arche-core

v0.2.0a3 safe
4.0
Medium Risk

African PII detection that cites the law it enforces. Government IDs, names, phones, addresses for NG/KE/ZA/GH, grounded in NDPA, POPIA, Kenya DPA, Ghana DPA. Composes with Presidio, GLiNER, and Splink.

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe based on low risks across all categories except metadata, which indicates potential new or inactive maintainer activity. However, there are no clear malicious indicators.

  • Low network, shell, obfuscation, and credential risks
  • Metadata risk due to potential new or inactive maintainer activity
Per-check LLM notes
  • Network: The presence of network calls is expected if the package relies on external services or APIs.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of potential new or inactive maintainer activity, but no clear malicious indicators.

📦 Package Quality Overall: Medium (5.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Documentation" -> https://docs.unpatterned.org
  • 2 documentation file(s) (e.g. __init__.py)
  • Detailed PyPI description (6513 chars)
◈ Medium Contributing Guide 7.0

Some contribution signals present

  • Governance file: governance.py
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 206 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 29 commits in unpatterned-labs/arche
  • Single author but highly active (29 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • memory. with ( httpx.Client( timeout=timeout_seconds, follow_r
✓ 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

Email domain looks legitimate: unpatterned.org>

✓ 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 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 arche-core 
Create a privacy compliance checker application using the 'arche-core' Python package. This application will help organizations ensure they are compliant with various data protection laws in Africa, such as Nigeria’s NDPA, South Africa’s POPIA, Kenya’s Data Protection Act, and Ghana’s Data Protection Act. The app should be able to detect and flag potential Personally Identifiable Information (PII) in text data, including government IDs, names, phone numbers, and addresses from specified countries. Additionally, the application should cite the relevant legal basis for each detected piece of PII, helping users understand which regulations apply to specific types of data.

Steps to create this application:
1. Set up a Python environment with all necessary dependencies installed, including 'arche-core'.
2. Design a user-friendly interface where users can input text data for analysis.
3. Implement functionality to detect PII elements within the provided text, leveraging 'arche-core'.
4. For each detected PII element, display the type of information found and the applicable law(s) from the mentioned jurisdictions.
5. Allow users to export the results in a structured format (CSV or JSON).
6. Add a feature to generate a summary report highlighting compliance risks and suggesting actions to mitigate them.
7. Ensure the application is well-documented, with clear instructions on installation and usage.

💬 Discussion Feed

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