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An incident response plan for AI-enabled infrastructure attacks should tell your organization who can declare an incident, how responders will investigate model and data issues, how AI-connected services can be contained without endangering operations, and how critical functions will continue. Build it around your own systems and dependencies: a national coordination framework is not a substitute for an organization-specific, rehearsable procedure.
What should an AI-enabled infrastructure incident plan cover?
Cover the full chain of services that could be involved in an incident, not just the model. A suspicious AI output may originate in an AI component, but investigation and response may also involve identity systems, cloud control planes, data pipelines, vendors, or operational technology (OT). Conversely, an incorrect output by itself is not proof of a cyberattack.
Start with an inventory of assets and dependencies. For each item, record its owner, purpose, criticality, and the other systems or functions that rely on it. Include:
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- Training, fine-tuning, retrieval, and other data sources; the pipelines that move or transform that data; and the systems that control access to it.
- Model-serving infrastructure, APIs, cloud services, identity and access systems, logging, and network dependencies.
- Third-party AI providers, cloud providers, integrators, and managed service providers, with service and support contacts.
- Any connected enterprise IT, OT, or industrial control system (ICS) assets, and the business, process, or safety function each supports.
Record data and model lineage where it is available. If responders cannot quickly determine which model version, dataset, API, or service a production function depends on, the plan should name who can establish that context during an incident.
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Keep organizational procedures distinct from national coordination
CISA’s National Cyber Incident Response Plan (NCIRP) is a strategic framework for national-level coordination; it is not a tactical response plan for an individual organization. Use it as context for how major incidents may involve wider coordination, but write your own operational steps, authority rules, contacts, and recovery criteria.
CISA’s Cross-Sector Cybersecurity Performance Goals (CPGs) organize cybersecurity work around Govern, Identify, Protect, Detect, Respond, and Recover, and include practices relevant to both IT and OT. That lifecycle can help check whether the organization has addressed more than detection and containment, but it does not replace procedures tailored to your systems.
Who has authority to activate and direct the response?
Write down who may declare an incident, who leads the response, and who can authorize actions that affect production or safety. Those authorities should be reachable outside business hours, with named backups. A response plan that says only “contact IT” leaves critical decisions and handoffs unresolved.
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Define activation criteria in terms responders can observe. For example, your organization might require formal incident handling when there is credible evidence of unauthorized access to a model or data pipeline, unexplained changes in AI behavior with security indicators, compromise of a provider or account used by a critical service, or potential impact to an OT or safety-critical process. Treat these as organization-specific examples, not universal thresholds. Distinguish a service-quality issue from a suspected security incident, while allowing responders to escalate when evidence is incomplete and potential impact is high.
For each severity level your organization uses, document the conditions that trigger it, the decision-maker, the response lead, the required notifications, and any heightened operational safeguards. Include a way to raise severity as evidence or impact changes. Do not invent a universal response-time target: set targets that fit your service commitments, risk tolerance, and applicable obligations.
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Assign named roles and backups
One person may fill more than one role in a small organization, but each responsibility still needs an owner and backup. Make clear which decisions belong to incident leadership and which require specialist approval.
| Role | Incident responsibility |
|---|---|
| Incident lead | Declares or coordinates the incident under the organization’s rules, maintains the decision log, assigns work, and escalates unresolved decisions. |
| Security operations | Coordinates detection, account and network investigation, evidence preservation, and security containment recommendations. |
| AI engineering or model owner | Identifies affected model versions, serving paths, data sources, behavior changes, and safe options to disable, revert, or constrain an AI function. |
| Infrastructure and cloud operations | Assesses compute, storage, identity, network, backups, and provider dependencies; carries out approved infrastructure changes. |
| OT, process operations, and safety | Assesses consequences for physical processes, safe states, monitoring, manual control, and the hazards of isolation or loss of automation. |
| Legal, privacy, and compliance | Assesses evidence-handling constraints, contractual and regulatory duties, privacy impacts, and external-notification decisions. |
| Communications and business continuity | Coordinates internal and external messaging and arrangements for continuing critical business functions. |
| Procurement or vendor management | Uses provider and supplier contacts, confirms service dependencies, and coordinates support or incident information requests. |
Some decisions should not be delegated to a technical responder acting alone. For example, disabling an AI feature may be a straightforward application change in one service and a process-safety decision in another. The plan should say who assesses that difference and who authorizes the action.
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AI incidents can be difficult to interpret because models are data-driven and may produce non-deterministic outputs. CISA’s Joint Cyber Defense Collaborative (JCDC) AI Cybersecurity Collaboration Playbook identifies model poisoning, data manipulation, and adversarial inputs as examples of malicious activity. These possibilities broaden the investigation; they do not mean every anomalous output indicates an attack.
Prepare before an incident by deciding which records can be preserved, where they are kept, who can access them, and how long they remain available under organizational policy. Practical records to consider include:
- Model identifiers, versions, deployment settings, configuration changes, and release history.
