Implementing Secret Scanning With Gitleaks
This skill covers implementing Gitleaks for detecting and preventing hardcoded secrets in git repositories. It addresses configuring pre-commit hooks, CI/CD pipeline integration, custom rule authoring for organization-specific secrets, baseline management for existing repositories, and remediation workflows for exposed credentials.
MCP get_skill({ skillId: "implementing-secret-scanning-with-gitleaks-c71d92cd" })Use this skill with your agent
Create a free account and connect via MCP
# Implementing Secret Scanning with Gitleaks
## When to Use
- When developers may accidentally commit API keys, passwords, tokens, or private keys to repositories
- When establishing pre-commit gates that prevent secrets from entering the git history
- When scanning existing repository history for previously committed secrets that need rotation
- When compliance requirements mandate secret detection across all source code repositories
- When migrating from manual secret audits to automated continuous scanning
**Do not use** for detecting secrets in running applications or memory (use runtime secret detection), for managing secrets after detection (use Vault or AWS Secrets Manager), or for scanning container images (use Trivy or Grype).
## Prerequisites
- Gitleaks v8.18+ installed via binary, Go install, or Docker
- Pre-commit framework installed for local hook integration
- Git repository with history to scan
- CI/CD platform access (GitHub Actions, GitLab CI, or equivalent)
## Workflow
### Step 1: Install and Run Initial Repository Scan
Perform a baseline scan of the repository to identify all existing secrets in the git history.
```bash
# Install Gitleaks
brew install gitleaks # macOS
# or download binary from https://github.com/gitleaks/gitleaks/releases
# Scan entire git history for secrets
gitleaks detect --source . --report-format json --report-path gitleaks-report.json -v
# Scan only staged changes (for pre-commit)
gitleaks protect --staged --report-format json --report-path gitleaks-staged.json
# Scan specific commit range
gitleaks detect --source . --log-opts="HEAD~10..HEAD" --report-format json
# Scan without git history (filesystem only)
gitleaks detect --source . --no-git --report-format json
```
### Step 2: Configure Pre-Commit Hook
Set up Gitleaks as a pre-commit hook to prevent secrets from being committed.
```yaml
# .pre-commit-config.yaml
repos:
- repo: https://github.com/gitleaks/gitleaks
rev: v8.21.2
hooks:
- id: gitleaks
name: gitleaks
description: Detect hardcoded secrets using Gitleaks
entry: gitleaks protect --staged --verbose --redact
language: golang
pass_filenames: false
```
```bash
# Install pre-commit framework
pip install pre-commit
# Install hooks defined in .pre-commit-config.yaml
pre-commit install
# Run against all files (not just staged)
pre-commit run gitleaks --all-files
# Test the hook with a deliberate secret
echo 'AWS_SECRET_ACCESS_KEY="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"' >> test.txt
git add test.txt
git commit -m "test" # Should be blocked by gitleaks
```
### Step 3: Integrate into GitHub Actions
```yaml
# .github/workflows/secret-scanning.yml
name: Secret Scanning
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
gitleaks:
name: Gitleaks Secret Scan
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0 # Full history for comprehensive scanning
- name: Run Gitleaks
uses: gitleaks/gitleaks-action@v2
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITLEAKS_LICENSE: ${{ secrets.GITLEAKS_LICENSE }} # Required for gitleaks-action v2
# Alternative: Run Gitleaks directly
- name: Install Gitleaks
run: |
wget -q https://github.com/gitleaks/gitleaks/releases/download/v8.21.2/gitleaks_8.21.2_linux_x64.tar.gz
tar -xzf gitleaks_8.21.2_linux_x64.tar.gz
chmod +x gitleaks
- name: Scan for secrets
run: |
if [ "${{ github.event_name }}" == "pull_request" ]; then
./gitleaks detect \
--source . \
--log-opts="${{ github.event.pull_request.base.sha }}..${{ github.event.pull_request.head.sha }}" \
--report-format sarif \
--report-path gitleaks.sarif \
--exit-code 1
else
./gitleaks detect \
--source . \
--report-format sarif \
--report-path gitleaks.sarif \
--exit-code 1 \
--baseline-path .gitleaks-baseline.json
fi
- name: Upload SARIF
if: always()
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: gitleaks.sarif
category: gitleaks
```
### Step 4: Author Custom Detection Rules
Create organization-specific rules for internal secret patterns.
