| # NYU CTF Bench |
|
|
| This repository hosts the NYU CTF Bench, a collection of CTF challenges from the CSAW CTF competitions, designed for evaluation of LLM agents. |
| The CTF challenges are dockerized and easily deployable to allow an LLM-based automation framework to interact with the challenge and attempt a solution. |
| The main benchmark dataset contains 200 challenges across 6 CTF categories: web, binary exploitation (pwn), forensics, reverse engineering (rev), cryptography (crypto), and miscellaneous (misc). |
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|
| ## Benchmark structure |
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| The `test/` folder contains the main benchmark dataset of 200 challenges. A smaller development set of 55 challenges is present in the `development/` folder. |
| The development set can be treated equivalent to a "train" split and used for building the agent, so that design decisions made to improve the agent do not bias the test scores. |
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|
| The folder structure is as follows: `<year>/<event>/<category>/<challenge>`. |
| `<year>` is the year of the competition, `<event>` is either "CSAW-Quals" or "CSAW-Finals", `<category>` is among the 6 categories, and `<challenge>` is the challenge name. |
| Note that the challenge name may have spaces and single-quotes, so it is advisable to wrap it in double-quotes when using in scripts. |
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|
| Each challenge contains a `challenge.json` containing the metadata of the challenge, and the corresponding challenge files. |
| Challenges that require a server to host some challenge files are set up with a docker image, and a `docker-compose.yaml` file. |
| The docker image is loaded directly using `docker compose up`. |
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|
| ## Setup |
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| Install the python package: |
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|
| ``` |
| pip install nyuctf |
| ``` |
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|
| The repository is automatically cloned when the `CTFDataset` is first instantiated with the `split` argument. |
| If needed, you can manually clone it by running: |
|
|
| ``` |
| python3 -m nyuctf.download |
| ``` |
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| ## Usage |
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| The following python snippet shows how to load challenge details using the python module: |
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|
| ``` |
| from nyuctf.dataset import CTFDataset |
| from nyuctf.challenge import CTFChallenge |
| |
| # Clones the repository for the first time, which takes a while |
| ds = CTFDataset(split="test") |
| chal = CTFChallenge(ds.get("2021f-rev-maze"), ds.basedir) |
| |
| print(chal.name) |
| print(chal.flag) |
| print(chal.files) |
| ``` |
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|
| ## Tests |
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| Run tests on the challenges, for docker setup and network connection. |
| Requires the docker network to be setup. |
|
|
| ``` |
| cd python |
| python -m unittest -v test.test_challenges |
| ``` |
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| Optionally filter the tests with the unittest `-k` flag. |
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