detecting-aws-credential-exposure-with-trufflehog

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-aws-credential-exposure-with-trufflehog
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summary

Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.

skill.md
name
detecting-aws-credential-exposure-with-trufflehog
description
'Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access. '
domain
cybersecurity
subdomain
cloud-security
tags
- cloud-security - aws - credential-exposure - trufflehog - secrets-detection - devsecops
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01

Detecting AWS Credential Exposure with TruffleHog

When to Use

  • When integrating secrets detection into CI/CD pipelines to prevent credential commits reaching production
  • When performing a security audit of existing repositories for historically committed AWS credentials
  • When responding to an AWS GuardDuty alert about credential usage from an unexpected IP or region
  • When onboarding repositories from acquired companies or third-party vendors
  • When validating that credential rotation processes have removed all references to old access keys

Do not use for real-time credential monitoring (use AWS GuardDuty or Amazon Macie), for managing secrets (use AWS Secrets Manager or HashiCorp Vault), or for detecting non-credential sensitive data like PII (use Amazon Macie or DLP tools).

Prerequisites

  • TruffleHog v3 installed (brew install trufflehog or pip install trufflehog)
  • git-secrets installed for pre-commit hook integration (brew install git-secrets)
  • Access to source code repositories (GitHub, GitLab, Bitbucket, or local git repos)
  • AWS CLI configured with permissions to check key status (iam:ListAccessKeys, iam:GetAccessKeyLastUsed)
  • GitHub or GitLab API token for scanning organization-wide repositories

Workflow

Step 1: Install and Configure TruffleHog

Install TruffleHog v3 and verify it can detect the AWS credential patterns.

# Install TruffleHog v3
pip install trufflehog

# Or install from binary release
curl -sSfL https://raw.githubusercontent.com/trufflesecurity/trufflehog/main/scripts/install.sh | sh -s -- -b /usr/local/bin

# Verify installation
trufflehog --version

# Test with a known test repository
trufflehog git https://github.com/trufflesecurity/test_keys --only-verified

Step 2: Scan Git Repositories for Exposed Credentials

Scan entire git history including all branches and commits for AWS access keys, secret keys, and session tokens.

# Scan a local git repository (full history)
trufflehog git file:///path/to/repo --only-verified --json > trufflehog-results.json

# Scan a GitHub organization's repositories
trufflehog github --org=your-organization --token=$GITHUB_TOKEN --only-verified

# Scan a specific GitHub repository with all branches
trufflehog git https://github.com/org/repo.git --only-verified --branch=main

# Scan a GitLab group
trufflehog gitlab --group=your-group --token=$GITLAB_TOKEN --only-verified

# Scan filesystem paths for credentials in config files
trufflehog filesystem /path/to/project --only-verified

Step 3: Analyze and Validate Detected Credentials

Parse TruffleHog results to identify verified (still-active) credentials versus rotated or test keys.

# Parse TruffleHog JSON output for AWS findings
cat trufflehog-results.json | python3 -c "
import json, sys
for line in sys.stdin:
    finding = json.loads(line)
    if 'AWS' in finding.get('DetectorName', ''):
        print(f\"Detector: {finding['DetectorName']}\")
        print(f\"Verified: {finding.get('Verified', False)}\")
        print(f\"Source: {finding.get('SourceMetadata', {})}\")
        print(f\"Commit: {finding.get('SourceMetadata', {}).get('Data', {}).get('Git', {}).get('commit', 'N/A')}\")
        print(f\"File: {finding.get('SourceMetadata', {}).get('Data', {}).get('Git', {}).get('file', 'N/A')}\")
        print('---')
"

# Check if a detected access key is still active
aws iam get-access-key-last-used --access-key-id AKIAIOSFODNN7EXAMPLE

# List all access keys for a user to find active keys
aws iam list-access-keys --user-name target-user \
  --query 'AccessKeyMetadata[*].[AccessKeyId,Status,CreateDate]' --output table

Step 4: Set Up Pre-Commit Hooks with git-secrets

Prevent credentials from being committed in the first place using git-secrets as a pre-commit hook.

