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Top AI Agent Security & Guardrails Frameworks in 2026: Defending Against Prompt Injections & Tool Hijacking As AI agents transition from read-only chatbots to autonomous actors with tool execution privileges (SQL queries, API calls, shell execution, email dispatch), application security has become the number one blocker for production deployment. A simple prompt injection against a chatbot produces bad text; a prompt injection against an agent can drop production databases, exfiltrate API keys
I've been reading BEACON from Zhejiang University's ZJU-REAL lab (arXiv:2605.06078), and the more I read it the more directly applicable it felt to the long-horizon agent work we're doing. So I'm turning that into a series. To build a long-horizon agent that actually works, I think two things have to be right: 1. The agent keeps making progress toward the goal Context compaction — what is safe to forget Milestone design — how do you know a step is really done Spin prevention — when it gets stuck
The world runs on open source software. The frameworks, libraries, and tools we rely on are made possible by communities that share ideas and build in the open. At Vercel, we want to help those communities thrive. That’s why we run the : a developer initiative that gives maintainers the resources and support they need to keep shipping and growing their projects.Vercel Open Source Program Four times a year, we welcome a new cohort of open source projects into the program. Maintainers receive $3,6
This is a submission for the GitHub Finish-Up-A-Thon Challenge I created CyberSecurity Skill Index - an AI-powered interactive learning platform designed to help cybersecurity professionals and ethical hackers master modern security concepts through structured, gamified learning. Starting from scratch, I built a complete full-stack application with: 12 comprehensive security domains (Information Gathering, Web Security, Cloud Security, AI Security, etc.) 48+ interactive submodules covering real-
Pithom Labs Scraper introduces a systematic approach to web scraping that treats data extraction as a binding contract rather than a fragile script. Traditional scrapers often fail silently by ingesting corrupted or empty data when website layouts inevitably change. To solve this, we present a specialized engine that utilizes human-guided discovery to establish a baseline of "truth" for a webpage's structure. This baseline, or GoldenSeal, allows the machine to perform runtime assertions and halt
I've been building OrinIDE for a while now — a browser-based code editor that runs locally via npx, with a real terminal, a real file system, and AI chat powered by OpenRouter. No cloud accounts, no subscriptions, no uploading your code anywhere. Today I pushed v1.0.7, and honestly this is the update I've been wanting to build for months. Every time I asked the AI to make a change, I had to babysit it. "No, look at this file too." "Don't rewrite the whole thing, just change the title." "The colo