Incident Score: Analysis & Impact (OPE1772180865)

In this Rankiteo incident briefing, we review the OpenClaw breach identified under incident ID OPE1772180865.

The analysis begins with a detailed overview of OpenClaw's information like the linkedin page: https://www.linkedin.com/company/openclawai, the number of followers: 2607, the industry type: Technology, Information and Internet and the number of employees: 5 employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 664 and after the incident was 659 with a difference of -5 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on OpenClaw and their customers.

On 25 February 2026, OpenClaw AI Agent disclosed Vulnerability Exploitation issues under the banner "OpenClaw AI Agent WebSocket Vulnerability Exploit".

OpenClaw, an open-source AI agent, was found to have a severe security flaw in its core architecture that allowed malicious websites to hijack the agent without user interaction.

The disruption is felt across the environment, affecting OpenClaw AI Agent (self-hosted instances), and exposing Sensitive data (e.g., Slack messages, API keys).

In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Patch released (version 2026.2.25), and began remediation that includes Fixed WebSocket gateway authentication and rate limiting.

The case underscores how Resolved, teams are taking away lessons such as The incident highlights risks in shadow AI adoption, where tools are deployed without IT oversight. It underscores the need for intent-based guardrails, audit trails, and structured oversight for autonomous AI agents, and recommending next steps like Implement intent-based guardrails for AI agents, Enforce centralized controls and audit trails and Improve visibility into self-hosted AI tools.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.