# Install git-secrets
git secrets --install  # In each repository

# Register AWS credential patterns
git secrets --register-aws

# Add custom patterns for internal credential formats
git secrets --add 'AKIA[0-9A-Z]{16}'
git secrets --add 'aws_secret_access_key\s*=\s*.{40}'
git secrets --add 'aws_session_token\s*=\s*.+'

# Scan entire repository history
git secrets --scan-history

# Add to global git template for all new repos
git secrets --install ~/.git-templates/git-secrets
git config --global init.templateDir ~/.git-templates/git-secrets

Step 5: Integrate TruffleHog into CI/CD Pipeline

Add TruffleHog scanning as a CI/CD gate to block deployments containing exposed credentials.

# GitHub Actions workflow (.github/workflows/secrets-scan.yml)
name: Secrets Scan
on: [push, pull_request]

jobs:
  trufflehog:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
      - name: TruffleHog Scan
        uses: trufflesecurity/trufflehog@main
        with:
          extra_args: --only-verified --results=verified
# GitLab CI (.gitlab-ci.yml)
secrets_scan:
  stage: test
  image: trufflesecurity/trufflehog:latest
  script:
    - trufflehog git file://$CI_PROJECT_DIR --since-commit $CI_COMMIT_BEFORE_SHA --only-verified --fail
  allow_failure: false

Step 6: Respond to Detected Credential Exposure

Execute incident response procedures when verified credentials are found exposed.

# IMMEDIATE: Deactivate the exposed access key
aws iam update-access-key \
  --user-name compromised-user \
  --access-key-id AKIAEXPOSEDKEY123456 \
  --status Inactive

# Generate new credentials
aws iam create-access-key --user-name compromised-user

# Review CloudTrail for unauthorized usage of the exposed key
aws cloudtrail lookup-events \
  --lookup-attributes AttributeKey=AccessKeyId,AttributeValue=AKIAEXPOSEDKEY123456 \
  --start-time 2026-01-01T00:00:00Z \
  --query 'Events[*].[EventTime,EventName,EventSource,SourceIPAddress]' \
  --output table

# Delete the exposed key after rotation is confirmed
aws iam delete-access-key \
  --user-name compromised-user \
  --access-key-id AKIAEXPOSEDKEY123456

# Remove the credential from git history using BFG Repo Cleaner
java -jar bfg.jar --replace-text credentials.txt repo.git

Key Concepts

TermDefinition
TruffleHogOpen-source secrets detection tool that scans git history, filesystems, and cloud services for exposed credentials using regex patterns and verification APIs
Verified SecretA credential that TruffleHog has confirmed is still active by making an API call to the target service (e.g., AWS STS GetCallerIdentity)
git-secretsAWS Labs pre-commit hook tool that prevents committing strings matching AWS credential patterns to git repositories
Access Key RotationThe practice of regularly replacing AWS access key pairs to limit the window of exposure if a key is compromised
BFG Repo CleanerTool for removing sensitive data from git history without rewriting the entire repository, faster than git filter-branch
GitHub Secret ScanningGitHub-native feature that scans public repositories for known credential patterns and notifies the credential provider

Tools & Systems

  • TruffleHog v3: Primary scanning engine supporting git, filesystem, S3, and CI/CD integration with verified credential detection
  • git-secrets: AWS Labs pre-commit hook for preventing credential commits at the developer workstation level
  • BFG Repo Cleaner: Fast tool for removing credentials from git history after exposure is detected
  • AWS GuardDuty: Threat detection service that alerts on anomalous usage of AWS credentials from unexpected locations
  • GitHub Advanced Security: Platform-native secret scanning for GitHub repositories with push protection

Common Scenarios

Scenario: Developer Commits AWS Credentials to a Public GitHub Repository

Context: GitHub secret scanning notifies that an AWS access key was pushed to a public repository. The key belongs to a developer with production S3 and DynamoDB access.

