argus-shield

v0.2.1 suspicious
4.0
Medium Risk

ARGUS Python SDK - Framework-agnostic AI agent guardrails and safety tool

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some legitimate use cases but raises concerns due to low community engagement and limited maintainer activity.

  • Metadata risk score of 6 out of 10 due to low community engagement and limited maintainer activity.
  • No significant risks detected in network, shell, obfuscation, or credential handling.
Per-check LLM notes
  • Network: The observed network calls are typical for an API interaction, suggesting the package likely uses HTTP requests to communicate with a server.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's lack of community engagement and the maintainer's limited activity raise concerns about potential malicious intent.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • 5 test file(s) detected (e.g. test_client.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://argus-nine-opal.vercel.app/docs
  • Detailed PyPI description (2242 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

  • 39 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 94 commits in tanishra/argus
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • .api_key self.http = httpx.Client(base_url=self.base_url, headers=headers, timeout=60.0)
  • .api_key self.http = httpx.AsyncClient(base_url=self.base_url, headers=headers, timeout=60.0)
  • } } resp = httpx.post(url, json=payload, headers=headers, timeout=10.0) re
  • ] } resp = httpx.post(url, json=payload, headers=headers, timeout=10.0) re
  • } resp = httpx.post(url, json=payload, headers=headers, timeout=5.0)
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 argus-shield 
Create a command-line utility named 'Guardian' using the Python package 'argus-shield'. This utility will serve as a framework-agnostic tool to monitor and enforce safety protocols for AI agents within a system. Your task is to design and implement a robust application that allows users to define safety rules and monitor AI agent behavior in real-time. Here are the key functionalities you need to include:

1. **Rule Definition**: Users should be able to specify safety rules through command-line arguments. These rules could include constraints on data usage, ethical guidelines, or operational limits.
2. **Agent Monitoring**: Implement a feature that continuously monitors AI agents for compliance with the defined rules. This monitoring should be capable of identifying potential violations and alerting the user.
3. **Violation Handling**: When a violation is detected, the application should take predefined actions, such as logging the event, pausing the agent, or applying corrective measures.
4. **Customizability**: Allow users to customize the types of violations and responses through configuration files or additional command-line options.
5. **Reporting**: Provide a reporting mechanism that summarizes the compliance status of monitored agents over time, highlighting any issues or trends.

Utilize the 'argus-shield' package to handle the enforcement and monitoring of these safety rules. Ensure your implementation leverages the package's capabilities for defining and enforcing guardrails effectively. Additionally, document your code thoroughly and provide clear instructions for setting up and running the 'Guardian' utility.

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