The Tool Desk
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1. Stabilize people and critical operations
Your first decision is operational, not forensic: is anyone in danger, and is the affected output still driving a consequential action? Treat threats to life, health, physical security, privacy, financial security, and essential services as higher priority than explaining the model’s behavior. A recommendation that is merely wrong in a low-impact setting is different from an automated decision that is denying medical care, opening a physical-security control, exposing personal data, or disrupting a critical service.
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Use the organization’s emergency procedures and assign a person with authority to make immediate safety decisions. If the AI output is being consumed by another application, a human operator, or a connected device, identify that downstream action and stop or review it where doing so will not create greater danger. NIST’s AI Risk Management Framework Core calls for prioritizing risk treatment, while NIST SP 800-61 Rev. 3, published in April 2025, organizes cybersecurity response around detection, analysis, containment, eradication, recovery, reporting, and communications.
Separate the incident category
Record the event’s characteristics without assuming a cause. Useful categories include:
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- Safety or reliability failure: the system produced harmful, unsafe, or materially incorrect behavior during intended use.
- Security compromise: an attacker, malicious input, stolen credential, vulnerable integration, or unauthorized change affected confidentiality, integrity, or availability.
- Privacy incident: personal or sensitive information was exposed, inferred, retained, or sent to an unintended party.
- Operational or business-continuity incident: the system or a dependency interrupted an essential process.
- Near miss: harmful consequences were avoided, but the event reveals a control weakness worth investigating.
These categories can overlap. A prompt-injection attack may cause a safety failure; a model hallucination may expose confidential information through an automated message. Document the observed impact and uncertainty separately from the suspected cause.
2. Decide whether to pause, bypass, or deactivate the system
Deactivation is a risk-control option, not an automatic ritual. NIST identifies mechanisms to supersede or deactivate an AI system when it behaves inconsistently with intended use, but the action must be safe and authorized. Consider what happens if the model keeps running and what happens if it stops.
| Response option | Use when | Checks before or during action |
|---|---|---|
| Pause a workflow | A specific queue, feature, model route, or automated action is causing harm and can be stopped without interrupting unrelated services. | Confirm queued jobs, retries, alerts, and any actions already handed to downstream systems. |
| Bypass with human review | A manual decision can safely replace the AI output for a limited period. | Provide trained staff, clear authority, workload limits, and a way to record decisions. |
| Supersede a component | A model, prompt, policy, data feed, or integration can be replaced while the surrounding service remains available. | Verify the replacement’s version, configuration, access rights, test results, and rollback path. |
| Full deactivation or isolation | Continued operation presents unacceptable risk, the system is compromised, or no reliable containment boundary exists. | Check physical and operational dependencies, safety interlocks, backup communications, and the effect on essential services. |
Prefer the least disruptive control that reliably reduces harm, but do not preserve availability at the expense of safety. Record who authorized the action, the time, the reason, the expected effect, and the fallback procedure. If the system controls equipment or another automated service, use a tested safe state rather than simply cutting power or connectivity without understanding the consequences.
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Use the organization’s incident plan, expanding it for AI-specific dependencies. Establish one incident lead and name owners for the functions that must act together:
- Operational safety: protects people, facilities, and service continuity.
- Cybersecurity: handles compromise, access, malware, monitoring, and containment.
- AI or model operations: understands model versions, prompts, evaluations, guardrails, data pipelines, and deployment controls.
- Privacy and records: assesses personal-data exposure, retention, and preservation requirements.
- Legal and regulatory review: identifies applicable duties and coordinates with counsel.
- Communications: prepares internal, customer, public, and regulator messages through one authorized channel.
- Business continuity: supplies manual or non-AI alternatives and manages service priorities.
Bring in a vendor or service provider when the system depends on a third-party model, hosting platform, software package, data source, or managed operation. Ask for the relevant model and service version, incident records, access logs, known limitations, containment actions, and preservation of their own evidence. NIST’s Traffic Sign Recognition Use Case Profile illustrates why conventional incident plans often need AI-specific ownership and communication arrangements.
