https://github.com/shivadharmi/cybersecurity-research-assistant
An advanced project for a cybersecurity research assistant utilizing Python, LangGraph, and various agents for comprehensive threat analysis and reporting.
https://github.com/shivadharmi/cybersecurity-research-assistant
botnet chatgpt cybersecurity cybersecurity-events gpt-4o langgraph llm malware python python3 ransomware vulnerability
Last synced: 11 months ago
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An advanced project for a cybersecurity research assistant utilizing Python, LangGraph, and various agents for comprehensive threat analysis and reporting.
- Host: GitHub
- URL: https://github.com/shivadharmi/cybersecurity-research-assistant
- Owner: shivadharmi
- Created: 2024-10-28T18:35:48.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-28T19:25:05.000Z (over 1 year ago)
- Last Synced: 2025-02-09T20:16:45.690Z (over 1 year ago)
- Topics: botnet, chatgpt, cybersecurity, cybersecurity-events, gpt-4o, langgraph, llm, malware, python, python3, ransomware, vulnerability
- Language: Python
- Homepage:
- Size: 43 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Cybersecurity Research Assistant with LangGraph Integration
An advanced project for a cybersecurity research assistant utilizing Python, LangGraph, and various agents for comprehensive threat analysis and reporting.
## Project Overview
This project showcases a sophisticated cybersecurity research assistant capable of gathering, analyzing, and summarizing information on vulnerabilities, ransomware, and cyber security events. It integrates multiple agents for specialized tasks, leveraging LangGraph for managing complex workflows and OpenAI's GPT models for natural language processing.
Key features:
- Multi-agent architecture for diverse cybersecurity tasks
- Real-time data gathering and analysis
- Natural language understanding and generation with OpenAI GPT models
- Comprehensive reporting capabilities
- Customizable parameters for different research scenarios
## Prerequisites
- Python 3.12+
- uv (An extremely fast Python package and project manager, written in Rust.)
- LangGraph CLI (optional, for easy environment setup)
## Installation
1. Clone the repository:
```console
git clone git@github.com:shivadharmi/cybersecurity-research-assistant.git
cd cybersecurity-research-assistant
```
## Setting Up `uv` and `ruff`
1. Install `uv`:
- For macOS and Linux:
```console
curl -LsSf https://astral.sh/uv/install.sh | sh
```
- For Windows:
```console
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```
2. Set up a virtual environment:
```console
uv venv --python 3.12.0
source .venv/bin/activate # On Windows, use `.venv\Scripts\activate`
```
3. Install `ruff` as a development dependency:
```console
uv add --dev ruff
```
4. Install `pre-commit` and configure the hook:
```console
uv add --dev pre-commit
pre-commit install
```
5. Install dependencies:
```console
uv add -r requirements.txt
```
6. Run pre-commit on all files:
```console
pre-commit run --all-files
```
## Environment Setup
1. Copy the example environment file:
```console
cp ./env/.env.example ./env/.env
```
2. Edit `.env.local` and fill in the required values:
- `OPENAI_API_KEY`
- `TAVILY_API_KEY`
- Any other necessary API keys for external services
## Running the Research Assistant
Start the cybersecurity research assistant by executing the `main.py` script with the desired agent and optional parameters. Here’s how to run it:
```console
python main.py [--month ] [--year ]
```
### Arguments
- ``: Specify which agent to run. Choices include:
- `vulnerability`: Analyze vulnerabilities.
- `ransomware`: Analyze ransomware threats.
- `events`: Analyze cyber security events.
- `cisa`: Get CISA-related information.
- `full`: Generate a comprehensive report.
- `--month `: (Optional) Specify the month to analyze (default is `September`).
- `--year `: (Optional) Specify the year to analyze (default is `2024`).
### Example Usage
To run the vulnerability agent for September 2024:
```console
python main.py vulnerability --month September --year 2024
```
To run the full report for October 2023:
```console
python main.py full --month October --year 2023
```
## Roadmap
- **Weekly Reports**: Implement functionality to generate weekly cybersecurity reports in addition to the existing monthly reports. This will allow for more frequent updates and timely insights into cybersecurity threats and vulnerabilities.
- **Daily Reports**: Explore the possibility of generating daily cybersecurity reports to provide real-time insights and updates on emerging threats and vulnerabilities.