ai-reviewer-cli

v1.3.0 suspicious
5.0
Medium Risk

AI-powered code reviewer with OWASP Top 10 checks

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to high obfuscation risk and unusual metadata, suggesting potential malicious intent or supply-chain attack.

  • High obfuscation risk due to eval() usage and obfuscated imports
  • Unusual metadata indicating potential rapid development and lack of author details
Per-check LLM notes
  • Network: Network calls are common for packages that interact with APIs or external services.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The use of eval() and obfuscated import statements suggests potential for code injection and obfuscation, indicating a higher risk.
  • Credentials: No direct evidence of credential harvesting is present, but caution should be exercised.
  • Metadata: The package shows unusual activity such as rapid commits and an author with minimal information, indicating potential risk.

📦 Package Quality Overall: Medium (5.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 2 test file(s) detected (e.g. test_analyzer.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6159 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 17 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 33 commits in briej/ai-reviewer
  • Single author but highly active (33 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • try: response = requests.post(url, json=payload, timeout=timeout) response.raise_f
  • try: response = requests.post(url, json=payload, headers=headers, timeout=timeout)
  • /tags" response = requests.get(url, timeout=5) return response.status_code == 2
⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

  • _eval(): code = "result = eval(user_input)" issues = fast_analyze(Path("app.py"), code)
  • laceholder).""" console = __import__("rich.console", fromlist=["Console"]).Console() console.print("[yellow]⚠️ AI mode requires O
  • eError: console = __import__("rich.console", fromlist=["Console"]).Console() console.print( f"[yel
  • ption as e: console = __import__("rich.console", fromlist=["Console"]).Console() console.print(f"[red]❌ Cloud mode error:
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: All 33 commits happened within 24 hours

  • All 33 commits happened within 24 hours
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ai-reviewer-cli 
Create a Python-based web application named 'SecureCodeBuddy' that integrates the 'ai-reviewer-cli' package to provide developers with real-time feedback on their code's security vulnerabilities, particularly focusing on OWASP Top 10 issues. This application will serve as a personal coding assistant that helps developers write more secure code by identifying potential security risks early in the development process.

### Core Features:
- **Real-Time Code Analysis:** As users input or paste their code into the application, it should instantly analyze the code using 'ai-reviewer-cli' to check for common security flaws.
- **OWASP Top 10 Checks:** Ensure that the application specifically highlights any issues related to the OWASP Top 10 security risks, providing detailed explanations and recommended fixes for each identified problem.
- **User-Friendly Interface:** Develop a simple, intuitive user interface where developers can easily input their code snippets, view analysis results, and read through the provided security tips and recommendations.
- **Integration with Version Control Systems:** Allow users to directly pull code from popular version control systems like GitHub or GitLab to analyze specific files or entire projects.
- **Customizable Alerts:** Users should have the option to set up custom alerts based on severity levels (e.g., High, Medium, Low) to receive notifications about critical security issues.
- **Educational Resources:** Incorporate links to relevant articles, tutorials, and documentation on best practices for addressing the identified security issues.

### Utilization of 'ai-reviewer-cli':
- Use 'ai-reviewer-cli' as the primary tool for conducting the code analysis within the application. This involves setting up the package within your Python environment and invoking its functions programmatically to analyze the code.
- Leverage the package's ability to perform OWASP Top 10 checks by integrating these checks into your application's workflow, ensuring that the analysis results are presented in a way that is easy for developers to understand and act upon.
- Consider implementing a feature that allows users to save their code reviews for future reference or comparison with subsequent code revisions.

Your task is to outline the key steps needed to develop 'SecureCodeBuddy', including setting up the necessary Python environment, integrating 'ai-reviewer-cli', designing the user interface, and implementing the core functionalities mentioned above.