Datasets:
File size: 5,024 Bytes
35fef0a | 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 | # Nemesis Cyber Threat Simulation Pack — Schema
One row = one simulated adversarial attack episode, end-to-end. All records share the same eight top-level fields.
Schema version: `1.0.0-nemesis-cyber-sample`
## Top-level fields
### `schema_version` — string
Schema identifier. Constant within a sample release. Used to detect pack version drift.
### `event` — struct
Identifier fields and the overall decision outcome.
| Field | Type | Notes |
|---|---|---|
| `id` | string | Stable episode identifier, e.g., `NEMESIS-1541935`. |
| `timestamp` | string (ISO-8601) | Episode start time. |
| `trace_id` | string (UUID) | Cross-links telemetry steps within the episode. |
| `weighted_score` | double | Aggregate risk score for this episode. |
| `decision_outcome` | string | One of: `detected_by_soc`, `blocked_by_edr`, `stealth_maintained`, `exfiltration_complete`, `impact_achieved`. |
### `risk_context` — struct
Environmental context and the triggering signal that initiated the adversarial episode.
| Field | Type | Notes |
|---|---|---|
| `trigger` | string | Short-code for the initial trigger (e.g., `phishing_attachment_opened`, `k8s_pod_escape`, `iam_policy_modification`, `unusual_ingress_traffic`). |
| `protocol` | string | Protection domain / environment: `AWS-Cloud`, `Active-Directory`, `Kubernetes`, `Web-App-Gateway`. |
| `chain` | string | Target environment identifier (e.g., `us-east-1`, `windows-server-2022`, `prod-cluster-01`, `ubuntu-22.04`). |
| `impacted_asset` | string | Named asset under attack (e.g., `ntds.dit`, `kube-apiserver`, IAM role name, app endpoint). |
| `anomaly_signature` | string | Human-readable summary of the triggering anomaly. |
### `agent_reasoning` — struct
Planner-side metadata for the adversarial agent that selected and executed this episode.
| Field | Type | Notes |
|---|---|---|
| `engine` | string | Planner engine label. In this sample: `nemesis_planner`. |
| `winning_strategy` | string | Selected top-level strategy (e.g., `Stealth_Escalation`). |
| `confidence_score` | double | Planner confidence in the chosen strategy at selection time. |
| `mcts_branches` | int64 | Number of MCTS branches considered before the selection. |
### `correlated_telemetry` — list<struct>
Ordered sequence of steps taken during the episode. One struct per step.
Step struct:
| Field | Type | Notes |
|---|---|---|
| `action` | string | ATT&CK-style action code (e.g., `USER_DISCOVERY`, `LSASS_MEMORY_DUMP`, `CRED_ACCESS_PASS_THE_HASH`, `LATERAL_SMB_EXEC`, `IMPACT_DATA_ENCRYPTED`). |
| `component` | string | Which internal component emitted the step (`NEMESIS_ORCHESTRATOR`, `NEMESIS_GHOST`, `NEMESIS_EXPLOIT`). |
| `timestamp` | string (ISO-8601) | Step timestamp. |
| `telemetry.evasion_score` | double | 0–1. Higher = more evasive. |
| `telemetry.latency_ms` | int64 | Step execution latency in milliseconds. |
| `telemetry.noise_level_db` | int64 | Relative noise generated by the step. |
| `telemetry.node_provider` | string | Observing detection surface (e.g., `Azure_Sentinel`, `CrowdStrike`, `CloudTrail`). |
### `execution_summary` — struct
Roll-up metrics for the full episode.
| Field | Type | Notes |
|---|---|---|
| `strategy` | string | Final strategy label executed (matches or post-adjusts the `agent_reasoning.winning_strategy`). |
| `success_rate` | double | 0–1 score of action-chain completion against plan. |
| `total_execution_ms` | int64 | End-to-end episode duration. |
| `noise_penalty` | double | Penalty contribution from cumulative step noise. |
### `genetic_optimizer_feedback` — struct
Outer-loop optimizer feedback used to tune future planner iterations.
| Field | Type | Notes |
|---|---|---|
| `fitness_score_update` | double | Delta applied to the strategy's fitness score after this episode. |
| `parameter_drift` | string | Coarse drift descriptor (`none`, `minor`, `major`, …). |
### `decision_outcome` — string
Duplicated from `event.decision_outcome` for quick grouping and classification without struct unpacking.
## Distribution of this sample
- 10,000 rows, stratified 2,000 per outcome class across all five outcomes.
- Balanced across four `protocol` environments: AWS-Cloud, Active-Directory, Kubernetes, Web-App-Gateway.
- Triggers map 1:1 to protocols in this sample.
- Planner engine label is constant (`nemesis_planner`) after sanitization of internal method identifiers.
## Sanitization notes
- Internal identifier prefixes (e.g., `SIMA-V4-CYBER-*`) have been normalized to `NEMESIS-*`.
- Internal planner engine code names have been normalized to `nemesis_planner`.
- No real hostnames, users, indicators of compromise, credentials, exploit code, or victim data are present.
## Relationship to the full pack
The production pack contains 2.5M episodes with a richer protocol and trigger space, adversary persona variants, campaign-level chains spanning multiple episodes, per-step process tree fragments, and defender-side reasoning traces. See the pack card for commercial access.
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