🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential risk, particularly concerning network security due to unverified HTTPS connections and metadata that suggests recent creation with little activity, raising suspicion about its legitimacy.

Network risk due to unverified HTTPS connections
Suspicious metadata with low activity and a new maintainer

Per-check LLM notes

Network: The use of unverified HTTPS connections may indicate potential risk, especially if the package is handling sensitive information.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating no immediate risk to secrets or credentials.
Metadata: Suspiciously low activity and new maintainer raises concerns about potential malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

) http_client = httpx.Client(verify=False) _client = OpenAI(api_key=api_key, htt

✓ 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: gmail.com

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks
Very few commits: 2 total
Single contributor with only 2 commit(s) — possibly throwaway account

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Devasish Banerjee" 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 agentmemory-openai

Create a personal knowledge management tool called 'MyBrain' using the Python package 'agentmemory-openai'. This tool will allow users to store, retrieve, and manage information in a conversational manner. Users can ask questions, add new facts, and even delete old ones as needed. Here’s a step-by-step guide on how to develop this tool:

1. **Setup**: Start by setting up a Python environment and installing the required packages including 'agentmemory-openai'.
2. **User Interface**: Design a simple command-line interface (CLI) where users can interact with 'MyBrain'. Ensure that the CLI provides clear prompts and feedback.
3. **Memory Storage**: Utilize 'agentmemory-openai' to store user inputs and responses. Each interaction should be saved along with metadata such as timestamp and context.
4. **Query Mechanism**: Implement a query system that allows users to search their stored memories based on keywords or specific contexts. The system should also support natural language queries.
5. **Update and Delete Functionality**: Enable users to update existing memories or delete them if they no longer wish to retain certain pieces of information.
6. **Contextual Recall**: Enhance the tool so that it can recall related memories when prompted, providing a more comprehensive answer to complex queries.
7. **Security Measures**: Since 'MyBrain' deals with potentially sensitive data, ensure that all stored information is encrypted and secure.
8. **Testing and Validation**: Before deployment, thoroughly test the tool to ensure all functionalities work as expected and are reliable.
9. **Documentation**: Provide detailed documentation explaining how to use 'MyBrain', its features, and any limitations.

Suggested Features:
- Voice Input/Output Support: Allow users to input queries and receive responses via voice commands.
- Integration with Calendar and Notes: Automatically sync relevant information from calendars and notes applications.
- Analytics Dashboard: Offer insights into usage patterns and memory retention rates.
- Multi-language Support: Make 'MyBrain' accessible to users worldwide by supporting multiple languages.

By following these steps and incorporating the suggested features, you'll create a robust and user-friendly knowledge management tool that leverages the power of 'agentmemory-openai'.