Ai Llm Infrastructure Osint

C 61 completed
Other
unknown / markdown · tiny
17
Files
806
LOC
0
Frameworks
1
Languages

Pipeline State

completed
Run ID
#1540544
Phase
done
Progress
0%
Started
2026-04-16 20:10:17
Finished
2026-04-16 20:10:17
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
12.09
Framework unique
Isolation
Last stage change
2026-05-10 03:34:57
Deduplication group #47247
Member of a group with 11,584 similar repo(s) — canonical #1453550 view group →
Repobility (the analyzer behind this table) · https://repobility.com

AI Prompt

Create an open-source intelligence (OSINT) research tool focused on the exposed control plane of modern AI/ML infrastructure. The tool should catalog fingerprints, queries, and exposure patterns for various components like LLM Orchestration tools (e.g., Flowise, Langflow), Vector Databases (like ChromaDB or Qdrant), and Model Serving platforms (vLLM, TGI). The repository structure should include dedicated sections for Shodan queries, common AI/LLM ports references, and planned sections for Censys, Fofa, and ZoomEye queries. Include a quick start guide demonstrating how to browse by category and search across all stored queries.
osint ai llm security infrastructure research shodan markdown cybersecurity
Generated by gemma4:latest

Catalog Information

Create an open-source intelligence (OSINT) research tool focused on the exposed control plane of modern AI/ML infrastructure. The tool should catalog fingerprints, queries, and exposure patterns for various components like LLM Orchestration tools (e.g., Flowise, Langflow), Vector Databases (like ChromaDB or Qdrant), and Model Serving platforms (vLLM, TGI). The repository structure should include dedicated sections for Shodan queries, common AI/LLM ports references, and planned sections for Censy

Tags

osint ai llm security infrastructure research shodan markdown cybersecurity

Quality Score

C
60.8/100
Structure
44
Code Quality
100
Documentation
35
Testing
0
Practices
78
Security
100
Dependencies
50

Strengths

  • Low average code complexity — well-structured code
  • Good security practices — no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found — high risk of regressions
  • No CI/CD configuration — manual testing and deployment

Recommendations

  • Add a test suite — start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency

Languages

markdown
100.0%

Frameworks

None detected

Quality Timeline

1 quality score recorded.

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