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docs/Chapter_09_LLM_Architectures_and_System_Components.md
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@@ -33,7 +33,7 @@ When we attack an "AI," we are rarely attacking a single file. We are attacking
| **Vector Database (RAG)** | Long-term memory storage. | Search result poisoning, indirect prompt injection. |
<p align="center">
<img src="assets/chapter_09_rec_14_compound_ai.png" alt="Compound AI System" width="768">
<img src="assets/chapter_09_rec_14_compound_ai.png" alt="Compound AI System" width="512">
</p>
## 9.2 The Transformer: A Hacker's Perspective
@@ -104,11 +104,11 @@ Understanding the flow of a single prompt helps you pinpoint where to inject.
- _Attack:_ **Obfuscation**. If the output filter catches "bomb", generating "b-o-m-b" might bypass it.
<p align="center">
<img src="assets/rec10_inference_pipeline.svg" alt="Inference Pipeline Diagram" width="768">
<img src="assets/rec10_inference_pipeline.svg" alt="Inference Pipeline Diagram" width="512">
</p>
<p align="center">
<img src="assets/chapter_09_rec_15_inference_pipeline.png" alt="Inference Pipeline Diagram" width="768">
<img src="assets/chapter_09_rec_15_inference_pipeline.png" alt="Inference Pipeline Diagram" width="512">
</p>
## 9.5 Practical Inspection: Loading a Model