| # Nemesis Cyber Threat Simulation Pack — Schema |
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| One row = one simulated adversarial attack episode, end-to-end. All records share the same eight top-level fields. |
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| Schema version: `1.0.0-nemesis-cyber-sample` |
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| ## Top-level fields |
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| ### `schema_version` — string |
| Schema identifier. Constant within a sample release. Used to detect pack version drift. |
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| ### `event` — struct |
| Identifier fields and the overall decision outcome. |
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| | Field | Type | Notes | |
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| | `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`. | |
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| ### `risk_context` — struct |
| Environmental context and the triggering signal that initiated the adversarial episode. |
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| | Field | Type | Notes | |
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| | `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. | |
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| ### `agent_reasoning` — struct |
| Planner-side metadata for the adversarial agent that selected and executed this episode. |
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| | Field | Type | Notes | |
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| | `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. | |
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| ### `correlated_telemetry` — list<struct> |
| Ordered sequence of steps taken during the episode. One struct per step. |
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| Step struct: |
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| | Field | Type | Notes | |
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| | `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`). | |
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| ### `execution_summary` — struct |
| Roll-up metrics for the full episode. |
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| | Field | Type | Notes | |
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| | `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. | |
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| ### `genetic_optimizer_feedback` — struct |
| Outer-loop optimizer feedback used to tune future planner iterations. |
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| | Field | Type | Notes | |
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| | `fitness_score_update` | double | Delta applied to the strategy's fitness score after this episode. | |
| | `parameter_drift` | string | Coarse drift descriptor (`none`, `minor`, `major`, …). | |
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| ### `decision_outcome` — string |
| Duplicated from `event.decision_outcome` for quick grouping and classification without struct unpacking. |
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| ## Distribution of this sample |
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| - 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. |
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| ## Sanitization notes |
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| - 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. |
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| ## Relationship to the full pack |
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| 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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