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What should you do first?
Work in a deliberate order: capture what triggered the response, preserve evidence, then contain access. Deleting resources or disabling an agent before recording relevant logs can make it harder to establish what happened. At the same time, leaving an active credential usable can allow further changes. Coordinate containment with the people responsible for affected workloads.
- Record the alert and context. Note the suspected agent, its service account, role, or other principal, the affected cloud account or project, the approximate time window, and the actions that raised concern. Preserve available agent-runtime, application, and alert records.
- Preserve relevant evidence. Back up logs and evidence from affected resources before cleanup or restoration. Google Cloud recommends backing up affected-resource logs for forensic analysis in its AI threat findings response guidance; AWS likewise advises backing up resources that need to remain available for investigation in its account-compromise guidance.
- Contain the implicated access. Identify the principal and credential types used for the suspicious actions. Revoke, disable, or restrict access using the provider’s current procedure, and consider stopping the implicated runtime or reducing its permissions if doing so will not create unacceptable operational impact.
- Start the investigation before destructive cleanup. Google Cloud Security Command Center’s guidance puts it plainly: “Before you take any action, you should investigate the findings; assess the information that you gather; and decide how to respond.”
How do you contain access without missing a usable credential?
Stopping an agent or suspending a user does not necessarily invalidate every credential the workload can use. Trace the suspicious API activity to its principal and session, then determine whether access came from a long-lived key, a short-lived token, a role session, or another identity mechanism. A credential may remain usable even when its owner or runtime is disabled.
Google Cloud specifically warns responders to account for both persistent service-account key files and short-lived access tokens when responding to compromised credentials. Follow its compromised-credentials guidance for the credential type involved, and check for legitimate workloads that may depend on the same identity before making a change that could interrupt service.
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- Identify the principal, role or service account, and session associated with the activity.
- Determine which credentials that principal could use, including stored key files and temporary credentials.
- Revoke, disable, or restrict the credentials and permissions implicated in the incident using the provider’s documented procedure.
- Where practical, stop or isolate the agent runtime while retaining the logs and resource evidence responders need.
How do you reconstruct what the agent did?
Start with provider audit records for the suspected principal and session, then widen the search across relevant services and Regions. An agent’s cloud actions are usually established through the identity and API events it generated—not solely from a model conversation or agent transcript. Build a timeline that includes successful and failed calls, identity changes, policy changes, and resource creation, modification, or deletion.
Correlate audit timestamps with service-specific records, network-flow logs, and application logs. If available and enabled, model-invocation records can add context about use of a model service. Treat external content the agent processed—such as documents, tickets, or logs—as a possible prompt-injection route to investigate, not as proof that prompt injection caused the event.
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- Search for events tied to the implicated identity, role session, service account, or agent identity.
- Include IAM and policy changes as well as API calls against ordinary cloud resources.
- Search across services and Regions rather than limiting the review to the location of the first alert.
- Compare event times with network and application records to see what preceded and followed each cloud action.
- Check whether relevant logs were enabled and retained for the incident window.
For AWS, the incident-response methodology for generative-AI workloads identifies CloudTrail, CloudWatch, VPC Flow Logs, S3 data events, and—when the application uses it—Amazon Bedrock model-invocation logs as relevant sources. Its CloudTrail investigation guidance recommends searching across Regions and services for events linked to the role session, then correlating CloudTrail times with VPC Flow Logs and application logs. If prompt-and-response logging was not enabled, that source cannot provide the missing prompt and response content.
How do you determine the scope and look for persistence?
Do not stop at the resource named in the alert. Search for additional changes attributable to the same principal, related identities, or the time window under investigation. Establish whether the agent accessed data or resources beyond the initial finding, and inspect whether the logs themselves are complete and trustworthy.
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- Identities and permissions: Look for newly created or altered service accounts, agent identities, roles, policies, grants, access keys, and temporary credentials.
- Agent infrastructure: Check for unfamiliar agent-runtime instances, sessions, or other agent resources.
- Cloud resources and data: Review relevant compute, storage, snapshots, and other resources for unexpected creation, modification, access, or deletion.
- Geographic and service coverage: Expand searches to the services and Regions the principal could reach, not just those already represented in the alert.
- Evidence integrity: Check for gaps, altered records, or disabled logging that could affect confidence in the timeline.
Google Cloud’s guidance for AI-agent service-account findings points investigators to audit records for service-account creation, IAM policy changes, and calls associated with the principal. Its AI threat response guidance also calls out unfamiliar Agent Runtime instances, sessions, service accounts, and agent identities as items to investigate.
Which provider logs and identity records are relevant?
The exact evidence depends on the cloud and identity platform involved. These official sources identify useful starting points; they do not replace checking the resource-specific logs for the services the agent touched.
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| Platform | Evidence to examine | Scope or limitation |
|---|---|---|
| AWS | CloudTrail events, CloudWatch, VPC Flow Logs, S3 data events, and Amazon Bedrock model-invocation logs if the application uses Bedrock. Search for the implicated role session and correlate audit events with network and application records. AWS generative-AI incident methodology; CloudTrail investigation guidance. | Search across relevant Regions and services. Prompt and response content is not recoverable from a logging source that was not enabled. |
| Google Cloud | Cloud Logging and Security Command Center findings; audit records for service-account creation, IAM policy changes, and calls by the principal; unfamiliar agent resources and identities. Credential-response guidance; AI threat response guidance; Service-account finding guidance. | Ensure investigators have the permissions needed to view the relevant audit and Data Access logs. |
| Microsoft Entra agent identities | Risk detection details, sign-in logs, and audit logs. Agent identity creation may appear in audit activity such as “Create user” or “Create service principal.” Microsoft Entra agent identity guidance. | This guidance covers the identity platform. Also examine applicable Azure resource logs when cloud resources were changed. |
AWS account-compromise guidance also recommends checking CloudTrail Event history for unsanctioned creation of access keys, policies, roles, or temporary credentials, and checking resources in all Regions. See Resolve issues with unauthorized activity in AWS accounts.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you remediate and restore services?
Once the evidence and operational impact are understood, remove the unauthorized access path as well as unauthorized changes. Removing a resource alone will not prevent the same identity, credential, or vulnerable agent entry point from making the change again.
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- Remove unauthorized access. Revoke or restrict implicated credentials and remove unauthorized permissions, policies, or identities. Check that the agent’s legitimate task does not require access you are removing.
- Remove or isolate unauthorized resources. Use the evidence and dependency review to decide what to delete, disable, or preserve. Retain copies of relevant logs and resource evidence before destructive actions.
- Fix the source of access. Review the application, agent configuration, and entry points that allowed the actions. Limit permissions to those the agent’s task actually needs.
- Restore from a known-good state. Recover affected data or services from a trusted source, validate that expected behavior has returned, and verify that the unauthorized changes are gone.
- Monitor for renewed use. Continue watching relevant audit and service logs for the implicated principal, related identities, and signs that the same access path is being used again.
How should you report what is known—and what is not?
Separate confirmed events from hypotheses. Record the evidence supporting each confirmed action, the identities and resources in scope, the containment and recovery steps taken, and any operational effects. State which logs were unavailable, not enabled, or outside retention, and explain how those gaps limit what can be established.
Missing telemetry is not evidence that an action did not happen. For example, when prompt-and-response logging was not enabled, investigators cannot recover that content from the absent log source; they can still document what the available cloud audit, service, network, and application records do establish.
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