auditview

v0.1.2 suspicious
4.0
Medium Risk

Code review/audit tool

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network, shell, obfuscation, and credential handling. However, the metadata quality and maintainer activity are questionable, raising concerns about its legitimacy and long-term support.

  • Low maintainer activity
  • Poor metadata quality
Per-check LLM notes
  • Network: No network calls detected, which is normal and expected.
  • Shell: The shell execution is likely for building the user interface and does not indicate malicious activity.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

  • Test runner config found: pyproject.toml
  • 2 test file(s) detected (e.g. test_reconciler_fuzz.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2298 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 13 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ("Building UI with pnpm") subprocess.run(["pnpm", "build"], cwd=UI_DIR, check=True) if not (UI_D
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with auditview 
Develop a code quality assurance tool called 'AuditBuddy' using the Python package 'auditview'. This tool will streamline the process of auditing and reviewing code repositories to ensure they meet specific coding standards and best practices. The application should have the following functionalities:

1. **Repository Connection**: Users should be able to connect their Git repositories (GitHub, GitLab, Bitbucket) to AuditBuddy.
2. **Configuration Management**: Allow users to define custom coding standards and rulesets based on common frameworks like PEP8, SonarQube, or custom rules.
3. **Code Auditing**: Utilize 'auditview' to perform automated code reviews and audits against the connected repositories, highlighting any discrepancies or violations of the defined standards.
4. **Report Generation**: Generate comprehensive reports summarizing the audit results, including details such as the number of violations, types of issues found, and recommendations for improvements.
5. **Integration with CI/CD Pipelines**: Provide integration capabilities to automatically run audits as part of continuous integration and delivery pipelines.
6. **User Interface**: Develop a user-friendly web interface using Flask or Django to manage configurations, view audit results, and interact with the application.
7. **Notifications**: Implement email notifications or Slack messages to inform users about the completion of audits and significant findings.

The 'auditview' package will be the backbone of the auditing functionality, enabling deep analysis of code quality and adherence to specified guidelines. Your task is to design and implement 'AuditBuddy', ensuring it is robust, scalable, and easy to use for developers and teams looking to enhance their code quality practices.

💬 Discussion Feed

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