---
license: cc-by-nc-4.0
task_categories:
- tabular-classification
- time-series-forecasting
tags:
- tsfile
- timeseries
- cybersecurity
- malware
- malware-classification
- threat-intelligence
- apt
- ransomware
- synthetic-data
- edr
- sandbox-evasion
- polymorphic
- time-series
- format:tsfile
pretty_name: CYB003 — Synthetic Malware Behaviour & Classification (Sample) (TsFile)
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: environment_profiles
    path: environment_profiles.tsfile
  - split: execution_events
    path: execution_events.tsfile
  - split: malware_samples
    path: malware_samples.tsfile
  - split: sample_summary
    path: sample_summary.tsfile
---

# CYB003 — Synthetic Malware Behaviour & Classification (Sample) (TsFile)

Apache TsFile version of [`xpertsystems/cyb003-sample`](https://huggingface.co/datasets/xpertsystems/cyb003-sample).

## Overview

**CYB003 — Synthetic Malware Behaviour & Classification Dataset (Sample)** — This is a **free preview** of the full **CYB003 — Synthetic Malware Behaviour & Classification Dataset** product. It contains roughly **1 / 56th of the full dataset** at identical schema, family/tier distribution, and statistical fingerprint, so you can evaluate fit before licensing the full product.

- **Tables:** `environment_profiles`, `execution_events`, `malware_samples`, `sample_summary`
- **Rows:** 7,256 across 4 TsFile table(s).
  - `environment_profiles`: 100 rows — Time is synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
  - `execution_events`: 1,056 rows — Time is the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
  - `malware_samples`: 6,000 rows — Time is the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
  - `sample_summary`: 100 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)

### `environment_profiles.tsfile`

- **Time** (INT64, milliseconds) — synthetic row index over the stable source order (0 … N-1); the source table has no per-row clock.
- **TAG**: `profile_id` — device dimension(s); query one device with `WHERE profile_id=...`.
- **FIELD** (11): `segment_id` (string), `endpoint_os` (string), `platform_type` (string), `ep_stack` (string), `patch_currency_score` (double), `user_privilege_level` (string), `network_segment_type` (string), `sandbox_presence_flag` (int64), `av_signature_age_days` (int64), `edr_behavioural_enabled` (int64), `network_egress_filtered` (int64)

### `execution_events.tsfile`

- **Time** (INT64, milliseconds) — the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- **TAG**: `sample_id` — device dimension(s); query one device with `WHERE sample_id=...`.
- **FIELD** (9): `family_id` (string), `event_type` (string), `execution_phase` (string), `target_pid` (int64), `api_call_name` (string), `registry_key_path` (string), `file_path_mutated` (string), `network_dst_ip_class` (string), `dns_query_domain_class` (string)

### `malware_samples.tsfile`

- **Time** (INT64, milliseconds) — the source `timestep` simulation step counter, stored as milliseconds (1 step = 1 ms).
- **TAG**: `sample_id` — device dimension(s); query one device with `WHERE sample_id=...`.
- **FIELD** (29): `family_id` (string), `threat_actor_id` (string), `malware_family` (string), `threat_actor_tier` (string), `target_platform` (string), `execution_phase` (string), `obfuscation_technique` (string), `api_call_rate` (double), `registry_write_count` (int64), `network_connection_count` (int64), `process_injection_flag` (int64), `c2_beacon_interval_sec` (double), `detection_outcome` (string), `av_signature_hit_flag` (int64), `sandbox_evasion_flag` (int64), `lateral_propagation_count` (int64), `privilege_escalation_flag` (int64), `ep_stack` (string), `pe_entropy_mean` (double), `pe_entropy_std` (double), `import_hash_cluster` (int64), `section_count` (int64), `packed_section_ratio` (double), `string_entropy_mean` (double), `byte_histogram_chi2` (double), `code_section_rx_ratio` (double), `resource_section_entropy` (double), `suspicious_import_count` (int64), `packer_detected_flag` (int64)

### `sample_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**: `sample_id` — device dimension(s); query one device with `WHERE sample_id=...`.
- **FIELD** (28): `family_id` (string), `threat_actor_id` (string), `malware_family` (string), `threat_actor_tier` (string), `target_platform` (string), `campaign_attribution_cluster` (int64), `obfuscation_complexity_score` (double), `total_api_calls` (int64), `unique_api_calls` (int64), `registry_mutations_total` (int64), `files_mutated_count` (int64), `network_connections_total` (int64), `lateral_propagation_count` (int64), `c2_sessions_established` (int64), `execution_duration_steps` (int64), `av_detection_flag` (int64), `edr_detection_flag` (int64), `sandbox_evasion_success` (int64), `definitive_detection_flag` (int64), `privilege_escalated_flag` (int64), `data_exfiltrated_flag` (int64), `dwell_time_ratio` (double), `family_attribution_confidence` (double), `lotl_technique_count` (int64), `packer_detected_flag` (int64), `threat_actor_roi_score` (double), `coordinated_campaign_flag` (int64), `campaign_success_flag` (int64)

## 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("environment_profiles.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/cyb003-sample`](https://huggingface.co/datasets/xpertsystems/cyb003-sample)
- Source card title / publisher: CYB003 — Synthetic Malware Behaviour & Classification (Sample)
- License: cc-by-nc-4.0 (as declared by the original dataset).