The Next Frontier of Cybersecurity Is AI Itself.
Cytomate is building the next generation of AI assurance, model security, forensics and threat hunting capabilities — extending cybersecurity validation into the systems that will increasingly reason, decide and act.
Built for AI Systems
Models, agents, RAG pipelines and MCP servers — not just infrastructure.
Evidence, Not Assumptions
Defensible technical proof behind every deployment and risk decision.
Validation Heritage
Breach & attack simulation DNA, applied to AI.
AI Is Becoming a New Attack Surface
As AI becomes infrastructure, the model itself, its behavior, its supply chain and its operational environment become new attack surfaces.
- The model itself — its behavior under normal and adversarial conditions
- Its supply chain — components, adapters and dependencies
- Its operational environment — data, tools, agents and actions
Everything AI Assurance Requires
Four capabilities that take AI systems from assumption to evidence — across assurance, investigation, hunting and inspection.
AEVA
Artificial Intelligence Evidence, Validation & Assurance.
A structured lifecycle for discovering AI systems, testing their behavior and exposure, validating controls, and producing defensible evidence for risk decisions.
ExploreAI Forensics
Evidence reconstruction and investigation for AI systems.
Reconstruct prompts, retrieved context, agent and tool-call timelines, and model provenance to support post-incident investigation.
ExploreAI Threat Hunting
Hunting hidden threats across models, agents and AI workflows.
Proactively surface behavior drift, poisoned context, agent manipulation and AI supply-chain risk before they become incidents.
ExploreModel MRI
Black-box behavioral drift detection for AI models.
A structured probe battery profiles model behavior; Jensen-Shannon divergence against a baseline quantifies drift over time — no access to weights or internals required.
ExploreThe Assurance Lifecycle
AEVA answers the questions every organization deploying AI eventually has to face.
- Q1What AI systems are we actually using?
- Q2Can they be manipulated or behave outside their intended purpose?
- Q3Do the security controls around them actually work?
- Q4Can we produce defensible evidence to support deployment and risk decisions?
Discover
Understand the AI system and its context.
Assess
Test behavior, exposure and attack paths.
Attack
Run adversarial attacks against models, agents and defenses.
Validate
Verify security controls and response.
Observe
Monitor behavior and drift over time.
Collect Evidence
Preserve traceable technical proof.
Find
Surface findings and residual risk.
Remediate
Close gaps and strengthen controls.
Retest
Reassess when systems and risks change.
Forensic Timeline
- Prompt input captured
- Retrieval context sourced
- Model reasoning captured
- Agent plan executed
- Tool call logged
- Action outcome recorded
- Control response verified
- Evidence preserved
AI Forensics
Every interaction leaves a trail. Cytomate reconstructs that trail end-to-end — from the original prompt through retrieval, model reasoning, agent and tool activity, to the controls that responded and the evidence preserved.
- Prompt & interaction reconstruction
- RAG & retrieved-context evidence
- Agent & tool-call timelines
- Model & application provenance
- Memory & state reconstruction
- Forensic evidence preservation
- Post-incident investigation
Validation DNA, Extended Into AI
Cytomate's heritage is in emulation, validation and proving whether defenses work under realistic attack conditions. We are extending that validation DNA into artificial intelligence.
Breach & Attack Simulation
Security-Control Validation
Cyber Deception
IT Environments
OT & Critical Infrastructure
Adversarial Security Research
Frequently Asked Questions
Answers to what people ask us most about AEVA, AI Forensics, Threat Hunting and Model MRI.
Still Have Questions?
Our team is happy to walk you through AEVA, Model MRI or anything else.
Talk to CytomateCytomate builds AI assurance infrastructure — model security, forensics and threat hunting capabilities for the systems that increasingly reason, decide and act on their own.
AEVA — Artificial Intelligence Evidence, Validation & Assurance — is a closed-loop assurance lifecycle (Discover, Assess, Attack, Validate, Observe, Collect Evidence, Find, Remediate, Retest) for proving whether your AI systems behave as intended and whether the controls around them actually work.
AI Forensics reconstructs what already happened — prompts, retrieved context, agent and tool-call timelines — for post-incident investigation. AI Threat Hunting proactively looks for hidden threats, like behavior drift or poisoned context, before they become incidents.
No. Model MRI runs entirely black-box: a structured probe battery profiles model behavior, and Jensen-Shannon divergence between baseline and current response distributions quantifies drift. No access to weights, activations or internals is required.
Yes. The AEVA MVP is operational, with core capabilities — adversarial testing, RAG security assessment, automated evidence collection and audit-ready reporting — validated and deployment-ready. Enterprise automation and advanced governance capabilities are in active development. Talk to us about deploying AEVA for your AI systems.
Any organization deploying AI systems — models, agents, RAG pipelines or MCP servers — that needs defensible evidence for deployment and risk decisions, not just assumptions.
Talk to Cytomate directly or follow us on LinkedIn for updates as AEVA's capabilities continue to expand.