4. Preserve evidence and build a reliable timeline
Containment should not destroy the information needed to understand the event. Follow your retention policy and legal advice, and avoid deleting, overwriting, or “cleaning up” records that may be relevant. Preserve originals where possible and work from copies for analysis.
Capture the following as soon as practical:
- Time zone, start and end times, discovery time, and the person or system that detected the event.
- System name, model and software versions, deployment environment, configuration, feature flags, and relevant policy or prompt versions.
- Inputs, outputs, tool calls, retrieval results, confidence or refusal signals, and human approvals connected to the event.
- Users, accounts, service identities, credentials, network paths, integrations, and data stores involved.
- Observed effects: decisions made, records changed, messages sent, equipment actions, people affected, and services unavailable.
- Alerts, dashboards, traces, access logs, audit records, tickets, screenshots, recordings, and copies of relevant communications.
- Every response action: who decided it, when it occurred, what was changed, and what result was observed.
Maintain a single chronological incident log with a clear distinction between facts, hypotheses, and decisions. Preserve the chain of custody for exported logs or forensic images if litigation, regulatory review, or a criminal investigation is possible. NIST’s AI guidance emphasizes tracking and documenting incidents, monitoring, response, recovery, and change management; its AI RMF Playbook provides voluntary suggested actions, not a mandatory checklist. As the Playbook states: “The Playbook is neither a checklist nor set of steps to be followed in its entirety.”
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5. Contain the event and investigate the cause
Containment limits additional harm while investigation tests competing explanations. Do not assume that the model itself is defective. The failure may be in the application, data, access controls, an integration, human operation, or malicious activity.
Questions about the model and prompts
- Can the behavior be reproduced with the same model version, context, temperature or sampling settings, tools, and prompt?
- Did a model update, fine-tune, policy change, safety-filter change, or configuration rollout precede the incident?
- Was the output within a known limitation, outside the intended use, or inconsistent with prior evaluation results?
- Did adversarial content, prompt injection, data poisoning, or an unusual input path influence the result?
Questions about data and integrations
- Which data sources were retrieved or supplied, and were they current, authorized, and correctly scoped?
- Could the system read or write more data than the user or service needed?
- Did an API, plug-in, tool, device, or workflow execute the output without an adequate validation step?
- Were credentials, tokens, personal information, or confidential records exposed?
Questions about people and controls
- Was a human expected to review the output, and did the interface, workload, or escalation design make that review ineffective?
- Were warnings, confidence indicators, refusal messages, or audit trails visible and understandable?
- Did training, access control, change approval, monitoring, or vendor oversight fail?
Apply targeted containment: revoke or rotate exposed credentials, isolate affected interfaces, block malicious inputs, disable a risky tool call, restrict permissions, roll back a deployment, quarantine poisoned data, or require human approval. Eradication means removing the underlying cause, not merely restarting the service. Test the proposed fix against the original event, plausible variations, and normal workloads before restoring automation.
6. Determine whether notification is required
Do not guess a deadline from the fact that an AI system was involved. The reviewed official guidance establishes no single universal AI-incident notification rule. Duties can depend on the country or state, sector, type of information, number and location of affected people, severity, contractual commitments, and whether the event is a privacy breach, cybersecurity incident, safety event, outage, or another regulated occurrence.
Make an early notification assessment with qualified counsel and the relevant compliance owners. Map:
- Where the organization, affected people, systems, and service providers are located.
- Which sector rules, privacy laws, critical-infrastructure rules, securities obligations, safety requirements, or contracts apply.
- What information or operational capability was affected, for how long, and with what likely consequences.
- Whether a regulator, customer, insurer, law-enforcement body, sector coordinator, or affected individual must be contacted.
- What evidence supports the assessment and what facts remain unknown.
