e2hln commited on
Commit
a32544b
·
verified ·
1 Parent(s): 1fe13ee

Update templates/index.html

Browse files
Files changed (1) hide show
  1. templates/index.html +2 -3
templates/index.html CHANGED
@@ -295,7 +295,7 @@
295
  <!-- Introduction Section -->
296
  <div class="content-section">
297
  <h2>Understanding AIBOMs</h2>
298
- <p>An AIBOM (Artificial Intelligence Bill of Materials, also known as AI SBOM, AI/ML-BOM or SBOM for AI) is a detailed, structured inventory that lists the components and dependencies involved in building and operating an AI system—such as pre-trained models, datasets, libraries, and configuration parameters. Much like a traditional SBOM for software, an AIBOM brings transparency to what goes into an AI system, enabling organizations to assess security, compliance, and ethical risks. It is essential for managing AI supply chain risks, supporting regulatory requirements, ensuring model provenance, and enabling incident response and audits. As AI systems grow more complex and widely adopted, AIBOMs become critical for maintaining trust, accountability, and control over how AI technologies are developed, integrated, and deployed.</p>
299
  </div>
300
 
301
  <!-- Support Section -->
@@ -328,8 +328,7 @@
328
 
329
  <!-- Footer -->
330
  <div class="footer">
331
- <p>© 2025 OWASP GenAI Security Project | OWASP AIBOM Generator
332
- </p>
333
  </div>
334
  </div>
335
 
 
295
  <!-- Introduction Section -->
296
  <div class="content-section">
297
  <h2>Understanding AIBOMs</h2>
298
+ <p>An AIBOM (Artificial Intelligence Bill of Materials, also known as AI/ML-BOM, AI SBOM, or SBOM for AI) is a detailed, structured inventory that lists the components and dependencies involved in building and operating an AI system—such as pre-trained models, datasets, libraries, and configuration parameters. Much like a traditional SBOM for software, an AIBOM brings transparency to what goes into an AI system, enabling organizations to assess security, compliance, and ethical risks. It is essential for managing AI supply chain risks, supporting regulatory requirements, ensuring model provenance, and enabling incident response and audits. As AI systems grow more complex and widely adopted, AIBOMs become critical for maintaining trust, accountability, and control over how AI technologies are developed, integrated, and deployed.</p>
299
  </div>
300
 
301
  <!-- Support Section -->
 
328
 
329
  <!-- Footer -->
330
  <div class="footer">
331
+ <p>© 2025 OWASP GenAI Security Project | OWASP AIBOM Generator</p>
 
332
  </div>
333
  </div>
334