AI Analysis
Final verdict: SUSPICIOUS
The package shows no signs of immediate malicious activity, but the metadata risk is high due to the newness of the repository, lack of maintainer activity, and missing author information.
- High metadata risk score
- Repository and package are very new
- No author information provided
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interaction for its functionality.
- Shell: No shell execution patterns detected, reducing likelihood of malicious activities involving system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk to secrets or credentials.
- Metadata: The repository and package are very new, the maintainer seems inactive, and there's no author information provided, which raises suspicion.
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: izusoft.tech>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository created very recently: 4 day(s) ago (2026-06-01T19:52:23Z)
Repository created very recently: 4 day(s) ago (2026-06-01T19:52:23Z)
Maintainer History
score 8.0
4 maintainer concern(s) found
Only one version has ever been released — brand new packagePackage is very new: uploaded 1 day(s) agoAuthor name is missing or very shortAuthor "" 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 aaep-ext-medical-hipaa
Develop a HIPAA-compliant patient data management system using the 'aaep-ext-medical-hipaa' Python package. This system will serve as a secure platform for healthcare providers to manage patient information while adhering to HIPAA regulations. The app should include the following key functionalities: 1. **Patient Data Entry**: Allow users to input patient information such as name, date of birth, medical history, etc., ensuring all data is stored securely. 2. **PHI Redaction**: Implement a feature that automatically redacts any personally identifiable health information (PHI) from documents or notes before they are shared with unauthorized parties. 3. **BAA Capability Negotiation**: Enable the system to negotiate Business Associate Agreements (BAAs) with third-party services that require access to patient data, ensuring compliance with HIPAA rules. 4. **Medical Risk Classification**: Integrate a module that classifies patients based on their medical risks, helping healthcare providers prioritize care. 5. **HL7-Aligned Audit Metadata**: Track and log all interactions with patient data in a manner compliant with HL7 standards for audit purposes. Utilize the 'aaep-ext-medical-hipaa' package throughout the development process to ensure that each feature aligns with HIPAA requirements. For instance, use its PHI redaction tools during data entry and sharing processes, leverage its BAA negotiation capabilities when integrating external services, apply its risk classification algorithms to assess patient conditions, and employ its audit metadata functions to maintain comprehensive logs of user activities. This project aims to demonstrate how modern healthcare applications can seamlessly integrate advanced privacy and security measures while providing essential functionality.