The Tool Desk
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1. Activate your incident response process
Use your established severity, escalation, legal, privacy, and communications procedures. Assign an incident lead and involve the teams responsible for the agent, identity and access management, connected services, logging, and affected business operations.
Record whether the event is a confirmed security incident, an unsafe action without evidence of malicious control, a suspected control failure, or an unresolved alert. Keep uncertainty explicit as the investigation develops. NIST’s SP 800-61 Rev. 3, published in April 2025, places incident response within broader cybersecurity risk management under CSF 2.0; OWASP’s GenAI Incident Response Guide 1.0, published July 28, 2025, is intended for security practitioners handling incidents involving generative AI applications.
2. Establish the agent’s effective authority
Identify the affected deployment and what it was actually able to do—not only what its intended task suggests. Record available details, noting where information is unknown:
- Agent name, version, environment, triggering task, and model or provider, if known.
- Prompt, policy, configuration, and deployment revisions in effect at the time.
- Enabled tools and extensions, connected services, data sources, and reachable agents or workflows.
- Identity context, delegated credentials, service accounts, and credential scopes.
- Approval controls and the actions permitted with or without approval.
Map read, write, delete, send, execute, administrative, and financial capabilities separately. Check the actual permissions enforced by connected services: an agent meant to read documents might also be able to delete them, or might operate under an over-privileged service identity. OWASP’s LLM06:2025 Excessive Agency and AI Agent Security Cheat Sheet describe excessive functionality, permissions, and autonomy as relevant risks.
3. Preserve evidence and reconstruct the timeline
Follow your organization’s evidence-handling procedures to preserve available records and system state. Build a chronology with timestamps, record sources, integrity information, and known gaps. Depending on what the deployment retains, examine:
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- User requests and external material the agent read, such as retrieved documents, email, websites, API responses, and tool results.
- Agent outputs; tool names and parameters; authorization decisions, denials, retries, loops, and approval events.
- Identity-provider, application, cloud, database, email, repository, and network records showing access or changes made with the agent’s identity or delegated credentials.
- Memory or retrieval-store writes, shared-state changes, configuration revisions, and deployment changes.
- Messages between agents and actions that followed in connected workflows.
These are investigative leads, not a claim that every platform records them. Corroborate the agent’s account against identity, tool, and downstream-system records; generated reasoning and model-provided explanations are not independently verified evidence. OWASP identifies data exfiltration, memory poisoning, and cascading failures as possible risk areas. NIST’s January 2025 agent-hijacking evaluation described scenarios involving code execution, data exfiltration, and phishing.
4. Test competing incident hypotheses
For each plausible cause, identify evidence that would support or weaken it. Do not assume that an unexpected action proves an attacker took control: OWASP notes that excessive agency can also result from hallucination or poor model performance.
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- Prompt injection: Could untrusted content have influenced the agent to override trusted instructions? NIST defines prompt injection as an attack that exploits the concatenation of untrusted input with a prompt constructed by a higher-trust party, such as an application designer.
- Tool or permission abuse: Was a tool compromised, misused, or granted more authority than the task required? Did the agent gain or exercise elevated privileges?
- Data exposure: Did the agent access or transmit information beyond the authorized task, and through which identity, tool, or destination?
- Memory or retrieval poisoning: Was stored or retrieved content changed in a way that could influence later actions?
- Execution or approval failure: Did unsafe generated code or shell execution run, or did a sensitive action bypass an approval control?
- Operational or configuration failure: Did runaway retries, chain depth, or spend cause harm? Were configuration changes malicious, accidental, or unauthorized?
- Cascading activity: Did the initial action trigger other agents, identities, or downstream workflows?
Distinguish malicious control from model error, ambiguous instructions, configuration mistakes, and ordinary software compromise. OWASP lists prompt injection, tool abuse, privilege escalation, data exfiltration, memory poisoning, excessive autonomy, cascading failures, and supply-chain attacks among relevant agent risks.
5. Contain the capability that could cause further harm
Select controls based on what is ongoing or could recur. An instruction telling the model to stop is not an access control. Prefer enforceable restrictions on the agent’s identity, tools, and downstream actions.
- Pause or disable the affected agent or workflow when feasible.
- Disable the abused tool or integration, or reduce its access to the narrowest necessary resources and operations.
- Revoke or rotate implicated credentials and delegated access; check whether those credentials remain usable elsewhere.
- Block destinations or downstream actions involved in suspected exfiltration.
- Suspend memory writes or isolate affected stores while they are reviewed.
- Require independent human approval for sensitive actions before restoring them.
Include connected agents and affected user identities in the containment scope. OWASP recommends least privilege, downstream authorization, monitoring, and human approval for high-impact actions. CISA and partner agencies’ May 1, 2026 guidance on adopting agentic AI services emphasizes restricted autonomy, layered defenses, strong identity management, and continuous monitoring.
Containment can interrupt legitimate work and may not stop actions already queued in downstream systems. Confirm cancellation or completion in those systems, and record business impact and any exceptions. The cited guidance does not establish a universal kill switch or a single containment sequence for every deployment.
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6. Remediate the weakness and validate the fix
Address the control failure that enabled the incident, not only the content that triggered it. Depending on the cause, remediation may include:
- Removing unnecessary tools or separating read and write capabilities.
- Narrowing service identities and OAuth scopes, and enforcing authorization on every downstream request.
- Separating untrusted data from trusted instructions and isolating or reviewing potentially poisoned memory.
- Binding approvals to the specific action and parameters being approved.
- Limiting retries, chain depth, and spend; improving logs for tool calls and downstream activity.
Test the observed abuse case and related failure modes, including prompt override, tool misuse, privilege escalation, exfiltration, memory poisoning, and approval bypass. Keep validation evidence tied to the agent version, tool policy, retrieval configuration, and observed approvals or denials. OWASP recommends structured adversarial validation as well as least functionality and privilege, human approval, and logging and monitoring.
7. Restore service and document residual risk
Restore capabilities incrementally after the relevant controls are in place and validation has addressed the incident’s abuse case. Monitor the agent and connected systems as access returns. Close the incident record with the timeline, affected identities and resources, actions taken, evidence gaps, root cause, business and data impact, notification decisions, recovery criteria, and residual risks.
Use the findings to update threat models, response playbooks, tool permissions, and repeatable security tests. CISA and partner agencies call for threat modeling, continuous monitoring, and regular security assessments; NIST frames incident response as part of broader cybersecurity risk management.
What agent-hijacking evaluations can—and cannot—tell you
In a specific 2025 CAISI Workspace evaluation against an upgraded Claude 3.5 Sonnet model, the strongest baseline attack succeeded 11% of the time and the strongest newly developed attack 81% of the time. Those results describe particular attacks, a particular model, and a controlled evaluation environment; they are not estimates of the probability of a real-world incident or a current cross-model benchmark. CAISI technical staff wrote, “Across all three new risk areas, CAISI was frequently able to induce the agent to follow the malicious instructions.” The evaluation demonstrates that hijacking can be induced in tested scenarios, not how often deployed agents are compromised.
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