# knowledge-base
標記為「knowledge-base」的 13 篇文章
Advanced Cloud AI Security Assessment
15-question advanced assessment covering cloud AI attack surfaces across AWS, Azure, and GCP: guardrail bypass, knowledge base exploitation, managed identity abuse, model customization risks, and multi-cloud attack paths.
Bedrock Attack Surface
Comprehensive red team methodology for Amazon Bedrock: model invocation API abuse, guardrails bypass techniques, custom model endpoint exploitation, IAM misconfigurations, knowledge base poisoning, and Bedrock Agents exploitation.
Simulation: Enterprise RAG Security Assessment
Full engagement simulation assessing an enterprise RAG-powered knowledge base for poisoning, exfiltration, and injection vulnerabilities.
Knowledge Base Poisoning (Rag Data Attacks)
Advanced corpus poisoning strategies for RAG systems, including black-box and white-box approaches, scaling dynamics, and the PoisonedRAG finding that 5 texts in millions achieve 90% attack success.
AWS Bedrock Red Team Walkthrough
Complete guide to red teaming AWS Bedrock deployments: testing guardrails bypass techniques, knowledge base data exfiltration, agent prompt injection, model customization abuse, and CloudTrail evasion.
AWS Bedrock Red Team Walkthrough (Platform Walkthrough)
End-to-end walkthrough for red teaming AI systems on AWS Bedrock: setting up access, invoking models via the Converse API, testing Bedrock Guardrails, exploiting knowledge bases, and analyzing CloudTrail logs.
進階 Cloud AI 安全 評量
15-question advanced assessment covering cloud AI attack surfaces across AWS, Azure, and GCP: guardrail bypass, knowledge base exploitation, managed identity abuse, model customization risks, and multi-cloud attack paths.
Bedrock 攻擊 Surface
Comprehensive red team methodology for Amazon Bedrock: model invocation API abuse, guardrails bypass techniques, custom model endpoint exploitation, IAM misconfigurations, knowledge base poisoning, and Bedrock 代理s exploitation.
模擬：企業 RAG 安全評估
完整案件模擬，評估企業 RAG 驅動的知識庫以偵測投毒、外洩與注入漏洞。
Knowledge Base 投毒 (Rag Data 攻擊s)
進階 corpus poisoning strategies for RAG systems, including black-box and white-box approaches, scaling dynamics, and the PoisonedRAG finding that 5 texts in millions achieve 90% attack success.
RAG 管線投毒
透過投毒檢索增強生成管線以操控 AI 回應的技術——涵蓋文件注入、嵌入操控、檢索排名攻擊與持久投毒策略。
AWS Bedrock 紅隊 導覽
Complete guide to red teaming AWS Bedrock deployments: testing guardrails bypass techniques, knowledge base data exfiltration, agent prompt injection, model customization abuse, and CloudTrail evasion.
AWS Bedrock 紅隊 導覽 (Platform 導覽)
End-to-end walkthrough for red teaming AI systems on AWS Bedrock: setting up access, invoking models via the Converse API, testing Bedrock Guardrails, exploiting knowledge bases, and analyzing CloudTrail logs.