Last seen October 28, 2025

AI Prompt Injection Vulnerability

Lakera has launched an open-source security benchmark specifically designed to evaluate and enhance the security posture of Large Language Model (LLM) backends integrated into AI agents. This benchmark aims to proactively identify and mitigate various potential vulnerabilities, such as prompt injection and data exfiltration risks, inherent in the deployment of advanced conversational AI systems.

Technical Severity
Low severity
Lifecycle Status

STABLE

What Happened

Lakera has launched an open-source security benchmark specifically designed to evaluate and enhance the security posture of Large Language Model (LLM) backends integrated into AI agents. This benchmark aims to proactively identify and mitigate various potential vulnerabilities, such as prompt injection and data exfiltration risks, inherent in the deployment of advanced conversational AI systems.

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

Oct 28, 2025 05:30

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

Exploitation status: UNKNOWN

Primary entities:

AI AgentsPrompt InjectionRemote Code Execution

Timeline

  • Incident first seen
    Oct 28, 2025 05:30

    BugSkan first recorded this incident.

  • Lakera Launches Open-Source Security Benchmark for LLM Backends in AI Agents - Business Wire
    Oct 28, 2025 05:30

    news.google.com · Research

Sources

Lakera Launches Open-Source Security Benchmark for LLM Backends in AI Agents - Business Wire

news.google.com · Oct 28, 2025 05:30

Lakera has launched an open-source security benchmark specifically designed to evaluate and enhance the security posture of Large Language Model (LLM) backends integrated into AI agents. This benchmark aims to proactively identify and mitigate various potential vulnerabilities, such as prompt injection and data exfiltration risks, inherent in the deployment of advanced conversational AI systems.

Open publisher source

My AI Stack Match

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