aiodeepseek

v0.1.1 suspicious
4.0
Medium Risk

High-performance async Python client for the private DeepSeek API

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk due to the use of unencrypted network connections, which could allow data interception. Additionally, the lack of detailed maintainer information raises some suspicion.

  • Unencrypted network connections
  • Lack of detailed maintainer information
Per-check LLM notes
  • Network: The use of unencrypted (ssl=False) network connections can be a security risk, potentially allowing interception and tampering of data.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating safe usage.
  • Metadata: The package is newly released and lacks detailed maintainer information, raising suspicion.

📦 Package Quality Overall: Low (4.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/boykopovar/aiodeepseek#documentation
  • Detailed PyPI description (4860 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

  • 53 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 24 commits in boykopovar/aiodeepseek
  • Single author but highly active (24 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • ssl=False) async with aiohttp.ClientSession(connector=connector) as session: async with sess
  • ssl=False) async with aiohttp.ClientSession(connector=connector) as session: guest_pow = awa
  • `.""" self._session = aiohttp.ClientSession( connector=aiohttp.TCPConnector(enable_cleanup_c
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository boykopovar/aiodeepseek appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 aiodeepseek 
Develop a fully-functional mini-application named 'DeepSeekQueryTool' using Python that leverages the high-performance asynchronous capabilities of the 'aiodeepseek' package to interact with the private DeepSeek API. This tool will enable users to query large datasets efficiently and retrieve insights asynchronously. The application should have a simple command-line interface (CLI) for user interaction.

Step-by-Step Guide:
1. Install the required packages including 'aiodeepseek', 'aiohttp' for handling asynchronous HTTP requests, and 'click' for creating a CLI.
2. Design the main class for the application, which initializes the connection to the DeepSeek API using 'aiodeepseek'.
3. Implement functions within this class that allow users to perform common queries such as fetching data based on specific criteria, searching through datasets, and retrieving statistical summaries.
4. Ensure that all interactions with the API are done asynchronously to maximize performance.
5. Create a CLI using 'click' that exposes commands for initiating these queries. Users should be able to specify query parameters directly from the command line.
6. Add error handling to manage potential issues such as network errors or invalid API responses gracefully.
7. Include a feature to save the results of queries to a local file for further analysis.
8. Finally, document the project thoroughly, explaining how to install dependencies, run the application, and interpret the output.

Suggested Features:
- Asynchronous querying to maintain high performance even when dealing with large datasets.
- Support for multiple types of queries including filtering, searching, and aggregation.
- User-friendly CLI for easy interaction.
- Robust error handling and informative feedback.
- Option to export query results to a CSV file.
- Basic authentication support if the DeepSeek API requires it.

How 'aiodeepseek' is Utilized:
- 'aiodeepseek' serves as the primary interface to the DeepSeek API, providing an asynchronous client that can handle complex queries efficiently.
- Use 'aiodeepseek' methods to construct and send queries to the API.
- Leverage 'aiodeepseek' to parse responses and extract meaningful data for display or export.

💬 Discussion Feed

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