aodhclient

v3.11.0 suspicious
4.0
Medium Risk

Python client library for Aodh

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate level of risk due to its network activity and the lack of detailed maintainer metadata.

  • network risk due to external endpoint calls
  • maintainer metadata lacking detailed information
Per-check LLM notes
  • Network: The package makes network calls to external endpoints which could indicate legitimate functionality but also raises concerns about potential unauthorized data transmission.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The maintainer has a new or inactive account and lacks detailed information, which raises some suspicion but does not conclusively indicate malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 13 test file(s) found

  • 13 test file(s) detected (e.g. base.py)
◈ Medium Documentation 7.0

Some documentation present

  • 1 documentation file(s) (e.g. conf.py)
  • Brief PyPI description (783 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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 score 3.0

Found 2 network call pattern(s)

  • enerate_uuid() req = requests.post( os.environ.get("GNOCCHI_ENDPOINT") + "/v1/resou
  • er_image_size" req = requests.get( os.environ.get("PROMETHEUS_ENDPOINT") +
✓ 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: lists.openstack.org>

✓ 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

  • 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 aodhclient 
Create a monitoring tool named 'AlertWatcher' using the Python package 'aodhclient'. This tool will allow users to monitor specific metrics in their OpenStack environment and set up alerts based on predefined thresholds. Here’s a step-by-step guide to building this application:

1. **Setup Environment**: Ensure you have Python installed along with pip. Install the 'aodhclient' package via pip.
2. **Authentication**: Implement a function to authenticate with the OpenStack Identity service (Keystone). Use 'aodhclient' to establish a connection to the Aodh service.
3. **Metric Monitoring**: Allow users to specify which metrics they want to monitor. Utilize 'aodhclient' to retrieve metric data from Aodh.
4. **Threshold Alerts**: Users should be able to define alert thresholds for these metrics. If a metric exceeds or falls below the threshold, 'AlertWatcher' should trigger an alert.
5. **Alert Actions**: When an alert is triggered, 'AlertWatcher' should perform actions such as sending an email notification or logging the event.
6. **User Interface**: Develop a simple command-line interface (CLI) for users to interact with 'AlertWatcher', including options to add new metrics, set thresholds, and view alert history.
7. **Testing and Validation**: Test 'AlertWatcher' thoroughly to ensure it correctly monitors metrics and triggers alerts under various conditions.

Suggested Features:
- Support for multiple alert thresholds per metric.
- Option to configure alert notifications (email, logging).
- Ability to save user configurations and settings persistently.
- Detailed logging of all events and alerts for auditing purposes.
- User-friendly CLI commands and help documentation.

Utilize 'aodhclient' to interact with the Aodh API for fetching metric data and setting up alarms. Your goal is to create a robust, user-friendly monitoring tool that integrates seamlessly with OpenStack environments.

💬 Discussion Feed

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