aida-sdk

v1.0.2 suspicious
5.0
Medium Risk

AIDA — AI DevOps Incident Intelligence SDK. Auto-captures logs, errors, and exceptions, streams them to your AIDA backend, and triggers AI-powered incident analysis.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of legitimacy but raises concerns due to the missing git repository and the maintainer's limited history on PyPI, suggesting potential risks that need further investigation.

  • Metadata risk: Missing git repository and single-package maintainer history.
  • No immediate high-risk activities detected (network, shell, obfuscation, credentials).
Per-check LLM notes
  • Network: The observed network call pattern suggests the package is likely performing legitimate HTTP requests, possibly for API interactions or updates.
  • Shell: No shell execution patterns detected, indicating no immediate risk associated with command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package has no typosquatting or email domain flags, but the git repository is not found and the maintainer has only one package on PyPI, which may indicate potential risks.

📦 Package Quality Overall: Low (3.6/10)

○ 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://docs.aida.dev
  • Detailed PyPI description (2408 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

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

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: with httpx.Client(timeout=10.0) as client: resp = client.p
✓ 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 score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "AIDA Team" 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 aida-sdk 
Create a real-time incident monitoring and analysis tool using the Python package 'aida-sdk'. This tool will serve as a mini-application for developers to monitor their applications' health in real time. Here’s a detailed plan on how to implement this project:

1. **Project Overview**: Develop a tool that integrates with various logging systems (e.g., syslog, Elasticsearch, etc.) to capture logs, errors, and exceptions. These captured incidents will be streamed to an AIDA backend for further analysis.

2. **Core Features**:
   - **Real-Time Log Monitoring**: Implement functionality to continuously stream log data from multiple sources into the AIDA backend.
   - **Error Detection & Analysis**: Automatically detect errors and exceptions within the logs and analyze them using AI-powered tools provided by AIDA.
   - **Incident Notification**: Set up alerts and notifications for critical incidents, ensuring that developers are informed immediately about any issues.

3. **Implementation Steps**:
   - **Step 1**: Install and configure the 'aida-sdk' package in your Python environment. Refer to the official documentation for setup instructions.
   - **Step 2**: Design a simple UI (using frameworks like Flask or Django) where users can input details of their logging systems and select which types of events they want to monitor.
   - **Step 3**: Integrate 'aida-sdk' to capture logs and exceptions. Use the SDK's APIs to stream these incidents to the AIDA backend.
   - **Step 4**: Utilize AIDA’s AI capabilities to analyze the incoming data. Display insights and recommendations back to the user through the UI.
   - **Step 5**: Implement a notification system (SMS, email, etc.) to alert users about critical incidents detected by the tool.

4. **Additional Features**:
   - Allow users to customize the severity levels of alerts based on their preferences.
   - Provide historical data visualization for better understanding of past incidents.
   - Enable users to integrate third-party services for additional incident management actions.

5. **Testing**: Conduct thorough testing to ensure all functionalities work as expected. Pay special attention to the integration between 'aida-sdk' and the UI, and the accuracy of the incident analysis provided by AIDA.

This project aims to simplify the process of monitoring and managing incidents in real-time for developers, leveraging the power of AI and automation.