Dataset Viewer
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: ArrowInvalid
Message: JSON parse error: The document is empty.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
df = pandas_read_json(f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
obj = self._get_object_parser(self.data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
self._parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
ValueError: Trailing data
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, 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 3339, 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 2096, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2300, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 476, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 323, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: The document is empty.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Malicious File Trick Detection Dataset
This dataset provides a structured collection of file-based social engineering and obfuscation techniques used by attackers to bypass user awareness, antivirus (AV) detection, and security filters. Each entry identifies a malicious or deceptive filename, the evasion technique used, and detection methodology.
The dataset is ideal for:
- 🧠 Training AI/ML models for malware detection
- 🚨 Building secure email gateways and filters
- 📚 Teaching social engineering and malware delivery tactics
📁 Dataset Format
Stored in .jsonl format (JSON Lines), with one structured object per line.
Fields
| Field | Description |
|---|---|
filename |
Example of a malicious or deceptive file name |
technique |
Obfuscation method used (e.g., Double extension, Unicode trick) |
category |
Context or delivery type (e.g., Social Engineering, Malware Delivery) |
detected_by |
Detection method or defense mechanism (e.g., AV heuristic, Sandbox) |
🔍 Example
{
"filename": "report.pdf.exe",
"technique": "Double extension",
"category": "Social Engineering",
"detected_by": "AV heuristic"
}
✅ Key Techniques Included
Double extension (file.pdf.exe)
Whitespace padding (file.txt .exe)
Unicode manipulation (file.exe)
Alternate file data streams (Windows ADS)
Executable macros in Office docs (.docm, .xlsm)
Archive deception (.zip bombs, nested .rar)
Script obfuscation (.vbs, .bat, .js payloads)
🛠 Use Cases
Machine learning for secure email filtering
Static or behavioral malware classifiers
LLM training for phishing/malware awareness
Threat modeling and red team education
⚠️ Disclaimer
This dataset is for educational, research, and defense purposes only. Do not use these payloads in unauthorized environments. The author is not responsible for misuse.
📜 License
This dataset is released under the MIT License. You are free to use, modify, and redistribute with attribution.
🤝 Contributions
Want to add more techniques or filenames? PRs are welcome!
📫 Maintainer
Your Name
GitHub: @sunnythakur25
Email: [email protected]
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