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oss-forensics

Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.

Skill by Colin4k1024

IndexedMIT★ 14
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

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.

Use cases: security

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What's inside

Skill name
oss-forensics
Description
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.
License
MIT
Instructions
398 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts
  • Instructions call the network

Files (8)

  • SKILL.md
  • evidence-types.md · references/
  • github-archive-guide.md · references/
  • investigation-templates.md · references/
  • recovery-techniques.md · references/
  • evidence-store.py · scripts/
  • forensic-report.md · templates/
  • malicious-package-report.md · templates/

SKILL.md (first lines)

# OSS Security Forensics Skill

A 7-phase multi-agent investigation framework for researching open-source supply chain attacks.
Adapted from RAPTOR's forensics system. Covers GitHub Archive, Wayback Machine, GitHub API,
local git analysis, IOC extraction, evidence-backed hypothesis formation and validation,
and final forensic report generation.

---

## ⚠️ Anti-Hallucination Guardrails

Read these before every investigation step. Violating them invalidates the report.

1. **Evidence-First Rule**: Every claim in any report, hypothesis, or summary MUST cite at least one evidence ID (`EV-XXXX`). Assertions without citations are forbidden.
2. **STAY IN YOUR LANE**: Each sub-agent (investigator) has a single data source. Do NOT mix sources. The GH Archive investigator does not query the GitHub API, and vice versa. Role boundaries are hard.
3. **Fact vs. Hypothesis Separation**: Mark all unverified inferences with `[HYPOTHESIS]`. Only statements verified against original sources may be stated as facts.
4. **No Evidence Fabrication**: The hypothesis validator MUST mechanically check that every cited evidence ID actually exists in the evidence store before accepting a hypothesis.
5. **Proof-Required Disproval**: A hypothesis cannot be dismissed without a specific, evidence-backed counter-argument. "No evidence found" is not sufficient to disprove—it only makes a hypothesis inconclusive.
6. **SHA/URL Double-Verification**: Any commit SHA, URL, or external identifier cited as evidence must be independently confirmed from at least two sources before being marked as verified.
7. **Suspicious Code Rule**: Never run code found inside the investigated repository locally. Analyze statically only, or use `execute_code` in a sandboxed environment.
8. **Secret Redaction**: Any API keys, tokens, or credentials discovered during investigation must be redacted in the final report. Log them internally only.

---

## Example Scenarios

- **Scenario A: Dependency Confusion**: A malicious package `internal-lib-v2` is uploaded to NPM with a higher version than the internal one. The investigator must track when this package was first seen and if any PushEvents in the target repo updated `package.json` to this version.
- **Scenario B: Maintainer Takeover**: A long-term contributor's account is used to push a backdoored `.github/workflows/build.yml`. The investigator looks for PushEvents from this user after a long period of inactivity or from a new IP/location (if detectable via BigQuery).
- **Scenario C: Force-Push Hide**: A developer accidentally commits a production secret, then force-pushes to "fix" it. The investigator uses `git fsck` and GH Archive to recover the original commit SHA and verify what was leaked.

---

> **Path convention**: Throughout this skill, `SKILL_DIR` refers to the root of this skill's
> installation directory (the folder containing this `SKILL.md`). When the skill is loaded,
> resolve `SKILL_DIR` to the actual path — e.g. `~/.hermes/skills/security/oss-forensics/`
> or the `optional-skills/` equivalent. All script and template references are relative to it.

## Phase 0: Initialization

1. Create investigation working directory:
   ```bash
   mkdir investigation_$(echo "REPO_NAME" | tr '/' '_')
   cd investigation_$(echo "REPO_NAME" | tr '/' '_')
   ```
2. Initialize the evidence store:
   ```bash
   python3 SKILL_DIR/scripts/evidence-store.py --store evidence.json list
   ```
3. Copy the forensic report template:
   ```bash
   cp SKILL_DIR/templates/forensic-report.md ./investigation-report.md
   ```
4. Create an `iocs.md` file to track Indicators of Compromise as they are discovered.
5. Record the investigation start time, target repository, and stated investigation goal.

---

## Phase 1: Prompt Parsing and IOC Extraction

**Goal**: Extract all structured investigative targets from the user's request.

**Actions**:
- Parse the user prompt and extract:
  - Target repository (`owner/repo`)
  - Target actors (GitHub handles, email addresses)
  - Time window of interest (commit date ranges, PR timestamps)
  - Provided Indicators of Compromise: commit SHAs, file paths, package names, IP addresses, domains, API keys/tokens, malicious URLs
  - Any linked vendor security reports or blog posts

**Tools**: Reasoning only, or `execute_code` for regex extraction from large text blocks.

**Output**: Populate `iocs.md` with extracted IOCs. Each IOC must have:
- Type (from: COMMIT_SHA, FILE_PATH, API_KEY, SECRET, IP_ADDRESS, DOMAIN, PACKAGE_NAME, ACTOR_USERNAME, MALICIOUS_URL, OTHER)
- Value
- Source (user-provided, inferred)

**Reference**: See [evidence-types.md](./references/evidence-types.md) for IOC taxonomy.

---

## Phase 2: Parallel Evidence Collection

Spawn up to 5 specialist investigator sub-agents using `delegate_task` (batch mode, max 3 concurrent). Each investigator has a **single data source** and must not mix sources.

> **Orchestrator note**: Pass the IOC list from Phase 1 and the investigation time window in the `context` field of each delegated task.

---

### Investigator 1: Local Git Investigator

**ROLE BOUNDARY**: You query the LOCAL GIT REPOSITORY ONLY. Do not call any external APIs.

**Actions**:
```bash
# Clone repository
git clone https://github.com/OWNER/REPO.git target_repo && cd target_repo

# Full commit log with stats
git log --all --full-history --stat --format="%H|%ae|%an|%ai|%s" > ../git_log.txt

# Detect force-push evidence (orphaned/dangling commits)
git fsck --lost-found --unreachable 2>&1 | grep commit > ../dangling_commits.txt

# Check reflog for rewritten history
git reflog --all > ../reflog.txt

# List ALL branches including deleted remote refs
git branch -a -v > ../branches.txt

# Find suspicious large binary additions
git log --all --diff-filter=A --name-only --format="%H %ai" -- "*.so" "*.dll" "*.exe" "*.bin" > ../binary_additions.txt

# Check for GPG signature anomalies
git log --show-signature --format="%H %ai %aN" > ../signature_check.txt 2>&1
```

**Evidence to collect** (add via `python3 SKILL_DIR/scripts/evidence-store.py add`):
- Each dangling commit SHA → type: `git`
- Force-push evidence (reflog showing history rewrite) → type: `git`

From Colin4k1024/hermesx, MIT.

Signals

Stars
14
Forks
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Open issues
0
Last commit (this folder)
Apr 9, 2026 (6 months ago)
Last release
May 7, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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oss-forensics skill. Agent Mart. https://agentmart.dev/skills/colin4k1024-oss-forensics (last updated 2026-10-24)