```toml
# .gitleaks.toml
title = "Organization Gitleaks Configuration"
[extend]
useDefault = true # Include all default rules
# Custom rule for internal API tokens
[[rules]]
id = "internal-api-token"
description = "Internal API token for service-to-service auth"
regex = '''(?i)x-internal-token["\s:=]+["\']?([a-zA-Z0-9_\-]{40,})["\']?'''
entropy = 3.5
keywords = ["x-internal-token"]
tags = ["internal", "api"]
[[rules]]
id = "database-connection-string"
description = "Database connection string with embedded credentials"
regex = '''(?i)(postgres|mysql|mongodb|redis)://[^:]+:[^@]+@[^/]+/\w+'''
keywords = ["postgres://", "mysql://", "mongodb://", "redis://"]
tags = ["database", "credentials"]
[[rules]]
id = "jwt-secret"
description = "JWT signing secret"
regex = '''(?i)(jwt[_-]?secret|jwt[_-]?key)["\s:=]+["\']?([a-zA-Z0-9/+_\-]{32,})["\']?'''
entropy = 3.0
keywords = ["jwt_secret", "jwt-secret", "jwt_key", "jwt-key"]
# Allowlist for test files and known safe patterns
[allowlist]
description = "Global allowlist"
paths = [
'''(^|/)test(s)?/''',
'''(^|/)spec/''',
'''\.test\.(js|ts|py)$''',
'''\.spec\.(js|ts|py)$''',
'''__mocks__/''',
'''fixtures/''',
'''(^|/)vendor/''',
'''node_modules/'''
]
regexes = [
'''EXAMPLE''',
'''example\.com''',
'''test[-_]?(key|secret|token|password)''',
'''(?i)placeholder''',
'''000000+'''
]
```
### Step 5: Manage Baselines for Existing Repositories
Create a baseline of known findings to avoid blocking development while historical secrets are being rotated.
```bash
# Generate baseline from current state
gitleaks detect --source . --report-format json --report-path .gitleaks-baseline.json
# Subsequent scans compare against baseline (only new findings trigger failures)
gitleaks detect --source . --baseline-path .gitleaks-baseline.json --exit-code 1
# Review baseline periodically and remove entries as secrets are rotated
cat .gitleaks-baseline.json | python3 -m json.tool | head -50
```
### Step 6: Remediate Exposed Secrets
When a secret is detected, follow the rotation and history cleanup procedure.
```bash
# 1. Immediately rotate the exposed credential
# - Revoke the old API key/token in the service provider
# - Generate a new credential
# - Store the new credential in a secrets manager
# 2. Remove secret from git history using git-filter-repo
pip install git-filter-repo
# Create expressions file for secrets to remove
cat > /tmp/expressions.txt << 'EOF'
regex:AKIA[0-9A-Z]{16}==>REDACTED_AWS_KEY
regex:(?i)password\s*=\s*"[^"]*"==>password="REDACTED"
EOF
git filter-repo --replace-text /tmp/expressions.txt --force
# 3. Force-push the cleaned history (coordinate with team)
# git push --force --all # WARNING: Requires team coordination
# 4. Add the secret pattern to .gitleaks.toml rules
# 5. Update the baseline file to remove the resolved finding
```
## Key Concepts
| Term | Definition |
|------|------------|
| Secret | Any credential, token, key, or sensitive string that should not appear in source code |
| Pre-commit Hook | Git hook that runs before a commit is created, blocking commits containing detected secrets |
| Entropy | Measure of randomness in a string; high-entropy strings are more likely to be secrets |
| Baseline | Snapshot of existing findings used to differentiate new secrets from pre-existing ones |
| Allowlist | Configuration specifying paths, patterns, or commits to exclude from detection |
| SARIF | Static Analysis Results Interchange Format for uploading findings to security dashboards |
| git-filter-repo | Tool for rewriting git history to remove sensitive data from all commits |
## Tools & Systems
- **Gitleaks**: Open-source secret detection tool supporting pre-commit hooks, CI/CD, and historical scanning
- **pre-commit**: Framework for managing and maintaining multi-language pre-commit hooks
- **git-filter-repo**: History rewriting tool for removing secrets from git history
- **TruffleHog**: Alternative secret scanner with verified secret detection capabilities
- **GitHub Secret Scanning**: Native GitHub feature that detects secrets matching partner patterns
## Common Scenarios
### Scenario: Onboarding Secret Scanning on a Legacy Repository
**Context**: A 5-year-old repository has never been scanned. The team needs to enable secret scanning without blocking all development while historical secrets are rotated.
