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guychuk/benign-malicious-prompt-classification

published by @guychuk

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
4.2K
Last 30 days
183
Likes
5
Size
177.7 MB
Created on HF
2024-06-29
Age
2 years ago

Description

Important Notes

This dataset goal is to help detect prompt injections / jailbreak intent. To achieve that, we decided to classify prompts to malicious only if there's an attemp to manipulate them - that means that a bad prompt (i.e asking how to create a bomb) will be classified as benign since it's a straight up question!

Tags

task_categories:text-classificationlanguage:enlicense:apache-2.0size_categories:100K<n<1Mformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:ussecurityprompt-injection

README current version from Hugging Face

language:

  • en
    license: apache-2.0
    task_categories:
  • text-classification
    pretty_name: ⚖️ Prompt Intent Classificaction
    dataset_info:
    features:
    • name: prompt
      dtype: string
    • name: label
      dtype:
      class_label:
      names:
      '0': benign
      '1': malicious

    splits:

    • name: train
      num_bytes: 483043593
      num_examples: 464470
      download_size: 186340131
      dataset_size: 483043593
      configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
      tags:
  • security
  • prompt-injection

Important Notes

This dataset goal is to help detect prompt injections / jailbreak intent. To achieve that, we decided to classify prompts to malicious only if there's an attemp to manipulate them - that means that a bad prompt (i.e asking how to create a bomb) will be classified as benign since it's a straight up question!

README history 7 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2024-07-04Librarian Bot: Add language metadata for dataset (#2)e130906887 B
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  2. 2024-06-30Initial commit7c63bb8872 B
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  3. 2024-06-30Initial commitb6165e5872 B
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  4. 2024-06-30Initial commitbaf33c6867 B
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  5. 2024-06-29Update README.mdf752832867 B
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  6. 2024-06-29Initial commite509fb0431 B
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  7. 2024-06-29initial commitfb8eb2431 B
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Used by abliterated models none yet

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Community discussions 2 threads · 2 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2024-07-04PRLibrarian Bot: Add language metadata for datasetmerged1 💬#2
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  2. 2024-06-30[bot] Conversion to Parquetclosed1 💬#1
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Metadata

License
apache-2.0

Repository

DIR data FILE .gitattributes FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python) 
from datasets import load_dataset
ds = load_dataset("guychuk/benign-malicious-prompt-classification")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="guychuk/benign-malicious-prompt-classification", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/guychuk/benign-malicious-prompt-classification
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