🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential risk, particularly concerning incomplete metadata and the use of HTTP requests, though no concrete evidence of malicious activity was found.

incomplete maintainer's author information
use of HTTP requests without clear context

Per-check LLM notes

Network: The use of HTTP requests via the 'httpx' library is common and not inherently suspicious; however, without clear documentation or context, it could indicate potential data exfiltration.
Shell: No shell execution patterns detected, which suggests a lower risk of executing arbitrary commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer's author information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 21 test file(s) found

Test runner config found: pyproject.toml
21 test file(s) detected (e.g. test_auth.py)

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://github.com/agentveil-protocol/agentveil-sdk#readme
Detailed PyPI description (5924 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

253 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 100 commits in agentveil-protocol/agentveil-sdk
Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

rough other code paths (raw ``requests.post(...)``, raw sockets, subprocesses, other libraries) are
= None) -> dict: with httpx.Client(base_url=self._base_url, timeout=self._timeout) as c:
y_data).encode() with httpx.Client(base_url=self._base_url, timeout=self._timeout) as c:
= None) -> str: with httpx.Client(base_url=self._base_url, timeout=self._timeout) as c:

✓ 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: agentveil.dev>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository agentveil-protocol/agentveil-sdk appears legitimate

⚠ 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 agentveil

Create a secure access control system using the 'agentveil' Python package. This system will manage access permissions for various agents (users or services) based on their actions and roles. Here’s a detailed plan for building this mini-app:

1. **Project Setup**: Initialize a new Python project. Install the necessary packages including 'agentveil'. Ensure your environment is set up correctly.
2. **User Authentication**: Implement a basic user authentication system where users can log in with credentials. For simplicity, use a hardcoded list of users and passwords.
3. **Role-Based Access Control (RBAC)**: Define different roles such as 'admin', 'editor', and 'viewer'. Each role will have specific permissions defined by 'action gates' from the 'agentveal' package.
4. **Action Gates Implementation**: Use 'agentveal' to define action gates that check if a user is allowed to perform certain actions based on their role. For example, an 'admin' can create, read, update, and delete data, while a 'viewer' can only read data.
5. **Posture Checks**: Implement posture checks to verify the security posture of the environment before allowing actions. This could include checking for outdated software versions or missing security patches.
6. **Signed Receipts**: After an action is performed, generate signed receipts using 'agentveal'. These receipts should confirm that the action was successfully executed within the security policy constraints.
7. **Proof Packets**: Create proof packets that contain evidence of the actions taken by each agent. These packets should be verifiable by other systems to ensure integrity and non-repudiation.
8. **Security Audit Logs**: Maintain logs of all actions performed, including failed attempts, and store them securely. Use these logs for auditing purposes.
9. **User Interface**: Develop a simple command-line interface (CLI) for users to interact with the system. This CLI should allow users to log in, view their permissions, and perform actions based on their role.
10. **Testing**: Thoroughly test the application to ensure that all security measures are functioning as expected. Verify that unauthorized actions are blocked, and all actions are logged and receipted properly.

This project aims to demonstrate the capabilities of the 'agentveal' package in managing complex access controls and ensuring security in a multi-agent environment.