Deterministic security solution for AI agents – OpenClaw and 2 more
Deterministic policy engine blocks agent actions without relying on fragile LLM guardrails.

Deterministic policy engine blocks agent actions without relying on fragile LLM guardrails.
It’s refreshingly focused: rules for prompt injection, hidden HTML comment instructions, exfiltration patterns and even HEAD checks against npm/PyPI for hallucinated packages. The site sells the minimalist ethos — small, audit-first tool for the offensive side of LLM security — but from the page it looks primarily pattern-driven, so expect heuristic false positives and limited context-aware analysis unless the engine goes deeper.
Comprehensive Substack API docs, but it's still just documentation for an unofficial API.
Three-layer security stack separates launch policy, secret release, and sandbox enforcement.
Sandbox agents via natural-language policy, not ambient authority—genuinely novel approach.
Eight specialist agents catch what Claude Code misses, but it's prompts not actual code analysis.