AI Defendo tracks every agent across every session, evaluating identity, intent, behavior, memory, context, and posture on every turn — at every tool call, memory operation, and data access. One verdict per turn.
AI Defendo discovers every agent, observes every action, and evaluates behavioral correctness before execution.
Agents fail in ways prompts don't predict.
Indirect injection. Goal drift. Memory poisoning. Compacted context. Cross-agent escalation.
Every one looks like legitimate behavior until you watch the full agent across the full session.
Named vendors with disclosed CVEs and real-world impact. In every case, the agent acted within its permissions. What didn't exist was a check on the agent's conduct.
Zero-click email triggered Copilot to embed an exfiltration URL in its response. ~$200M impact across 160+ orgs.
User said "code freeze." Agent dropped tables anyway. 1,206 executives + 1,196 companies deleted. 4,000 fake users fabricated.
Cross-session attack. Memory poisoned in one chat — every chat after silently exfiltrated user data through legitimate APIs.
Web-to-Lead form hijacked Agentforce into exfiltrating CRM records. An expired domain still in the CSP allowed the egress.
Public-channel injection made Slack AI surface private-channel content to a low-trust user. Slack's response: "intended behavior."
Cross-agent escalation. Low-privilege agent tricked a higher-privilege one into exporting case files externally. ServiceNow: "works as intended."
None of them verify whether the agent's behavior was correct.
Every agent action raises six questions. Miss any one and you can't say what really happened.
Who acted?
The principal behind this turn — and the effective scope of their grant.
What were they commissioned to do?
The task the user or system actually asked the agent to perform.
What did they actually do?
The action itself — tool called, entity touched, and where this turn sits in the sequence.
What had they learned before this turn?
The agent's accumulated state from prior turns and prior sessions.
What inputs reached the agent, and from where?
The data the agent is reasoning over this turn, and whether it can be trusted.
Was the environment trusted?
The configuration around the workload — permissions, allowlists, baselines.
AI Defendo answers all six on every turn.
Threats hit the agent lifecycle — input, reasoning, memory, tools, output. They reshape the data — exposure, exfiltration, secret leakage, compliance. AI Defendo maps both — and that's Behavioral Correctness.
inferred task: investigate data anomaly · active directive: code freeze in effect
The Agent Awareness Engine sits at the center — the mechanism for Behavioral Correctness. Continuous detection, multi-mode sensors, and runtime actuators wrap completely around it.
Continuous inventory across cloud, endpoint, and browser. Nothing autonomous stays invisible to the platform.
Kernel sensors and inline interceptors capture the full bidirectional agent trajectory — request and response, tool call and result, MCP and skill I/O — including what your existing stack can't see.
Six dimensions joined, every turn. One verdict per action, sub-200ms, cryptographically signed.
Inline enforcement at the egress point. Tools never run, data never leaves, secrets never surface — unless the verdict says they should. Or rewritten in place when the content can be safely sanitized.
AI Defendo deploys inside your environment. The control plane, the inference, the verdict-signing keys, and the audit trail all run where your data lives.
The Agent Awareness Engine and its control plane deploy inside your VPC. Verdicts happen where the agent runs.
Choose sovereign mode — local inference in your tenant — or managed mode via a routed LLM provider. The customer-data path stays the same: your traffic, your verdicts, your storage.
Signing keys are generated and held by your deployment. Signed verdicts write to your storage. The audit trail lives where you can see it.
Other AI security platforms ingest your agent traffic into vendor clouds and call out to managed LLMs for analysis. Your data lives in three places before a verdict comes back. AI Defendo's sovereign deployment is one place — yours.
You can't secure what you can't see. You can't trust what you can't verify turn by turn. Five capabilities, one engine — evaluating Behavioral Correctness on every turn.
Find every AI agent, app, and MCP server across your environment — including the ones nobody told you about.
Protect deployed AI workloads — inference servers, RAG pipelines, agent runtimes — from runtime exploitation.
One risk map across every agent, identity, and configuration gap — with prioritized paths to close them.
The behavioral correctness wedge. The AI Interceptor inspects every agent turn against the six-dimension verdict — stopping trajectory drift, indirect injection, and unauthorized actions before they execute. Choose your posture per environment.
Zero-trust identity for every agent action. Cryptographic principal chains, just-in-time scoped grants, and per-turn re-authorization on every tool call — so the agent never inherits more privilege than the current turn requires.
Join the Beta to begin mapping and securing multi-turn workflows inside your production environment.