🛡️

Security & Guardrails

AI safety evaluation, red-teaming, LLM guardrails, vulnerability scanning, and compliance audit tools

62 projects

(24 / 62)

Related Articles

Agent 评估LLM 评测自动化测试

Agent Evaluation and Testing: From Vibe Checks to End-to-End Pipelines

Most teams evaluate agents by checking a few examples. Real evaluation needs layered metrics, non-rotting datasets, and judges that push back. This article provides runnable code patterns and a practical decision framework.

security-guardrailsred-teamprompt-injection

AI Agent Guardrails and Red Teaming in Practice: From Rule Engines to Adversarial Evaluation

Five-layer defense plus red-team loop, built on five open-source projects you can copy.

AI Agent安全Prompt Injection

AI Agent Security in Practice: From Prompt Injection to Defense in Depth

A systematic walkthrough of three major attack surfaces in AI agents, with practical code examples for prompt injection defense, tool permission scoping, and output filtering.

AI 编程Coding AgentCLI

AI Coding Agents Deep Dive: Architecture Trade-offs from CLI to IDE-Integrated

A deep architectural comparison of seven open-source coding agents across three paradigms — CLI-first, IDE-integrated, and fully autonomous — examining context management, tool access, and autonomy levels to help you pick the right tool for each development scenario.

AI Agent沙箱代码执行

Sandboxing AI Agents: Isolation Strategies for Safe Code Execution

Comparing container, WebAssembly, and process-level isolation approaches, with practical code for safely executing agent-generated code.

llm-gatewaymodel-routingcost-optimization

LLM Routing and Multi-Model Gateways in Practice: A Production-Grade Multi-Model Architecture

Four LLM gateways compared, with production patterns for fallback, smart routing, cost observability, and scheduling.