🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no direct signs of malicious activity but the metadata risk score is elevated due to sparse author information and a single maintained package, which raises some concerns about its provenance.

Metadata risk is moderately high
Shell execution detected but with benign use cases

Per-check LLM notes

Network: No network calls detected, indicating low risk.
Shell: Shell execution is used for local command execution, likely for functionalities like running Docker commands, which suggests moderate risk but not necessarily malicious intent without additional context.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The author's information is sparse and the maintainer has only one package, which may indicate a less established or potentially suspicious account.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

s platforms process = subprocess.Popen(cmd) # Set up signal handler to forward signals to
] try: result = subprocess.run(cmd, check=False) sys.exit(result.returncode) ex
") try: result = subprocess.run(cmd, check=False) if result.returncode == 0:
se try: result = subprocess.run( ["docker", "info"], capture_output=
Desktop result = subprocess.run( ["open", "-a", "Docker"], c

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ 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 aegra-cli

Create a fully-functional mini-application called 'AgentDeployer' using the Python package 'aegra-cli'. This application will streamline the process of deploying and managing self-hosted agents across multiple environments. The goal is to provide an easy-to-use interface for users to manage their agent deployments, including starting, stopping, updating, and monitoring these agents.

Step-by-Step Requirements:
1. Installation: Ensure that the user can install the 'AgentDeployer' application via pip or another standard Python package manager.
2. Configuration: Allow users to configure their environment settings such as specifying the deployment directory, agent configurations, and network settings through a configuration file or command-line arguments.
3. Deployment Management: Implement commands within the 'AgentDeployer' application that utilize 'aegra-cli' to start, stop, update, and monitor the status of deployed agents. Each command should be intuitive and easy to use, providing clear feedback on the action's success or failure.
4. Monitoring and Logging: Integrate logging capabilities into 'AgentDeployer' so that it can capture and display real-time logs from running agents. Additionally, allow users to view historical logs for troubleshooting purposes.
5. Security Enhancements: Provide options for securing agent communications and data storage. For example, support for encrypted configuration files and secure communication protocols between the 'AgentDeployer' and the agents.
6. User Interface: Develop a simple yet effective command-line interface (CLI) for interacting with 'AgentDeployer'. Commands should be well-documented and accessible through a help menu.
7. Testing and Documentation: Include comprehensive testing for each feature of 'AgentDeployer', ensuring reliability and ease of use. Also, provide thorough documentation explaining how to install, configure, and use 'AgentDeployer'.

Suggested Features:
- Support for multiple deployment profiles, allowing users to easily switch between different environments (e.g., development, staging, production).
- Automatic agent updates based on specified schedules or triggers.
- Integration with popular CI/CD tools for automated deployment processes.
- Detailed analytics on agent performance and resource usage.
- Support for agent clustering and load balancing.

How 'aegra-cli' is Utilized:
- Use 'aegra-cli' to execute deployment-related tasks such as initializing new agent instances, configuring existing ones, and performing health checks. 'aegra-cli' commands should be invoked through 'AgentDeployer', acting as a bridge between the user's input and the underlying management operations of the agents.