appthreat-vulnerability-db

v6.7.0 suspicious
6.0
Medium Risk

AppThreat's vulnerability database and package search library with a built-in sqlite based storage. OSV, CVE, GitHub, npm are the primary sources of vulnerabilities.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has significant credential risk due to handling of GITHUB_TOKEN and moderate obfuscation, raising concerns about potential hidden functionality or complexity.

  • High credential risk due to direct usage of GITHUB_TOKEN
  • Moderate obfuscation suggesting possible hidden functionality
Per-check LLM notes
  • Network: The network calls are likely intended for fetching vulnerability data, which is expected for a package focused on security updates.
  • Shell: No shell execution patterns detected, indicating no immediate risk related to command execution.
  • Obfuscation: The use of base64 decoding suggests an attempt to obfuscate code, which may hide malicious intent or complexity.
  • Credentials: Direct extraction and usage of GITHUB_TOKEN from environment variables indicates potential unauthorized access risks.
  • Metadata: The maintainer's author information is incomplete, and the account seems new or inactive, which raises some suspicion but not enough to conclusively determine malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 9 test file(s) found

  • Test runner config found: pyproject.toml
  • 9 test file(s) detected (e.g. test_aqua_cache.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (47259 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 119 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in appthreat/vulnerability-db
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • try: client = httpx.Client(http2=True, follow_redirects=True, timeout=180)
  • pe ) client = httpx.Client(http2=True, follow_redirects=True, timeout=180) r =
  • data=False): client = httpx.Client(http2=True, follow_redirects=True, timeout=180) LOG.
  • ecent CVE""" client = httpx.Client(http2=True, follow_redirects=True, timeout=180) url
  • ta_list = [] client = httpx.Client(http2=True, follow_redirects=True, timeout=180) url
  • try: with httpx.Client( http2=True, follow_redirects=True, time
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • [ base64.b64decode(sm.value).decode("utf-8") for sm in
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • Logger(__name__) api_token = os.environ.get("GITHUB_TOKEN") headers = {"Authorization": f"token {api_token}"} vendo
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: appthreat.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository appthreat/vulnerability-db appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 appthreat-vulnerability-db 
Create a web-based vulnerability scanner tool using Python and the 'appthreat-vulnerability-db' package. This tool will allow users to input a package name and version to check for known vulnerabilities. Here’s how the application should work:

1. **User Interface**: Develop a simple, intuitive user interface where users can enter the package name and version they want to scan.
2. **Data Retrieval**: Utilize the 'appthreat-vulnerability-db' package to query the vulnerability database for the entered package and version. The package leverages OSV, CVE, GitHub, and npm as its data sources.
3. **Result Display**: Present the results to the user in a clear format. Include details such as the severity level of each vulnerability, the date it was discovered, and any known fixes or patches.
4. **Additional Features**:
   - **Automatic Updates**: Implement a feature that allows the tool to periodically update its local SQLite database with the latest vulnerability data from the internet.
   - **History Log**: Keep a history log of all scans performed by the user, allowing them to review past queries and their outcomes.
   - **Alert System**: If a new critical vulnerability is found in a previously scanned package, notify the user via email.
5. **Security Considerations**: Ensure that the application handles data securely, especially when storing and transmitting information like package names and versions.
6. **Testing**: Conduct thorough testing of the application to ensure it works correctly under various conditions and handles errors gracefully.
7. **Documentation**: Provide comprehensive documentation on how to install, use, and maintain the tool.

This project aims to demonstrate how the 'appthreat-vulnerability-db' package can be effectively integrated into a real-world application to enhance security practices.

💬 Discussion Feed

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