aigc-skillhub

v1.0.10 suspicious
5.0
Medium Risk

(No description)

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to high shell risk and low metadata quality, though it lacks clear indicators of malicious intent such as obfuscation or credential harvesting.

  • High shell risk
  • Low metadata quality
Per-check LLM notes
  • Network: The network call to PyPI is likely for version checking or dependency fetching and is generally benign.
  • Shell: Executing shell commands without proper validation or handling can lead to potential security risks such as command injection.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low maintenance and metadata quality, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • : try: response = requests.get("https://pypi.org/pypi/aigc-skillhub/json", timeout=5)
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • try: completed = subprocess.run(command, check=False) except OSError as exc: pri
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aigc-skillhub 
Create a personalized AI-driven skill recommendation app called 'SkillMaster' using the Python package 'aigc-skillhub'. This app will help users discover new skills based on their interests and career goals. Here’s how it works:

1. **User Profile Creation**: Users start by creating a profile where they input basic information such as name, age, current job role, and areas of interest.
2. **Skill Recommendation Engine**: Utilize the 'aigc-skillhub' package to analyze user data and recommend relevant skills. The package likely offers APIs or functions that can process this data and suggest skills accordingly.
3. **Skill Details Page**: For each recommended skill, provide detailed information including brief descriptions, learning resources, and potential career benefits.
4. **Progress Tracking**: Allow users to track their progress in these skills. They can mark skills as 'Learning', 'Mastered', or 'Interested'.
5. **Community Integration**: Integrate a feature where users can connect with others who are also learning the same skills, fostering a community feel.
6. **Notifications & Reminders**: Implement a notification system to remind users about their learning goals and recent progress.

The 'aigc-skillhub' package plays a crucial role in analyzing user inputs and generating personalized skill recommendations. It might involve calling specific functions from the package to fetch skill data, analyze user profiles, and match them with suitable skills. Ensure the app is user-friendly and visually appealing, making the learning journey enjoyable and motivating.

💬 Discussion Feed

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