detecting-aws-credential-exposure-with-trufflehog▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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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.
| 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 trufflehogorpip 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
| Term | Definition |
|---|---|
| TruffleHog | Open-source secrets detection tool that scans git history, filesystems, and cloud services for exposed credentials using regex patterns and verification APIs |
| Verified Secret | A credential that TruffleHog has confirmed is still active by making an API call to the target service (e.g., AWS STS GetCallerIdentity) |
| git-secrets | AWS Labs pre-commit hook tool that prevents committing strings matching AWS credential patterns to git repositories |
| Access Key Rotation | The practice of regularly replacing AWS access key pairs to limit the window of exposure if a key is compromised |
| BFG Repo Cleaner | Tool for removing sensitive data from git history without rewriting the entire repository, faster than git filter-branch |
| GitHub Secret Scanning | GitHub-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:
- Immediately deactivate the access key using
aws iam update-access-key --status Inactive - Run
aws cloudtrail lookup-eventsfiltering by the exposed AccessKeyId to check for unauthorized usage - Scan the full repository history with
trufflehog gitto find any other exposed credentials - Generate a new access key for the developer and deliver it through Secrets Manager
- Remove the credential from git history using BFG Repo Cleaner
- Install git-secrets pre-commit hook on the developer's workstation
- 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 on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches detecting-aws-credential-exposure-with-trufflehog from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★71 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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