AI Analysis
Final verdict: SAFE
The package appears safe with low risks across all categories except for some potential obfuscation techniques. There is no indication of network activity, shell execution, or credential harvesting.
- No network calls detected.
- No shell execution patterns found.
- Potential use of obfuscation techniques.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
- Obfuscation: The code uses regex and json encoding which could be used for obfuscating logic or data, but without context it's hard to determine malicious intent.
- Credentials: No direct evidence of credential harvesting is present.
- Metadata: The author's information is sparse, suggesting potential unreliability, but no other red flags are present.
Package Quality Overall: Medium (5.8/10)
✦ High
Test Suite
9.0
Test suite present — 32 test file(s) found
Test runner config found: pyproject.tomlTest runner config found: pyproject.tomlTest runner config found: conftest.py32 test file(s) detected (e.g. benchmark.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (41807 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
265 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 100 commits in ai-2070/netTwo distinct contributors found
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 4.0
Found 2 obfuscation pattern(s)
============= _NUMERIC_RE = __import__("re").compile(r"^-?\d+(\.\d+)?$") def _try_parse_float(s: str)n strings).""" return __import__("json").dumps(s) def _pred_debug_label(p: Predicate) -> str:
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
Repository ai-2070/net appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
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