Approach:

  1. Immediately deactivate the access key using aws iam update-access-key --status Inactive
  2. Run aws cloudtrail lookup-events filtering by the exposed AccessKeyId to check for unauthorized usage
  3. Scan the full repository history with trufflehog git to find any other exposed credentials
  4. Generate a new access key for the developer and deliver it through Secrets Manager
  5. Remove the credential from git history using BFG Repo Cleaner
  6. Install git-secrets pre-commit hook on the developer's workstation
  7. Add TruffleHog to the repository's CI/CD pipeline to prevent recurrence

Pitfalls: Simply deleting the commit or force-pushing does not remove credentials from GitHub's cache or forks. The key must be deactivated at the AWS level immediately. GitHub secret scanning may have already notified AWS, triggering automated key deactivation.

Output Format

AWS Credential Exposure Scan Report
======================================
Scan Target: github.com/acme-corp (42 repositories)
Scan Date: 2026-02-23
Tool: TruffleHog v3.63.0
Mode: Full git history scan with verification

VERIFIED FINDINGS (Active Credentials):
[CRED-001] AWS Access Key - VERIFIED ACTIVE
  Key ID: AKIA...WXYZ
  Repository: acme-corp/backend-api
  File: deploy/config.env
  Commit: a1b2c3d (2025-08-15)
  Author: [email protected]
  IAM User: svc-backend-deploy
  Permissions: S3, DynamoDB, SQS (production)
  Status: CRITICAL - Key active and used from 3 IP addresses
  Action Required: Immediate deactivation and rotation

[CRED-002] AWS Secret Key - VERIFIED ACTIVE
  Repository: acme-corp/data-pipeline
  File: scripts/etl_config.py
  Commit: d4e5f6g (2025-11-22)
  Author: [email protected]
  Status: HIGH - Key active, last used 2 days ago

UNVERIFIED FINDINGS (Potential Credentials):
  Total pattern matches: 15
  Likely test/example keys: 12
  Requires manual review: 3

SUMMARY:
  Repositories scanned: 42
  Commits analyzed: 125,847
  Verified active credentials: 2
  Unverified credential patterns: 15
  Repositories with pre-commit hooks: 8 / 42
how to use detecting-aws-credential-exposure-with-trufflehog

How to use detecting-aws-credential-exposure-with-trufflehog on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add detecting-aws-credential-exposure-with-trufflehog
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-aws-credential-exposure-with-trufflehog

The skills CLI fetches detecting-aws-credential-exposure-with-trufflehog from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
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│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/detecting-aws-credential-exposure-with-trufflehog

Reload or restart Cursor to activate detecting-aws-credential-exposure-with-trufflehog. Access the skill through slash commands (e.g., /detecting-aws-credential-exposure-with-trufflehog) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.871 reviews
  • Chen Khan· Dec 20, 2024

    detecting-aws-credential-exposure-with-trufflehog fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Amelia Taylor· Dec 20, 2024

    I recommend detecting-aws-credential-exposure-with-trufflehog for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chaitanya Patil· Dec 16, 2024

    detecting-aws-credential-exposure-with-trufflehog fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Benjamin Khanna· Dec 16, 2024

    detecting-aws-credential-exposure-with-trufflehog reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Daniel Li· Dec 8, 2024

    Keeps context tight: detecting-aws-credential-exposure-with-trufflehog is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chen Johnson· Nov 27, 2024

    We added detecting-aws-credential-exposure-with-trufflehog from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Daniel Mehta· Nov 11, 2024

    detecting-aws-credential-exposure-with-trufflehog is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Benjamin Jain· Nov 11, 2024

    detecting-aws-credential-exposure-with-trufflehog reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Nov 7, 2024

    detecting-aws-credential-exposure-with-trufflehog is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Isabella Desai· Nov 7, 2024

    I recommend detecting-aws-credential-exposure-with-trufflehog for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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