🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a suspicious metadata profile with a lack of maintainer history and an untraceable repository, raising concerns about its legitimacy despite showing no immediate technical risks.

Lack of maintainer history
Untraceable repository

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 of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
Metadata: The package shows signs of being potentially malicious due to the lack of maintainer history and an untraceable repository.

🔬 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

No author email provided

✓ 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 agentguard-runtime

Create a Python-based mini-application named 'SecureLangAgent' that leverages the 'agentguard-runtime' package to secure interactions between users and a LangChain agent. This application will serve as a runtime security firewall, ensuring that all tool calls made by the LangChain agent adhere to predefined security policies. The application should have the following functionalities:

1. **Policy Definition**: Allow users to define security policies using YAML files. These policies should specify which tools the LangChain agent is allowed to call, under what conditions, and any additional constraints.
2. **Runtime Enforcement**: Utilize 'agentguard-runtime' to intercept every tool call made by the LangChain agent during runtime. Enforce the defined YAML policies on these calls to ensure they comply with the security rules set by the user.
3. **Logging Mechanism**: Implement logging of all intercepted tool calls to an SQLite database. Each log entry should include details such as the timestamp, the tool called, the parameters passed, whether the call was allowed or denied, and the reason for any denial.
4. **User Interface**: Develop a simple command-line interface (CLI) that allows users to interact with the application. Users should be able to load policies, start the LangChain agent with the runtime security enabled, view logs, and manage exceptions dynamically.
5. **Dynamic Policy Management**: Provide the capability to update and reload policies without restarting the application, ensuring flexible security management.
6. **Exception Handling**: Include robust error handling to gracefully manage any issues that arise during policy enforcement or logging, providing clear feedback to the user through the CLI.

The 'agentguard-runtime' package will be central to the enforcement and interception logic, serving as the backbone of the runtime security mechanism. Your task is to design and implement this mini-application, ensuring it is modular, easy to extend, and well-documented. Additionally, consider writing unit tests to verify the functionality of each component.