AI Analysis
Final verdict: SAFE
The SeaFreeze package appears safe with minimal risks identified. The primary concern lies in metadata, but it does not suggest any malicious activity.
- No network or shell risks detected.
- Minor issues in metadata but no strong indicators of malicious behavior.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution detected, indicating the package does not execute system commands which reduces risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some minor red flags, but nothing strongly indicative 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
score 3.0
Suspicious email domain flags: Very short email domain: uw.edu
Very short email domain: uw.edu
Suspicious Page Links
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://link.aps.org/doi/10.1103/PhysRevB.91.014308
Git Repository History
Repository Bjournaux/SeaFreeze appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Baptiste Journaux" 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 SeaFreeze
Create a Python-based mini-application called 'OceanTherm' that utilizes the SeaFreeze package to simulate and analyze the thermodynamic properties of seawater under various conditions. The application should allow users to input parameters such as temperature, salinity, and pressure, and then calculate and display properties like density, enthalpy, entropy, and specific volume. Additionally, include a feature that visualizes the data using matplotlib or a similar library, allowing users to see how these properties change over different ranges of input values. Finally, implement a user-friendly interface using a simple command-line interface (CLI) or a basic web front-end built with Flask. This will enable both technical and non-technical users to easily interact with the application and gain insights into the complex behavior of seawater.
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