adversarial-provenance-sdk

v0.2.0 suspicious
4.0
Medium Risk

Enterprise-grade adversarial provenance middleware

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks in terms of network usage, shell execution, and code obfuscation. However, the metadata quality is concerning, indicating potential issues with transparency and authenticity.

  • Metadata risk score of 6 out of 10
  • Lack of package description
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires online services.
  • Shell: No shell executions detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
  • Metadata: The package shows signs of low effort and potential lack of transparency, raising concerns about its authenticity and purpose.

🔬 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

No author email provided

Suspicious Page Links

All external links appear legitimate

Git Repository History

No GitHub repository linked

  • No GitHub repository link found
Maintainer History score 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with adversarial-provenance-sdk
Build a simple Python application using the adversarial-provenance-sdk package to demonstrate its core features.