🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks across all categories analyzed and does not exhibit any suspicious or malicious behavior. It appears to be a legitimate educational tool.

No network or shell risks detected
Low metadata risk

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
Metadata: The package shows some minor concerns but no clear signs of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://www.onem2m.org

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Andreas Kraft" 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 acmecse

Create a mini-application called 'AcmeCSE Tutor' that leverages the 'acmecse' package to provide students with personalized learning experiences in computer science education. The application should integrate with educational platforms and offer real-time feedback on coding exercises, as well as suggest additional resources based on student performance.

Step-by-Step Guide:
1. Set up the initial project structure and install the 'acmecse' package using pip.
2. Develop a user authentication system to manage student accounts and track their progress.
3. Implement a feature to upload and manage coding exercises. Each exercise should include a problem description, example code snippets, and test cases.
4. Integrate the 'acmecse' package to automatically grade student submissions based on predefined criteria and provide immediate feedback.
5. Utilize the 'acmecse' package's capabilities to analyze student performance data and recommend supplementary materials such as articles, videos, or practice problems.
6. Design a user-friendly interface that allows students to view their progress, access recommended resources, and interact with the platform seamlessly.
7. Ensure the application is scalable and secure, allowing for easy integration with existing educational systems.

Suggested Features:
- Real-time syntax highlighting and error detection during code submission.
- Detailed explanations for incorrect answers to help students understand their mistakes.
- Adaptive learning paths that adjust based on student performance.
- Integration with popular coding environments and IDEs.
- Analytics dashboard for educators to monitor class performance.

How to Utilize 'acmecse':
- Use 'acmecse' to set up a middleware service that handles the communication between the application and the backend educational database.
- Leverage 'acmecse' functionalities to automate grading processes and generate comprehensive reports on student performance.
- Employ 'acmecse' to facilitate the recommendation of additional learning resources based on individual student needs.