The Overview
AI security product targeting prompt injection in commercial LLM deployments. Goes beyond regex guardrails to implement identity anchoring, latent-space drift detection, and output parity verification.
The Problem
Most AI security is probabilistic guardrails — more AI trying to detect if other AI is misbehaving. Fails across four attack vectors: encoded payloads, persona drift, semantic drift, and tool-call injection. 99% success rate means 100% vulnerability.
The Solution
Four-gate system: G1 Payload Base-X (encoded jailbreaks), G2 Persona Drift (identity consistency), G3 Zero-Trust Schema (system metadata blocking), G4 Recursive Loop (token-burning detection). Three pillars: Identity Anchoring, Latent-Space Locks, Output Parity / Truth-Lock.
The Result
Deterministic security layer handling encoded, semantic, persona-drift, and structural attacks. Identity Anchoring means the agent cannot process contradictory instructions. Built from a documented Adversarial Vector Map, not theoretical research.