AI Analysis
The package exhibits low risks in terms of network calls, shell execution, obfuscation, and credential harvesting. However, the metadata risk score of 6 out of 10 due to missing maintainer history and an incomplete author profile raises suspicion, suggesting potential issues with the package's provenance.
- Low network, shell, obfuscation, and credential risks
- High metadata risk due to incomplete maintainer history and author profile
Per-check LLM notes
- Network: The network call appears to be a benign data fetching operation from a public API.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package is suspicious due to lack of maintainer history and an incomplete author profile.
Package Quality Overall: Low (2.8/10)
Test suite present — 20 test file(s) found
Test runner config found: conftest.py20 test file(s) detected (e.g. test_dict_extract.py)
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 1 network call pattern(s)
son def get_data(): r = requests.post( url="https://jsonplaceholder.typicode.com/posts",
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
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 Python-based mini-application named 'AssertManTester' that leverages the 'assertman2' package to validate various aspects of a simple user input form. This application will serve as a robust testing tool for ensuring data integrity and correctness before processing any user inputs. The form will accept basic user information such as name, email, and age. Your task is to design and implement a series of assertions using 'assertman2' to validate each field according to specific criteria. For instance, ensure the name contains only alphabetic characters, the email adheres to standard email format rules, and the age falls within a reasonable range (e.g., between 18 and 99 years old). Additionally, the application should provide clear error messages when validation fails, guiding the user on how to correct their input. Suggested features include a user-friendly interface for submitting forms, real-time validation feedback, and a summary report upon successful submission. Explore how 'assertman2' can enhance your application's reliability and maintainability through structured assertion handling.
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