cloud-iam-deep

To analyze exposed cloud credentials for IAM privilege escalation, you validate the leaked identity and enumerate its active AWS, Azure, GCP, or Kubernetes permissions to map external attack chains. This process identifies what actions the credential grants and highlights likely escalation techniques.

Checking permissions for a leaked AWS access key or GCP service account JSON involves making identity verification calls and scoped permission enumeration. This determines the exact IAM permissions the exposed credential can exercise and reveals potential cross-account trust relationships.

SSRF reaching instance metadata services like AWS IMDS leads to cloud IAM abuse by allowing attackers to extract credentials or managed identity tokens. Once extracted, these credentials can be validated to determine their control-plane access and identify plausible privilege escalation patterns.

Yes, you can validate a Kubernetes service account JWT token by analyzing the exposed credential to determine its control-plane access. The process enumerates the token's scoped permissions and maps engagement-safe IAM privilege escalation patterns within the cluster.

Limitations when mapping external cloud attack chains include the need for frontloaded credential identification and strict audit awareness. The analysis focuses on least-destructive, engagement-safe escalation patterns with clear guardrails to avoid unintended side effects during permission enumeration.

To enumerate Azure managed identity permissions after a token leak, you analyze the exposed token context to verify the identity and list its actual IAM permissions. This identifies potential managed identity abuse paths and maps structured escalation techniques.