AI Analysis
Final verdict: SAFE
Based on the provided analysis notes, the package 'audiness' appears to be safe with no indications of malicious activity. The low scores across all risk categories suggest minimal risk.
- No network or shell risks
- No signs of obfuscation or credential harvesting
- Metadata risk slightly elevated due to a single-package maintainer
Per-check LLM notes
- Network: No network calls suggest the package does not engage in external communications, which is typical for many packages.
- Shell: No shell executions indicate that the package is not directly executing system commands, reducing risk of unauthorized operations.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, suggesting a new or less active account which may warrant further investigation but does not strongly indicate malicious intent.
Package Quality Overall: Medium (5.2/10)
◈ 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 (4003 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
12 type-annotated function signatures detected in source
✦ High
Multiple Contributors
8.0
Active multi-contributor project
4 unique contributor(s) across 100 commits in audius/audinessSmall but multi-author team (3–4 contributors)
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
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: audius.de
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository audius/audiness appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Fabian Affolter" 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 audiness
Create a Python-based vulnerability assessment mini-app named 'NessusQuickScan' that leverages the 'audiness' package to interact with Tenable's Nessus API. This app will streamline the process of conducting quick vulnerability scans on networks or specific hosts, making it easier for security professionals to identify potential threats. ### Core Functionality: - **Login to Nessus:** Implement a login feature using 'audiness' to authenticate with a Nessus instance. This should include handling credentials securely. - **Scan Creation:** Allow users to create custom scans targeting either entire networks or specific IP addresses. Users should be able to specify scan templates, schedule scans, and set up policies. - **Scan Execution:** Execute scans based on user input and monitor their progress. The app should provide real-time updates on scan status. - **Results Analysis:** Once a scan completes, parse the results using 'audiness' and present them in a user-friendly format. Highlight critical vulnerabilities and offer brief descriptions of each issue. - **Export Options:** Provide options to export scan results in various formats (CSV, PDF, HTML). ### Suggested Features: - **Dashboard View:** A simple dashboard that summarizes the scan status, recent scans, and any notable findings. - **Alert System:** Set up alerts for high-risk vulnerabilities detected during scans. - **Integration with Other Tools:** Allow integration with other security tools or platforms for further analysis or remediation. - **User Management:** Basic user management capabilities to control access to different Nessus instances and scan configurations. ### How 'audiness' is Utilized: - **Authentication:** Use 'audiness' to handle authentication with Nessus, including token generation and management. - **API Requests:** Leverage 'audiness' for making API requests to create, manage, and execute scans. - **Data Parsing:** Utilize 'audiness' to parse scan results into structured data for easier analysis and presentation. - **Error Handling:** Implement robust error handling for all interactions with the Nessus API through 'audiness'. This mini-app aims to simplify the process of conducting vulnerability assessments and make it accessible to both experienced security professionals and beginners.
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