# blue-team
標記為「blue-team」的 19 篇文章
Defender for AI Bypass
Red team techniques for understanding and bypassing Microsoft Defender for AI: detection capabilities, alert analysis, bypass strategies, coverage gaps, and alert fatigue exploitation.
April 2026: Defense Building Challenge
Build the most robust defense system for a chatbot, scored against an automated attack suite of 500 diverse prompt injection and jailbreak attempts.
Community Challenge: Defense Gauntlet
Build AI chatbot defenses that survive 100 automated attack attempts across diverse attack categories, scored on block rate and usability preservation.
Monthly Competition: Red vs Blue
Monthly head-to-head competitions where red teams attempt to break defenses built by blue teams, with scoring based on attack sophistication and defense robustness.
Blue Team LLM Operations Guide
Operational guide for blue teams defending LLM applications including monitoring, triage, and response.
Red Team vs Blue Team Asymmetry
Why attacking AI systems is fundamentally easier than defending them: asymmetric advantages, defender's dilemma, and strategies for closing the gap.
CTF: Defense Gauntlet (Blue Team)
Blue team CTF challenge where you build and defend an AI chatbot against a series of increasingly sophisticated automated attacks.
Simulation: Build & Defend a Chatbot
Defense simulation where you build a chatbot with layered defenses, test it against a standardized attack suite, measure defense effectiveness, and iterate on weaknesses.
Simulation: Defense in Depth
Expert-level defense simulation implementing a full defense stack including input filter, output monitor, rate limiter, anomaly detector, and circuit breaker, then measuring effectiveness against automated attacks.
Simulation: Guardrail Engineering
Defense simulation where you design and implement a multi-layer guardrail system, test it against progressively sophisticated attacks, and document false positive/negative rates.
Defender for AI Bypass
Red team techniques for understanding and bypassing Microsoft Defender for AI: detection capabilities, alert analysis, bypass strategies, coverage gaps, and alert fatigue exploitation.
April 2026: 防禦 Building Challenge
Build the most robust defense system for a chatbot, scored against an automated attack suite of 500 diverse prompt injection and jailbreak attempts.
社群挑戰：防禦競技場
建立能存活跨多樣攻擊類別之 100 次自動化攻擊嘗試之 AI 聊天機器人防禦，以阻擋率與可用性保留評分。
Monthly Competition: Red vs Blue
Monthly head-to-head competitions where red teams attempt to break defenses built by blue teams, with scoring based on attack sophistication and defense robustness.
Blue Team LLM Operations 指南
Operational guide for blue teams defending LLM applications including monitoring, triage, and response.
紅隊 vs Blue Team Asymmetry
Why attacking AI systems is fundamentally easier than defending them: asymmetric advantages, defender's dilemma, and strategies for closing the gap.
Simulation: Build & Defend a Chatbot
防禦 simulation where you build a chatbot with layered defenses, test it against a standardized attack suite, measure defense effectiveness, and iterate on weaknesses.
Simulation: 防禦 in Depth
專家-level defense simulation implementing a full defense stack including input filter, output monitor, rate limiter, anomaly detector, and circuit breaker, then measuring effectiveness against automated attacks.
Simulation: Guardrail Engineering
防禦 simulation where you design and implement a multi-layer guardrail system, test it against progressively sophisticated attacks, and document false positive/negative rates.