ILION: Deterministic Pre-Execution Safety Gates for Agentic AI Systems

V34 - The proliferation of autonomous AI agents capable of executing real-world actions introduces significant safety risks at the execution layer, where incorrect or unauthorized tool invocations may cause irreversible damage. Existing safety systems predominantly focus on linguistic content moderation rather than operational authorization, creating a critical gap between text safety and execution safety.

We present ILION (Intelligent Logic Identity Operations Network), a deterministic pre-execution safety gate designed to classify proposed agent actions as BLOCK or ALLOW before execution. ILION employs a multi-layer cascade architecture combining Transient Identity Imprint (TII), Identity Drift Control (IDC), Identity Resonance Score (IRS), and Consensus Veto Layer (CVL) mechanisms to provide interpretable authorization decisions with sub-millisecond latency and no training data requirements.

We evaluate ILION on ILION-Bench v2, a purpose-built benchmark of 380 agent action scenarios across multiple attack categories. ILION achieves an F1 score of 0.8515 with a false positive rate of 7.9% at a mean latency of 143 microseconds. Comparative experiments demonstrate substantial performance advantages over both commercial safety baselines and general-purpose semantic embedding approaches, highlighting a fundamental task mismatch between text moderation systems and execution safety requirements.

This work provides evidence that deterministic, domain-specific verification architectures may offer a complementary and necessary safety layer for autonomous AI systems.