AI Analysis
The package exhibits elevated risks due to its network and shell execution behaviors, which could potentially lead to security vulnerabilities. However, there is no direct evidence of malicious intent or obfuscation.
- High network risk due to potential unvetted downloads
- High shell risk due to uncontrolled execution of external commands
Per-check LLM notes
- Network: The network call pattern suggests the package may download external resources which could be potentially malicious if not properly vetted.
- Shell: The shell execution patterns indicate the package executes external commands, which can pose significant risks if not controlled properly, possibly leading to system compromise.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows several red flags including a suspicious non-HTTPS link, rapid commit history, and an author with minimal information and activity.
Package Quality Overall: Low (4.0/10)
Partial test coverage signals detected
2 test file(s) detected (e.g. test_cvrp.py)
Some documentation present
Detailed PyPI description (6322 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
8 type-annotated function signatures (partial)
Single-author or unverifiable project
1 unique contributor(s) across 5 commits in chkwon/PyAILSIISingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
Found 1 network call pattern(s)
ream sources from {url}") urllib.request.urlretrieve(url, dest) digest = hashlib.sha256(dest.read
No obfuscation patterns detected
Found 3 shell execution pattern(s)
in(argv)) proc = subprocess.run(argv, capture_output=True, text=True, check=False)files)} .java files") subprocess.run( ["javac", "-encoding", "UTF-8", "-d", str(build=True, exist_ok=True) subprocess.run( ["jar", "cfe", str(JAR_DEST), JAR_MAIN_CLASS, *
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: omelet.ai>
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://vrp.galgos.inf.puc-rio.br/
Git history flags: All 5 commits happened within 24 hours
All 5 commits happened within 24 hours
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a web-based application using Flask (a micro web framework written in Python) that leverages the 'ailsii' package to solve the Capacitated Vehicle Routing Problem (CVRP). The application should allow users to input various parameters such as the number of vehicles, vehicle capacity, depot location, and customer locations with their respective demands. Users should also be able to upload a map image or provide coordinates to visualize the routes on an interactive map. The application should output the optimized routes, total distance traveled, and other relevant statistics. Additionally, include features like saving the route solutions to a database for future reference, allowing users to compare different solution iterations, and providing a REST API endpoint for integrating the CVRP solver into other applications. Use the 'ailsii' package to perform the optimization process and ensure that the application is user-friendly and efficient.
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