Dashboard / Repos / Doc Sql Audit

Doc Sql Audit

D 56 completed
Cli Tool
unknown / python · tiny
11
Files
847
LOC
0
Frameworks
5
Languages
OverviewFiles & MetricsGit ActivityCall GraphSecurityReports

Pipeline State

completed
Run ID
#369969
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
23.49
Framework unique
—
Isolation
—
Last stage change
2026-04-16 18:15:42
Deduplication group #47591
Member of a group with 1 similar repo(s) — canonical #65621 view group →
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/

AI Prompt

I need a Python-based tool to audit PostgreSQL databases. Could you build a SQL audit tool that connects to a Postgresql database? It should read configuration details, perhaps from a YAML or TOML file, and then perform various checks on the SQL structure. The goal is to generate a comprehensive audit report based on the database schema.
python postgresql sql audit database tool security
Generated by gemma4:latest

Catalog Information

This project provides a SQL audit tool for Postgresql databases.

Description

The doc-sql-audit project is designed to provide a comprehensive audit of SQL queries executed on Postgresql databases. It leverages the power of Python, NumPy, and Pandas to analyze database activity and identify potential security risks or performance bottlenecks. This tool is intended for database administrators and security professionals who need to monitor and optimize their database's SQL query behavior.

الوصف

يهدف مشروع doc-sql-audit إلى تقديم فحص شامل للطلبات SQL المنفذة على قواعد البيانات Postgresql. يستخدم هذا المشروع قوة لغة Python، NumPy، وPandas لتحليل نشاط قاعدة البيانات وتحديد مخاطر أمنية أو نقاط ضعف في الأداء. يهدف هذا الأداة إلى مسؤولي قواعد البيانات والأفراد المسؤولين عن الأمان الذين يحتاجون إلى مراقبة وتحسين سلوك طلبات SQL لقاعدة بياناتهم.

Novelty

5/10

Tags

sql-audit database-security query-analysis performance-optimization security-risk-detection

Technologies

numpy pandas

Claude Models

claude-opus-4.6

Quality Score

D
56.2/100
Structure
48
Code Quality
100
Documentation
18
Testing
0
Practices
65
Security
92
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Low average code complexity \u2014 well-structured code
  • Good security practices \u2014 no major issues detected

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No LICENSE file \u2014 legal ambiguity for contributors
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

4.1h
Tech Debt (E)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (10)
Want fix-PRs on findings? Install Repobility's GitHub App · github.com/apps/repobility-bot
Unknown
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
58.6%
yaml
25.6%
text
8.0%
json
4.7%
toml
3.2%

Frameworks

None detected

Quality Timeline

1 quality score recorded.

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