Static agent forms claims
An LLM agent reads the deobfuscated extension source and produces specific, falsifiable claims about what the extension does - not a generic risk category, but a concrete hypothesis: this code path exfiltrates form data, this endpoint receives credentials, this payload is assembled at runtime.
Dynamic agent tries to prove them
A second LLM agent runs the extension in a live instrumented sandbox with those claims in hand. It drives the extension specifically to test each hypothesis - visiting pages, triggering interactions, watching network traffic. It is trying to prove the static agent right, not just passively observing.
Evidence collection
All evidence from the sandbox run is collected alongside the LLM-generated reasoning from both agents - network captures, DOM observations, decoded payloads, and the chain of inference that led to each claim.
Claim verification
Claims are checked against the collected evidence. Verification is mixed: LLM and human. High-severity findings get a human researcher before they reach your dashboard. Low-confidence findings are flagged separately so you can judge them yourself.