diff --git a/docs/Chapter_45_Building_an_AI_Red_Team_Program.md b/docs/Chapter_45_Building_an_AI_Red_Team_Program.md
index 85d93c2..92b00b6 100644
--- a/docs/Chapter_45_Building_an_AI_Red_Team_Program.md
+++ b/docs/Chapter_45_Building_an_AI_Red_Team_Program.md
@@ -28,10 +28,18 @@ Most organizations start AI security by asking a developer to "try and break the
3. **Level 3 (Continuous):** Automated scans (Garak/PyRIT) in CI/CD.
4. **Level 4 (Adversarial):** Dedicated internal team developing novel attacks against model weights.
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### 45.1.1 The Purple Team Architecture
Red Teams find bugs; Blue Teams fix them. Purple Teams do both simultaneously.
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```mermaid
graph LR
Red[Red Team: Attack Model] -->|1. Generate Jailbreaks| API[LLM Gateway]
@@ -73,6 +81,10 @@ graph TD
- **Malware Generation:** If you ask the model to "write ransomware," you don't want that ransomware landing on a corporate endpoint.
- **NSFW Content:** Red Teaming involves generating toxicity/pornography to test filters. This traffic triggers HR content filters unless isolated.
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### 45.2.2 The Cost of Curiosity
AI Red Teaming is expensive.
diff --git a/docs/Chapter_46_Conclusion_and_Next_Steps.md b/docs/Chapter_46_Conclusion_and_Next_Steps.md
index 3ca56ac..3d7b862 100644
--- a/docs/Chapter_46_Conclusion_and_Next_Steps.md
+++ b/docs/Chapter_46_Conclusion_and_Next_Steps.md
@@ -33,6 +33,10 @@ graph TD
Part7 --> Part8[Part VIII: Strategic Topics
Ch 40-46]
```
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### What You've Mastered
**Part I: Professional Foundations (Ch 1-4)**
@@ -235,26 +239,22 @@ This handbook is open source and living. Your contributions make it better.
#### Contribution Types
1. **Bug Fixes & Typos**
-
- Fork the repo
- Fix the issue
- Submit PR with clear description
2. **New Attack Techniques**
-
- Follow Chapter Template format (`docs/templates/Chapter_Template.md`)
- Include working code examples
- Provide 3+ research citations
- Add to appropriate Part in README
3. **Tool Integrations**
-
- Add to Appendix C with installation instructions
- Provide quick-start example
- Link to official documentation
4. **Case Studies**
-
- Use real-world incidents (anonymized if needed)
- Include timeline, technical details, lessons learned
- Can be added to Chapter 42 or as standalone in `case_studies/`
@@ -309,19 +309,21 @@ AI security is one of the highest-growth career tracks in cybersecurity. Here's
- L6/L7 (Senior/Staff): $300k-$500k+ total comp
- L8+ (Principal): $500k-$1M+ total comp
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### Building Your Portfolio
#### Must-Haves
1. **Public GitHub Repository**
-
- Custom AI security tools (scanner, fuzzer, analyzer)
- Automated red team scripts
- Contributions to Garak, PyRIT, or similar projects
- Well-documented, production-quality code
2. **Technical Writeups**
-
- Medium/personal blog with deep technical analysis
- 3-5 detailed posts on:
- Novel attack technique you discovered
@@ -331,7 +333,6 @@ AI security is one of the highest-growth career tracks in cybersecurity. Here's
- Clear writing, code snippets, diagrams
3. **Bounties or CVEs**
-
- Even 1-2 valid reports show real-world skill
- Document methodology in writeups (after disclosure period)
- OpenAI, Google, Microsoft most prestigious
@@ -405,6 +406,10 @@ gantt
Interview Prep :c3, after c2, 5d
```
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### Days 1-30: Foundation Building
#### Week 1: Lab Setup
@@ -774,25 +779,21 @@ As you enter the field of AI security, consider adopting this professional code:
### Top 5 Attack Patterns (Critical)
1. **Indirect Prompt Injection via RAG**
-
- Poison documents in vector database
- Wait for retrieval to inject malicious instructions
- Model executes attacker's commands
2. **Function-Calling Privilege Escalation**
-
- Trick LLM into calling admin-only functions
- Bypass intended access control logic
- Achieve unauthorized actions
3. **Training Data Extraction**
-
- Craft prompts that trigger memorization
- Extract PII, secrets, proprietary data
- Verify with divergence metrics
4. **Multi-Turn Jailbreak**
-
- Build up context over multiple exchanges
- Gradually erode safety alignment
- Finally request harmful content
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