🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of potential risks with no evidence of malicious activities. However, the unavailability of the repository and the maintainer's low activity level introduce some uncertainty.

Low network, shell, obfuscation, and credential risks.
Repository not found, single-package maintainer with low activity.

Per-check LLM notes

Network: The network call pattern suggests the package is making HTTP requests, possibly to an API endpoint. This could be legitimate if the package interacts with external services like OpenAI.
Shell: No shell execution patterns detected, indicating low risk for executing system commands without explicit user input.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
Metadata: The repository is not found and the maintainer has only one package, which may indicate low activity or a new account.

📦 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 (2105 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

10 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

losed self._session = requests.Session() self._session.headers.update({ "Conten

✓ 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: antarraksha.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 2.0

1 maintainer concern(s) found

Author "Akash Kumar Dey" 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 antarraksha-openai-agents

Create a fully-functional mini-app called 'SecurityGuard' using the Python package 'antarraksha-openai-agents'. This app will serve as an AI-driven security system that monitors and enforces security policies in real-time environments, such as corporate networks or cloud infrastructures. The primary goal of SecurityGuard is to detect anomalies, enforce security protocols, and manage access control efficiently.

Steps to create SecurityGuard:
1. Set up a virtual environment and install the required dependencies, including 'antarraksha-openai-agents'.
2. Design the core functionalities of SecurityGuard, focusing on anomaly detection, policy enforcement, and access control management.
3. Implement a user-friendly interface for configuring security policies and monitoring the system status.
4. Integrate the 'antarraksha-openai-agents' package to leverage its capabilities in enforcing AI-driven security measures.
5. Test the application thoroughly under various scenarios to ensure it performs as expected.
6. Document the setup process, configuration options, and usage guidelines for end-users.

Suggested Features:
- Real-time monitoring of network traffic and system logs for anomaly detection.
- Automated response mechanisms to security threats based on predefined policies.
- Dynamic access control management based on user roles and permissions.
- Detailed reporting and alerting systems for security incidents.
- Integration with existing security tools and platforms for seamless operation.

How 'antarraksha-openai-agents' is Utilized:
- Use the SDK provided by 'antarraksha-openai-agents' to implement AI-driven security measures.
- Leverage the enforcement capabilities of the SDK to automatically apply security policies.
- Utilize the SDK's monitoring functions to continuously evaluate the security posture of the system.
- Implement the SDK's access control features to dynamically manage user permissions and access levels.