atp-platform

v2.0.0 suspicious
5.0
Medium Risk

Framework-agnostic platform for testing and evaluating AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits some potential risks that require further investigation, particularly concerning shell execution and metadata indicators.

  • Shell risk due to potential user-defined command execution.
  • Metadata risk from a non-existent repository and a single-package maintainer.
Per-check LLM notes
  • Network: The network calls appear to be standard HTTP requests, possibly for API interactions, which may be normal for a platform tool.
  • Shell: The shell executions involve Git commands and a potentially user-defined command ('uv sync'), which could indicate benign operations like version control or syncing, but also pose a risk if not properly controlled.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The repository is not found and the maintainer has only one package, which may indicate a new or less active account.

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/atp-platform/atp-platform
  • Detailed PyPI description (21159 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

  • 383 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 7.5

Found 5 network call pattern(s)

  • d: self._client = httpx.AsyncClient( timeout=httpx.Timeout(self._config.timeout_
  • y: self._client = httpx.AsyncClient( timeout=httpx.Timeout(
  • } async with httpx.AsyncClient(timeout=self._timeout) as client: response =
  • cts. """ with httpx.Client(timeout=60.0, follow_redirects=True) as client:
  • try: with smtplib.SMTP(smtp_host, smtp_port) as server: if
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • in or master)""" result = subprocess.run( ["git", "symbolic-ref", "refs/remotes/origin/HEAD"]
  • , "master"]: result = subprocess.run( ["git", "rev-parse", "--verify", branch],
  • ependencies...") result = subprocess.run( ["uv", "sync"], capture_output=True, text=True, cwd
  • t exists result = subprocess.run( ["git", "rev-parse", "--git-dir"],
  • in_branch(config) subprocess.run( ["git", "checkout", main_branch],
  • h exists result = subprocess.run( ["git", "rev-parse", "--verify", branch_nam
✓ 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 2.0

1 maintainer concern(s) found

  • Author "ATP Platform Contributors" 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 atp-platform 
Your task is to develop a simple yet functional application that showcases the capabilities of the 'atp-platform' Python package. This package serves as a framework-agnostic platform designed specifically for testing and evaluating AI agents. Your goal is to create a mini-application that allows users to simulate and evaluate different AI agent behaviors in a controlled environment. Here’s a detailed breakdown of your project requirements:

1. **Application Overview**: Create a command-line tool that allows users to define AI agents, set up environments for these agents to operate in, and run simulations to evaluate their performance.

2. **Agent Definition**: Users should be able to define AI agents using simple configurations. These configurations will include details such as the type of AI algorithm used, parameters for the algorithm, and any other relevant settings.

3. **Environment Setup**: Provide a mechanism for setting up different types of environments. Environments could range from simple grid-worlds to more complex scenarios like traffic simulation. Each environment should have its own set of rules and challenges for the AI agents.

4. **Simulation Execution**: Implement functionality that runs simulations where defined AI agents interact with the set-up environments. Simulations should be repeatable with the same setup to ensure consistency in evaluation.

5. **Performance Evaluation**: After each simulation, provide detailed metrics on how well the AI agents performed. Metrics could include success rates, efficiency scores, and other relevant performance indicators.

6. **Utilizing 'atp-platform'**: Throughout the development process, leverage the 'atp-platform' package to handle the core functionalities of agent definition, environment setup, simulation execution, and performance evaluation. This package provides tools and utilities that simplify the implementation of these features.

7. **Additional Features**:
   - Allow users to save and load agent definitions and environment setups for future use.
   - Implement a feature that compares the performance of multiple AI agents in the same environment.
   - Provide visualizations of simulation results for better understanding and analysis.

8. **Documentation**: Ensure your application is well-documented, including clear instructions on how to install dependencies, configure the application, and run simulations.

This project aims to demonstrate the versatility and power of the 'atp-platform' package in creating robust AI testing and evaluation applications.

💬 Discussion Feed

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