AI Analysis
Final verdict: SAFE
The package shows minimal risks across all assessed categories. Although the metadata risk is slightly elevated due to the maintainer's limited package history, there is no concrete evidence of malicious intent.
- Low network, shell, obfuscation, and credential risks
- Elevated metadata risk due to limited package history
Per-check LLM notes
- Network: The observed network calls are typical for an API-based service interaction, likely for authentication and key management purposes.
- Shell: No shell execution patterns detected, indicating no immediate risk associated with unauthorized system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which could indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (3.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (2748 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
51 type-annotated function signatures detected in source
○ 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 7.5
Found 5 network call pattern(s)
e_url) self._client = httpx.Client( headers={"X-API-Key": api_key, "Content-Type":_url(base_url) resp = httpx.post( f"{base_url}/v1/keys", json={"agent_url(base_url) resp = httpx.post( f"{base_url}/v1/admin/keys", json={_url(base_url) resp = httpx.post( f"{base_url}/v1/admin/minting", jsoe_url) self._client = httpx.AsyncClient( headers={"X-API-Key": api_key, "Content-Type":
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
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Oakstack" 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 backchannel-sdk
Develop a real-time collaboration tool for AI agents using the 'backchannel-sdk' Python package. This tool will enable multiple AI agents to communicate and coordinate tasks in a secure and ephemeral manner, ensuring that messages are not stored beyond the duration of their usefulness. The application should include the following features: 1. **Agent Registration**: Allow users to register AI agents with unique identifiers. Each agent will need to authenticate to ensure secure communication. 2. **Message Bus Initialization**: Use the 'backchannel-sdk' to initialize an ephemeral message bus. This bus will serve as the communication channel between agents. 3. **Real-Time Messaging**: Implement a feature where agents can send and receive messages in real-time. Messages should be deleted from the bus once they have been processed, adhering to the ephemeral nature of Backchannel. 4. **Task Coordination**: Enable agents to coordinate tasks by sending task requests and responses through the message bus. For example, one agent might request data processing from another, and the receiving agent would respond with the results. 5. **Error Handling**: Ensure that the application gracefully handles errors such as failed connections, authentication failures, and message processing issues. 6. **Logging and Monitoring**: Include logging capabilities to monitor the communication between agents and track any issues that arise during operation. 7. **User Interface (Optional)**: While primarily a command-line interface (CLI) application, consider adding a simple web-based user interface for monitoring the status of agents and messages. To utilize the 'backchannel-sdk', start by installing the package via pip. Then, use its functions to set up the message bus, manage agent connections, and handle message transmission. The goal is to demonstrate how the SDK can facilitate seamless and secure communication between AI agents in real-world applications.
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