HackerGPT

HackerGPT is a cutting-edge AI tool designed explicitly for the cybersecurity sector, particularly beneficial for individuals involved in ethical hacking, such as bug bounty hunters.

This advanced assistant is at the cutting edge of cyber intelligence, offering a vast repository of hacking methods, tools, and tactics. More than a mere repository of information, HackerGPT actively engages with users, aiding them through the complexities of cybersecurity.

There are several ChatGPT-powered tools, such as OSINVGPT, PentestGPT, WormGPT, and BurpGPT, that have already been developed for the cyber security community, and HackerGPT is writing a new chapter for the same.

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What is the Purpose of HackerGPT:

It leverages the capabilities of ChatGPT, enhanced with specialized training data, to assist in various cybersecurity tasks, including network and mobile hacking, and understand different hacking tactics without resorting to unethical practices like jailbreaking.

HackerGPT generates responses to user queries in real-time, adhering to ethical guidelines. It supports both GPT-3 and GPT-4 models, providing users with access to a wide range of hacking techniques and methodologies.

The tool is available for use via a web browser, with plans to develop an app version in the future. It offers a 14-day trial with unlimited messages and faster response times.

HackerGPT aims to streamline the hacking process, making it significantly easier for cybersecurity professionals to generate payloads, understand attack vectors, and communicate complex technical results effectively.

This AI-powered assistant is seen as a valuable resource for enhancing security evaluations and facilitating the understanding of potential risks and countermeasures among both technical and non-technical stakeholders

Recently, HackerGPT released 2.0, and the beta is now available here.

Functionality of HackerGPT:

Upon posing a query to HackerGPT, the process begins with authentication of the user and management of query allowances, which differ for free and premium users.

The system then probes its extensive database to find the most relevant information to the query. For non-English inquiries, translation is employed to ensure the database search is effective.

If a suitable match is discovered, it is integrated into the AI’s response mechanism. The query is securely transmitted to OpenAI or OpenRouter for processing, ensuring no personal data is included. The response you receive depends on the module in use:

  • HackerGPT Module: A customized version of Mixtral 8x7B with semantic search capabilities tailored to our database.
  • GPT-4 Turbo: The most recent innovation from OpenAI, enhanced with our specialized prompts.
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Guidelines for Issues:
The “Issues” section is strictly for problems directly related to the codebase. We’ve noticed an influx of non-codebase-related issues, such as feature requests or cloud provider problems. Please consult the “Help” section under the “Discussions” tab for setup-related queries. Issues not pertinent to the codebase are typically closed promptly.

Engagement in Discussions:
We strongly encourage active participation in the “Discussions” tab! It’s an excellent platform for asking questions, exchanging ideas, and seeking assistance. Chances are, others might have the same question if you have a question.

Updating Process:
To update your local Chatbot UI repository, navigate to the root directory in your terminal and execute:

npm run update

For hosted instances, you’ll also need to run:

npm run db-push

This will apply the latest migrations to your live database.

Setting Up Locally:
To set up your own instance of Chatbot UI locally, follow these steps:

  1. Clone the Repository:
git clone https://github.com/mckaywrigley/chatbot-ui.git
  1. Install Dependencies:

Navigate to the root directory of your local Chatbot UI repository and run:

npm install
  1. Install Supabase & Run Locally:

Supabase is chosen for its ease of use, open-source nature, and free tier for hosted instances. It replaces local browser storage, addressing security concerns, storage limitations, and enabling multi-modal use cases.

  • Install Docker: Necessary for running Supabase locally. Download it for free from the official site.
  • Install Supabase CLI: Use Homebrew for macOS/Linux or Scoop for Windows.
  • Start Supabase: Execute supabase start in your terminal at the root of the Chatbot UI repository.
  • Fill in Secrets: Copy the .env.local.example file to .env.local and populate it with values obtained from supabase status.
  1. Optional Local Model Installation:

For local models, follow the instructions provided for Ollama installation.

  1. Run the App Locally:

Finally, run npm run chat in your terminal. Your local instance should now be accessible at http://localhost:3000.

Setting Up a Hosted Instance:

To deploy your Chatbot UI instance in the cloud, follow the local setup steps here . Then, create a separate repository for your hosted instance and push your code to GitHub.

Set up the backend with Supabase by creating a new project and configuring authentication. Connect to the hosted database and configure the frontend with Vercel, adding necessary environment variables. Deploy, and your hosted Chatbot UI instance should be live and accessible through the Vercel-provided URL. You can read the complete GitHub repository here.

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