Datasets:
File size: 7,199 Bytes
477a77a 58b9318 477a77a 58b9318 477a77a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | ---
license: cc-by-nc-4.0
task_categories:
- tabular-classification
- time-series-forecasting
tags:
- tsfile
- timeseries
- cybersecurity
- mitre-attack
- kill-chain
- apt
- ransomware
- synthetic-data
- threat-modeling
- red-team
- blue-team
- time-series
- format:tsfile
pretty_name: CYB002 — Synthetic Cyber Attack Dataset (Sample) (TsFile)
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: attack_events
path: attack_events.tsfile
- split: campaign_events
path: campaign_events.tsfile
- split: campaign_summary
path: campaign_summary.tsfile
- split: network_topology
path: network_topology.tsfile
---
# CYB002 — Synthetic Cyber Attack Dataset (Sample) (TsFile)
Apache TsFile version of [`xpertsystems/cyb002-sample`](https://huggingface.co/datasets/xpertsystems/cyb002-sample).
## Overview
**CYB002 — Synthetic Cyber Attack Dataset (Sample)** — This is a **free preview** of the full **CYB002 — Synthetic Cyber Attack Dataset** product. It contains roughly **1 / 60th of the full dataset** at identical schema, attacker-tier distribution, and statistical fingerprint, so you can evaluate fit before licensing the full product.
- **Tables:** `attack_events`, `campaign_events`, `campaign_summary`, `network_topology`
- **Rows:** 5,843 across 4 TsFile table(s).
- `attack_events`: 4,353 rows — Time is the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- `campaign_events`: 739 rows — Time is the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- `campaign_summary`: 100 rows — Time is synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
- `network_topology`: 651 rows — Time is synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
## Schema (TsFile structure)
### `attack_events.tsfile`
- **Time** (INT64, milliseconds) — the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- **TAG**: `campaign_id` — device dimension(s); query one device with `WHERE campaign_id=...`.
- **FIELD** (22): `attacker_id` (string), `kill_chain_phase` (string), `technique_id` (string), `technique_name` (string), `tactic_category` (string), `target_segment_id` (string), `target_asset_type` (string), `source_ip_class` (string), `dest_port` (int64), `protocol` (string), `bytes_transferred` (double), `connection_duration_s` (double), `auth_failure_count` (int64), `process_injection_flag` (int64), `lateral_hop_count` (int64), `c2_beacon_interval_s` (double), `detection_outcome` (string), `alert_severity` (string), `siem_rule_triggered` (int64), `edr_blocked_flag` (int64), `attacker_capability_tier` (string), `defender_maturity_level` (string)
### `campaign_events.tsfile`
- **Time** (INT64, milliseconds) — the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- **TAG**: `campaign_id` — device dimension(s); query one device with `WHERE campaign_id=...`.
- **FIELD** (6): `attacker_id` (string), `event_type` (string), `target_segment_id` (string), `target_asset_id` (string), `responder_id` (string), `related_campaign_id` (string)
### `campaign_summary.tsfile`
- **Time** (INT64, milliseconds) — synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
- **TAG**: `campaign_id` — device dimension(s); query one device with `WHERE campaign_id=...`.
- **FIELD** (30): `attacker_id` (string), `attacker_capability_tier` (string), `campaign_type` (string), `target_environment_type` (string), `kill_chain_phases_reached` (string), `highest_phase_achieved` (string), `lateral_hops_total` (int64), `assets_compromised_count` (int64), `data_exfil_gb` (double), `dwell_time_hours` (double), `detection_rate` (double), `alert_volume_total` (int64), `suppressed_alert_count` (int64), `edr_block_count` (int64), `ir_escalation_count` (int64), `campaign_duration_steps` (int64), `campaign_success_flag` (int64), `ransomware_deployed_flag` (int64), `c2_sessions_established` (int64), `technique_count_unique` (int64), `tactic_breadth_score` (double), `attacker_stealth_score` (double), `defender_response_score` (double), `mttd_hours` (double), `mttr_hours` (double), `coordinated_attack_flag` (int64), `exfiltration_success_flag` (int64), `privesc_success_flag` (int64), `phase_detection_coverage` (double), `attacker_roi_score` (double)
### `network_topology.tsfile`
- **Time** (INT64, milliseconds) — synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
- **TAG**: `segment_id` — device dimension(s); query one device with `WHERE segment_id=...`.
- **FIELD** (17): `asset_id` (string), `segment_type` (string), `asset_type` (string), `os_family` (string), `patch_lag_days` (int64), `exposure_score` (double), `defender_maturity_level` (string), `siem_coverage_flag` (int64), `edr_deployed_flag` (int64), `ndr_coverage_flag` (int64), `mfa_enforced_flag` (int64), `vulnerability_count` (int64), `trust_zone` (string), `inter_segment_trust_level` (double), `alert_threshold_sensitivity` (double), `mttd_baseline_hours` (double), `mttr_baseline_hours` (double)
## Conversion notes
- Each CSV of the sample is converted into its own TsFile table (4 tables), so no table is merged with another and no column is dropped.
- Event/telemetry tables use the source simulation clock as Time (INT64 milliseconds): `timestep` step counters and millisecond offsets are stored as-is, minute-based columns are multiplied by 60,000, and ISO/UTC strings are parsed to epoch milliseconds.
- Static inventory/topology/summary tables have no per-row clock; their Time is a synthetic row index (0..N-1) over the stable source order.
- Low-cardinality dimensions of each table (campaign/incident/asset/session ids, phases, labels) are declared as TAG columns; query one simulation with e.g. `WHERE campaign_id='...'`.
## Usage
Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file:
```python
from pathlib import Path
from tsfile import TsFileReader
path = Path("attack_events.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
```
## Source & license
- Original dataset: [`xpertsystems/cyb002-sample`](https://huggingface.co/datasets/xpertsystems/cyb002-sample)
- Source card title / publisher: CYB002 — Synthetic Cyber Attack Dataset (Sample)
- License: cc-by-nc-4.0 (as declared by the original dataset).
|