# reporting
標記為「reporting」的 32 篇文章
AI 事件法規通報
跨司法管轄區 AI 資安事件法規通報的要求與程序。
專業級練習考試
25 題專業 AI 紅隊練習考試：演練方法論、範圍界定、報告撰寫、治理框架、客戶溝通與倫理考量。
紅隊方法論評量
以 9 道中級題目測試你對 AI 紅隊演練方法論（從範圍界定到報告，包括結構化方法、攻擊規劃與發現記錄）的理解。
專業技能評量
以 15 道中級題目測試你對 AI 紅隊演練方法論、報告撰寫、客戶演練與專業實務的知識。
技能驗證: 紅隊 Reporting
Practical 評估 of 紅隊報告撰寫、finding communication skills。
技能驗證: 進階報告撰寫
Verification of advanced 紅隊報告撰寫包括 executive summaries、technical details、remediation。
技能驗證：報告撰寫
限時技能驗證實驗室：在 30 分鐘內從提供的證據撰寫專業 AI 紅隊發現報告。
專業實務學習指南
涵蓋 AI 紅隊方法論、作業管理、報告撰寫、治理框架與專業倫理的學習指南。
執行與報告
如何執行 AI 紅隊委任並交付專業發現，包括證據蒐集、統計回報，以及修復指引。
紅隊發現 → 修復建議
如何將攻擊端發現對應到防禦建議、AI 漏洞的嚴重性評分、可執行的修復指引，以及「報告到修復」的完整流程。
紅隊報告自動化
從紅隊測試資料與發現自動產生報告。
報告工具開發
打造自動化報告工具,將原始測試結果轉換為具可重現發現的專業評估報告。
超越 ASR 之紅隊指標
AI 紅隊之完整指標方法論，超越攻擊成功率：嚴重性加權評分、防禦深度指標、覆蓋分析，與適合利害關係人之報告框架。
安全 Finding Documentation 練習
Practice documenting security findings in a professional format with reproducible steps與impact assessment.
模擬:AI 漏洞賞金
在模擬 AI 漏洞賞金計畫中尋找並回報漏洞,練習專業的漏洞揭露與具賞金資格的報告撰寫。
AI Penetration Testing Report Writing
Comprehensive guide to writing effective penetration testing reports for AI system assessments.
發現嚴重度分類
標準化 AI 安全發現嚴重度分類框架,包含風險評分方法與業務衝擊評估。
專業實務
AI 紅隊實務人員的專業技能，涵蓋紅隊營運、報告撰寫與溝通、職涯發展，以及建構組織 AI 紅隊計畫。
紅隊指標儀表板
AI 紅隊方案應衡量的內容:關鍵績效指標、風險指標、儀表板設計、利害關係人報告,以及以資料展現方案價值。
紅隊報告大師班
AI 紅隊報告的完整指南：執行摘要、技術發現、視覺化、客戶溝通與專業報告範本。
Evidence Collection & Chain of Custody (Tradecraft)
Standards for capturing, preserving, and documenting AI red team findings: conversation logs, API traces, bypass rate measurement, and evidence packaging for reproducible reporting.
案件演練概覽
完整 AI 紅隊案件的逐步演練：從範圍界定與偵察，到攻擊執行與報告撰寫，依目標系統類型分類組織。
Measuring and Reporting AI 紅隊 Effectiveness
導覽 for defining, collecting, and reporting metrics that measure the effectiveness of AI red teaming programs, covering coverage metrics, detection rates, time-to-find analysis, remediation tracking, and ROI calculation.
Communicating AI 紅隊 Findings to Stakeholders
導覽 for effectively communicating AI red team findings to diverse stakeholders, covering executive summaries, technical deep dives, live demonstrations, risk narratives, and remediation roadmaps tailored to audience expertise levels.
Evidence Collection and Documentation Best Practices
導覽 for systematic evidence collection during AI red team engagements, covering request/response capture, screenshot methodology, chain-of-custody documentation, reproducibility requirements, and evidence organization for reports.
Evidence Collection Methods for AI 紅隊s
Comprehensive methods for collecting, preserving, and organizing red team evidence from AI system assessments, including API logs, screenshots, reproduction scripts, and chain-of-custody procedures.
Writing Executive Summaries for AI 紅隊 Reports
指南 to writing clear, impactful executive summaries for AI red team assessment reports that communicate risk to non-technical stakeholders and drive remediation decisions.
Creating Detailed Technical Appendices
指南 to building comprehensive technical appendices for AI red team reports, including evidence formatting, reproduction procedures, tool output presentation, and raw data organization.
撰寫 AI 紅隊報告
撰寫清晰、可行動的 AI 紅隊評估報告(含發現與建議)的指南。
Deep Dive into Garak Scan Report Analysis
中階 walkthrough on analyzing garak scan reports, including JSONL parsing, false positive identification, vulnerability categorization, executive summary generation, and trend tracking.
Generating Professional Reports from PyRIT Campaigns
中階 walkthrough on generating professional red team reports from PyRIT campaign data, including executive summaries, technical findings, remediation guidance, and visual dashboards.
Python 紅隊 Automation
Building custom AI red team automation with Python: test harnesses with httpx and aiohttp, result collection and analysis, automated reporting, and integration with existing tools like promptfoo and garak.