apex-coder

v1.0.2 suspicious
7.0
High Risk

APEX - AI powered terminal coding assistant

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks due to its use of subprocess.Popen with shell=True and network calls that could be exploited for unauthorized data transfer. Additionally, the lack of a discoverable repository and minimal maintainer information raises concerns about its legitimacy.

  • High network risk
  • Use of subprocess.Popen with shell=True
  • Limited maintainer information
Per-check LLM notes
  • Network: Detected network calls suggest interaction with external APIs which could potentially be used for unauthorized data transfer.
  • Shell: Use of subprocess.Popen with shell=True is risky and can lead to arbitrary code execution, suggesting potential for malicious activities.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository is not found and the maintainer has limited information and few packages, raising suspicion.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6756 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

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

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • THUB_TOKEN}"} response = requests.get(url , headers = headers, params = params) if response.s
  • ate" : False} response = requests.post("https://api.github.com/user/repos", headers = headers, json
  • file_name}" existing = requests.get(url, headers = headers) sha = existing.get("sha")
  • /cyan]"): response = requests.put(url , headers = headers, json = body) if response
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • keyword in SERVER): subprocess.Popen(command, shell=True) return f"Server started in bac
  • try : result = subprocess.run( commands, shell = True,
  • try: result = subprocess.run( ["python", "-m", "unittest", "test_apex",
  • subprocess.Popen(command, shell=True) return f"Server started in background: {command}"
  • commands, shell = True, capture_output = True, text = Tr
✓ 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 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 apex-coder 
Create a terminal-based code generation assistant called 'CodeGenPro' using the 'apex-coder' package. This application will help developers quickly generate boilerplate code for common programming tasks such as creating REST APIs, setting up database models, and initializing web frameworks. Here’s a detailed breakdown of the steps and features:

1. **Setup Environment**: Ensure your development environment includes Python and the 'apex-coder' package. Use pip to install 'apex-coder'.
2. **Define CLI Interface**: Design a simple command-line interface (CLI) where users can input commands to generate different types of code snippets.
3. **Integrate 'apex-coder'**: Utilize 'apex-coder' to handle the intelligent generation of code based on user inputs. For instance, if a user wants to create a new Flask app, 'apex-coder' should provide the necessary scaffolding.
4. **Feature Implementation**:
   - **REST API Generator**: Allow users to specify endpoints and methods (GET, POST, etc.), and 'apex-coder' will generate the corresponding API code.
   - **Database Model Creator**: Enable users to define database tables and columns, and 'apex-coder' will generate ORM classes for those models.
   - **Web Framework Initialization**: Support initialization scripts for popular web frameworks like Flask, Django, and FastAPI.
5. **Interactive Mode**: Implement an interactive mode where 'apex-coder' can suggest code improvements and optimizations as the user types, enhancing productivity.
6. **Customization Options**: Provide options for customizing the generated code, such as choosing between different programming styles (e.g., PEP8 vs. Google Style).
7. **Testing and Validation**: Include functionality to validate the generated code against common errors and best practices before finalizing it.
8. **Documentation and Help**: Create comprehensive documentation and a help system within the CLI to guide users through all features and functionalities.

Your goal is to create a robust, user-friendly tool that significantly reduces the time spent on repetitive coding tasks, leveraging the power of 'apex-coder' to streamline development workflows.

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