- Training, fine-tuning, and retrieval-data lineage, including relevant pipeline activity and access records.
- API requests and responses, service errors, and relevant provider notifications.
- Identity events, administrative actions, cloud control-plane activity, and changes to permissions or secrets.
- Network and application logs that can show whether activity extended beyond the AI component.
- Prompts, inputs, or outputs only where collection is permitted by privacy, confidentiality, retention, and other applicable rules.
These are planning considerations, not a checklist mandated by CISA. Agree with privacy, legal, engineering, and security owners in advance about what is appropriate to collect. Preserve timestamps and relevant context; an isolated output without its model version, request path, or surrounding events may be difficult to interpret.
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Use a consistent triage sequence
- Establish the report. Record who reported the issue, what was observed, when it began, which service or process is affected, and what is known versus suspected. Preserve the original report and timestamps.
- Identify the affected path. Trace the function from user or process input through the application, model or provider, data sources, identity controls, serving infrastructure, and any downstream IT or OT system.
- Test competing explanations. Ask whether the model output is malicious, manipulated, degraded, or simply incorrect. Look for corroborating indicators such as unauthorized access, unexpected configuration or data changes, suspicious API activity, or a provider alert.
- Check for wider impact. Determine whether access or effects extend beyond the model or AI service, including to cloud accounts, business systems, OT, safety functions, or sensitive data.
- Set and revisit severity. Apply the organization’s impact criteria, record the decision owner, and update severity when new evidence changes the risk.
- Maintain a decision record. Log key facts, hypotheses, evidence sources, containment actions, approvals, and timestamps. Mark uncertainty explicitly rather than turning a working theory into a confirmed finding.
Useful triage questions include: Is the issue in the model, training or retrieval data, serving environment, API, identity or cloud control plane, provider, or connected process? Which model and configuration were active? Can the suspected behavior be reproduced safely? What systems consumed the output? Has there been access or impact outside the AI component? Those questions help responders avoid both underreacting to a broader compromise and overreacting to a model error without security evidence.
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For infrastructure environments, containment is not simply a matter of disconnecting the suspected system. CISA, the FBI, and the NSA advise organizations to identify IT/OT interdependencies, plan safe isolation and manual controls, and test contingency plans so safety-critical functions can continue. A change that reduces cyber exposure can still create operational or safety risk if it removes monitoring, automation, or a required control path.
Before an incident, operations and safety personnel should assess the consequences of disabling, isolating, reverting, or restricting each AI-connected function. Define which functions can be moved to human-supervised operation or a manual workaround, what conditions make that safe, and who approves the transition. The procedure should identify dependencies that may be less obvious than the AI service itself, such as remote monitoring or control channels.
Make containment decisions by service, not by label
Document a containment option for each critical AI-enabled service. An organization may choose to disable an AI feature, route work through a non-AI process, limit permissions or traffic, revert to a known configuration, or isolate a component. These are options to assess in advance, not universal instructions. For each option, specify the authorizer, the technical owner, the operational impact to check, and how the team will verify the action worked.
| Decision to plan | Questions the procedure should answer |
|---|---|
| Disable or restrict an AI function | Which users, applications, or processes will lose the function? Is a non-AI or human-supervised alternative available? Who approves the change? |
| Isolate a system or connection | What depends on the connection? Could isolation remove monitoring, remote support, or safe control? Have operations and safety owners assessed the process impact? |
| Revert a model or configuration | Which version or configuration is trusted, and how will its provenance be checked? Could the rollback restore a known vulnerability or an incompatible dependency? |
| Use manual or contingency operation | Who is qualified to operate it, what conditions permit it, how is the transition communicated, and how will safe service be maintained? |
During an incident, have security recommend containment based on evidence, but require the designated operations and safety authorities to assess process consequences before actions that affect OT or safety-critical functions. If immediate danger is suspected, follow the organization’s emergency and safety procedures rather than improvising a cyber-only isolation step. Record what was changed, who approved it, and what service impact followed.
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How should you coordinate with AI providers and external organizations?
Maintain a contact path for AI providers, cloud providers, integrators, and managed service providers before an incident. Record support channels, escalation contacts, account or tenant identifiers needed to open a case, and what information the provider may need to investigate. Keep primary and backup contacts accessible to the response team outside normal business hours.
CISA’s JCDC AI Cybersecurity Collaboration Playbook, dated January 14, 2025, describes voluntary processes for sharing AI-related cybersecurity incident and vulnerability information with CISA and partners. It is aimed at AI providers, developers, adopters, and partners, and describes information-sharing protections and actions CISA may take after receiving shared information. It can inform an organization’s coordination path; participation is not a substitute for its own incident procedures.
