auntiepypi

v0.8.5 suspicious
6.0
Medium Risk

auntiepypi — both ends of the Python distribution pipe for the AgentCulture mesh.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to potential credential harvesting and significant obfuscation techniques, raising concerns about its true intentions.

  • High obfuscation risk through base64 decoding
  • Potential credential harvesting via direct use of getpass.getpass
Per-check LLM notes
  • Network: The package makes network calls which could be legitimate for functionality like checking updates or communicating with a server, but requires further investigation to confirm its purpose and destination.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The presence of base64 decoding with validation suggests an attempt to decode potentially sensitive information, indicative of obfuscation for malicious purposes.
  • Credentials: Direct usage of getpass.getpass without context suggests potential harvesting of credentials, but it could also be part of a legitimate authentication process.
  • Metadata: The package has no typosquatting or email domain flags, but the maintainer's new account and link to an IP address raise some concern.

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8586 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

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

Limited contributor diversity

  • 1 unique contributor(s) across 27 commits in agentculture/auntiepypi
  • Single author but highly active (27 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • > bool: try: with socket.create_connection((host, port), timeout=timeout): return True
  • y=None, error=None) req = urllib.request.Request(url, headers={"User-Agent": _USER_AGENT, "Accept": "
  • e set by caller. with urllib.request.urlopen( # noqa: S310 # nosec B310 req, timeout
  • ")).decode("ascii") req = urllib.request.Request( # noqa: S310 - URL comes from cfg.host/port
  • verify) try: with urllib.request.urlopen( # noqa: S310 # nosec B310 - http/https only
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • () try: decoded = base64.b64decode(payload, validate=True) except binascii.Error: #
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • password: password = getpass.getpass("password: ") return user, password def _build_url(hos
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Link to raw IP address: https://0.0.0.0:3141/
✓ Git Repository History

Repository agentculture/auntiepypi appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "AgentCulture" 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 auntiepypi 
Create a Python-based mini-application named 'PipMonitor' that leverages the 'auntiepypi' package to monitor and manage dependencies within a Python project. This tool will allow users to track updates, vulnerabilities, and other important changes in their project's dependencies hosted on PyPI. Here’s a step-by-step guide to building PipMonitor:

1. **Project Setup**: Start by setting up your Python environment. Install the 'auntiepypi' package using pip.
2. **Feature Implementation**:
   - **Dependency Tracker**: Implement a feature that regularly checks for updates on all dependencies listed in a user's requirements.txt file. This should include fetching metadata from PyPI about each package.
   - **Vulnerability Scanner**: Integrate a functionality to scan dependencies for known security vulnerabilities based on data fetched from PyPI.
   - **Notification System**: Develop a system to notify users via email or console when there are new updates available or if a dependency has a critical vulnerability.
3. **User Interface**: Design a simple command-line interface (CLI) for interacting with PipMonitor. Users should be able to add, remove, and update tracked projects easily.
4. **Configuration Management**: Allow users to configure their preferences such as notification settings and frequency of checks through a configuration file.
5. **Testing & Documentation**: Ensure thorough testing of all functionalities and provide comprehensive documentation to guide users on how to use PipMonitor effectively.

By utilizing the 'auntiepypi' package, you'll be able to interact directly with the PyPI ecosystem, making it easier to keep track of your Python project's dependencies.

💬 Discussion Feed

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