astrea-agent

v0.7.2 suspicious
6.0
Medium Risk

ASTrea - Autonomous Software Engineering Agent

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows a moderate level of risk due to potential credential harvesting and shell execution risks. While there's no direct evidence of malicious intent, the combination of these factors raises concerns.

  • Potential credential harvesting behavior
  • Unsanitized shell execution
Per-check LLM notes
  • Network: No network calls were detected, which is neutral from a security perspective.
  • Shell: Shell execution with 'subprocess.run' and 'shell=True' can be risky if not properly sanitized or controlled, potentially leading to code injection attacks.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: Detected code may be attempting to read sensitive files and could indicate potential credential harvesting behavior.
  • Metadata: The package shows signs of being newly created with limited activity, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.0/10)

○ 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 (9305 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

  • 199 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 9 commits in dfjmsf/ASTrea-AGENT
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • te(code) result = subprocess.run( [sys.executable, "-c", f"import importlib.u
  • ne try: result = subprocess.run( command, shell=True, ca
  • command, shell=True, capture_output=True, text=True,
⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • ") TOKEN_WARNING_LIMIT = int(os.getenv("TOKEN_WARNING_LIMIT", 50000)) # 保留 class LLMProvider: """单
  • ad_file", {"file_path": "../../etc/passwd"}) assert "禁止" in result or "错误" in result
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: All 9 commits happened within 24 hours

  • All 9 commits happened within 24 hours
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "DFJMSF" 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 astrea-agent 
Create a mini-application named 'CodeCraft' using the Python package 'astrea-agent'. This application will serve as a personal code development assistant, helping developers streamline their workflow by automating repetitive tasks and providing intelligent suggestions. Here are the key functionalities of CodeCraft:

1. **Code Snippet Generation**: Based on comments or brief descriptions provided by the user, CodeCraft should generate relevant code snippets. For example, if a user inputs 'create a function to calculate the Fibonacci sequence', the application should output a Python function that accomplishes this task.
2. **Automated Testing Suggestions**: Upon analyzing a piece of code, CodeCraft should suggest appropriate unit tests that could be written to ensure the functionality works as expected. It should also provide guidance on where these tests might be best placed within the existing test suite.
3. **Code Refactoring Recommendations**: Analyze a given piece of code and provide recommendations for refactoring it to improve readability, maintainability, or performance. Suggestions could include simplifying complex expressions, breaking down large functions into smaller ones, or optimizing loops.
4. **Dependency Management**: Assist in identifying outdated or unused dependencies in a project and suggest updates or removals based on current best practices.
5. **Integration with Version Control Systems**: Enable users to integrate CodeCraft directly with their version control systems (like Git). This integration should allow CodeCraft to analyze commit messages and suggest improvements or additional actions post-commit.

To achieve these functionalities, you'll need to leverage 'astrea-agent' effectively. Specifically, use its capabilities in natural language understanding to interpret user inputs for generating code snippets and suggesting tests. Employ its code analysis tools to perform static analysis on provided codebases for refactoring suggestions and dependency management. Lastly, utilize any available APIs or integrations offered by 'astrea-agent' to connect with version control systems seamlessly.

Your task is to design and implement a fully-functional prototype of CodeCraft that showcases at least three out of the five mentioned features. Ensure your application is well-documented, easy to install, and includes examples of how each feature can be used.

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