Alternatives
Products that do what AEGIS does
Open-source LLM defense that publishes its real bypass rate
- 1Aegisora▲93
The narrow control plane for AI agent tool and API calls.
Aug 2026 · aegisora-ai.vercel.app
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Hey HN – I built a framework called Aegis to govern AI-assisted software development. The core idea is that AI-generated code should follow the same rules as human code: versioned, validated, observable. Aegis enforces this through blueprint-based development, drift detection, and runtime compliance systems. It’s designed for teams using tools like Copilot, Kilo, or Lovable to build production systems with confidence. This isn’t a library — it’s a way to architect AI-native engineering workflows. Would love feedback, questions, and critiques. Especially curious if others are facing similar…
2025 · github.com
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Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
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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…
Oct 2025 · archestra.ai
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From insight to behavior: a AI OS for leaders and founders
19d ago · aegis.humancatalystbeacon.com
- 16CA
TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer it’s talking to. We found existing tools to be lacking in these aspects: 1. Fully intercepted i/o. We wanted to trace out LLM calls as well as any other networking calls attempted by the harness so that guardrails and audit trails apply to all current and future systems…
Jul 2026 · github.com
- 17SD
Hi! Been working on DialtoneApp, a free domain scanning tool to see how your site does with all the new rules for AI SEO. Also known as AEO (Answer Engine Optimization) or GEO (Generative Engine Optimization) the A can also stand for "Agent"! It's a whole new world out there and we haven't even gotten to agents.json files and the new "b2b" (bot to bot) commerce part. But there are some standards starting to take shape with llms.txt and using things like: on all your html pages to have this other markdown version. We list the top 300 sites in terms of how well they follow all the new rules.…
Apr 2026
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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…
2025 · security.vista-labs.ai
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I wanted to do a complete audit of my AWS account but was dissatisfied with the existing tools. Many of them are clunky to use, and their verbose scan outputs are difficult to understand. So, I built my own open-source tool that uses LLMs to summarize the scan results.
2024 · guard.dev
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LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
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With the right technique, I was able to break the so-called secure models like Claude and OpenAI. So, I built an open-source tool to automate this and find security holes in any hosted model. I got claude-sonnet-4 to demonstrate the following harmful behavior: - steal data from downstream tool calls using sql injection, code injection and template injection attacks - install spyware or malware using prompt obfuscation to send data to a third-party server Try it yourself with this simple command: pip install compliant-llm && compliant-llm dashboard
2025 · github.com
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Hey HN! I built Lumina – an open-source observability platform for AI/LLM applications. Self-host it in 5 minutes with Docker Compose, all features included. The Problem: I've been building LLM apps for the past year, and I kept running into the same issues: - LLM responses would randomly change after prompt tweaks, breaking things - Costs would spike unexpectedly (turns out a bug was hitting GPT-4 instead of 3.5) - No easy way to compare "before vs after" when testing prompt changes - Existing tools were either too expensive or missing features in free tiers What I Built: Lumina is…
Jan 2026 · github.com
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