
VibeLint - AI Agent Security for Code, Tools, and Workflows
VibeLint 为 AI 代理提供代码检查、权限控制和审批工作流。
@RElharrak39428 · X
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24 projects

VibeLint 为 AI 代理提供代码检查、权限控制和审批工作流。
@RElharrak39428 · X

为GitHub仓库运行安全审计,检测密钥泄露、认证问题和部署漏洞。
@emanueldev4 · X
Building Preflight a simple way to catch issues before your website goes live.

扫描你的应用程序,检测泄露的 API 密钥、开放数据库和身份验证漏洞。
@Nqspq · X
been building a security scanner for vibe-coded apps — it catches leaked API keys, open databases, logins you can bypass. tested it on a repo made for testing scanners. it caught everything — report below free if you want to check yours:

用对抗测试检查LLM端点安全,获取OWASP审计报告。
@aryaan_sheth · X
- LLM security for small teams


ARGUS:为AI代理流程的可观测性平台,检测故障并解释根本原因。
@VaraadDurgaay · X
Solving the prb of observability in ai agents

CanaryHub 实时监控应用和 API,故障时通过 Telegram 即时警报。
u/AgitatedLemon6836 · Reddit
I've got too many sites to monitor at this point I have been working on a bunch of different SAAS ideas at this point, some of them are just parked right now as I have decided to market others or have lost passion for the project. Its hard to check logs in a unified fashion for a bunch of different sites, I have backend's on Fly io, Heroku, Vercel, Hetzner and AWS (for varying reasons, some consulting, some work etc). just wanted like text message updates for things with a summary, like "3

在几分钟内跨设备和浏览器测试应用程序,自动捕获错误。
@vibe_and_go · X

通过正常运行时间检查、值班升级和 AI 根本原因诊断来监控服务器。
@iamjackwiz · X

对你的网络应用和 API 运行真实漏洞测试,用完整证明展示每个安全发现。
@yedil_bek · X
Building RedRun - security testing that proves what it finds. Runs the real exploit + hands you the exact request/response: SQLi, IDOR, SSRF, XSS, JWT + AI prompt-injection. Zero false positives. Free scan → Active engine invite-only - DM for access code

GOSafe:查看旅游目的地的灾害和位置风险
@HappyMonkeyAI · X
GOSafe was another #AI powered #app concept from last week too that aims to help to #travellers stay informed about destinations they are thinking of visiting

由AI驱动的代码审查工具,在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db