The accompanying fact sheet states: “This playbook does not create policies, impose requirements, mandate actions, or override existing legal or regulatory obligations.” It also says safety issues involving people, property, or the environment are outside the playbook’s intended scope and should be handled through applicable organizational procedures.
Build a notification decision path, not a universal deadline
List the external parties that may need to be considered: relevant CISA/JCDC channels, sector-specific coordination bodies, service providers, vendors, insurers, regulators, law enforcement, and affected customers or partners. For each, identify the internal decision owner and what facts or approvals are needed before contact.
Do not put a single notification deadline in the plan as if it applied to every organization. Reporting and disclosure duties vary with jurisdiction, sector, contract, incident facts, and the type of data or service involved. Assign counsel or compliance owners to confirm the organization’s applicable obligations and to review them when services, locations, or rules change. The plan should also distinguish a voluntary information-sharing decision from a legally required notice.
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What should recovery and post-incident review include?
Containment does not establish that a model, dataset, or environment is trustworthy. Give a named authority responsibility for approving recovery, and define the evidence needed before restoring an affected AI service or reconnecting it to a critical process.
- Identify trusted backups, configurations, model versions, and data sources, and establish how their provenance and integrity will be checked.
- Specify how to restore or rebuild model-serving and data pipelines, including dependent identity, cloud, and application components.
- Validate behavior and security controls in an appropriate environment before production use; document who accepts the operational risk.
- Set conditions for reconnection to IT, OT, or ICS systems, with approval from the relevant operations and safety owners.
- Use heightened monitoring after restoration and define which indicators would trigger renewed containment or escalation.
- Confirm that business owners accept the restored service and that contingency arrangements can end safely.
After the incident, conduct a review that records the root cause if established, affected dependencies, evidence gaps, decisions and their owners, service or safety impacts, and corrective-action owners. If root cause remains uncertain, say so and track what further work is needed. Convert findings into changes to controls, contacts, retention, recovery steps, or exercises rather than treating the review as a narrative-only report.
How do you exercise the plan?
CISA recommends realistic incident response drills at least annually. Smaller organizations can use a spoken walkthrough or simple rehearsal rather than a complex technical exercise. CISA also advises involving senior business leaders and board members in major-incident planning and testing continuity for critical business functions.
Choose an exercise format that tests the decisions your plan depends on. A walkthrough can reveal unclear authority or missing contacts; a tabletop can test coordination across teams; a technical simulation can examine logging and containment procedures; a continuity test can verify whether critical functions can continue under the planned workaround. A more elaborate exercise is not automatically more useful if it bypasses the real operational decision-makers.
Exercise a combined AI and infrastructure scenario
Use a scenario such as suspected data manipulation, adversarial inputs, compromised credentials, loss of an AI provider, uncertain model behavior, or a need to isolate an AI-connected OT function. These are planning scenarios, not claims that a particular event has occurred. Introduce information gradually so participants must distinguish confirmed facts from assumptions.
During the exercise, test whether participants can:
- Find the service owner, model and data lineage, provider contacts, and critical dependencies.
- Recognize that an anomalous model output is a lead to investigate, not conclusive proof of compromise.
- Preserve relevant records while respecting privacy and evidence-handling rules.
- Reach the incident lead, technical specialists, legal and privacy owners, and operations or safety decision-makers.
- Choose a containment path that considers safe isolation, manual operation, and continuity of critical functions.
- Decide whether to coordinate or share information externally and identify who checks applicable legal duties.
- Agree on recovery evidence, restoration authority, monitoring, and business acceptance.
Afterward, assign an owner and due date to each identified gap. Update the plan and contact lists, then rehearse significant changes. CISA’s AI roadmap for 2023–2024 called for incorporating cyber defense, incident management, and redress procedures into AI systems and processes, as well as continuous model evaluation. Treat that roadmap as strategic context for ongoing governance, not as a replacement for current operational procedures.
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What a usable plan looks like
A useful plan is a controlled operational document that responders can reach and follow under pressure. Keep the core procedure concise enough to navigate, with linked or attached system-specific runbooks, dependency maps, contact lists, and recovery steps. Test that the materials remain accessible if the normal identity, collaboration, or cloud service is unavailable.
Quick Recap
- Scope: covered AI, data, infrastructure, provider, IT, and OT assets, with named owners and critical dependencies.
- Activation: observable criteria, severity rules, declaration authority, and an escalation path.
- People: primary and backup incident roles, after-hours contacts, and decision rights.
- Investigation: evidence sources, privacy-aware preservation steps, triage questions, and a decision log.
- Containment: pre-assessed options, authorization rules, safe isolation considerations, and continuity alternatives.
- Coordination: provider, sector, CISA/JCDC, regulator, insurer, and law-enforcement decision paths, with legal review where applicable.
- Recovery: trusted restoration sources, validation gates, reconnection authority, monitoring, and business acceptance.
- Exercise and improvement: a realistic rehearsal at least annually, findings with owners, and updates when systems or obligations change.
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