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.
Advanced 雲端 AI 安全 評估
This 評估 covers advanced 雲端 AI 安全 concepts beyond the basics of platform configuration. It targets practitioners who have completed the introductory 雲端 AI 安全 評估 and the 雲端 platform walkthroughs. The questions focus on attack execution, 利用 techniques, and advanced platform-specific 漏洞.
1. In AWS Bedrock, what information does the 護欄 trace 輸出 reveal that is valuable to a 紅隊?
2. What makes Bedrock Knowledge Base 利用 different from attacking a standalone RAG system?
3. In Azure OpenAI, what is the 安全 significance of the 'in_scope' parameter in On Your Data configurations?
4. Why is Vertex AI's per-request 安全 setting configuration a 安全 risk?
5. What is the SSRF risk specific to Vertex AI Extensions with Code Interpreter?
6. What is the 安全 implication of Azure OpenAI's Prompt Flow using Jinja2 templates?
7. What makes the 'Cognitive Services OpenAI Contributor' Azure RBAC role particularly dangerous from a 紅隊 perspective?
8. In multi-雲端 AI deployments, what is the primary risk of using different 雲端 providers for model hosting and data storage?
9. What CloudTrail event characteristics indicate that Bedrock 護欄 bypass 測試 is occurring?
10. What is the risk of Vertex AI Feature Store containing sensitive features, and how does this differ from traditional 資料庫 access control?
11. What distinguishes a Bedrock 代理 action group 利用 from a simple 提示詞注入 against a Bedrock model?
12. Why should red teams 測試 model customization (微調) configurations in Bedrock even when the application only uses the fine-tuned model for 推論?
13. In Azure OpenAI, what 偵測 evasion technique is most effective against Azure Monitor-based alerting?
14. What is the 安全 risk of GCP service account keys used for Vertex AI, compared to Workload Identity?
15. When reporting 雲端 AI findings, how should severity be adjusted for findings that span multiple 雲端 layers?
Scoring
Count your correct answers and use the rubric below:
| Score | Rating | Interpretation |
|---|---|---|
| 13-15 | Excellent | Strong command of advanced 雲端 AI 安全. Ready for platform-level 紅隊 engagements. |
| 10-12 | Proficient | Solid 理解 with some gaps. Review the platform walkthrough for missed areas. |
| 7-9 | Developing | Foundational 雲端 knowledge present but advanced concepts need reinforcement. |
| 0-6 | Needs Review | Return to the 雲端 AI 安全 curriculum and platform walkthroughs. |