oss-forensics
Skill38 starsChanged 5 months agoMITView on GitHub
Investigate open-source repository compromise, deleted commits, force-pushes, suspicious releases, and supply-chain indicators with evidence IDs.
- Reads credentials
1 other project uses a version of this.
Adopted by
Most recently taken up by
- nobodyohm-web/Thottheir own version, first seen Oct 13, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- nobodyohm-web/Thot★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository76 other files it gives its agents.
- AGENTS.mdAGENTS.md
- templates/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 9
Use this for defensive supply-chain investigations: suspicious commits, force-pushes, deleted releases, maintainer takeover concerns, …
- Distinctive: line 15
Do not run code from the investigated repository.
- Distinctive: line 21
Create a working directory outside the target repo:
- Very specific: line 52
Use GITHUB_TOKEN if available to avoid low rate limits.
- Distinctive: line 63
Create hypotheses, then validate:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
OSS Forensics
Use this for defensive supply-chain investigations: suspicious commits, force-pushes, deleted releases, maintainer takeover concerns, leaked secrets, or package compromise.
Guardrails
- Evidence first. Every claim needs an evidence ID such as
EV-0001. - Separate fact from hypothesis. Prefix unverified inferences with
[HYPOTHESIS]. - Do not run code from the investigated repository.
- Redact secrets in chat and reports.
- Double-check SHAs, URLs, package versions, and actor names against more than one source when possible.
Evidence Store
Create a working directory outside the target repo:
INVESTIGATION="oss-forensics-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$INVESTIGATION"/{evidence,reports}
cd "$INVESTIGATION"
printf "# Evidence\n\n" > evidence/index.mdEvidence entry shape:
EV-0001
Source: local git log
Time collected: <ISO timestamp>
Claim supported: <short claim>
Artifact: evidence/git-log.txt
Notes: <why it matters>Collection Plan
- Extract targets:
- repo, package names, SHAs, actors, date range, releases, domains, URLs.
- Local git source:
git clone --mirroror normal clone.git log --all --full-history --stat --format="%H|%ae|%an|%ai|%s".git fsck --lost-found --unreachable.git branch -a -v, tags, release branches, suspicious binaries.
- GitHub/API source:
- commits, PRs, issues, releases, events, tags.
- Use
GITHUB_TOKENif available to avoid low rate limits.
- Archive sources:
- Wayback CDX for deleted PRs/issues/releases.
- GH Archive or public event datasets when date windows matter.
- Package registries:
- npm/PyPI/crates/GitHub Releases metadata, checksums, publish dates.
- IOC extraction:
- domains, IPs, package names, hashes, suspicious scripts, workflow edits.
Analysis
Create hypotheses, then validate:
- Force-push hide: evidence from local unreachable commits plus public events.
- Maintainer takeover: unusual actor timing, permissions, workflow changes, signed commit drift.
- Release/package swap: tag/release/package timestamps disagree or artifacts changed.
- Secret leak: secret-like material existed in a reachable/dangling commit and was pushed externally.
Report
Include:
- Scope and timeline.
- Evidence table.
- Findings with severity and supporting evidence IDs.
- Hypotheses ruled out and why.
- Recommended containment, rotation, and hardening steps.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

