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12 changes: 6 additions & 6 deletions README.md
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HackingBuddyGPT helps security researchers use LLMs to discover new attack vectors and save the world (or earn bug bounties) in 50 lines of code or less. In the long run, we hope to make the world a safer place by empowering security professionals to get more hacking done by using AI. The more testing they can do, the safer all of us will get.

We aim to become **THE go-to framework for security researchers** and pen-testers interested in using LLMs or LLM-based autonomous agents for security testing. To aid their experiments, we also offer re-usable [linux priv-esc benchmarks](https://github.com/ipa-lab/benchmark-privesc-linux) and publish all our findings as open-access reports. All source code can be found on [github](https://github.com/ipa-lab/hackingbuddyGPT).
We aim to become **THE go-to framework for security researchers** and pen-testers interested in using LLMs or LLM-based autonomous agents for security testing. To aid their experiments, we also offer re-usable [linux priv-esc benchmarks](https://github.com/ipa-lab/benchmark-privesc-linux) and publish all our findings as open-access reports.

How can LLMs aid or even emulate hackers? Threat actors are [already using LLMs](https://arxiv.org/abs/2307.00691), to better protect against this new threat we must learn more about LLMs' capabilities and help blue teams to prepare for them.

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| Name | Description | Screenshot |
|--------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|
| minimal | A minimal 50 LoC Linux Priv-Esc example. This is the usecase from [Build your own Agent/Usecase](#build-your-own-agentusecase) | ![A very minimal run](docs/usecase_minimal.png) |
| [linux-privesc](docs/linux_privesc.md) | Given a SSH-connection for a low-privilege user, task the LLM to become the root user. This would be a typical Linux privilege escalation attack. We published two academic papers about this: [paper #1](https://arxiv.org/abs/2308.00121) and [paper #2](https://arxiv.org/abs/2310.11409) | ![Example wintermute run](docs/example_run_gpt4.png) |
| [web-pentest (WIP)](docs/web_page.md) | Directly hack a webpage. Currently in heavy development and pre-alpha stage. | ![Test Run for a simple Blog Page](docs/usecase_web_page_run.png) |
| [web-api-pentest (WIP)](docs/web-api-pentest.md) | Directly test a REST API. Currently in heavy development and pre-alpha stage. (Documentation and testing of REST API.) | Documentation:![web_api_documentation.png](docs%2Fold_runs%2Fweb_api_documentation.png) Testing:![web_api_testing.png](docs%2Fold_runs%2Fweb_api_testing.png) |
| [minimal](https://docs.hackingbuddy.ai/docs/dev-guide/dev-quickstart) | A minimal 50 LoC Linux Priv-Esc example. This is the usecase from [Build your own Agent/Usecase](#build-your-own-agentusecase) | ![A very minimal run](docs/usecase_minimal.png) |
| [linux-privesc](https://docs.hackingbuddy.ai/docs/usecases/linux-priv-esc) | Given a SSH-connection for a low-privilege user, task the LLM to become the root user. This would be a typical Linux privilege escalation attack. We published two academic papers about this: [paper #1](https://arxiv.org/abs/2308.00121) and [paper #2](https://arxiv.org/abs/2310.11409) | ![Example wintermute run](docs/example_run_gpt4.png) |
| [web-pentest (WIP)](https://docs.hackingbuddy.ai/docs/usecases/web) | Directly hack a webpage. Currently in heavy development and pre-alpha stage. | ![Test Run for a simple Blog Page](docs/usecase_web_page_run.png) |
| [web-api-pentest (WIP)](https://docs.hackingbuddy.ai/docs/usecases/web-api) | Directly test a REST API. Currently in heavy development and pre-alpha stage. (Documentation and testing of REST API.) | Documentation:![web_api_documentation.png](docs%2Fold_runs%2Fweb_api_documentation.png) Testing:![web_api_testing.png](docs%2Fold_runs%2Fweb_api_testing.png) |

## Build your own Agent/Usecase

So you want to create your own LLM hacking agent? We've got you covered and taken care of the tedious ground work.

Create a new usecase and implement `perform_round` containing all system/LLM interactions. We provide multiple helper and base classes, so that a new experiment can be implemented in a few dozens lines of code. Tedious tasks, such as
connecting to the LLM, logging, etc. are taken care of by our framework. Check our [developer quickstart quide](docs/dev_quickstart.md) for more information.
connecting to the LLM, logging, etc. are taken care of by our framework. Check our [developer quickstart quide](https://docs.hackingbuddy.ai/docs/dev-guide/dev-quickstart) for more information.

The following would create a new (minimal) linux privilege-escalation agent. Through using our infrastructure, this already uses configurable LLM-connections (e.g., for testing OpenAI or locally run LLMs), logs trace data to a local sqlite database for each run, implements a round limit (after which the agent will stop if root has not been achieved until then) and is able to connect to a linux target over SSH for fully-autonomous command execution (as well as password guessing).

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