Halil, I’d treat this as three control planes, not one “cloud incident”: AWS GovCloud/IAM, Microsoft 365/Graph/Entra, and AI-platform/API credentials.
For AWS GovCloud exposed in GitHub, rotate or disable the exposed AWS access keys immediately, rotate any plaintext internal passwords found alongside them, and invalidate any derived app secrets that could have been used from those credentials. Then restrict with an emergency SCP or IAM boundary: deny high-risk APIs unless coming from approved principals/locations, block creation of new access keys, new IAM users, new trust policies, and new external role assumptions until reviewed. Log and review CloudTrail for AssumeRole, CreateAccessKey, UpdateAssumeRolePolicy, PutRolePolicy, CreateUser, GetSecretValue, S3 listing/downloads, and GovCloud cross-account trust changes. This is customer/contractor secret handling, not an AWS control-plane failure — shared responsibility still has teeth.
For Hugging Face, the sources say the breach involved a malicious uploaded dataset abusing code execution in a dataset-processing environment, privilege escalation, node-level access, and harvesting of cloud/cluster credentials; Hugging Face reportedly rotated exposed credentials and urged users to rotate keys stored on the platform. So teams should rotate Hugging Face tokens, model/dataset access tokens, CI/CD secrets, cloud keys stored in Spaces or pipelines, Kubernetes service-account tokens exposed to data workers, and any downstream LLM/API keys reachable from that pipeline. Restrict dataset-processing workers hard: no broad cloud metadata access, no reusable long-lived credentials, tight egress, short-lived workload identity only. Do not overreact by assuming all public models or Spaces were modified; one source says Hugging Face found no evidence public models, user-facing datasets, or Spaces were altered, but customer/partner data exposure remained unclear.
For Microsoft 365 device-code phishing and Graph/calendar abuse, rotate is the wrong first verb — revoke first. Revoke refresh tokens and sessions for affected users, remove malicious OAuth consents/service principals, reset passwords only where credential capture is confirmed, and reissue device credentials if compliant-device trust was abused. Restrict device-code auth for unmanaged users, require phishing-resistant MFA for privileged roles, lock Graph app consent behind admin approval, and narrow Graph scopes like mail, files, calendar, and offline access. Log Entra sign-ins, device-code flow events, consent grants, service-principal additions, Graph calendar/mail/file activity, mailbox audit, and unusual calendar item creation or external sharing. Do not block Microsoft Graph tenant-wide unless you enjoy breaking your own SaaS nervous system.
For unauthorized LLM API proxies, rotate exposed OpenAI/Anthropic/Hugging Face-style API keys, restrict keys by project, budget, IP/VPC egress where supported, and add per-key spend/rate caps. Log prompt/API metadata, source workload, key ID, model used, token volume, destination proxy domain, and failed auth attempts. Avoid the theater move of banning all LLM usage; the practical fix is key inventory, egress control, and least-privilege API keys. “Serverless AI pipeline” still has servers and credentials — you just have fewer excuses for not knowing which principal spent the money.