autokattis

v2.1.5 safe
3.0
Low Risk

Updated Kattis API wrapper

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate based on its purpose and the absence of malicious indicators such as obfuscation, shell execution, or credential harvesting. However, the low metadata quality and single-package maintainer suggest caution.

  • Low risk of network, shell, obfuscation, and credential risks.
  • Maintainer has only one package and lacks detailed metadata.
Per-check LLM notes
  • Network: The use of requests.Session() suggests network communication which could be legitimate if the package interacts with an API or external service.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The maintainer has only one package and lacks PyPI classifiers, indicating low effort or newness.

📦 Package Quality Overall: Low (3.4/10)

○ 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 (6348 chars)
○ 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
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 68 commits in RussellDash332/autokattis
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • ngs() self.session = requests.Session() self.session.__init__() self.base_url =
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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

Repository RussellDash332/autokattis appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Russell Saerang" 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 autokattis 
Create a comprehensive problem-solving assistant application using the 'autokattis' package. This application will serve as a bridge between users and the Kattis platform, enabling them to easily interact with problems, submit solutions, and track their progress. The application should include the following features:

1. **Problem Fetching**: Allow users to browse through Kattis problems by category or difficulty level. Use the 'autokattis' package to fetch problem details such as title, description, input/output specifications, and sample test cases.

2. **Solution Submission**: Provide functionality for users to write code solutions directly within the app or upload existing files. Utilize 'autokattis' to handle the submission process and display real-time feedback on solution correctness.

3. **Progress Tracking**: Implement a dashboard where users can view their solved problems, attempted problems, and overall statistics. Integrate 'autokattis' to periodically update these metrics based on the user's activity on the Kattis platform.

4. **Community Interaction**: Enable users to share their solutions, discuss problem-solving strategies, and collaborate with others through integrated chat rooms or forums. While not directly provided by 'autokattis', you can use external APIs or services to facilitate community interaction.

5. **Personalized Learning Path**: Recommend problems tailored to each user's skill level and learning goals. Use 'autokattis' data to analyze past performance and suggest problems that will help users improve.

To start, focus on building the core functionalities around problem fetching and solution submission, ensuring that the 'autokattis' package is utilized effectively to manage interactions with the Kattis API. As you develop these features, consider how they can be expanded or enhanced in future updates.

💬 Discussion Feed

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