🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential misuse, particularly due to the unavailability of the git repository and the presence of base64 encoding. However, the lack of network calls, shell risks, and credential risks keeps the overall score moderate.

Unavailability of git repository
Use of base64 encoding

Per-check LLM notes

Network: No network calls detected, which is normal and expected.
Shell: Git commands are used to check the current state of the repository, likely for version control purposes.
Obfuscation: The use of base64 decoding suggests some level of obfuscation, but it could be for legitimate purposes such as data encryption.
Credentials: No clear signs of credential harvesting detected.
Metadata: The maintainer has only one package and the git repository is not found, which raises some suspicion.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

try: decoded = base64.b64decode(normalized, validate=True) except (binascii.Error, V

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

y]]: try: subprocess.run( ["git", "rev-parse", "--git-dir"], capture_
) commit_hash = subprocess.run( ["git", "rev-parse", "HEAD"], capture_outpu
.strip() branch = subprocess.run( ["git", "branch", "--show-current"], captur
.strip() status = subprocess.run( ["git", "status", "--porcelain", "--untrack

✓ 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 "Diego ZoracKy" 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 agentdeck-ai

Create a mini-application that simulates a simple game environment for AI agents using the 'agentdeck-ai' package. This application will allow users to design and run different game scenarios to observe and analyze the behavior of AI agents under various conditions. Here’s a step-by-step guide on how to build this application:

1. **Setup Project Environment**: Start by setting up a Python virtual environment and installing the 'agentdeck-ai' package.
2. **Define Game Scenarios**: Use 'agentdeck-ai' to define at least three distinct game scenarios. Each scenario should have its own rules, objectives, and challenges for the AI agents.
3. **Implement AI Agents**: Develop a set of AI agents that can participate in these games. These agents could use different strategies or algorithms to achieve their goals within the game scenarios.
4. **User Interface**: Create a basic user interface where users can select which game scenario they want to run and observe the interactions between the AI agents in real-time.
5. **Data Collection and Analysis**: Implement functionality to collect data from each game session, such as agent performance metrics, decision-making patterns, and other relevant statistics. Provide tools for analyzing this data to draw insights about the AI behaviors.
6. **Customization Options**: Allow users to customize certain aspects of the game scenarios and AI agents, such as adjusting parameters, adding new rules, or even designing new agents.
7. **Documentation and Instructions**: Ensure that your application comes with comprehensive documentation explaining how to install, configure, and use the application effectively.

This project will not only demonstrate the capabilities of the 'agentdeck-ai' package but also provide a practical tool for educational purposes and behavioral research in AI.