AI Defendo tracks every agent across every session, evaluating identity, intent, behavior, memory, context, and posture before they access data, invoke tools, or execute actions — one verdict per turn.
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 behavior.
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?
What were they commissioned to do?
What did they actually do?
What had they learned before this turn?
What inputs reached the agent, and from where?
Was the environment trusted?
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 Awareness Engine sits at the center. 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-level sensors and inline interceptors capture the full agent trajectory — including what your existing stack can't see.
Six dimensions joined, every turn. Sub-200ms processing core evaluates historical trajectories across all active dimensions, stamping a cryptographically verifiable token validation badge on safe tasks.
Inline enforcement at the egress point. Tools never run, data never leaves, secrets never surface — unless the verdict says they should.
You can't secure what you can't see. You can't trust what you can't verify turn by turn. AI Defendo gives you both.
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.