aptitude-publisher

v0.1.7 suspicious
4.0
Medium Risk

Publisher CLI for evaluating and publishing Aptitude skills

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks in terms of network, shell, obfuscation, and credential usage, but the metadata suggests potential issues with an anonymous maintainer and low repository activity, raising suspicion.

  • Anonymous maintainer
  • Low activity in the git repository
Per-check LLM notes
  • Network: No network calls detected, which is normal and expected.
  • Shell: Shell execution patterns detected may be related to compression/decompression or version control operations, suggesting the package performs local file operations rather than executing potentially harmful commands.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some red flags such as an anonymous maintainer and low activity in the git repository, indicating potential risks.

📦 Package Quality Overall: Medium (6.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/aptitude-stack/publisher/tree/main/docs
  • Detailed PyPI description (4071 chars)
✦ High Contributing Guide 9.0

Has contribution guidelines and governance files

  • Governance file: security.py
  • Governance file: security.py
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 262 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 41 commits in aptitude-stack/publisher
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • """ try: result = subprocess.run( ["zstd", "--quiet", "--stdout"], in
  • re text output.""" return subprocess.run( command, cwd=str(cwd), env=dict(env
  • vailable.""" result = subprocess.run( ["zstd", "--quiet", "--stdout"], in
  • try: result = subprocess.run( ["git", "-C", str(skill_root), "rev-parse",
  • try: result = subprocess.run( ["git", "-C", str(skill_root), "remote", "g
✓ 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 score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 aptitude-publisher 
Your task is to develop a Python-based command-line tool named 'SkillMaster' that leverages the 'aptitude-publisher' package to evaluate and publish user's Aptitude skills. This tool will serve as a platform where users can take skill assessments, receive immediate feedback on their performance, and share their results publicly or privately.

Step 1: Setup and Configuration
- Begin by installing the 'aptitude-publisher' package if it's not already installed.
- Configure SkillMaster to allow users to create profiles, including basic information like username and preferred language.

Step 2: Skill Assessment
- Implement a feature where users can select from various Aptitude skill categories such as logical reasoning, numerical ability, etc.
- Each category should have a set of pre-defined questions that users must answer within a time limit.
- Utilize the 'aptitude-publisher' package to automatically grade the answers based on correctness and speed.

Step 3: Feedback and Analysis
- After completing an assessment, provide users with detailed feedback, highlighting strengths and areas for improvement.
- Use 'aptitude-publisher' to generate personalized reports summarizing performance across different categories.

Step 4: Publishing Results
- Allow users to choose whether they want their results to be published anonymously or under their profile name.
- Integrate with social media platforms to enable sharing of results directly from the application.
- Ensure that all published results comply with privacy regulations and respect user preferences regarding data visibility.

Suggested Features:
- User authentication system for secure access.
- Ability to track progress over time through saved assessment histories.
- Integration with gamification elements such as badges and leaderboards to enhance engagement.
- Option to schedule regular skill assessments for continuous improvement.
- Support for multiple languages to cater to a global audience.

How to Utilize 'aptitude-publisher':
- Use the evaluation functions provided by 'aptitude-publisher' to assess user responses accurately and efficiently.
- Leverage the publishing capabilities to share assessment outcomes securely and effectively.
- Consider extending the functionality of 'aptitude-publisher' to include custom metrics or scoring algorithms tailored to specific skill sets.