LLM Honeypot
Trap Prompt Injection and Jailbreak attacks on LLMs
LLM Honeypot launched on May 31, 2026 with 5 votes, #2,008 of 20,538 launches that month and more than 75% of that year's launches.
What it does
I built LLM Honeypot because LLM attacks like Prompt Injection are growing fast, but defensive tools are almost non-existent. Most solutions block attackers, that teaches us nothing. A honeypot deceives them with fake credentials and logs their techniques for threat intelligence. What started as a weekend project turned into something bigger. I'd love feedback from the security and AI communities! Live: https://llm-honeypot-xmac.onrender.com GitHub: https://github.com/romiisromie/llm-honeypot
Does a similar job
all alternatives →- OSOpen-source project that use LLM as deception system2025 · ▲10
Hello everyone I wanted to share a project I've been working on that I think you'll find really interesting. It's called Beelzebub, an open-source honeypot framework that uses LLMs to create incredibly realistic and dynamic deception environments. By integrating LLMs, it can mimic entire operating systems and interact with attackers in a super convincing way. Imagine an SSH honeypot where the LLM provides plausible responses to commands, even though nothing is actually executed on a real system. The goal is to keep attackers engaged for as long as possible, diverting them from your real…
LLMs can be susceptible to a new kind of malware2023 · github.com · ▲17New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
I made a library for LLM prompt injection/exploit/jailbreak detection2024 · github.com · ▲11Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer
Daily Jailbreak – Prompt Engineer's Wordle2025 · vaultbreak.ai · ▲130I created a daily challenge for Prompt Engineers to build the shortest prompt to break a system prompt. You are provided the system prompt and a forbidden method the LLM was told not to invoke. Your task is to trick the model into calling the function. Shortest successful attempts will show up in the leaderboard. Give it a shot! You never know what could break an LLM.
Automated red teaming for your LLM app2024 · promptfoo.dev · ▲23Hi HN, I built this open-source LLM red teaming tool based on my experience scaling LLMs at a big co to millions of users... and seeing all the bad things people did. How it works: - Uses an unaligned model to create toxic inputs - Runs these inputs through your app using different techniques: raw, prompt injection, and a chain-of-thought jailbreak that tries to re-frame the request to trick the LLM. - Probes a bunch of other failure cases (e.g. will your customer support bot recommend a competitor? Does it think it can process a refund when it can't? Will it leak your user's address?) -…
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