AI Analysis
Final verdict: SUSPICIOUS
The package has minimal direct risks but raises concerns due to sparse author information and lack of repository activity, potentially indicating a less legitimate source.
- Sparse author information
- No recent repository activity
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external API interactions.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
- Metadata: The author's information is sparse, and the repository shows no activity, raising concerns about its legitimacy.
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: mailbox.org>
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 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 aadr-resolve
Create a genetic research tool using the 'aadr-resolve' Python package. This tool will facilitate the integration of genetic data from various ancient DNA studies by resolving GeneticIDs and MasterIDs across different versions. The application should allow researchers to input a set of GeneticIDs from one study and map them to their corresponding MasterIDs from another version, ensuring consistency and compatibility between datasets. Key Features: 1. User-friendly interface for uploading GeneticID lists. 2. Integration with 'aadr-resolve' to perform cross-version joins on these IDs. 3. Option to select specific versions of the MasterID database for comparison. 4. Export functionality to save the resolved IDs in a CSV format for further analysis. 5. Detailed logs for each operation, including any errors encountered during the resolution process. Steps to Implement: 1. Set up a Python environment with Flask or Django for the web-based user interface. 2. Install the 'aadr-resolve' package via pip to handle the ID resolution logic. 3. Design a simple HTML form for users to upload their GeneticID lists. 4. Develop a backend function that calls 'aadr-resolve' with the uploaded IDs and chosen database version. 5. Implement error handling to manage cases where IDs cannot be resolved or if there are issues with the selected database version. 6. Create a download feature that allows users to export the resolved IDs as a CSV file. 7. Add logging capabilities to track each operation performed through the application, including any exceptions or errors.