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Update 2.0_Threat_Modeling_for_AI_Systems.md

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@@ -33,7 +33,7 @@ It’s important to map threats to a comprehensive AI architecture. (*) As threa
In Stage II of PASTA, we define the architectural scope by aligning it with the Secure AI Framework (SAIF) [12], establishing a structured view of the AI system’s core security-relevant components. SAIF serves as a publicly available model for securing AI systems at scale, offering a practical, adaptable, and business-aligned framework that connects AI system security with broader risk management and operational resilience objectives. Specifically, the SAIF Risk Map [13] serves as a visual guide for navigating AI security and is central to understanding SAIF as a comprehensive security framework. It highlights many risks that may be unfamiliar to developers, such as prompt injection, data poisoning, and rogue actions. By mapping the AI development process, the SAIF Map helps identify where these risks emerge and, critically, where corresponding security controls can be applied. In Fig 1.1. we provide the visual of the SAIF components.
<p align="center">
<img src="/Document/assets/images/AISystemArchitecture.png" alt="Description" width="800"/>
<img src="/Document/images/AISystemArchitecture.png" alt="Description" width="800"/>
</p>
**Fig 1.1 SAIF Architecture Layers & Components**