On Thursday March 6th, an urgent alert was received from one of our customers in the insurance sector regarding a potential zero-day threat in their environment. The alert raised concerns about an unreleased, non-public vulnerability, triggering immediate action.
This case study details how the Vectra AI Platform enabled rapid collaboration and precise detection—transforming uncertainty into actionable insights.
Incident Timeline & Response
Initial alert
Time: Thursday, 9:56 AM
An urgent message notified our managed services team of a possible zero-day threat. The customer was unsure if the vulnerability had been exploited and needed assistance with a custom detection.
Team mobilization
Time: By 10:02 AM
Our cross-functional team—including Security Research, MDR, CSM, and Sales—immediately joined a call with the customer. This collaboration set the stage for a sprint to develop and deploy custom detection measures.
Building the custom detection
Time: By Friday at 11 PM
Using Vectra NDR’s Suspect Protocol Activity (SPA) detections feature, our Security Research team was able to rapidly craft a custom signature. SPA detections, powered by a Suricata engine on our Vectra Sensors and mixed-mode appliances, can be created much more quickly than traditional AI-based models. This approach not only enhances our overall threat coverage but also provides immediate visibility in the Vectra UI and contributes to host entity scoring.
Our MDR team then deployed Recall Saved Searches, enabling retrospective hunting of the vulnerability across historical data.
By integrating this signature context with the comprehensive analytics of the Vectra AI Platform, we were able to detect the Apache Camel vulnerability swiftly and accurately.
Understanding the Vulnerability
The vulnerability, later identified as CVE-2025-27636, is associated with Apache Camel’s header injection flaw in the Camel-bean component. Due to a shortfall in the default header filtering mechanism, the system does not adequately block custom headers. This gap allows an attacker to send HTTP requests with specially crafted Apache Headers that bypass expected controls.
With this vulnerability, an attacker could potentially:
- Alter method invocation: Force the Camel-bean component to invoke an unintended method on a bean, thereby triggering operations that were not part of the original design.
- Reroute messages: In configurations using components like camel-jms, the injected headers could reroute messages to unauthorized queues or destinations, potentially leading to data interception or tampering.
- Bypass security controls: Exploit the weak filtering to manipulate the application's behavior, ultimately bypassing standard security measures and exposing sensitive information.
Though the vulnerability has been flagged as moderate, its exploitation could still lead to significant operational issues—such as unintended method invocations and unauthorized message rerouting. Since this flaw can be remedied by applying an Apache Camel software update, it underscores the importance of timely patching and maintaining robust Apache Header validation and filtering mechanisms.
Operational Impact & Customer Success
Immediate outcomes
The Security Research team meticulously developed and tested the custom signature to ensure it wouldn’t cause disruptions in production environments. Once deployed, the signature proved pivotal in identifying hits on the Apache Camel vulnerability—even on sensors that weren’t initially targeted—thereby providing critical coverage without impacting system stability.
By Friday at 11 PM, our customer was informed that custom/tailored Metadata based queries had been created and were now available in their Vectra UI for further investigation.
Customer feedback
On Monday, the customer expressed their gratitude:
"I am writing to express my sincere gratitude for your hard and fast response this past weekend to the CVE-2025-27636 Bypass/Injection vulnerability in the Apache Camel-Bean component. Your team's prompt action was instrumental in addressing this critical issue under particular conditions... Thank you once again for your unwavering support and commitment to our cybersecurity efforts."
Lessons Learned & Best Practices
1. Agile collaboration
The incident underscored the value of rapid, coordinated response. The integrated efforts of both the Security Research and MDR teams enabled the swift identification and mitigation of the threat, showcasing the importance of a well-orchestrated incident response plan. By working closely together, these teams were able to share insights quickly, validate findings, and keep the response effort focused on critical risks.
2. Team excellence
- Security Research Team: Their deep technical expertise was pivotal in developing and testing a custom signature that effectively addressed the vulnerability. This rigorous approach ensured the signature was both accurate and safe to deploy, preventing any unintended impact on production systems.
- MDR Team: By pairing the newly developed signature with advanced threat hunting and rapid analysis, the MDR team ensured even subtle indicators of compromise were detected. This collaboration highlights how a dedicated MDR service can accelerate detection and guide more effective responses, ultimately minimizing the threat’s impact on the customer’s environment.
3. Custom detection capabilities
The ability to quickly develop tailored Metadata queries using Vectra AI for Networks further highlighted how combining signature-based intelligence with AI-driven detection can provide comprehensive visibility into both known vulnerabilities and emerging threats. This flexibility allows security teams to adapt faster to novel attack patterns and evolving exploits.
4. Optimized workflow and continuous improvement
Integrating MDR services into the overall security posture not only streamlined response times but also reinforced the importance of continuous monitoring and improvement. This case serves as a reminder to continuously refine detection methods and invest in teams that can adapt quickly to evolving threats.
5. Actionable insights
The incident provided clear takeaways regarding the importance of robust input sanitization, tailored threat detection, and a unified approach to security. These insights can guide other organizations in optimizing their incident response strategies and reinforcing their cybersecurity defenses.
This case study serves as a clear example of how rapid response and precise detection can mitigate potential threats before they escalate into full-blown incidents. By leveraging the capabilities of the Vectra AI Platform, cybersecurity teams can address vulnerabilities—even those unknown until they surface—with efficiency and confidence. Learn more about our platform by requesting a demo or contact us to talk to our experts. Not ready to get in touch just yet? Watch our self-guided tour!