Scanners hand you a list of maybes. CVE Monster hands you the exploit and the patch.

1. 01Map

   Build a knowledge graph of the code

   The target is parsed into a graph: functions, call paths, data flow, trust boundaries, and the routes untrusted input can take to reach sensitive operations. Everything downstream queries this graph rather than grepping text, so the engine reasons about reachability instead of pattern-matching strings.

2. 02Analyze

   Run in-house AI static analysis

   Our own AI-powered SAST runs against the graph — tuned for the bug classes that actually get paid: memory corruption, type confusion, injection, path traversal, SSRF, authorization gaps. It reads context the way a reviewer does, so it flags the dangerous call that looks safe and skips the scary-looking one that isn't reachable.

3. 03Fuzz

   Fuzz the paths worth fuzzing

   Coverage-guided fuzzing, aimed by the graph instead of thrown at the whole binary. Parsers, decoders, and protocol handlers get hammered where the analysis says input can actually arrive — which is how you find the memory-safety bugs static analysis argues about and humans never reach by hand.

4. 04Swarm

   Turn agent swarms loose on the code

   Swarms of LLM-powered agents work the target in parallel, each chasing its own hypothesis about how the code breaks. They argue with the graph, with the fuzzer's crashes, and with each other. Breadth no single reviewer can match, running continuously rather than for the length of an engagement.

5. 05Prove

   Build the end-to-end exploit

   A candidate is not a finding until it runs. Each one gets a working end-to-end exploit and a test case that fails against the vulnerable build and passes against the fixed one. This is the stage that kills the false positives every other tool forwards to your inbox.

6. 06Patch

   Write the fix, not just the complaint

   The engine authors a patch against the real defect — informed by the same graph that found it, so the fix closes the reachable path instead of papering over the symptom. Finding a bug creates work for the maintainer. Finding it with the patch removes it.

7. 07Report

   Submit, then retest

   Findings go to the program with a reproduction, the exploit, and the patch in one package. When the fix lands we retest against the original case to confirm it actually closed — and feed the result back into stage 01, where the graph learns what shipped.

Browsers, geospatial SDKs, password managers, CI systems, identity providers, an anonymity network, and a crypto exchange. The engine is not tuned to one stack.