iqcc-shared

v0.1.0 suspicious
4.0
Medium Risk

Hybrid cryptographic utilities: ML-KEM-768 key encapsulation, ML-DSA-65 signing, AES-256-GCM payload encryption, and msgpack serialization

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package iqcc-shared v0.1.0 has low individual risk scores across all categories except for metadata, which raises concern due to its recent creation without any maintainer history or author information. This combination suggests potential suspicion but does not definitively indicate malicious intent.

  • Newly created package with no maintainer history
  • Missing author information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communications.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or unauthorized system access.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows several red flags including being newly created with no maintainer history and missing author information.

🔬 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 10.0

5 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Package uploaded less than 24 hours ago (2026-06-05T09:23:14.000Z)
  • 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)