aorta-sirius-dev

v0.275 suspicious
4.0
Medium Risk

(No description)

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits medium risk due to its network behavior and metadata indicators, suggesting potential security concerns despite no direct evidence of malicious activity.

  • Unverified SSL connections during network calls
  • Maintainer's new or inactive account and lack of detailed package metadata
Per-check LLM notes
  • Network: The package makes network calls to pypi.org, which could be legitimate for version checking or updates, but the use of unverified SSL connections raises suspicion.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The maintainer's new or inactive account and lack of PyPI classifiers suggest low effort or potential inactivity, raising some suspicion.

📦 Package Quality Overall: Low (3.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
◈ Medium Contributing Guide 7.0

Some contribution signals present

  • Governance file: security.py
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 140 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 6.0

Found 4 network call pattern(s)

  • nse response: Response = requests.get(f"https://pypi.org/pypi/{get_package_name()}/json") asse
  • httpx.AsyncClient] = lambda: httpx.AsyncClient(timeout=httpx.Timeout(connect=5.0, read=read_timeout, write=
  • rl) _session.client = httpx.AsyncClient(verify=False, timeout=60) return _session class IBKRE
  • # } # # async with httpx.AsyncClient() as client: # response: httpx._models.Response = aw
✓ 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: kih.com.sg

✓ 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 4.0

2 maintainer concern(s) found

  • Author "Kavindu Athaudha" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aorta-sirius-dev 
Develop a real-time data monitoring and alerting tool using the 'aorta-sirius-dev' Python package. This tool will serve as a comprehensive solution for tracking critical metrics from various sources and sending out alerts when predefined thresholds are breached. The application should have the following key features:

1. **Data Source Integration**: The tool must be able to connect to multiple data sources such as APIs, databases, or IoT devices to fetch real-time data.
2. **Threshold-Based Alerts**: Users should be able to set up custom thresholds for each metric being monitored. When a metric crosses its threshold, the system should trigger an alert.
3. **Alert Notification**: Upon triggering an alert, the system should notify users via email, SMS, or push notifications.
4. **Dashboard Visualization**: A simple yet effective dashboard should display all the metrics being monitored in real-time, with clear visual indicators of any active alerts.
5. **Configuration Management**: Provide an intuitive configuration interface where users can manage their data sources, thresholds, and notification settings.
6. **Logging and Reporting**: Implement logging of all events and generate periodic reports summarizing the activity.

To achieve these functionalities, you will heavily rely on the 'aorta-sirius-dev' package, which provides essential tools for data processing, alert generation, and integration with external services. Your task is to explore the package documentation and understand its core capabilities, then integrate them into your application design. Ensure that your application is scalable and maintainable, allowing for easy addition of new data sources and alert types in the future.