Agent Skills: Python Packaging Git Audit

Python Packaging Git Audit

Inspects the recent git history of a Python package repository for commits that modify supply-chain-sensitive files (setup.py, CI configs, .pth files, etc.) and contain suspicious patterns. Produces a self-contained "Git History Analysis" report section with triaged findings and a risk assessment.

Inputs

• repo_path (required): Local filesystem path to a git repository
• output_file (optional): Write the report section to this file path instead of returning it inline. The first line of the file must be RISK_RATING:<value> so the orchestrator can parse it without reading the full report.

Step 1: Enumerate Commits

Determine the number of commits available and scan up to the last 50:

git -C <repo-path> log -50 --format='%H'

Step 2: Filter Sensitive Files

From those commits, identify ones that modify supply-chain-sensitive files:

• setup.py, setup.cfg, pyproject.toml, MANIFEST.in
• .github/workflows/*.yml, .gitlab-ci.yml
• Any .pth files
• __init__.py files at package root

git -C <repo-path> log -50 --diff-filter=ACMR --name-only --format='COMMIT:%H|%aI|%ae' -- \
  setup.py setup.cfg pyproject.toml MANIFEST.in \
  '.github/workflows/*.yml' .gitlab-ci.yml \
  '*.pth' '*/__init__.py'

Step 3: Search for Suspicious Patterns

For each flagged commit, extract the diff and search for suspicious patterns:

• Code execution: eval(, exec(, compile(
• Process spawning: subprocess, os.system, os.popen
• Encoding/serialization: base64, marshal, pickle
• Network access: socket, urllib, requests.get, httpx
• Native code: ctypes, cffi
• Embedded URLs: http://, https://

git -C "<repo-path>" show --format= -m --first-parent "<commit>" -- "<file>" | \
  grep -nE 'eval\(|exec\(|compile\(|subprocess|os\.system|os\.popen|base64|marshal|pickle|socket|urllib|requests\.get|httpx|ctypes|cffi|https?://'

Collect per finding: commit hash, author, date, file modified, and matching patterns.

Step 4: Triage

Review git history findings with AI reasoning. There are no deterministic rules for this phase — each finding requires contextual judgment.

For each flagged commit, consider:

• Is this a normal dependency version bump or configuration change?
• Does the pattern match the package's stated purpose?
• Is the author a known maintainer with a history of contributions?
• Does the change introduce new capabilities that seem out of scope?

Flag commits that introduced suspicious patterns into sensitive files. Assign a verdict to each:

• Likely legitimate — change is a normal maintenance or dependency update
• Suspicious — change introduces unexpected capabilities or patterns
• Critical — change strongly indicates malicious intent (e.g., encoded payload in install hook)

Output Format

Produce the following markdown section:

## Git History Analysis (Last 50 Commits)

**Commits touching sensitive files:** {N}

| Commit | Date | Author | File | Patterns Found |
|--------|------|--------|------|----------------|
| abc1234 | 2026-03-15 | user@example.com | setup.py | subprocess, os.system |

**AI Assessment:** {Brief narrative on whether the git history changes look normal or concerning, with reasoning}

The risk_rating for this phase is one of:

• no_issues — No sensitive files modified in recent history
• low_risk — All findings classified as "likely legitimate"
• needs_review — One or more findings classified as "suspicious"
• critical — One or more findings classified as "critical"

If output_file is provided, write the file with the first line as RISK_RATING:<value> followed by a blank line and then the markdown section above. If output_file is not provided, return the report section inline.

Error Handling

| Scenario | Behavior | |----------|----------| | Path is not a git repository | Report "not a git repository", risk_rating = needs_review | | Fewer than 50 commits available | Scan all available commits, note count in report | | No sensitive files modified in history | Report "no sensitive files found", risk_rating = no_issues |