Last seen February 11, 2026

AI Prompt Injection Vulnerability

The article highlights significant security risks posed by AI personal assistants like OpenClaw, primarily focusing on prompt injection as a key vulnerability. This exploit allows attackers to effectively hijack Large Language Models (LLMs) by embedding malicious text in data, potentially leading to unauthorized data access, arbitrary command execution, or system compromise.

Technical Severity
Low severity
Lifecycle Status

STABLE

What Happened

The article highlights significant security risks posed by AI personal assistants like OpenClaw, primarily focusing on prompt injection as a key vulnerability. This exploit allows attackers to effectively hijack Large Language Models (LLMs) by embedding malicious text in data, potentially leading to unauthorized data access, arbitrary command execution, or system compromise.

Why This Matters

Current evidence identifies a security issue involving the affected technology, but does not yet support a more specific impact claim.

Recommended Action

No confirmed vendor remediation is available in the current evidence. Confirm whether the affected technology is present in your environment and review the affected configuration.

Exposure

My AI Stack Exposure

Exposure unknown

Recommended Response
Last Seen

Feb 11, 2026 05:30

Exposure reason: This incident does not currently match a technology in My AI Stack.

Exploitation status: UNKNOWN

Primary entities:

AI AgentsJailbreakingPrompt Injection

Timeline

  • Incident first seen
    Feb 11, 2026 05:30

    BugSkan first recorded this incident.

  • Is a secure AI assistant possible? - MIT Technology Review
    Feb 11, 2026 05:30

    technologyreview.com · Research

Sources

Is a secure AI assistant possible? - MIT Technology Review

technologyreview.com · Feb 11, 2026 05:30

The article highlights significant security risks posed by AI personal assistants like OpenClaw, primarily focusing on prompt injection as a key vulnerability. This exploit allows attackers to effectively hijack Large Language Models (LLMs) by embedding malicious text in data, potentially leading to unauthorized data access, arbitrary command execution, or system compromise.

Open publisher source

My AI Stack Match

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