identity-access-risk

To detect IAM privilege escalation, analyze AWS CloudTrail logs for suspicious patterns like enumeration bursts, backdoor role creation, and defense evasion. This approach maps findings to MITRE ATT&CK techniques and assesses blast radius for critical assets.

The best way to identify overprivileged IAM identities is by analyzing IAM policies and access patterns to uncover potential attack paths. This risk assessment provides specific, actionable recommendations for revoking access, correcting policies, and enforcing security best practices.

Yes, you can analyze unusual AssumeRole activity triggered by alerts from unknown IPs. The analysis evaluates the involved roles, assesses the blast radius for critical cloud assets, and recommends immediate session revocation to mitigate risk.

Yes, you need boto3 along with python-json-logger and requests dependencies to automate IAM anomaly detection. These libraries facilitate AWS API interactions, structured logging, and HTTP requests required for analyzing IAM policies and CloudTrail events.

Mapping cloud security findings to MITRE ATT&CK techniques improves remediation by contextualizing IAM anomalies and privilege escalation attempts within known adversary tactics. This mapping helps prioritize responses based on the specific attack behaviors detected in CloudTrail logs.

Limitations when analyzing CloudTrail logs for identity and access risks include reliance on the completeness of CloudTrail logging and IAM policy configurations. Accurate detection of lateral movement and credential stuffing requires comprehensive visibility into all API events and access patterns.