github-secret-hunting – Coding skill for AI agents
Find leaked API keys, tokens, and credentials in public GitHub repositories.
Install the github-secret-hunting skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/github-secret-hunting-00779.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /github-secret-hunting – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/github-secret-hunting-00779.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $github-secret-hunting – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/github-secret-hunting-00779.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /github-secret-hunting – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/github-secret-hunting-00779.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /github-secret-hunting – then describe the task you want done.
SKILL.md content
GitHub Secret Hunting
Scan public GitHub repositories for leaked API keys, tokens, passwords, and internal infrastructure details. Developers accidentally push secrets constantly — this skill uses targeted dorking, automated scanning tools, and real-time monitoring to find credentials before the developer notices and revokes them.
When to Use
- Target has public repositories under an organization account.
- JS bundle analysis reveals internal service names — search GitHub for related config files.
- Need to find valid API keys for cloud services, payment gateways, or third-party integrations.
- The target uses CI/CD systems that may leak tokens in build logs or workflow files.
- Want real-time monitoring for new secret leaks from the target org.
Prerequisites
terminalwith python3, curl, git.- GitHub Personal Access Token (only
public_reposcope needed). - Tool dependencies: TruffleHog, GitDorker, gitleaks.
Quick Detection
# Basic GitHub code search for sensitive patterns in target repos
echo "target.com" | while read domain; do
curl --max-time 30 --connect-timeout 10 -s -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/search/code?q=$domain+filename:.env" \
| jq '.items[]?.html_url'
doneProcedure
Phase 1 — Targeted Dorking with GitDorker
# Clone the dork collection and run against target
git clone https://github.com/Proviesec/github-dorks
python3 GitDorker.py \
-tf $GITHUB_TOKEN \
-q target.com \
-d dorks/medium_dorks.txt \
-o gitdorker_target.txt
# Also search by employee emails found in LinkedIn or metadata
python3 GitDorker.py \
-tf $GITHUB_TOKEN \
-q "[email protected]" \
-d dorks/medium_dorks.txt
# Custom dork: find env files
python3 GitDorker.py -tf $GITHUB_TOKEN \
-q "org:target filename:.env DB_PASSWORD" -d dorks/medium_dorks.txtPhase 2 — TruffleHog Deep Scanning
# Scan a specific repo (finds secrets even in deleted commits)
trufflehog git https://github.com/target/repo --results=verified
# Scan entire GitHub org
trufflehog github --org=target --token=$GITHUB_TOKEN \
--only-verified --threads=20 --json > trufflehog_org.json
# Docker variant
docker run --rm -it trufflesecurity/trufflehog:latest \
github --only-verified --org=target
# Parse verified secrets
cat trufflehog_org.json | jq -r 'select(.Verified == true) | "\(.DetectorName): \(.RawV2)"'Phase 3 — Real-Time Monitoring with shhgit
# Monitor globally for secrets being pushed right now
shhgit --search-query \
'path:*.env OR "DB_PASSWORD=" OR "AWS_ACCESS_KEY_ID=" OR "-----BEGIN RSA PRIVATE KEY-----"'
# Monitor specific org
shhgit --search-query \
'target.com (path:*.env OR "DB_PASSWORD=" OR "api_key=")'Phase 4 — File Type and Extension Search
# git-wild-hunt: find specific file types
python3 git-wild-hunt.py \
-s "org:Target extension:json filename:creds language:JSON"
python3 git-wild-hunt.py \
-s "org:Target extension:sql filename:backup"
python3 git-wild-hunt.py \
-s "target.com gitlab_token"
# Manual search patterns via GitHub API
for pattern in "filename:.env DB_PASSWORD" "filename:credentials.json" \
"filename:config.json api_key" "filename:id_rsa" \
"filename:.npmrc" "extension:pem BEGIN RSA" \
"filename:service-account.json"; do
curl --max-time 30 --connect-timeout 10 -s -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/search/code?q=target.com+$pattern" \
| jq '.total_count, (.items[:3][].html_url)'
donePhase 5 — Hardcoded Credential Verification
# Pipeline: find → extract → verify
echo "target.com" | gau | grep -E '\.js$|\.json$|\.env$|\.config$' \
| httpx -silent -mc 200 \
| parallel -j 10 "curl --max-time 30 --connect-timeout 10 -s {} | grep -Eo \
'(?:api[_-]?key|secret|token)[\"'\''']?\s*[:=]\s*[\"'\''']?([A-Za-z0-9_\-]{20,})' \
| tee -a api_keys.txt"
# Verify found keys
for key in $(cat api_keys.txt | awk -F':' '{print $2}' | tr -d '"'\'' ' | sort -u); do
# OpenAI
curl --max-time 30 --connect-timeout 10 -s "https://api.openai.com/v1/models" -H "Authorization: Bearer $key" | jq '.data[].id' 2>/dev/null && echo "VALID OPENAI: $key"
# GitHub
curl --max-time 30 --connect-timeout 10 -s "https://api.github.com/user" -H "Authorization: token $key" | jq '.login' 2>/dev/null && echo "VALID GITHUB: $key"
donePhase 6 — GitLab Private Instances
# Discover self-hosted GitLab
# Check: gitlab.target.com, git.target.com, code.target.com
curl --max-time 30 --connect-timeout 10 -sk "https://gitlab.target.com/api/v4/projects?visibility=public"
# With a found token
curl --max-time 30 --connect-timeout 10 --header "PRIVATE-TOKEN: $GITLAB_TOKEN" \
"https://gitlab.target.com/api/v4/user"
curl --max-time 30 --connect-timeout 10 --header "PRIVATE-TOKEN: $GITLAB_TOKEN" \
"https://gitlab.target.com/api/v4/projects?membership=true&simple=true"
# Deep scan for secrets across accessible repos
gitleaks detect \
--source https://gitlab.target.com \
--access-token $GITLAB_TOKEN -vPhase 7 — Metadata Extraction from Public Documents
# metafinder: downloads public documents and extracts metadata
# Reveals usernames, software versions, internal file paths, email patterns
metafinder -d "target.com" -l 10 -go -bi -ba -o metadata_target.txt
metafinder -d "dev.target.com" -l 10 -go -bi -ba -o metadata_dev.txt
# Manual: check PDF metadata
curl --max-time 30 --connect-timeout 10 -sk "https://target.com/document.pdf" -o doc.pdf
exiftool doc.pdf | grep -i "author\|creator\|producer"Pitfalls
- Most search results are documentation and examples, not real leaks. Focus on
.env,.config,.npmrc, and CI/CD workflow files. - Rate limiting on GitHub API is strict. Use multiple tokens or rotate IPs.
- Verified secrets may already be revoked. Always verify before reporting.
- Self-hosted GitLab instances may block external scanning. Test connectivity first.
- Never use found credentials for unauthorized access. Verify minimally, document, and report.
Verification
1. TruffleHog or GitDorker identifies a potential secret with context.
2. Verify the secret by making a minimal API call (e.g., GET /user for GitHub tokens).
3. Confirm the secret was committed recently (check commit date) — stale secrets are lower priority.
4. Check if the repo is public and the secret grants meaningful access (admin vs read-only).
5. Document the exact file path, commit hash, and line number for the report.
Related Skills
js-secrets-extraction— Find API keys and endpoints in JavaScript bundles that may lead to GitHub repos.hardcoded-credential-hunt— Detect hardcoded passwords in HTML, JS, and API responses.source-leak-hunt— Find exposed config files (.env, .git) on live web servers.
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