**Approach**:
1. Run `gitleaks detect` against full history and generate a baseline JSON file
2. Triage each finding: classify as active (needs rotation), inactive (already rotated), or false positive
3. Immediately rotate all active secrets and update consuming services
4. Commit the baseline file (excluding active secrets that have been fixed)
5. Enable pre-commit hooks for new development immediately
6. Add CI/CD scanning with the baseline to catch only new secrets
7. Progressively reduce the baseline as historical secrets are rotated
**Pitfalls**: Generating a baseline without triaging means accepting risk on unrotated secrets. Never assume a historical secret is inactive without verifying with the service provider. Running git-filter-repo on a shared repository without coordination will cause rebase conflicts for all team members.
## Output Format
```
Gitleaks Secret Scanning Report
=================================
Repository: org/web-application
Scan Type: Full History
Commits Scanned: 4,523
Date: 2026-02-23
FINDINGS:
Total: 12
New (not in baseline): 3
Baseline (pre-existing): 9
NEW FINDINGS (blocking):
[1] AWS Access Key ID
Rule: aws-access-key-id
File: src/config/aws.py:23
Commit: a1b2c3d (2026-02-22, dev@company.com)
Secret: AKIA...REDACTED
Entropy: 3.8
[2] GitHub Personal Access Token
Rule: github-pat
File: scripts/deploy.sh:15
Commit: d4e5f6g (2026-02-21, ops@company.com)
Secret: ghp_...REDACTED
Entropy: 4.2
[3] Internal API Token
Rule: internal-api-token
File: src/services/auth.py:89
Commit: h7i8j9k (2026-02-20, dev@company.com)
QUALITY GATE: FAILED (3 new findings)
Action: Rotate exposed credentials immediately.
```Related Skills
More skills in Security & Compliance
1password
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
1password
Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.
Accessibility Lead
Accessibility team lead and orchestrator. Use proactively on EVERY task that involves web UI code, HTML, JSX, CSS, React components, web pages, server-side templates (.leaf, .ejs, .erb, .hbs), or any user-facing web content. This agent coordinates the accessibility specialist team and ensures no accessibility requirement is missed. Runs the final review before any UI code is considered complete. Applies to any web framework, server-side templating framework (Vapor/Leaf, Rails/ERB, Django/Jinja, Express/EJS), or vanilla HTML/CSS/JS. Works alongside other team leads (e.g., swift-lead) in multi-language projects.
Accessibility Regression Detector
Detects accessibility regressions by comparing audit results across commits/branches. Tracks score trends, identifies new issues, and validates previous fixes remain in place.
Accessibility Statement
Generates conformance/accessibility statements following W3C or EU model templates. Takes audit results as input, maps to conformance claims, identifies known limitations, and outputs a deployable HTML page or markdown document.
Accessibility Tool Builder
Expert in building accessibility scanning tools, rule engines, document parsers, report generators, and audit automation. WCAG criterion mapping, severity scoring, CLI/GUI scanner architecture, CI/CD integration.
Explore Other Categories
Skills from other categories with shared topics
Analyzing Malicious PDF With Peepdf
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
Analyzing PDF Malware With Pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
Building Devsecops Pipeline With GitLab CI
Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.