Scanners have no context. They flag everything with a CVSS score, then leave the judgment to you. Horus uses adversarial AI to argue both sides of every ambiguous finding before it reaches your team.
Every ambiguous finding goes through a 3-step adversarial process before it gets an SSVC priority.
Red Team agent builds a concrete exploit path: threat actor motive, blast radius, attack vector. Context-aware, not boilerplate CVSS descriptions.
Blue Team agent counters: compensating controls, network segmentation, non-exploitable conditions. Checks whether the finding is already mitigated.
A third LLM weighs both arguments and outputs a confidence score 0.0-1.0. Verdict stored. Future scans inherit it without re-debating. Triage time drops to zero.
Red/Blue debate, attack simulation and community verdict memory.
For ambiguous findings (confidence 0.2–0.9, no known exploit): Red argues attack, Blue argues defense, Judge calibrates. KEV-active findings skip debate, they're auto-confirmed. Verdicts stored and inherited across scans.
Full adversarial cycles against your live infrastructure. Red Team generates attack findings across multiple categories. Results feed into the main findings pipeline.
Anonymous aggregation of verdicts across all Horus orgs. k-anonymity guarantee. New customers benefit from industry-learned FP suppression from day one.
The live demo includes Red/Blue debate transcripts and Red Team simulation results.