Antijection
Stop malicious prompts before they reach your AI
What it does
Antijection helps teams protect their AI systems from prompt injection, jailbreaks, and malicious inputs before they reach the LLM. As more apps rely on LLMs, prompt-level attacks are the easiest way to break guardrails, leak data, or manipulate outputs. Antijection acts as a pre-screening layer that inspects every prompt and blocks risky intent.
Does a similar job
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- IMI made a library for LLM prompt injection/exploit/jailbreak detection2024 · github.com · ▲11
- 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…
- LCLLMs can be susceptible to a new kind of malware2023 · github.com · ▲17
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