AETHERWARD

Service / 07

AI Incident Response & System Repair

Rapid containment, evidence preservation, root-cause analysis, and durable repair after an AI system fails, leaks, drifts, or acts outside policy.

07
The objective

Contain what is happening now, reconstruct how it happened, and repair the system so the same path cannot quietly return.

AI incidents can span prompts, memory, model behavior, data pipelines, tools, identities, third-party services, and automated actions. We help teams establish the timeline and preserve the evidence needed to distinguish model error, malicious manipulation, control failure, data compromise, and operational drift.

The response moves from immediate authority reduction and containment to trace reconstruction, root cause, recovery validation, and structural remediation. Where evidence is incomplete, uncertainty and gaps remain explicit rather than being filled with assumptions.

Often requested as

AI incident responseLLM forensicsAgent failure investigationModel rollback supportEmergency AI security repair
Assessment surface

What we cover

  1. 01Prompt, trace, tool-call, identity, memory, and data forensics
  2. 02Immediate capability reduction and containment planning
  3. 03Timeline reconstruction and evidence chain of custody
  4. 04Poisoning, compromise, drift, and policy-failure diagnosis
  5. 05Model, prompt, tool, knowledge-base, and integration rollback
  6. 06Credential rotation and authority re-establishment
  7. 07Recovery validation and adversarial regression testing
  8. 08Post-incident architecture repair and runbook improvement
The handoff

What you receive

  1. 01Incident timeline and evidence inventory
  2. 02Containment and safe-recovery plan
  3. 03Root-cause and contributing-control analysis
  4. 04Remediation and regression-validation package
  5. 05Leadership brief and improved response runbooks

Designed outcomes

Controlled incidentPreserved evidenceKnown root causeValidated recovery
How it works
01

Stabilize

Reduce authority, preserve volatile evidence, and contain affected components without destroying the investigation path.

02

Reconstruct

Connect prompts, traces, identities, tools, context, model versions, and infrastructure into a defensible timeline.

03

Repair

Address the immediate weakness and the architectural conditions that allowed it to propagate.

04

Prove recovery

Retest the incident path, validate controls, document gaps, and improve monitoring and runbooks.

Operating boundary: All work is performed within explicitly authorized scope. High-risk actions remain human-approved, and findings are communicated with evidence, uncertainty, and practical remediation context.

Research-driven security

Built for attack surfaces traditional security models were not designed to see.

Aetherward’s assessment methods are informed by continuous internal research into behavioral attack chains, legitimate-tool abuse, permission composition, cross-tool escalation, context manipulation, model-to-tool boundary failures, poisoning, and abnormal agent behavior.

Explore Aetherward research ↗
Additional capabilities

Fixed-scope or project-based

Security Automation Engineering

Custom security tooling for teams that need specialized automation without building a full internal platform.

Triage automationDetection toolingScope-aware scannersEvidence collectionThreat-intelligence workflowsAnalyst tooling

Recurring engagement

Ongoing AI Security & Architecture Advisory

Independent review as models, data, integrations, vendors, threats, and business requirements change.

Architecture reviewIntegration reviewThreat updatesRelease gatesSecurity driftDecision support

Building or deploying an AI system?

Assess it. Secure it. Build it. Repair it. ↗