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The dataset viewer is not available for this subset.
Cannot get the split names for the config '1024-unrolled' of the dataset.
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 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
                                                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
                  cls = get_filesystem_class(protocol)
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
                  raise ValueError(f"Protocol not known: {protocol}")
              ValueError: Protocol not known: memory
              
              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 66, 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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COSOCO: Compromised Software Containers Image Dataset

Dataset Description

COSOCO (Compromised Software Containers) is a synthetic dataset of 3364 images representing benign and malware-compromised software containers. Each image in the dataset represents a dockerized software container that has been converted to an image using common byte-to-pixel tools widely used in malware analysis. Software container records are labelled (1) benign or (2) compromised: A benign software container will have installed commonly used harmless packages and tools, whereas a compromised software container, will have, among harmless benign tools and packages, its underlying file system affected by some activated malware instance. Each compromised instance is accompanied by a mask, i.e. a black and white image which marks the pixels that correspond to the files of the underlying system that have been altered by a malware. COSOCO aims to support the identification of compromised software containers via the task of image classification task and the identification of compromised files and file system regions inside a container via the image segmentation task.

Acknowledgements

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101093069 (P2CODE). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation

The users of this dataset are kindly asked to cite the following paper:

@misc{
  nousias2025malwaredetectiondockercontainers, 
  title={Malware Detection in Docker Containers: An Image is Worth a Thousand Logs},  
  author={Akis Nousias and Efklidis Katsaros and Evangelos Syrmos and Panagiotis Radoglou-Grammatikis and Thomas Lagkas and Vasileios Argyriou and Ioannis Moscholios and Evangelos Markakis and Sotirios Goudos and Panagiotis Sarigiannidis},
  year={2025}, 
  eprint={2504.03238},
  archivePrefix={arXiv}, 
  primaryClass={cs.CR}, 
  url={https://arxiv.org/abs/2504.03238}, 
}

Contact

Contact Panagiotis Radoglou-Grammatikis for questions or comments.

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