mukul975/anthropic-cybersecurity-skills

implementing-secrets-scanning-in-ci-cd

Integrate gitleaks and trufflehog into CI/CD pipelines to detect leaked secrets before deployment

First seen Mar 18, 2026

Installation

$ npx skills add mukul975/anthropic-cybersecurity-skills --skill implementing-secrets-scanning-in-ci-cd

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More details

Agent compatibility

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Repository health

Stars 32.4K
License LICENSE
Default branch main
Open issues 20
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0
LicenseApache-2.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,822 B
  • docs SUMMARY.md 143 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 169 installs

SKILL.md

Implementing Secrets Scanning in CI/CD

Overview

This skill covers implementing automated secrets scanning in CI/CD pipelines using gitleaks and trufflehog. It enables security teams to detect API keys, tokens, passwords, and other credentials that have been accidentally committed to source code repositories, providing a CI gate that blocks deployments containing high-severity findings.

Gitleaks scans git repositories and directories for hardcoded secrets using regex patterns and entropy analysis. TruffleHog performs filesystem and git history scans with optional secret verification against live services. Together they provide comprehensive coverage for secrets detection.

When to Use

  • When deploying or configuring implementing secrets scanning in ci cd capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Python 3.9 or later
  • gitleaks v8.x installed and available on PATH
  • trufflehog v3.x installed and available on PATH
  • A git repository or directory to scan
  • Access to CI/CD platform (GitHub Actions, GitLab CI, Jenkins)

Steps

  1. Install scanning tools: Install gitleaks via package manager or binary download. Install trufflehog via brew install trufflehog or download from GitHub releases.
  1. Configure gitleaks: Create a .gitleaks.toml configuration file in the repository root to define custom rules, allowlists, and path exclusions. Use --config flag to point to custom configs.
  1. Run gitleaks directory scan: Execute gitleaks dir --source . --report-format json --report-path gitleaks-report.json to scan the working directory and generate a JSON report.
  1. Run trufflehog filesystem scan: Execute trufflehog filesystem /path/to/repo --json > trufflehog-report.json to scan files and output JSON findings to a report file.
  1. Parse and filter findings: Use the agent script to parse both JSON reports, filter findings by severity (critical, high, medium, low), and determine whether the CI pipeline should pass or fail.
  1. Integrate into CI pipeline: Add the scanning step to your GitHub Actions workflow, GitLab CI config, or Jenkins pipeline as a pre-deployment gate. Use --exit-code flag in gitleaks to control pipeline behavior.
  1. Configure pre-commit hooks: Set up gitleaks as a pre-commit hook using gitleaks protect --staged to catch secrets before they are committed.
  1. Review and triage findings: Examine the JSON output for false positives, add legitimate entries to .gitleaksignore, and rotate any confirmed leaked credentials immediately.

Expected Output

The agent script produces a JSON report containing:

  • Total findings count from each scanner
  • Findings grouped by severity level
  • Individual finding details including file path, line number, rule ID, and redacted secret
  • A CI gate verdict (pass/fail) based on the configured severity threshold
  • Execution metadata including scan duration and tool versions
{
  "scan_summary": {
    "tool": "both",
    "total_findings": 3,
    "critical": 1,
    "high": 1,
    "medium": 1,
    "low": 0,
    "ci_gate": "FAIL",
    "fail_reason": "Found 1 critical and 1 high severity findings"
  },
  "findings": [...]
}