🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk in terms of network, shell, and obfuscation activities, but its metadata raises some suspicion due to the maintainer's limited activity and the package being newly released.

Metadata risk due to new package and limited maintainer activity
No detected malicious activities like network calls, shell executions, or obfuscation

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no immediate risk from command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is new and the maintainer has limited activity, raising some suspicion but not conclusive evidence of malice.

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: All 8 commits happened within 24 hours

All 8 commits happened within 24 hours

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "goww7" 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 acttrace-mcp

Create a mini-application called 'AI Transparency Checker' that leverages the 'acttrace-mcp' package to ensure compliance with the EU AI Act for non-financial SaaS applications. This application will allow users to input details about their AI systems, classify them according to the EU AI Act's risk categories, and automatically generate Article 50 transparency notices. Here are the steps and features your application should include:

1. **User Input Interface**: Develop a user-friendly interface where users can enter information about their AI system, including purpose, type of data processed, and intended use.
2. **Risk Classification**: Utilize 'acttrace-mcp' to classify the AI system into one of the EU AI Act’s defined risk categories based on the provided information.
3. **Transparency Notice Generation**: Once the system is classified, the application should automatically generate an Article 50 transparency notice tailored to the specific risk category and the details provided by the user.
4. **Save and Share Functionality**: Allow users to save their AI system details and generated notices for future reference. Additionally, provide options for sharing these notices via email or download as a PDF.
5. **Educational Resources**: Integrate a section within the app that provides brief explanations about each risk category, the requirements of Article 50, and tips for compliance.
6. **Feedback Loop**: Implement a feature where users can submit feedback on the accuracy of the classification and transparency notice generation, helping to improve the application over time.

Utilize the 'acttrace-mcp' package to handle the backend processing of risk classification and transparency notice generation, ensuring that all functionalities comply with the EU AI Act standards. This project aims to simplify the compliance process for developers and businesses working with AI in non-financial SaaS environments.