akasicdb

v1.0.0 suspicious
4.0
Medium Risk

Python client library for AkasicDB, a Vector-Graph-Relational DBMS based on PostgreSQL

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package appears to be low-risk based on its current analysis, with no signs of malicious activity such as network calls, shell execution, or obfuscation. However, the lack of a GitHub repository and the fact that it is a single-version release raises concerns about its development status and potential reliability.

  • Lack of a GitHub repository
  • Single-version release
Per-check LLM notes
  • Network: No network calls suggest normal behavior for a database package.
  • Shell: No shell execution suggests no immediate risk of command injection or similar attacks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package seems relatively benign, but the lack of a GitHub repository and single-version release suggest it may be underdeveloped or suspicious.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

  • Test runner config found: pyproject.toml
  • 12 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1818 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 144 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "GraphAI Co., Ltd." 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 akasicdb 
Create a social network analysis tool using the AkasicDB Python client library. This tool will allow users to import a dataset representing social connections (e.g., friendships, interactions) and perform various analyses on it. Here’s a detailed breakdown of the application’s functionalities:

1. **Data Importation**: Users should be able to upload a CSV file containing social connections data. Each row represents a connection between two individuals (nodes), including details like date of interaction, type of interaction, etc.

2. **Graph Visualization**: Implement a feature to visualize the imported data as a graph where nodes represent individuals and edges represent their connections. Use different colors and sizes for nodes and edges based on factors such as frequency of interactions or types of relationships.

3. **Network Metrics Calculation**: Calculate and display key network metrics such as degree centrality, betweenness centrality, and closeness centrality for each node. These metrics will help in understanding the importance of each individual within the network.

4. **Community Detection**: Apply community detection algorithms to identify clusters or communities within the social network. Visualize these communities in the graph and provide a summary of community characteristics.

5. **Query Interface**: Provide an interface where users can query specific nodes or edges based on attributes such as interaction dates or types. Utilize the AkasicDB’s querying capabilities to efficiently handle complex queries involving both relational and graph data.

6. **Export Results**: Allow users to export the analyzed results, including visualizations and calculated metrics, into various formats like CSV, JSON, or PNG images.

The AkasicDB Python client library is essential for storing and managing the social network data. It allows you to leverage PostgreSQL’s powerful relational database capabilities while also benefiting from advanced graph analytics. Ensure that your application makes efficient use of AkasicDB’s features to support real-time data manipulation and complex querying.

💬 Discussion Feed

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