🤖 AI Analysis

Final verdict: SAFE

The package is considered safe with low risks across most categories. While there is some obfuscation through base64 encoding, it does not raise significant red flags without additional context.

Low network and shell execution risks
Potential obfuscation through base64 encoding
No signs of credential harvesting or other malicious activities

Per-check LLM notes

Network: The detected network calls are typical for packages that require internet access to communicate with APIs or external services.
Shell: No shell execution patterns were detected, indicating low risk of local system compromise.
Obfuscation: The use of base64 encoding for decoding content may indicate obfuscation, but it could also be a legitimate practice such as handling encrypted data.
Credentials: No clear signs of credential harvesting detected.
Metadata: The maintainer has only one package, and there's no linked GitHub repository, which could indicate a less experienced or potentially suspicious actor.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (5290 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

376 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

erify) self._client = httpx.AsyncClient( timeout=timeout, headers=self.heade
target_path}") async with httpx.AsyncClient(timeout=60.0, follow_redirects=True) as http_client:

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

ent, file_path) decoded = base64.b64decode(downloaded["content_base64"]).decode() if decoded != or

✓ 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: attackiq.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Rajesh Sharma" 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 aiq-platform-api

Develop a comprehensive security assessment tool using the 'aiq-platform-api' Python package. This tool will serve as a bridge between your local environment and the AttackIQ platform, enabling you to automate and streamline the process of security testing and validation. Your task is to create a user-friendly command-line interface (CLI) that allows security professionals to interact with the AttackIQ platform more efficiently. Here’s a detailed breakdown of what your application should accomplish:

1. **User Authentication**: Implement a secure method for users to authenticate their credentials against the AttackIQ platform. Ensure that the authentication process complies with best practices for handling sensitive information.
2. **List Available Tests**: Provide functionality to list all available security tests within the AttackIQ platform. Users should be able to filter these tests based on various criteria such as test name, status, or creation date.
3. **Run Security Tests**: Allow users to select and run specific security tests from the CLI. The application should provide real-time feedback on the progress of each test and notify the user once the test has completed.
4. **Generate Test Reports**: After a test has been executed, generate a detailed report summarizing the findings. These reports should include metrics like pass/fail rates, vulnerabilities identified, and recommendations for remediation.
5. **Custom Test Creation**: Enable advanced users to create custom security tests directly through the CLI. This feature should support the definition of test scenarios, expected outcomes, and any necessary configurations.
6. **Integration with External Tools**: Explore integrating your application with external tools such as Jira for issue tracking or Slack for notifications. This integration should enhance the workflow for security teams by automating the reporting and communication processes.
7. **Documentation and Support**: Develop comprehensive documentation for your application, including setup instructions, usage guides, and troubleshooting tips. Additionally, implement a basic support system within the application to help users resolve common issues.

To achieve these objectives, you will extensively utilize the 'aiq-platform-api' package, which provides essential functions for interacting with the AttackIQ platform’s API. Familiarize yourself with the package’s documentation to understand how to authenticate requests, retrieve data, execute commands, and handle responses effectively. By leveraging this package, you will be able to focus on building a robust and user-centric application rather than dealing with low-level API interactions.