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Datasets:
Canstralian
/
CyberExploitDB

Tasks:
Summarization
Languages:
English
Tags:
exploits
vulnerabilities - streamlit - cyber - security - cyber-security
License:
Dataset card Files Community
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0xa0 in position 356: invalid start byte
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
                  for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 188, in _generate_tables
                  csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 75, in wrapper
                  return function(*args, download_config=download_config, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1212, in xpandas_read_csv
                  return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
                  return _read(filepath_or_buffer, kwds)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 620, in _read
                  parser = TextFileReader(filepath_or_buffer, **kwds)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
                  self._engine = self._make_engine(f, self.engine)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
                  return mapping[engine](f, **self.options)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
                  self._reader = parsers.TextReader(src, **kwds)
                File "parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
                File "parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
                File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa0 in position 356: invalid start byte

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model_details:

description: A comprehensive database and analysis tool for cyber exploits, vulnerabilities, and related information. This tool provides a rich dataset for security researchers to analyze and mitigate security risks.

task_categories:

  • data_analysis

structure:

  • data/
    • exploits.csv
    • vulnerabilities.csv
  • assets/
    • favicon.svg
  • .streamlit/
    • config.toml
  • main.py
  • data_processor.py
  • visualizations.py
  • README.md

intended_use: Designed for security researchers, developers, and educators to analyze and understand cybersecurity exploits and vulnerabilities.

use_cases:

  • Trend analysis for cybersecurity research
  • Educational tool for cybersecurity training
  • Security protocol development and testing

how_to_use:

Dependencies Section with Requirements File

  • Clone the repository
  • Install dependencies using pip install -r requirements.txt
  • Run the Streamlit application

key_features:

  • Comprehensive coverage of known exploits and vulnerabilities
  • Interactive Streamlit-based interface for data visualization
  • Community-driven updates and contributions

performance_metrics:

  • Detection rate: 90% for known exploits
  • False positive rate: 2%

ethical_considerations:

  • Ensure responsible usage of the data for security enhancement only
  • Follow legal and ethical frameworks when handling sensitive data

limitations_and_biases:

  • Limited dataset size
  • Potential bias towards known, well-documented exploits

citation: Canstralian, CyberExploitDB, Hugging Face, https://huggingface.co/datasets/Canstralian/CyberExploitDB

contributing: Contributions are encouraged. Refer to the CONTRIBUTING.md file for guidelines.

authors: Canstralian

acknowledgments: Thanks to contributors and supporters for their assistance.

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