Last seen October 9, 2025

AI agent Remote Code Execution Vulnerability

Attackers can achieve remote code execution (RCE) on developer machines by leveraging indirect prompt injection against agentic AI developer tools. This is accomplished by introducing untrusted data, such as malicious commands in GitHub issues or hidden payloads in fake Python packages within pull requests, which the AI agent autonomously executes.

Technical Severity
Low severity
Lifecycle Status

STABLE

What Happened

Attackers can achieve remote code execution (RCE) on developer machines by leveraging indirect prompt injection against agentic AI developer tools. This is accomplished by introducing untrusted data, such as malicious commands in GitHub issues or hidden payloads in fake Python packages within pull requests, which the AI agent autonomously executes.

Why This Matters

Publisher reporting describes a security event affecting GitHub. BugSkan could not yet bind a CVE or affected version, so treat the source details as the current record.

Recommended Action

Confirm whether GitHub is present in your environment and review vendor guidance for this report. Apply available patches or mitigations if your deployment matches the described conditions.

Exposure

My Interests Exposure

Exposure unknown

Recommended Response
Last Seen

Oct 09, 2025 05:30

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

Exploitation status: UNKNOWN

Primary entities:

GitHubAI agentAgentic AIGitHub issuesPython packagesagentic AI developer tools

Timeline

  • Incident first seen
    Oct 09, 2025 05:30

    BugSkan first recorded this incident.

  • From Assistant to Adversary: Exploiting Agentic AI Developer Tools - NVIDIA Developer
    Oct 09, 2025 05:30

    developer.nvidia.com · Vulnerability

Sources

From Assistant to Adversary: Exploiting Agentic AI Developer Tools - NVIDIA Developer

developer.nvidia.com · Oct 09, 2025 05:30

Attackers can achieve remote code execution (RCE) on developer machines by leveraging indirect prompt injection against agentic AI developer tools. This is accomplished by introducing untrusted data, such as malicious commands in GitHub issues or hidden payloads in fake Python packages within pull requests, which the AI agent autonomously executes.

Open publisher source

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