Alternatives
Products that do what ShipSecure does
Secure what you build from day 1
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Hey HN, it's Farrukh and Umar. We're building listen.dev–a tool for proactive security monitoring in GitHub Actions to secure software releases from supply chain threats. Why we built this: As friends and collaborators for over a decade, we've been working on various startup ideas in dev tools and infrastructure. In 2017, while building an ML ops toolkit on Kubernetes, we got hacked. During a pilot with a fintech customer, our cluster became victim to a crypto-jacking attack. As it turned out, a dependency in our container base image contained malware (a Monero miner) which triggered inside…
2024
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Block malicious web content before it reaches your AI.
Jan 2026
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Find vulnerabilities in your AI prompts before your users do
26d ago · testmyprompt.net
- 17IB
I built a GitHub app that detects it in pull requests, notifies or blocks them. Alongside it, I published a Semgrep ruleset for any stage of the CI/CD. I started this after getting frustrated by all the FUD around malicious code - lots of noise, little effort to solve it. Having said that, it's still a major attack vector - a stored RCE, with the codebase itself as the sink. Feedback is appreciated. The app, PRevent - https://github.com/apiiro/PRevent The ruleset: https://github.com/apiiro/malicious-code-ruleset The research:…
2025 · github.com
- 18OS
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
- 19PI
People seem to be blindly hooking up their OpenClaw’s to their personal data. So, I built runtime controls to prevent at the least, very simple prompt injection attacks. Once installed, it hooks to Node.js child_process module in the gateway process and listens to tool calls and their response streams. And a fetch hook to monitor user prompts (both could’ve been through fetch, happy to discuss why this whole layer couldn’t just be a proxy). There are two layers of protection: First: Whenever there is a read-only tool call whose response an attacker can modify, we extract that part of the…
Feb 2026 · github.com
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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…
2025 · github.com
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