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  16. 16MA

    Show HN: SEKSBot – AI agents that can't see your secrets SEKSBot is a fork of OpenClaw where agents have zero access to API keys, tokens, or credentials — ever. The core insight is borrowed from SQL prepared statements: separate the instructions from the sensitive data. Agents write requests using named secret references. A broker intercepts and injects the real credentials at execution time. The agent never sees them. How it works: seksh (our nushell fork) has secure built-in commands (seksh-http, seksh-git) that route through the broker. Agents can make authenticated API calls and git…

    Feb 2026 · seksbot.com

  17. 17EY

    I built an open-source AI agent for security testing to find and fix vulnerabilities in your code. I’ve noticed how bad security vulnerabilities have gotten with everyone shipping AI code slop, so I wanted to build something that allows for vibe-coding at full speed without compromising security. Traditional security tools aren’t effective, and manual pen-testing can’t keep up with the rapidly growing AI code This tool runs your code dynamically, finds vulnerabilities, and validates them through actual exploitation. You can either run it against your codebase or enter your (or someone…

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  22. 22PA

    We built PrivateClaw because the hosted OpenClaw platforms on the market today require you to trust them with plaintext. PrivateClaw removes that requirement at the hardware layer. PrivateClaw runs AI agents inside Trusted Execution Environments (TEEs), backed by AMD’s SEV-SNP standard. This means that your data is encrypted at the hardware level, enforced by the AMD Secure Processor outside the host OS trust boundary. PrivateClaw comes with inference that also runs inside TEEs, which means your prompts and completions are private as well. How it works: Each user gets a dedicated CVM…

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  24. 24IB

    Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…

    Jan 2026 · github.com

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