authsec-langgraph-sdk

v0.1.0 suspicious
4.0
Medium Risk

AuthSec identity and delegation for LangGraph stateful agent workflows

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network calls, shell execution, and obfuscation. However, the metadata risk score is elevated due to missing repository and sparse author details, which raises suspicion.

  • Metadata risk score is high at 6 out of 10
  • Non-existent repository and limited author information
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows several red flags including a non-existent repository and an author with limited information, suggesting potential risk.

📦 Package Quality Overall: Medium (5.2/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. test_node.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.authsec.ai
  • Detailed PyPI description (4597 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

  • 9 type-annotated function signatures (partial)
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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: authsec.ai>

✓ 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 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 authsec-langgraph-sdk 
Create a mini-application called 'Secure Workflow Manager' that leverages the 'authsec-langgraph-sdk' package to manage secure workflows for stateful agents. This application should allow users to define, execute, and monitor workflows while ensuring that each step is authenticated and authorized properly. Here’s a detailed breakdown of the steps and features your application should include:

1. **User Authentication**: Implement a simple user authentication system where users can sign up, log in, and manage their profiles. Use 'authsec-langgraph-sdk' to handle the security aspects of user identities.
2. **Workflow Definition**: Allow users to define custom workflows. Each workflow should consist of a series of steps, with each step having specific actions that need to be executed. Utilize the 'authsec-langgraph-sdk' to ensure that only authorized users can define or modify workflows.
3. **Step Authorization**: For each step in a workflow, specify which users or roles are allowed to execute it. Again, rely on 'authsec-langgraph-sdk' to enforce these authorization rules.
4. **Execution Tracking**: Track the execution of workflows, recording which steps have been completed and by whom. Use 'authsec-langgraph-sdk' to securely store and retrieve this information.
5. **Monitoring Interface**: Provide a monitoring interface where users can view the status of all active workflows, including any errors encountered during execution. Ensure that access to this interface is controlled based on user permissions using 'authsec-langgraph-sdk'.
6. **Error Handling**: Implement robust error handling to manage cases where a step in a workflow fails. Use 'authsec-langgraph-sdk' to log and audit these errors securely.
7. **Documentation**: Include comprehensive documentation detailing how to set up and use the 'Secure Workflow Manager', as well as how to integrate it into existing systems.

By utilizing 'authsec-langgraph-sdk', your application will provide a secure environment for managing complex workflows, ensuring that only authorized actions are taken at each step. This project will showcase the capabilities of the package in real-world scenarios.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!