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A practical guide to deploying AI agents safely: input validation, permission scoping, human approval, rate limiting, and rollback strategies.
Destructive Command Guard (dcg) trended on GitHub in July 2026 (Rust, MIT, 2.3k stars) as a sub-millisecond PreToolUse hook that blocks your AI coding agent from running rm -rf, git reset --hard, forc
Alibaba released Qwen3Guard, its first open safety-guardrail model, whose streaming variant classifies an AI response for safety as each token is generated rather than after the fact -- and adds a 'Controversial' tier between Safe and Unsafe that app
Teams deploying AI applications require robust content safety. This guide compares leading AI...
Honesty Theater: Why Disclosure ≠ Reliability in LLM Guardrails When a guardrail says it...
Manual approval gates and legacy modernization paralysis are killing our delivery velocity. When...
AI Fabric Eventhouse MCP Guardrails: Securing Natural-Language KQL Before Real-Time Data...
The guardrail stack teams keep rebuilding — destructive-command guards, anti-slop gates, context hygiene — and the build-vs-buy read.
🛡️ Need implementation, not just insights? Let’s build it securely, strategically, and...
why the increasing capability of ai models leads to them taking more liberties, and why we need robust guardrails to prevent unrecoverable mistakes
Beyond the Vibe: Why "Secure by Default" is the Only Way to Build in 2026 We’ve all been...
Navigating the Agentic AI Guardrails: Why Open Source is the Key to AI in Regulated Industries ![tech news cover](https://www.linuxfoundation.org/hubf...