oss-forensics
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories. Covers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence collection, hypothesis formation/validation, and structured forensic reporting. Inspired by RAPTOR's 1800+ line OSS Forensics system.
67
81%
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Critical
Do not install without reviewing
Security
2 findings: 1 critical severity, 1 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
E005: Suspicious download URL detected in skill instructions.
What this means
Detected a suspicious URL in the skill instructions that could lead the agent to download and execute malicious scripts or binaries. This includes links to executables from untrusted sources, typosquatting of official packages, URL shorteners that obscure the destination, and personal file hosting services.
Why it was flagged
The majority of listed URLs are GitHub, GitHub API, or Wayback Machine links (low risk), but the presence of a direct .sh downloader hosted on an untrusted domain (https://evil.example.com/payload.sh) is a high-risk indicator of malicious payload distribution.
W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The skill explicitly instructs the agent to extract and store API keys/tokens as IOC "Value" (Phase 1) and even shows an example token pattern ("export GITHUB_TOKEN=ghp_..."), which forces the LLM to handle secret values verbatim (despite later advising redaction), creating a high exfiltration risk.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow fetches outsider-authored content at runtime (e.g., via the Wayback Machine in Investigator 3 and evidence store entries derived from `web_archive` content), and that recovered page text can be carried into `evidence.json` and then into the agent’s LLM context during report generation/summarization.
- Repository
- NousResearch/hermes-agent
- Commit
d92bfa0
- Audited
- Security analysis
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