cisco-ai-defense

cisco-ai-defense / aibom

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AI Bill of Materials through source code scanning

33
3
100% credibility
Found Feb 17, 2026 at 20 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

AI BOM scans Python code and container images to create an inventory of AI components including models, agents, tools, and prompts.

How It Works

1
🔍 Discover AI BOM

You hear about a helpful tool that scans your code to list all the AI building blocks like models and tools inside.

2
📥 Install easily

Add the scanner to your computer with a quick one-line setup so it's ready to use.

3
📚 Get AI knowledge list

Download the latest directory of known AI parts so the tool recognizes everything accurately.

4
🚀 Scan your project

Point the tool at your code folder or app package and watch it uncover hidden AI models, prompts, agents, and connections.

5
📊 View your inventory

Open the colorful report or interactive viewer to browse the full list of AI components found.

✅ AI map complete

Celebrate having a clear, shareable bill of materials showing exactly what AI powers your project.

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AI-Generated Review

What is aibom?

Aibom is a Python CLI tool that scans Python codebases and Docker containers to generate an AI Bill of Materials (BOM), inventorying models, agents, tools, prompts, and frameworks. It solves the bill materials meaning problem for AI apps by statically parsing code for fully qualified symbols, matching them against a curated DuckDB catalog, and outputting structured reports in JSON, plaintext, or via a FastAPI server. Users get workflow context, derived relationships like agent-to-tool links, and optional LLM enrichment for model names—all in commands like `cisco-aibom analyze myapp --output json`.

Why is it gaining traction?

Unlike generic bill ocr github scanners or basic dependency tools, aibom focuses on AI-specific components with container support (pulls and extracts /app or site-packages), call-graph workflows, and relationships that reveal how agents use LLMs or tools. The hook is its zero-config install via uv, rich CLI summaries, and POST to Cisco AI Defense—perfect for quick audits without setup hassle. Among aibom tools, it stands out for handling real-world bill materials format needs like line numbers and model extraction.

Who should use this?

Security engineers assessing AI supply chain risks in Python apps, compliance teams generating bill materials template excel exports for audits, or platform devs tracking aipom ai components across microservices and containers. Ideal for teams evolving aipom evolution-style agentic codebases needing visibility into hidden LLMs or tools.

Verdict

Try it for lightweight AI BOM generation—solid docs and CLI make the 18 stars and 1.0% credibility score forgivable for an early Cisco project. Maturity is low (limited testing scope), but it's production-ready for Python scans if you grab the DuckDB catalog from releases.

(198 words)

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