AI Analysis
The package exhibits a moderate risk profile due to its use of 'eval', which can be exploited for code injection, and the redirection of network calls to an external service with unknown trustworthiness.
- High obfuscation risk due to 'eval' usage
- Potential network risk from redirected HTTP calls
Per-check LLM notes
- Network: The presence of network calls with authorization tokens suggests potential data exchange with external services, which could be legitimate but also poses risks if the token is misused.
- Shell: No shell execution patterns were detected.
- Obfuscation: The presence of 'eval' with user input suggests potential for code injection and obfuscation, indicating a high risk.
- Credentials: No clear patterns of credential harvesting detected.
- Metadata: The repository and package are very new with minimal activity, raising suspicion but not conclusive evidence of malice.
Heuristic Checks
Found 2 network call pattern(s)
TH}" self._session = requests.Session() self._session.headers["Authorization"] = f"Token {nt) -> List[int]: r = requests.get( f"{self._base}/projects/{project_code}/plans/{p
Found 1 obfuscation pattern(s)
cted): ... assert eval(test_input) == expected :param argnames: A comma-se
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: Repository created very recently: 2 day(s) ago (2026-06-03T04:59:58Z)
Repository created very recently: 2 day(s) ago (2026-06-03T04:59:58Z)Repository has zero stars and zero forks
2 maintainer concern(s) found
Package is very new: uploaded 2 day(s) agoAuthor "Didit Setiawan" 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 mini-application that integrates the FamacasePytest package into a basic web application testing framework. This application will serve as a proof of concept for using FamacasePytest to manage and report tests within a continuous integration/continuous deployment (CI/CD) pipeline. The goal is to demonstrate how the FamacasePytest package can seamlessly replace qase-pytest for reporting test results to the Famacase Reporter Ingestion API. Steps to follow: 1. Set up a simple Flask web application with at least three endpoints: Home, About, and Contact. 2. Write unit tests for each endpoint using pytest. 3. Integrate FamacasePytest into your test suite to replace qase-pytest. 4. Configure FamacasePytest to send test results to the Famacase Reporter Ingestion API. 5. Automate the test execution process through a GitHub Actions workflow. 6. Ensure that the application can generate detailed reports based on the test results stored in Famacase. Suggested Features: - Implement fixtures for database connections and setup. - Use environment variables for configuration settings such as API keys and base URLs for Famacase. - Add logging capabilities to track test execution and any errors encountered. - Create a dashboard within the Flask app that displays recent test results and statuses from Famacase. - Include a feature to trigger manual re-runs of the test suite via the web interface. How FamacasePytest is Utilized: - Replace the standard pytest execution with FamacasePytest to ensure all test results are reported to Famacase. - Configure FamacasePytest to include custom metadata about each test case, such as the endpoint being tested and the expected outcome. - Leverage the FamacasePytest plugin to handle different types of test failures and successes, providing granular insights into the health of the application. - Utilize the Famacase API to fetch and display test results directly within the Flask application's dashboard.
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