生产力1 month ago · 1 次试用
Vault Desk — Zero-knowledge encrypted cloud storage
用端到端加密存储和同步文件，对服务器完全隐藏。
@vaultdesk · X
完整作品展
技术栈
9 projects
用端到端加密存储和同步文件，对服务器完全隐藏。
@vaultdesk · X
Secra是检测AI代理的提示注入、角色劫持和数据泄露的安全中间件。
@SecraHQ · X
使用AI增强的安全分析扫描代码和应用漏洞。
u/swifi_ai · Reddit
After 10 years of keeping this idea alive, I finally launched my AI security platform to beta After more than 10 years of keeping this idea alive in one form or another, I finally pushed Swifi live to beta: https://swifi.ai Swifi is an AI-augmented application security platform. The goal: combine traditional security scanning with AI so teams can understand risk across code, vulnerabilities, and production context without stitching together a dozen disconnected tools. Why now? AI change
The Lineup 体育博彩分析工具，包含 +EV 公平价值检查、预测和追踪。
u/sweetnessssss · Reddit
Nine months ago I quit my data science job to build an app. The app is still hungry. Nine months ago I left a comfortable data science job at a travel company to build a sports betting app. Comfortable is and odd word for a job - it means the money arrives on schedule and nobody in your family asks if you're okay. The app is called THE LINEUP ( https://thelineup.pro/ ) -- it does the unromantic parts of betting: comparing prices, working with projections and tracking what happened afterwar
监控 SSL 证书和网站安全，包含自动续期检测、安全头部监控和 DNS 健康检查。
@di_spivak · X
使用硬件认证和OTP保护GitHub拉取请求。
jallmann · HN
> want without a PR process that requires hardware authentication or proof of presence Just curious, what do you use for this? I built OTP Guard [1] a few years ago for exactly this problem, although I haven't seen any alternatives in the space. Does GitHub have something built-in now? The original framing was more "local malware compromising your GitHub account" ... it never occurred to me that the malware could be a LLM. I really should update the page. [1] https://otpguard.com
在攻击者利用前，发现你的 external attack surface 中的风险。
@OGVeilScan · X
Vulnsy是为安全团队提供的渗透测试报告平台，可10倍快速交付客户报告。
@TurvSec · X
为AI应用提供MCP服务器、REST API和行级安全的后端服务平台。
u/bob__io · Reddit
What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation