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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+  - tabular-classification
+  - time-series-forecasting
+tags:
+  - cybersecurity
+  - adversarial-machine-learning
+  - ai-security
+  - adversarial-attacks
+  - evasion-attacks
+  - apt
+  - synthetic-data
+  - ml-security
+  - model-robustness
+  - mlops-security
+pretty_name: CYB011 — Synthetic AI Evasion Attack Trajectories (Sample)
+size_categories:
+  - 10K<n<100K
+---
+
+# CYB011 — Synthetic AI Evasion Attack Trajectory Dataset (Sample)
+
+**XpertSystems.ai Synthetic Data Platform · SKU: CYB011-SAMPLE · Version 1.0.0**
+
+This is a **free preview** of the full **CYB011 — Synthetic AI Evasion Attack
+Trajectory Dataset** product. It contains roughly **~4% of the full dataset**
+at identical schema, attacker-tier distribution, and statistical fingerprint,
+so you can evaluate fit before licensing the full product.
+
+| File                          | Rows (sample) | Rows (full)   | Description                                  |
+|-------------------------------|---------------|---------------|----------------------------------------------|
+| `network_topology.csv`        | ~200           | ~2,800        | Network segment / defender registry          |
+| `campaign_summary.csv`        | ~200           | ~5,500        | Per-campaign aggregate outcomes              |
+| `campaign_events.csv`         | ~13,310        | ~55,000       | Discrete campaign event log                  |
+| `attack_trajectories.csv`     | ~14,000        | ~320,000      | Per-timestep adversarial trajectories        |
+
+## Dataset Summary
+
+CYB011 simulates end-to-end **adversarial AI evasion attack campaigns**
+against ML-based security detection systems, modeled as a **6-phase
+adversarial state machine**:
+
+- **6 adversarial phases**: reconnaissance → feature_space_probe →
+  perturbation_craft → evasion_attempt → feedback_adaptation →
+  campaign_consolidation
+- **4 attacker capability tiers**: script_kiddie, opportunistic,
+  advanced_persistent_threat (APT), nation_state — with per-tier
+  ε-budgets (L∞ perturbation), query budgets (50 → 5,000), base evasion
+  rates, and stealth weights
+- **8 defender detection architectures** with per-architecture
+  detection_strength (e.g. ensemble_layered 0.91, gradient_boosted 0.78,
+  neural_network 0.74, isolation_forest 0.62)
+- **L∞ perturbation budget modeling** — calibrated mean ε ≈ 0.185
+  representing realistic imperceptibility constraints
+- **Query budget tracking** — black-box vs white-box attack distinction
+- **Concept drift injection** — adversarial data poisoning of training
+  distributions, ~8% injection rate
+- **Retraining trigger modeling** — defender model refresh after drift
+  detection (~14% trigger rate)
+- **Transfer attack modeling** — perturbations crafted on surrogate
+  models, 31% transfer success rate
+- **Honeypot density** — deception model coverage (5% baseline)
+- **Coordinated multi-attacker campaigns** with 12% coordination rate
+- **MLOps security signals** — gradient access patterns, feature-space
+  probing, lateral pivoting between models
+
+## Calibrated Benchmark Targets
+
+The full product is calibrated to 12 benchmark validation tests drawn from
+authoritative adversarial ML research (MITRE ATLAS, NIST AI 100-2 Adversarial
+ML Taxonomy, OWASP ML Top 10, USENIX Security adversarial ML papers, IEEE
+SaTML, Microsoft Counterfit, IBM Adversarial Robustness Toolbox, Anthropic /
+OpenAI red team reports).
+
+Sample benchmark results:
+
+| Test | Target | Observed | Verdict |
+|------|--------|----------|---------|
+| evasion_success_rate_apt | 0.1430 | 0.1764 | ✓ PASS |
+| detection_rate_ensemble | 0.9100 | 0.9100 | ✓ PASS |
+| alert_suppression_rate | 0.0720 | 0.0720 | ✓ PASS |
+| perturbation_budget_mean | 0.1850 | 0.1891 | ✓ PASS |
+| query_volume_rate | 0.1450 | 0.1250 | ✓ PASS |
+| concept_drift_injection_rate | 0.0800 | 0.0600 | ✓ PASS |
+| stealth_score_apt | 0.7200 | 0.7200 | ✓ PASS |
+| retrain_trigger_rate | 0.1400 | 0.1250 | ✓ PASS |
+| campaign_success_rate | 0.3800 | 0.3950 | ✓ PASS |
+| lateral_pivot_rate | 0.0950 | 0.0950 | ✓ PASS |
+| transfer_attack_success_rate | 0.3100 | 0.3100 | ✓ PASS |
+| attribution_risk_score | 0.2800 | 0.3201 | ✓ PASS |
+
+*Every CYB011 benchmark in the sample lands within the same calibrated
+tolerance as the full product. The sample uses 200 campaigns (vs 5,500 at
+full scale); APT-tier conditional benchmarks (≈ 22% of campaigns) have
+~44 samples for robust convergence.*
+
+## Schema Highlights
+
+### `attack_trajectories.csv` (primary file, per-timestep)
+
+| Column                          | Type    | Description                                  |
+|---------------------------------|---------|----------------------------------------------|
+| campaign_id                     | string  | Unique adversarial campaign ID               |
+| attacker_id                     | string  | Attacker ID                                  |
+| timestep                        | int     | Step in 6-phase lifecycle (0–69)             |
+| adversarial_phase               | string  | 1 of 6 phases                                |
+| attacker_tier                   | string  | script_kiddie / opportunistic / apt / nation_state |
+| defender_architecture           | string  | ensemble / gradient_boosted / nn / isolation_forest / etc. |
+| segment_id                      | string  | FK to `network_topology.csv`                 |
+| perturbation_linf               | float   | L∞ perturbation magnitude (ε)                |
+| perturbation_l2                 | float   | L2 perturbation magnitude                    |
+| queries_used                    | int     | Cumulative model queries                     |
+| query_budget_remaining          | int     | Tier-cap minus queries_used                  |
+| gradient_access                 | int     | Boolean — white-box gradient access          |
+| evasion_attempted               | int     | Boolean — evasion submitted at this step     |
+| evasion_succeeded               | int     | Boolean — evasion bypassed detection         |
+| defender_detection_strength     | float   | Per-architecture detection strength (0–1)    |
+| concept_drift_injected          | int     | Boolean — drift injection at this step       |
+| transfer_attack_used            | int     | Boolean — perturbation from surrogate model  |
+| stealth_score                   | float   | Cumulative stealth (0–1)                     |
+| feature_space_dim               | int     | Target model feature dimensionality          |
+
+### `campaign_summary.csv` (per-campaign outcome)
+
+| Column                          | Type    | Description                                  |
+|---------------------------------|---------|----------------------------------------------|
+| campaign_id, attacker_id        | string  | Identifiers                                  |
+| attacker_tier                   | string  | Tier classification target                   |
+| defender_architecture           | string  | Defender model classification target         |
+| campaign_outcome                | string  | success / detected / aborted / blocked       |
+| evasion_success_flag            | int     | Boolean — evasion ever succeeded             |
+| total_queries_used              | int     | Cumulative query count                       |
+| perturbation_budget_mean        | float   | Mean ε across campaign                       |
+| concept_drift_injected_flag     | int     | Boolean — drift injection used               |
+| retrain_triggered_flag          | int     | Boolean — defender retraining triggered      |
+| transfer_attack_success_flag    | int     | Boolean — transfer attack succeeded          |
+| lateral_pivot_flag              | int     | Boolean — pivot to second model              |
+| stealth_score_final             | float   | Final stealth score                          |
+| attribution_risk_score          | float   | Likelihood of attribution (0–1)              |
+
+See `campaign_events.csv` and `network_topology.csv` for the discrete event
+log and segment/defender registry schemas respectively.
+
+## Suggested Use Cases
+
+- Training **adversarial example detectors** — distinguish clean vs
+  perturbed inputs from feature-space telemetry
+- **Attacker tier attribution** — 4-class classification of evasion
+  campaigns by capability tier
+- **Defender architecture vulnerability assessment** — predict which
+  defender architectures are most evadable
+- **L∞ / L2 perturbation budget detection** — calibrate ε-thresholds
+- **Query budget exhaustion attacks** — model black-box query patterns
+- **Concept drift poisoning detection** — distinguish natural drift
+  from adversarial injection
+- **Transfer attack detection** — identify perturbations crafted on
+  surrogate models
+- **MLOps adversarial robustness benchmarking** — evaluate model
+  hardening before deployment
+- **Honeypot effectiveness analysis** — deception model coverage tuning
+- **Adversarial ML threat modeling** — MITRE ATLAS tactic coverage
+- **Anthropic / OpenAI-style red team simulation** — synthetic
+  jailbreak/evasion training data
+
+## Loading the Data
+
+```python
+import pandas as pd
+
+trajectories = pd.read_csv("attack_trajectories.csv")
+summaries    = pd.read_csv("campaign_summary.csv")
+events       = pd.read_csv("campaign_events.csv")
+topology     = pd.read_csv("network_topology.csv")
+
+# Join trajectory data with campaign-level labels
+enriched = trajectories.merge(summaries, on=["campaign_id", "attacker_id"],
+                              how="left", suffixes=("", "_summary"))
+enriched = enriched.merge(topology, on="segment_id", how="left")
+
+# 4-class attacker tier target
+y_tier = summaries["attacker_tier"]
+
+# Binary evasion success target
+y_evasion = summaries["evasion_success_flag"]
+
+# Multi-class defender architecture target
+y_defender = topology["defender_architecture"]
+
+# Binary concept drift / poisoning detection
+y_poisoned = summaries["concept_drift_injected_flag"]
+```
+
+## License
+
+This **sample** is released under **CC-BY-NC-4.0** (free for non-commercial
+research and evaluation). The **full production dataset** is licensed
+commercially — contact XpertSystems.ai for licensing terms.
+
+## Full Product
+
+The full CYB011 dataset includes **~383,000 rows** across all four files,
+with calibrated benchmark validation against 12 metrics drawn from
+authoritative adversarial ML research sources (MITRE ATLAS, NIST AI 100-2,
+OWASP ML Top 10).
+
+📧  **pradeep@xpertsystems.ai**
+🌐  **https://xpertsystems.ai**
+
+## Citation
+
+```bibtex
+@dataset{xpertsystems_cyb011_sample_2026,
+  title  = {CYB011: Synthetic AI Evasion Attack Trajectory Dataset (Sample)},
+  author = {XpertSystems.ai},
+  year   = {2026},
+  url    = {https://huggingface.co/datasets/xpertsystems/cyb011-sample}
+}
+```
+
+## Generation Details
+
+- Generator version : 1.0.0
+- Random seed       : 42
+- Generated         : 2026-05-16 14:56:19 UTC
+- Adversarial model : 6-phase evasion campaign state machine
+- Overall benchmark : 100.0 / 100  (grade A+)

campaign_summary.csv

@@ -0,0 +1,201 @@
+campaign_id,attacker_id,attacker_capability_tier,target_environment_type,campaign_type,total_queries_issued,evasion_attempts_total,evasion_successes,evasion_success_rate,detection_rate,perturbation_budget_consumed,avg_perturbation_magnitude,max_perturbation_linf,campaign_duration_steps,lateral_pivot_count,detector_blind_spots_mapped,concept_drift_events,retrain_triggers_caused,campaign_success_flag,attribution_risk_score,stealth_score,attack_efficiency_score,model_extraction_queries,transfer_attack_count,coordinated_attack_flag
+ATK0001_C0001,ATK0001,script_kiddie,zero_trust_network,transfer_attack_chain,46,40,2,0.05,0.5,1.0,0.206548,0.464439,70,0,1,0,1,0,0.0884,0.9116,0.043478,5,0,0
+ATK0001_C0002,ATK0001,script_kiddie,enterprise_network,boundary_probe_blackbox,46,42,1,0.02381,0.690476,1.0,0.196657,0.573969,70,0,0,0,0,0,0.1652,0.8348,0.021739,2,0,0
+ATK0001_C0003,ATK0001,script_kiddie,enterprise_network,coordinated_multi_agent,44,36,0,0.0,0.527778,1.0,0.193799,0.470573,70,0,0,0,0,1,0.1652,0.8348,0.0,6,0,0
+ATK0001_C0004,ATK0001,script_kiddie,cloud_workload,boundary_probe_blackbox,46,44,3,0.068182,0.431818,1.0,0.211125,0.488682,70,0,1,0,0,1,0.1652,0.8348,0.065217,1,0,0
+ATK0001_C0005,ATK0001,script_kiddie,enterprise_network,transfer_attack_chain,41,38,0,0.0,0.868421,1.0,0.204792,0.449914,70,0,0,0,0,0,0.1268,0.8732,0.0,2,0,0
+ATK0001_C0006,ATK0001,script_kiddie,endpoint_fleet,lateral_movement_evasion,42,38,1,0.026316,0.578947,1.0,0.191858,0.509745,70,0,0,0,0,1,0.1268,0.8732,0.02381,2,0,0
+ATK0001_C0007,ATK0001,script_kiddie,ot_ics_environment,coordinated_multi_agent,38,34,3,0.088235,0.705882,1.0,0.195203,0.359184,70,0,1,0,0,1,0.2036,0.7964,0.078947,3,0,0
+ATK0001_C0008,ATK0001,script_kiddie,zero_trust_network,boundary_probe_blackbox,51,40,2,0.05,0.725,1.0,0.179263,0.409265,70,1,1,0,0,1,0.1652,0.8348,0.039216,7,0,0
+ATK0001_C0009,ATK0001,script_kiddie,cloud_workload,model_extraction_reuse,51,45,1,0.022222,0.622222,1.0,0.179531,0.380955,70,0,1,0,1,0,0.1268,0.8732,0.019608,4,0,1
+ATK0001_C0010,ATK0001,script_kiddie,endpoint_fleet,concept_drift_injection,38,25,3,0.12,0.48,1.0,0.186487,0.464217,70,0,1,0,0,0,0.1268,0.8732,0.078947,12,0,0
+ATK0001_C0011,ATK0001,script_kiddie,endpoint_fleet,adaptive_threshold_hunting,46,40,3,0.075,0.575,1.0,0.190169,0.451427,70,0,0,0,0,0,0.1652,0.8348,0.065217,4,0,0
+ATK0001_C0012,ATK0001,script_kiddie,endpoint_fleet,lateral_movement_evasion,39,36,3,0.083333,0.555556,1.0,0.191136,0.407167,70,0,2,0,0,0,0.0884,0.9116,0.076923,3,0,0
+ATK0001_C0013,ATK0001,script_kiddie,soc_management_plane,coordinated_multi_agent,46,41,2,0.04878,0.756098,1.0,0.179034,0.436825,70,1,1,0,0,1,0.2036,0.7964,0.043478,3,0,1
+ATK0001_C0014,ATK0001,script_kiddie,cloud_workload,lateral_movement_evasion,47,43,1,0.023256,0.651163,1.0,0.201614,0.477348,70,0,0,0,0,1,0.1652,0.8348,0.021277,4,0,0
+ATK0001_C0015,ATK0001,script_kiddie,endpoint_fleet,gradient_evasion_whitebox,46,42,2,0.047619,0.666667,1.0,0.192787,0.546143,70,0,1,0,1,0,0.1652,0.8348,0.043478,4,0,0
