anosys-sdk-openai-agents

v1.0.12 suspicious
4.0
Medium Risk

AnoSys SDK for OpenAI Agents - Automatic instrumentation and logging for OpenAI Agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate network activity that appears to be logging, and the metadata suggests it may come from a less established source, raising some suspicion.

  • Moderate network risk due to logging activities.
  • Incomplete author information and single-package maintainer.
Per-check LLM notes
  • Network: The observed network calls appear to be logging activities, which could be legitimate if the package is designed for analytics or telemetry.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of secrets.
  • Metadata: The author information is incomplete and the maintainer has a single package, which could indicate a less established or potentially suspicious account.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_openai_agents.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.anosys.ai
  • Detailed PyPI description (2091 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

  • 12 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 85 commits in anosys-ai/anosys-sdk
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • response = requests.post(_log_api_url, json=cleaned_data, timeout=5)
  • ormed) response = requests.post(self.log_api_url, json=cleaned_transformed, timeout=5)
✓ 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: anosys.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository anosys-ai/anosys-sdk appears legitimate

⚠ 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 anosys-sdk-openai-agents 
Create a fully functional mini-application called 'AgentMonitor' which leverages the 'anosys-sdk-openai-agents' package to monitor and log interactions between users and OpenAI agents in real-time. This application will serve as a tool for developers and researchers to better understand user-agent interactions, optimize agent performance, and improve user experience. Here are the steps and features to implement:

1. **Setup**: Begin by installing the required packages including 'anosys-sdk-openai-agents'. Ensure your development environment is set up with Python and any necessary dependencies.
2. **User Interface**: Develop a simple yet effective web interface using Flask or Django. This UI should allow users to initiate conversations with an OpenAI agent and display logs of these interactions in real-time.
3. **Logging and Instrumentation**: Utilize 'anosys-sdk-openai-agents' to automatically instrument and log all interactions between users and the OpenAI agent. Logs should capture timestamps, user inputs, agent responses, and any errors encountered during the interaction.
4. **Real-Time Monitoring**: Implement a feature that allows users to view these logs in real-time within the web interface. This could involve using WebSocket technology to push updates from the server to the client.
5. **Customizable Agent Configuration**: Provide options for users to customize the behavior of the OpenAI agent, such as adjusting response times or changing the tone of the responses, through settings defined via 'anosys-sdk-openai-agents'.
6. **Analytics Dashboard**: Create a dashboard within the web application that provides analytics on agent performance based on logged data. Metrics could include average response time, error rates, and user satisfaction scores derived from interaction logs.
7. **Security Measures**: Ensure that all user data is handled securely, adhering to best practices for data protection and privacy.
8. **Documentation**: Write comprehensive documentation for both users and developers explaining how to use 'AgentMonitor', configure the OpenAI agent, and interpret the logs and analytics provided by the application.

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