Models act on instructions. Instructions can come from anyone. We test what happens when they do — continuously, not once a year.
We test what your bot can be talked into doing, not just what it can be talked into saying. Deleting records, exporting data, sending email on your behalf.
A yearly test is out of date the week your bot changes. We re-test every prompt, model and tool update, so nothing new slips through unnoticed.
Agents connect to tools that reach real systems. We map what each connection can actually do, and try to reach the dangerous ones through the chat itself.
A downloaded model is unvetted third-party code with the keys to your data. We check it before it ever reaches production, and again each time it changes.
We break it. You fix it. We prove it stays fixed.
Not a filter on a generic vulnerability scanner. MCP servers, agent skills and tool permissions are assets in their own right, with their own attack library and their own blast radius.
Hosted and third-party models in use, with owner, environment and data sensitivity — alongside registered MCP servers, their exposed tools, auth mode and last capability change.
Continuously running attack campaigns with cadence, coverage of the library, and the delta since the last result — because a model that changed last Tuesday is a different system.
Probes grouped by objective — prompt injection, tool abuse, data exfiltration, privilege escalation, memory poisoning and supply chain.
Captured successful exploits with a deterministic step-through of the exchange — prompt, tool calls, responses, and the exact moment the boundary failed.
Runtime controls for injection, tool scope, egress and output filtering — with a simulation tab, like every other enforcement surface in the platform.
The browser module finds the AI tools your people use. This module finds the ones your systems use — endpoints, servers and skills nobody registered.
"The model may be susceptible to prompt injection" gets forwarded and forgotten. A deterministic replay showing the exact retrieved document, the exact tool call it triggered and the exact records that left gets fixed the same week — and re-verified in one click when it is.
The two newly-succeeding attacks appeared after a routine model version bump. A point-in-time pentest would have missed both.
An MCP server is a permission surface that changes without a deploy. A capability added upstream, a tool renamed, an auth mode relaxed — each one alters what an agent can be talked into doing. We track the surface and re-test it when it moves.
You will get a replayable trace of anything that worked — and a way to prove the fix landed.
No credit card. No agent on the endpoint. Nothing leaves your network.