tracedsa

v1.0.0 suspicious
6.0
Medium Risk

Visualize Data Structures in real time — Python TUI + C++ backend

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is flagged as suspicious due to its high metadata risk and potential shell execution risks.

  • High metadata risk with recent upload, single version, low maintainer activity, and incomplete author details.
  • Potential shell execution risk detected, indicating possible command injection or unauthorized code execution.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network functionality.
  • Shell: Detection of shell execution may indicate potential for command injection or unauthorized code execution, warranting further investigation.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: High risk due to recent upload, single version, low maintainer activity, and incomplete author details.

🔬 Heuristic Checks

Outbound Network Calls

No suspicious network call patterns found

Code Obfuscation

No obfuscation patterns detected

Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • me = name self.proc = subprocess.Popen( [get_binary(name)], stdin=subproces
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 score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
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 (2026-06-05T05:11:03.000Z)
  • 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)