NIST’s Incident Response life-cycle resources directory points to distinct CISA, HHS, FTC, state-law, and SEC materials rather than one combined rule. The OECD’s 2025 proposal, Towards a common reporting framework for AI incidents, uses 29 criteria as a global benchmark that can be adapted to domestic legal and policy frameworks; it is not itself a replacement for local law.
7. Communicate with confirmed facts
Designate one communications lead and keep public, customer, employee, regulator, and partner messages consistent. Explain what is confirmed, what is still being investigated, the practical effect on recipients, protective steps they should take, and when the next update will arrive. State uncertainty plainly instead of presenting a preliminary cause as established fact.
If personal information, account access, or a consequential decision may be involved, provide specific protective instructions: change a credential, review a transaction, contact a support channel, avoid relying on a particular output, or seek a human review. Do not publish sensitive logs, personal data, exploit details, or speculative blame. Correct an inaccurate statement promptly and preserve each version of material communications in the incident record. NIST’s AI RMF calls for communication with relevant AI actors and affected communities, and its use-case guidance assigns management oversight for public disclosure when an incident directly affects the public.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Recover safely and verify the result
Recovery is more than turning the model back on. Define conditions for restoration, obtain approval from the operational and safety owners, and start with restricted scope, heightened monitoring, and a tested fallback. Confirm that the triggering condition is removed or controlled, affected data and credentials are addressed, access is least-privilege, and downstream systems have been checked for unauthorized or harmful actions.
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For incidents with ransomware or comparable cyber characteristics, use the cyber-specific portions of CISA’s #StopRansomware Guide: restore critical services from clean backups, validate the restored environment, document lessons learned, and consider information sharing with CISA or an appropriate sector information-sharing and analysis center. Those recommendations are not a universal recovery recipe for a model-quality failure or a non-cyber safety incident.
During recovery, monitor the exact signals that would reveal recurrence: unsafe outputs, abnormal tool calls, access anomalies, data leakage, override rates, error rates, latency, and user reports. Keep the manual fallback available until the system has met the documented release criteria for a defined observation period.
9. Turn the incident into control improvements
Run a blameless but accountable review after immediate risk is controlled. Reconstruct the timeline, identify the first failed or missing control, and distinguish contributing conditions from the proximate trigger. Assign owners and due dates for corrective actions rather than recording only a narrative.
- Update intended-use boundaries, prohibited uses, safety cases, and escalation thresholds.
- Add evaluations for the observed failure mode and realistic variations, including adversarial and out-of-distribution inputs.
- Improve logging, traceability, alerting, human review, and the ability to supersede or deactivate the system.
- Reduce permissions, separate environments, rotate secrets, and add validation around tools and consequential actions.
- Review vendor contracts for incident notice, evidence access, model-change notice, cooperation, and service continuity.
- Test manual fallback, backup, communications, and restoration procedures in exercises.
- Update training and runbooks so staff know who can pause automation and how to report a near miss.
Keep the final report proportional to the event but complete enough to support regulatory answers, insurance, legal review, future engineering, and governance decisions. Include impact, affected scope, timeline, evidence, decisions, containment, root and contributing causes, notifications, recovery tests, and outstanding risk.
Quick Recap
A compact response checklist
- Protect people, privacy, and essential services; stop consequential actions that are still unsafe.
- Classify the observed event without presuming whether the cause is model, cyber, data, human, or integration related.
- Pause, bypass, supersede, isolate, or deactivate the affected capability when that reduces risk and a safe fallback exists.
- Activate operational safety, cybersecurity, AI operations, privacy, legal, communications, continuity, and vendor owners.
- Preserve logs, inputs, outputs, configurations, access records, decisions, and communications; start a time-stamped timeline.
- Contain affected accounts, interfaces, data, tools, and deployments while testing the cause.
- Assess jurisdiction-, sector-, contract-, and fact-specific notification duties with qualified counsel.
- Communicate confirmed facts, protective actions, uncertainty, and the next update through an authorized lead.
- Restore in stages with monitoring, approval, and a working manual or non-AI fallback.
- Document lessons, assign corrective actions, and test whether the changes prevent recurrence.
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