Sentinel Cve

C 69 completed
Cli Tool
cli / python · tiny
44
Files
9,220
LOC
1
Frameworks
5
Languages

Pipeline State

completed
Run ID
#351507
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
59.54
Framework unique
Isolation
Last stage change
2026-05-10 03:35:10
Deduplication group #58683
Member of a group with 5 similar repo(s) — canonical #22348 view group →
Top concepts (2)
Project DescriptionWeb Backend
Repobility · code-quality intelligence · https://repobility.com

AI Prompt

Create a command-line tool using Python that acts as a CVE explainer. I need it to take a CVE ID as an argument and fetch data from NVD, OSV.dev, and MITRE. The tool should use an AI model, like Claude, to generate a detailed, multi-section vulnerability briefing. It must support different output formats, such as a default 5-section 'security' report, a concise 'executive' summary, or a deep 'engineer' advisory. Additionally, please include options to output the results as JSON or Markdown, and a flag to show verbose details.
python cli cve security ai fastapi nvd osv
Generated by gemma4:latest

Catalog Information

Generate concise, AI‑powered explanations of CVE vulnerabilities via a command‑line interface.

Description

Sentinel‑CVE is a command‑line tool that takes a CVE identifier and returns a clear, actionable briefing in seconds. It leverages an AI model to translate technical vulnerability data into plain language, highlighting impact, affected components, and recommended mitigations. The tool stores recent queries in a lightweight SQLite cache to speed up repeat lookups. Designed for security professionals and developers, it streamlines the process of understanding new CVEs without sifting through long advisories. The integration with a fast API layer allows optional web access for automated workflows.

الوصف

يُعد Sentinel‑CVE أداة سطر أوامر تُستَخدم لتحويل معرف CVE إلى شرح واضح ومُفَصَّل في ثوانٍ معدودة. تعتمد الأداة على نموذج ذكاء اصطناعي لتبسيط بيانات الثغرة التقنية إلى لغة سهلة الفهم، مع إبراز الأثر، والمكونات المتأثرة، وخطوات التخفيف المقترحة. تُخزّن الاستعلامات الأخيرة في قاعدة بيانات SQLite خفيفة الوزن لتسريع عمليات البحث المتكررة. صُممت هذه الأداة للمحترفين في مجال الأمن والمطورين لتسريع فهم الثغرات الجديدة دون الحاجة للبحث في تقارير طويلة. يتيح دمجها مع طبقة API سريعة إمكانية الوصول عبر الويب لتكامل سلس مع سير العمل الآلي. تُعطي الأداة ملخصات سريعة، وتُسهم في تقليل وقت التحليل، وتُحسّن استجابة الفرق الأمنية للتهديدات الجديدة. كما تُوفر واجهة بسيطة ومباشرة تُسهل استخدامها في بيئات التطوير والاختبار.

Novelty

7/10

Tags

vulnerability-analysis cve-explanation ai‑powered-briefings security-awareness command-line

Technologies

anthropic click fastapi rich uvicorn

Claude Models

claude-opus-4.6

Quality Score

C
69.1/100
Structure
75
Code Quality
62
Documentation
65
Testing
60
Practices
66
Security
100
Dependencies
60

Strengths

  • Good test coverage (33% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Containerized deployment (Docker)
  • Properly licensed project

Weaknesses

  • No CI/CD configuration \u2014 manual testing and deployment
  • 676 duplicate lines detected \u2014 consider DRY refactoring
  • 2 'god files' with >500 LOC need decomposition

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment

Security & Health

5.6h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/
MIT
License
3.7%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
74.7%
markdown
23.4%
yaml
1.0%
json
0.6%
toml
0.3%

Frameworks

FastAPI

Concepts (2)

Open data · scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Repobility — same analyzer, your code, free for public repos · /scan/
auto_descriptionProject Description"Does this CVE even affect me?" — answered in seconds, not hours.80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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