azpytools

v1.1.26 suspicious
6.0
Medium Risk

Tools for Python development

πŸ€– AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high risks associated with network calls and obfuscation techniques, suggesting potential unauthorized data transmission and attempts to hide malicious activities.

  • High network risk due to potential secret handling
  • High obfuscation risk through custom base64 decoding and encryption
Per-check LLM notes
  • Network: The presence of network calls with potential secret handling suggests possible unauthorized data transmission.
  • Shell: No shell execution patterns detected.
  • Obfuscation: The presence of custom base64 decoding and encryption suggests an attempt to obfuscate code, which could be used for malicious purposes.
  • Credentials: No clear patterns of credential harvesting detected, but the use of encryption libraries might mask such activities.
  • Metadata: The package shows some signs of low maintenance and effort, but there are no clear indicators of malicious intent.

πŸ“¦ Package Quality Overall: Low (2.0/10)

β—‹ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
β—‹ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
β—‹ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β—ˆ Medium Type Annotations 5.0

Partial type annotation coverage

  • 53 type-annotated function signatures detected in source
β—‹ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked β€” contributor count unavailable

πŸ”¬ Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • ECRET_KEY} return str(requests.post(url, params=params).json().get("access_token")) def sen
  • None: self.session = requests.Session() self.__url = url self.__headers = header
  • aders) # response = requests.get(self.__url, headers=self.__headers) return response
  • None: self.session = requests.Session() self.session.headers.update(self.DEFAULT_HEADERS)
  • = 5): self.session = requests.Session() self.session.headers.update(self.DEFAULT_HEADERS)
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • e64(_string): return base64.b64decode(_string).decode() # MD5εŠ ε―†(不可逆) """ MD5 Mess
  • ncode('utf8') data = base64.b64decode(_string) cipher = AES.new(passKey, AES.MODE_ECB)
βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

βœ“ Typosquatting

No typosquatting candidates detected

βœ“ Registered Email Domain

Email domain looks legitimate: live.com

βœ“ Suspicious Page Links

All external links appear legitimate

βœ“ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "AndyZhu" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with azpytools 
Create a command-line utility called 'CodeAnalyzer' using the Python package 'azpytools'. This tool will help developers analyze their Python codebase for common issues such as unused imports, redundant code, and potential bugs. The application should be able to scan a specified directory containing Python files and provide a summary of findings.

**Step-by-Step Requirements:**
1. **Setup**: Initialize a new Python project and install 'azpytools'. Use 'azpytools' to streamline the setup process, including dependency management and project structure.
2. **Directory Scan**: Implement functionality to scan a user-specified directory for Python files. Utilize 'azpytools' to handle file operations efficiently and manage any exceptions that might occur during the scanning process.
3. **Code Analysis**: Analyze each Python file for:
   - Unused imports
   - Redundant code blocks
   - Potential bugs or inefficiencies
Use 'azpytools' to leverage pre-built tools and utilities that can assist in parsing Python code and identifying these issues.
4. **Results Summary**: After analyzing all files, generate a summary report that includes a count of issues found, categorized by type. Employ 'azpytools' to format and output the results in a clear, readable manner.
5. **Interactive Mode**: Add an interactive mode where users can input specific file paths and receive immediate feedback on potential improvements.
6. **Configuration Options**: Allow users to configure analysis settings, such as ignoring certain types of warnings or specifying custom rules.

**Suggested Features**:
- Customizable warning levels
- Integration with version control systems like Git to track changes over time
- Support for multiple programming languages in future updates
- User-friendly CLI interface

In your implementation, demonstrate how 'azpytools' simplifies the development process by handling complex tasks like dependency management, error handling, and file operations. This will showcase the package's value in building robust and maintainable applications.

πŸ’¬ Discussion Feed

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