🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of legitimacy but the network risk and metadata risk elevate concerns, especially given the unverified maintainer and repository status.

network risk 5/10
metadata risk 5/10

Per-check LLM notes

Network: The observed network call patterns could be legitimate if the package is designed to interact with external services, but they also raise concerns about potential data exfiltration or command and control communications.
Shell: No shell execution patterns were detected, indicating low risk of direct system command execution.
Obfuscation: No obfuscation patterns detected, suggesting low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The repository is not found and the maintainer has a new or inactive account, which raises some suspicion.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

t=str).encode() req = urllib.request.Request( url, data=data,
try: with urllib.request.urlopen(req, timeout=self._timeout): pass

✓ 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 4.0

2 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Takumu Hata" 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 agentblackbox

Create a mini-application named 'AgentTracker' that uses the 'agentblackbox' package to monitor and analyze the behavior of AI agents in a simulated environment. This application will serve as a 'flight recorder' for AI agents, logging all their decisions, tool calls, and any failures they encounter during a series of tasks. Here are the steps and features you should include:

1. **Setup Environment**: Begin by setting up a Python virtual environment and installing necessary packages including 'agentblackbox'.
2. **Define Tasks**: Create a set of predefined tasks for the AI agents to perform. These tasks could range from simple problem-solving tasks to more complex scenarios involving interaction with external tools.
3. **Integrate AgentBlackBox**: Utilize 'agentblackbox' to log every action taken by the AI agents, including decisions made, tools called upon, and any errors encountered. Ensure that this data is stored in a structured format that allows for easy retrieval and analysis.
4. **Visual Analytics Dashboard**: Develop a simple web-based dashboard using Flask or Django that visualizes the logged data. This dashboard should allow users to filter logs based on different criteria such as time, task type, or specific agent actions.
5. **Analysis Tools**: Implement basic analysis tools within the dashboard to help understand patterns in agent behavior. For example, identify common failure points, frequently used tools, and trends over time.
6. **Simulation Module**: Add a simulation module that allows users to run multiple iterations of tasks with varying parameters (e.g., changing the difficulty of tasks or introducing new tools) and observe how these changes affect agent performance.
7. **Export Functionality**: Provide functionality to export the logged data into various formats like CSV or JSON for further offline analysis.
8. **Documentation**: Write comprehensive documentation detailing how to install and use 'AgentTracker', including examples of how to integrate it with different types of AI agents.

By completing this project, you will have a powerful tool for monitoring and improving the performance of AI agents in a variety of applications.