Full Report
We explore how AWS neutralizes exposed IAM credentials using managed policies, detailing GitHub secret scanning and CloudTrail monitoring strategies. The post From Exposure to Lockdown: How AWS Neutralizes Compromised IAM Credentials through Managed Policies appeared first on Unit 42.
Analysis Summary
# Best Practices: Neutralizing Exposed IAM Credentials
## Overview
These practices address the critical risk of AWS Identity and Access Management (IAM) credential leakage. Specifically, they leverage AWS’s automated response mechanisms (such as the `AWSRevokeOlderSessions` policy) and integration with secret scanning services like GitHub to minimize the window of opportunity for attackers once credentials have been accidentally committed to public repositories.
## Key Recommendations
### Immediate Actions
1. **Enable GitHub Secret Scanning:** Configure your organization’s GitHub repositories to automatically scan for secrets. Ensure "Push Protection" is enabled to prevent credentials from ever reaching the public domain.
2. **Monitor CloudTrail for Quarantine Events:** Set up alerts for the `AttachUserPolicy` or `AttachRolePolicy` events where the policy ARN is `arn:aws:iam::aws:policy/AWSRevokeOlderSessions`. This indicates AWS has detected a leak and taken action.
3. **Audit IAM User Permissions:** Immediately rotate any credentials that have been flagged by AWS or identified as exposed in public repositories.
### Short-term Improvements (1-3 months)
1. **Automate Remediation Workflows:** Develop AWS Lambda functions triggered by EventBridge to automatically deactivate or delete access keys when a "Compromised Key" notification is received via the AWS Health Dashboard.
2. **Implement Least Privilege:** Review existing IAM policies to ensure that even if a key is leaked, the potential blast radius is minimized by removing administrative or broad permissions.
3. **Enforce MFA:** Require Multi-Factor Authentication for all console access and sensitive API operations, which serves as a second layer of defense if static credentials are stolen.
### Long-term Strategy (3+ months)
1. **Transition to IAM Roles:** Systematically phase out long-lived IAM User Access Keys in favor of temporary credentials provided by IAM Roles (via AWS STS), using OIDC for CI/CD pipelines (e.g., GitHub Actions to AWS).
2. **Centralized Secret Management:** Adopt AWS Secrets Manager or HashiCorp Vault to programmatically handle secrets, reducing the need for developers to handle raw credentials.
## Implementation Guidance
### For Small Organizations
- Focus on enabling the free **GitHub Secret Scanning** for public repos.
- Rely on AWS’s default managed policies to neutralize leaks.
- Manually rotate keys immediately upon receiving an AWS Health alert.
### For Medium Organizations
- Implement **AWS Config Rules** to detect and flag IAM users with access keys older than 90 days.
- Use **Amazon GuardDuty** to detect anomalous behavior (e.g., API calls from unauthorized IPs) that might indicate a leaked key is being used.
### For Large Enterprises
- Deploy **Service Control Policies (SCPs)** to restrict the ability to create long-lived access keys in specific OUs.
- Integrate secret scanning alerts into a centralized **Security Operations Center (SOC)** via SIEM (e.g., Splunk or Cortex XSOAR) for automated incident response.
## Configuration Examples
### Identifying AWS Quarantine Policy via CLI
To check if a specific user has been quarantined by AWS after a leak:
bash
aws iam list-attached-user-policies --user-name <USERNAME> | grep "AWSRevokeOlderSessions"
### EventBridge Pattern for Leaked Credentials
Use this pattern to trigger a response when AWS Health detects a compromised key:
json
{
"source": ["aws.health"],
"detail-type": ["AWS Health Event"],
"detail": {
"service": ["RISK"],
"eventTypeCode": ["AWS_RISK_CREDENTIALS_EXPOSED"]
}
}
## Compliance Alignment
- **NIST SP 800-53:** IA-5 (Authenticator Management) and AC-2 (Account Management).
- **ISO/IEC 27001:** Annex A.9.2 (User Access Management).
- **CIS AWS Foundations Benchmark:** Section 1.x (Identity and Access Management).
## Common Pitfalls to Avoid
- **Ignoring the "Revoke Sessions" Policy:** Assuming that because AWS attached a restrictive policy, the key is "safe." The key is still compromised and must be deleted.
- **Hardcoding Credentials in Scripts:** Using `access_key_id` and `secret_access_key` inside `.sh` or `.py` files instead of using Environment Variables or IAM Roles.
- **Incomplete Clean-up:** Deleting the leaked key but failing to check for backdoors (e.g., new IAM users or modified trust relationships) created by the attacker during the exposure window.
## Resources
- **AWS Health Dashboard:** `https://health.aws.amazon[.]com/`
- **GitHub Secret Scanning Documentation:** `https://docs.github[.]com/en/code-security/secret-scanning/about-secret-scanning`
- **AWS Managed Policy Reference:** `arn:aws:iam::aws:policy/AWSRevokeOlderSessions`
- **Unit 42 Cloud Threat Report:** `https://unit42.paloaltonetworks[.]com/`