The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Missing a colon after a name of object member. in row 104
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: Missing a colon after a name of object member. in row 104Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
🛡️ Incident Response Playbook Dataset
A comprehensive collection of 175 structured incident response playbooks designed to assist cybersecurity researchers, analysts, red teams, and automation engineers in building, simulating, and training robust defense strategies. 📁 Dataset Overview
Format: JSONL (1 playbook per line)
Total Entries: 175
Use Cases:
Automating SOC workflows
Simulating incident response scenarios
Red team/blue team playbook development
Training ML/LLM-based security agents
📌 Data Schema
Each entry contains: { "incident_id": "IR-2025-0001", "incident_type": "Phishing Attack", "target_asset": "Windows AD Server", "detection_source": "SIEM Rule", "initial_vector": "Email Attachment", "tactics_techniques": [ {"tactic": "Initial Access", "technique": "Phishing"}, {"tactic": "Execution", "technique": "Command and Scripting Interpreter"}, {"tactic": "Impact", "technique": "Data Encrypted for Impact"} ], "severity": "High", "playbook_steps": [ { "phase": "Identification", "action": "Identification actions for Phishing Attack", "tools": ["SIEM", "Logs Review"], "response_time_min": 45 }, ... ], "final_status": "Resolved", "response_duration_total_min": 215, "tags": ["phishing", "data_encrypted_for_impact", "command_scripting"] }
🔍 Key Fields
| Field | Description |
|---|---|
incident_type |
Type of cyber incident (e.g., DDoS, Malware, Insider Threat) |
initial_vector |
Entry method used by the attacker |
tactics_techniques |
Mapped MITRE ATT&CK tactics and techniques |
playbook_steps |
Step-by-step IR actions by phase |
tools |
Tools used in each phase |
severity |
Severity classification (Low to Critical) |
tags |
Normalized tags for filtering/search |
| 📊 Sample Use Cases |
🔁 Security Automation Pipelines
🧠 Train LLMs for SOC Agent Simulations
📚 Education for Incident Responders
📈 Analytics for MITRE Coverage Gaps
🧪 Red/Blue Team Simulation Models
🤝 Contribution
Feel free to open issues or PRs for:
New attack types
Playbook enrichment
Mappings to MITRE updates
📄 License
This dataset is released under the MIT license.
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