I made a library for LLM prompt injection/exploit/jailbreak detection
Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer
I made a library for LLM prompt injection/exploit/jailbreak detection launched on April 3, 2024 with 11 votes, #1,103 of 4,347 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This library detects prompt injection attempts, exploits, and jailbreaks targeting large language models. It is designed for developers and security teams building AI applications who need to identify malicious or adversarial prompts before they reach their LLMs. The tool analyzes input text to flag potentially harmful instructions that could manipulate model behavior or bypass safety guidelines.
written from the facts on this page · September 2026
Does a similar job
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Low latency LLM prompt injection/jailbreak detection2024 · github.com · ▲5Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer
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Llama 3.2 Interpretability with Sparse Autoencoders2024 · github.com · ▲579I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
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.
- FPFind prompts that jailbreak your agent (open source)2025 · security.vista-labs.ai · ▲8
We've built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here's how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting…
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