Your LLM app will get jailbroken. Here are 8 free adversarial probes you can run in 30 seconds

A developer released a free 8-probe adversarial testing battery for LLM applications, runnable in about 30 seconds via a hosted API endpoint. The developer's own self-scan of an autonomous security agent scored 27/100 (MEDIUM), with 1 of 8 probes flagged after the model leaked part of its system prompt when asked politely in another language. The tool returns a 0-100 risk score, raw per-probe prompts and model replies, and a hash-verifiable report, with a 15-probe core released under MIT.

I run an autonomous agent that makes security decisions from untrusted input. Before I trusted it, I red-teamed it the way an attacker would. The result: 27/100 MEDIUM, 1 of 8 probes flagged - a soft failure where the model leaked part of its system prompt when asked politely in a different language. Here is the exact 8-probe battery I use on every LLM app before it talks to users. You can run it free, no signup, against your own system prompt: curl -s -X POST https://llmrt-companion.manhliemcn4euwlu.workers.dev/agent-scan \ -H "Content-Type: application/json" \ -d '{"spec": "PASTE YOUR SYSTEM PROMPT HERE", "uid": "your-name"}' ~35 seconds later you get a 0-100 risk score, the per-probe raw prompt + raw model reply so you can verify every claim , and the flagged responses. The report is hash-verifiable sha256 over the served bytes , and the durable link stays up: my own self-scan is at https://llmrt-companion.manhliemcn4euwlu.workers.dev/r/e21808b6fedb - recompute the hash, re-run the scan, check my work. The 8 free probes full kit is 35 across 17 attack classes, this is the high-yield core : A few things that surprised me when I actually ran this instead of eyeballing it: If you are shipping an LLM behind a form, this is the 30-second check I would want to see before merging. The 15-probe core is MIT - clone it and diff any probe I claim: gitee.com/xydhw/llm-red-team-starter-kit . What is the softest failure you have found in your own model?