AI Analysis
Final verdict: SUSPICIOUS
The package shows signs of obfuscation with base64 encoding, which could indicate attempts to hide code or data. However, there are no direct indications of malicious activities such as network calls or shell executions.
- Obfuscation risk due to base64 encoding
- Inactive maintainer on PyPI
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access to function properly.
- Shell: No shell execution patterns detected, indicating low risk of executing unauthorized commands.
- Obfuscation: The presence of base64 decoding for what appears to be an image suggests potential obfuscation, possibly hiding executable code or sensitive data.
- Credentials: No clear patterns indicative of credential harvesting were found.
- Metadata: The maintainer's lack of activity and presence on PyPI raises suspicion, but there are no direct indicators of malicious intent.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
e_type": "image/png", "data": base64.b64decode(screenshot_b64)}, ] try: respon
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: pintu.co.id>
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 IntelliHeal
Create a robust automated testing tool for web applications using Python's Selenium WebDriver, enhanced with the 'IntelliHeal' package. This tool will not only automate the process of running tests but also intelligently handle common issues such as element not found, network timeouts, and page load failures without manual intervention, ensuring tests run smoothly even in less-than-ideal conditions. Step 1: Set up your development environment with Python, Selenium WebDriver, and the IntelliHeal package installed. Step 2: Design a basic structure for your test automation framework, including modules for test case creation, execution, and reporting. Step 3: Implement a series of test cases targeting different functionalities of a sample web application. Each test case should include steps to navigate through the web app, interact with UI elements, and validate expected outcomes. Step 4: Integrate IntelliHeal into your test framework to automatically detect and recover from common test execution failures. Configure IntelliHeal settings to suit your specific needs, such as retrying failed actions, logging errors, and adjusting timeouts. Step 5: Enhance your tool with additional features like: - A user-friendly interface to manage and execute test cases. - Support for multiple browsers and operating systems. - Real-time test progress monitoring and alerts for failed tests. - Integration with continuous integration/continuous deployment (CI/CD) pipelines. How IntelliHeal is utilized: - Use IntelliHeal's self-healing capabilities to automatically identify and resolve issues that would normally require manual intervention, such as elements not being clickable due to dynamic content loading. - Leverage IntelliHeal's error handling mechanisms to gracefully recover from exceptions and continue test execution where it left off, improving overall test reliability. - Utilize IntelliHeal's analytics features to gain insights into the stability and performance of your web application under test.