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Show HN: Built firewall for LLMs after prompt injection bypass GPT-4s guardrails

https://github.com/WardLink/TrustLayer--Security-Control-Plane-For-LLM-AI

After watching prompt injection attacks bypass every major LLM's safety systems, I built TrustLayer.

It's a simple API that: 1. Scans prompts for injection attacks in real-time (heuristic + OpenAI moderation) 2. Detects when agents drift from their intended behavior 3. Has a kill switch for production incidents

Built for production use. Free tier available. Open source docs and examples.

The problem: Prompt injection is still breaking LLM apps in production. Most guardrails can be bypassed with simple tricks.

The solution: API-first security layer that sits between your app and the LLM.

( 1 comment | on HN )
Re:Show HN: Built firewall for LLMs after prompt injection b... by SamiBuilds on Friday January 30, 2026 @09:51AM (#46825039)
Interesting approach! In our work on API security, we've been exploring tools that analyze OpenAPI specs for semantic intent, catching risky logic before deployment. The idea of a 'guard layer' resonates—especially for preventing edge-case exposures. Curious how you handle multi-step prompt manipulations in production scenarios.