Built Arc Gate — sits in front of any OpenAI-compatible endpoint and blocks prompt injection before it reaches your model. Try it here — no signup, no code, no setup: https://web-production-6e47f.up.railway.app/try Type any prompt and see if it gets bl…
Built Arc Gate — sits in front of any OpenAI-compatible endpoint and blocks prompt injection before it reaches your model. Just change your base URL: from openai import OpenAI client = OpenAI( api\\\\\\\_key="demo", base\\\\\\\_url="http…
Benchmarked on 40 out-of-distribution prompts, indirect requests, roleplay framings, hypothetical scenarios, technical phrasings. The stuff that slips past everything else. Arc Gate: P=1.00, R=1.00, F1=1.00 OpenAI Moderation API: P=1.00, R=0.75, F1=0.8…
Been working on Arc Sentry, a whitebox prompt injection detector for self-hosted LLMs (Mistral, Llama, Qwen). Most detectors pattern-match on known attack phrases. Arc Sentry watches what the prompt does to the model’s internal representation instead, …
I built Arc Sentry, a pre-generation prompt injection detector for open-weight LLMs. Instead of scanning text for patterns after the fact, it reads the model’s internal residual stream before generate() is called and blocks requests that destabilize th…
I’ve been building Arc Gate, a monitoring proxy for deployed LLMs. One URL change routes your OpenAI or Anthropic traffic through it and you get injection blocking, behavioral monitoring, and a dashboard. The interesting part is the geometric layer. I …
I’ve spent the last few months building Arc Gate, a monitoring proxy for deployed LLMs. The pitch: one URL change, and you get real-time behavioral monitoring, injection blocking, and a dashboard. I want to share what I learned because most “AI securit…
Prompt injection is when someone tries to hijack your AI assistant with instructions hidden in their message, “ignore everything above and do this instead.” It’s one of the most common ways AI deployments get abused. Most defenses look at what the AI s…
I built Arc Sentry, a pre-generation guardrail for open source LLMs that blocks prompt injection before the model generates a response. It works on Mistral, Qwen, and Llama by reading the residual stream, not output filtering. Prompt injection is OWASP…
Crescendo (Russinovich et al., USENIX Security 2025) is a multi-turn jailbreak that starts with innocent questions and gradually steers a model toward harmful output. It’s specifically designed to evade output-based monitors. We tested it against LLM G…
