Datasets:

tavialiu
/

CAD-data

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 80, in _split_generators
                  raise ValueError(
                  ...<2 lines>...
                  )
              ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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CAD Data

Sentence-annotated indirect prompt injection data used to train and evaluate CAD, from Robust Context-Aware Detection of Malicious Instructions in Text (Liu, Ma, and Vorobeychik, 2026).

Code: https://github.com/tavia-liu/CAD · Models: https://huggingface.co/tavialiu/CAD-models

Each record pairs a user query with a tool-returned document into which an injection task has been inserted. Records are built from the AgentDojo banking, slack, and travel suites.

File	Description	Records
`training_data_original.tar.gz`	Training set	1,080
`testing_data_original.tar.gz`	Test set (AgentDojo v1.2.2)	389
`training_data_paraphrased.tar.gz`	Paraphrased injections of the training set, used for LLM-paraphrase adversarial training	3,376

Each archive extracts to a folder of the same name containing one JSON file per record.

Fields

Field	Description
`user`	User query given to the agent
`data`	Clean tool-returned document
`injected`	Document with the injection inserted (original train and test)
`injection`	Injected instruction text
`user_task_id`, `injection_task_id`	AgentDojo task identifiers
`sentence_segments`	The attacked document split into numbered sentence units (`[i] ...`)
`injection_span_unit`	Inclusive `start`/`end` indices of the injected units
`injection_span_char`	Character span of the injection (test set)
`total_units`	Number of sentence units
`suite_name`	Suite name (test set)
`style`	Paraphrase style (paraphrased set)
`source_file`	Original training record the paraphrase was derived from (paraphrased set)

Sentence-level labels: a unit i is malicious if start <= i <= end in injection_span_unit, and benign otherwise.

Paraphrase styles: authority_citation, code_comment, conditional_note, error_recovery, fake_dialogue, fluent_prose, step_by_step. Each paraphrased record keeps the user query and clean data of its source record and replaces only the injection text.

Usage

From the root of the CAD repository:

hf download tavialiu/CAD-data --repo-type dataset --local-dir data
for f in data/*.tar.gz; do tar -xzf "$f" -C data; done

Utility and attack success

Records are static. Task utility and attack success are measured by running the agent in AgentDojo, whose per-task utility and security checks serve as the oracles. The benchmark code used in the paper is included in the CAD repository under third_party/AutoDojo/.

License

Released under CC BY 4.0. Documents, user tasks, and injection tasks are derived from AgentDojo (MIT). Please also cite AgentDojo when using this data.

Citation

@article{liu2026cad,
  title   = {Robust Context-Aware Detection of Malicious Instructions in Text},
  author  = {Liu, Buzhao and Ma, Xinhang and Vorobeychik, Yevgeniy},
  journal = {arXiv preprint},
  year    = {2026}
}

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Total file size:

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Models trained or fine-tuned on tavialiu/CAD-data

tavialiu/CAD-models

Updated about 21 hours ago