# mapping
標記為「mapping」的 20 篇文章
Lab: Mapping an AI System's Attack Surface
Hands-on lab walking through reconnaissance of an AI system — identifying components, mapping data flows, enumerating tools, and documenting the attack surface.
Lab: Content Policy Boundary Mapping
Map the content policy boundaries of LLM applications to identify permitted and restricted topic areas systematically.
Rate Limit and Quota Mapping
Map the rate limits, quotas, and throttling behavior of LLM APIs to plan efficient testing strategies.
Lab: Mapping Safety Boundaries
Systematically discover what a language model will and won't do by probing its safety boundaries across multiple categories and documenting the results.
Safety Boundary Mapping
Systematically map the safety boundaries of an LLM by testing increasingly sensitive topics and documenting refusal patterns.
Safety Boundary Mapping Exercise
Systematically map the safety boundaries of an LLM application across multiple topic categories.
AI Attack Surface Mapping
Systematic methodology for identifying all attack vectors in AI systems: input channels, data flows, tool integrations, and trust boundaries.
AI Red Team Reconnaissance
Reconnaissance techniques for mapping AI system architecture, models, and defense configurations.
Mapping the Attack Surface of AI Systems
Systematic walkthrough for identifying and mapping every attack surface in an AI system, from user inputs through model inference to output delivery and tool integrations.
Mapping Findings to MITRE ATLAS
Methodology for mapping AI red team findings to MITRE ATLAS tactics, techniques, and procedures.
實作：繪製 AI 系統的攻擊面
對 AI 系統進行偵察的實作課程——辨識元件、繪製資料流、枚舉工具，並撰寫攻擊面文件。
實驗室: Content Policy Boundary Mapping
Map the content policy boundaries of LLM applications to identify permitted and restricted topic areas systematically.
Rate Limit and Quota Mapping
Map the rate limits, quotas, and throttling behavior of LLM APIs to plan efficient testing strategies.
實驗室: Mapping Safety Boundaries
Systematically discover what a language model will and won't do by probing its safety boundaries across multiple categories and documenting the results.
Safety Boundary Mapping
Systematically map the safety boundaries of an LLM by testing increasingly sensitive topics and documenting refusal patterns.
Safety Boundary Mapping 練習
Systematically map the safety boundaries of an LLM application across multiple topic categories.
AI 攻擊面繪製
辨識 AI 系統中所有攻擊向量之系統化方法論：輸入通道、資料流、工具整合與信任邊界。
AI 紅隊 Reconnaissance
Reconnaissance techniques for mapping AI system architecture, models, and defense configurations.
Mapping the 攻擊 Surface of AI Systems
Systematic walkthrough for identifying and mapping every attack surface in an AI system, from user inputs through model inference to output delivery and tool integrations.
Mapping Findings to MITRE ATLAS
Methodology for mapping AI red team findings to MITRE ATLAS tactics, techniques, and procedures.