortinet’s FortiManager , Palo Alto firewall devices, and more.  

Stay tuned for part II of this series which dives deeper into the differences between NDR types.

Credit to Nathaniel Jones VP, Security & AI Strategy, FCISO & Ashanka Iddya, Senior Director of Product Marketing for their contribution to this blog.

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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April 22, 2025

Obfuscation Overdrive: Next-Gen Cryptojacking with Layers

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Out of all the services honeypotted by Darktrace, Docker is the most commonly attacked, with new strains of malware emerging daily. This blog will analyze a novel malware campaign with a unique obfuscation technique and a new cryptojacking technique.

What is obfuscation?

Obfuscation is a common technique employed by threat actors to prevent signature-based detection of their code, and to make analysis more difficult. This novel campaign uses an interesting technique of obfuscating its payload.

Docker image analysis

The attack begins with a request to launch a container from Docker Hub, specifically the kazutod/tene:ten image. Using Docker Hub’s layer viewer, an analyst can quickly identify what the container is designed to do. In this case, the container is designed to run the ten.py script which is built into itself.

 Docker Hub Image Layers, referencing the script ten.py.
Figure 1: Docker Hub Image Layers, referencing the script ten.py.

To gain more information on the Python file, Docker’s built in tooling can be used to download the image (docker pull kazutod/tene:ten) and then save it into a format that is easier to work with (docker image save kazutod/tene:ten -o tene.tar). It can then be extracted as a regular tar file for further investigation.

Extraction of the resulting tar file.
Figure 2: Extraction of the resulting tar file.

The Docker image uses the OCI format, which is a little different to a regular file system. Instead of having a static folder of files, the image consists of layers. Indeed, when running the file command over the sha256 directory, each layer is shown as a tar file, along with a JSON metadata file.

Output of the file command over the sha256 directory.
Figure 3: Output of the file command over the sha256 directory.

As the detailed layers are not necessary for analysis, a single command can be used to extract all of them into a single directory, recreating what the container file system would look like:

find blobs/sha256 -type f -exec sh -c 'file "{}" | grep -q "tar archive" && tar -xf "{}" -C root_dir' \;

Result of running the command above.
Figure 4: Result of running the command above.

The find command can then be used to quickly locate where the ten.py script is.

find root_dir -name ten.py

root_dir/app/ten.py

Details of the above ten.py script.
Figure 5: Details of the above ten.py script.

This may look complicated at first glance, however after breaking it down, it is fairly simple. The script defines a lambda function (effectively a variable that contains executable code) and runs zlib decompress on the output of base64 decode, which is run on the reversed input. The script then runs the lambda function with an input of the base64 string, and then passes it to exec, which runs the decoded string as Python code.

To help illustrate this, the code can be cleaned up to this simplified function:

def decode(input):
   reversed = input[::-1]

   decoded = base64.decode(reversed)
   decompressed = zlib.decompress(decoded)
   return decompressed

decoded_string = decode(the_big_text_blob)
exec(decoded_string) # run the decoded string

This can then be set up as a recipe in Cyberchef, an online tool for data manipulation, to decode it.

Use of Cyberchef to decode the ten.py script.
Figure 6: Use of Cyberchef to decode the ten.py script.

The decoded payload calls the decode function again and puts the output into exec. Copy and pasting the new payload into the input shows that it does this another time. Instead of copy-pasting the output into the input all day, a quick script can be used to decode this.

The script below uses the decode function from earlier in order to decode the base64 data and then uses some simple string manipulation to get to the next payload. The script will run this over and over until something interesting happens.

# Decode the initial base64

decoded = decode(initial)
# Remove the first 11 characters and last 3

# so we just have the next base64 string

clamped = decoded[11:-3]

for i in range(1, 100):
   # Decode the new payload

   decoded = decode(clamped)
   # Print it with the current step so we

   # can see what’s going on

   print(f"Step {i}")

   print(decoded)
   # Fetch the next base64 string from the

   # output, so the next loop iteration will

   # decode it

   clamped = decoded[11:-3]

Result of the 63rd iteration of this script.
Figure 7: Result of the 63rd iteration of this script.

After 63 iterations, the script returns actual code, accompanied by an error from the decode function as a stopping condition was never defined. It not clear what the attacker’s motive to perform so many layers of obfuscation was, as one round of obfuscation versus several likely would not make any meaningful difference to bypassing signature analysis. It’s possible this is an attempt to stop analysts or other hackers from reverse engineering the code. However,  it took a matter of minutes to thwart their efforts.

Cryptojacking 2.0?

Cleaned up version of the de-obfuscated code.
Figure 8: Cleaned up version of the de-obfuscated code.

The cleaned up code indicates that the malware attempts to set up a connection to teneo[.]pro, which appears to belong to a Web3 startup company.

Teneo appears to be a legitimate company, with Crunchbase reporting that they have raised USD 3 million as part of their seed round [1]. Their service allows users to join a decentralized network, to “make sure their data benefits you” [2]. Practically, their node functions as a distributed social media scraper. In exchange for doing so, users are rewarded with “Teneo Points”, which are a private crypto token.

The malware script simply connects to the websocket and sends keep-alive pings in order to gain more points from Teneo and does not do any actual scraping. Based on the website, most of the rewards are gated behind the number of heartbeats performed, which is likely why this works [2].

Checking out the attacker’s dockerhub profile, this sort of attack seems to be their modus operandi. The most recent container runs an instance of the nexus network client, which is a project to perform distributed zero-knowledge compute tasks in exchange for cryptocurrency.

Typically, traditional cryptojacking attacks rely on using XMRig to directly mine cryptocurrency, however as XMRig is highly detected, attackers are shifting to alternative methods of generating crypto. Whether this is more profitable remains to be seen. There is not currently an easy way to determine the earnings of the attackers due to the more “closed” nature of the private tokens. Translating a user ID to a wallet address does not appear to be possible, and there is limited public information about the tokens themselves. For example, the Teneo token is listed as “preview only” on CoinGecko, with no price information available.

Conclusion

This blog explores an example of Python obfuscation and how to unravel it. Obfuscation remains a ubiquitous technique employed by the majority of malware to aid in detection/defense evasion and being able to de-obfuscate code is an important skill for analysts to possess.

We have also seen this new avenue of cryptominers being deployed, demonstrating that attackers’ techniques are still evolving - even tried and tested fields. The illegitimate use of legitimate tools to obtain rewards is an increasingly common vector. For example,  as has been previously documented, 9hits has been used maliciously to earn rewards for the attack in a similar fashion.

Docker remains a highly targeted service, and system administrators need to take steps to ensure it is secure. In general, Docker should never be exposed to the wider internet unless absolutely necessary, and if it is necessary both authentication and firewalling should be employed to ensure only authorized users are able to access the service. Attacks happen every minute, and even leaving the service open for a short period of time may result in a serious compromise.

References

1. https://www.crunchbase.com/funding_round/teneo-protocol-seed--a8ff2ad4

2. https://teneo.pro/

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About the author
Nate Bill
Threat Researcher
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