InferShield – open-source security proxy for LLM inference
LLM-specific threat detection (prompt injection, jailbreaks, exfiltration) that WAFs completely miss.

Another AI security wrapper in a crowded market, but agent-side integration is interesting.
Security teams, CISOs, Enterprise IT
Lakera Guard · PromptArmor · Nightfall
Most enterprises are "shadow-prompting"—employees use personal accounts on Gemini/ChatGPT/Claude, and security teams have zero visibility. We saw the recent reports on malicious extensions harvesting these prompts and decided to build a "defensive" version.
It’s a lightweight Chromium extension for Privent. No heavy proxies or network changes. It categorizes outgoing data and scores risk locally.
We’re keeping it 100% free because we want to see the actual scale of data leakage across different industries. We're looking for 10 teams to run a pilot this week and get a 24-hour visibility report.
Demo: https://cal.com/asilozyildirim/30min Trust: https://trust.privent.ai/
LLM-specific threat detection (prompt injection, jailbreaks, exfiltration) that WAFs completely miss.
Isolated LLM with no tools or memory makes prompt injection hit a dead end.
Regression tests catch cross-domain hallucinations, but prompt-based approach won't scale.
Zero-code LLM firewall; heuristics under 1ms, optional Groq semantic layer.
Drop-in LLM traffic guard with PII redaction and prompt injection detection, one command.
Lifecycle-aware security pipeline, not point tools—shared context from ingress through output.