grimly.ai

What it does

Your AI is one bad prompt away from disaster. grimly.ai defends against prompt injections, jailbreaks, and abuse in real time. Add it to your stack in minutes. Works with any LLM. No agents, no fine-tuning — just security that works.

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  CtrlAIMar 2026 · github.com · ▲104

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  CodokiNov 2025 · codoki.ai · ▲25

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  LLMs can be susceptible to a new kind of malware2023 · github.com · ▲17

  New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.

• FP
  Find 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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  Open-Source Gateway to Stop Tool-Abusing Prompt Injections2025 · archestra.ai · ▲9

  Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

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  CalusJun 2026 · usecalus.com · ▲3

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  Work · 2025 · tapflow.ai

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