+ATK0001_C0016,ATK0001,script_kiddie,soc_management_plane,boundary_probe_blackbox,41,28,1,0.035714,0.785714,1.0,0.175708,0.496205,70,0,0,0,1,1,0.1652,0.8348,0.02439,10,4,0
+ATK0001_C0017,ATK0001,script_kiddie,zero_trust_network,concept_drift_injection,51,47,1,0.021277,0.702128,1.0,0.181181,0.47963,70,0,1,0,0,1,0.2852,0.7148,0.019608,2,0,0
+ATK0001_C0018,ATK0001,script_kiddie,endpoint_fleet,gradient_evasion_whitebox,47,39,1,0.025641,0.666667,1.0,0.178038,0.370159,70,0,0,0,0,1,0.1652,0.8348,0.021277,6,4,1
+ATK0001_C0019,ATK0001,script_kiddie,endpoint_fleet,transfer_attack_chain,45,35,0,0.0,0.714286,1.0,0.192791,0.396159,70,0,0,0,0,1,0.0884,0.9116,0.0,9,3,0
+ATK0001_C0020,ATK0001,script_kiddie,zero_trust_network,boundary_probe_blackbox,44,40,1,0.025,0.575,1.0,0.200603,0.417194,70,0,0,0,0,0,0.1652,0.8348,0.022727,4,0,0
+ATK0002_C0001,ATK0002,script_kiddie,endpoint_fleet,model_extraction_reuse,39,28,0,0.0,0.714286,1.0,0.176777,0.353256,70,1,0,0,1,0,0.1652,0.8348,0.0,8,5,0
+ATK0002_C0002,ATK0002,script_kiddie,zero_trust_network,lateral_movement_evasion,42,36,1,0.027778,0.583333,1.0,0.211202,0.512891,70,0,0,0,0,0,0.1652,0.8348,0.02381,4,0,0
+ATK0002_C0003,ATK0002,script_kiddie,endpoint_fleet,coordinated_multi_agent,43,41,2,0.04878,0.756098,1.0,0.193838,0.481809,70,0,1,0,0,0,0.1268,0.8732,0.046512,1,6,0
+ATK0002_C0004,ATK0002,script_kiddie,zero_trust_network,model_extraction_reuse,42,37,1,0.027027,0.756757,1.0,0.218596,0.638659,70,0,0,0,0,0,0.1268,0.8732,0.02381,5,0,0
+ATK0002_C0005,ATK0002,script_kiddie,enterprise_network,transfer_attack_chain,43,38,1,0.026316,0.631579,1.0,0.198007,0.43565,70,1,0,0,0,0,0.1652,0.8348,0.023256,5,2,0
+ATK0002_C0006,ATK0002,script_kiddie,enterprise_network,coordinated_multi_agent,42,35,2,0.057143,0.657143,1.0,0.206287,0.458038,70,0,1,0,0,0,0.2468,0.7532,0.047619,3,5,0
+ATK0002_C0007,ATK0002,script_kiddie,endpoint_fleet,lateral_movement_evasion,45,40,2,0.05,0.6,1.0,0.202192,0.493116,70,1,1,0,0,1,0.2852,0.7148,0.044444,4,0,0
+ATK0002_C0008,ATK0002,script_kiddie,endpoint_fleet,transfer_attack_chain,43,37,2,0.054054,0.540541,1.0,0.200326,0.413103,70,0,1,4,0,0,0.1652,0.8348,0.046512,5,4,0
+ATK0002_C0009,ATK0002,script_kiddie,soc_management_plane,coordinated_multi_agent,44,32,2,0.0625,0.71875,1.0,0.193881,0.464526,70,1,0,0,0,0,0.2036,0.7964,0.045455,9,0,0
+ATK0002_C0010,ATK0002,script_kiddie,zero_trust_network,transfer_attack_chain,48,34,0,0.0,0.764706,1.0,0.18181,0.409174,70,0,0,0,0,1,0.1268,0.8732,0.0,10,0,1
+ATK0002_C0011,ATK0002,script_kiddie,enterprise_network,coordinated_multi_agent,44,37,1,0.027027,0.756757,1.0,0.173039,0.510565,70,0,0,0,0,1,0.0884,0.9116,0.022727,7,1,0
+ATK0002_C0012,ATK0002,script_kiddie,zero_trust_network,lateral_movement_evasion,39,32,1,0.03125,0.71875,1.0,0.204047,0.461325,70,0,0,0,1,1,0.1268,0.8732,0.025641,4,6,1
+ATK0002_C0013,ATK0002,script_kiddie,enterprise_network,adaptive_threshold_hunting,41,34,0,0.0,0.676471,1.0,0.184027,0.505582,70,0,0,0,0,0,0.1268,0.8732,0.0,6,0,0
+ATK0002_C0014,ATK0002,script_kiddie,endpoint_fleet,model_extraction_reuse,45,41,1,0.02439,0.731707,1.0,0.194743,0.438054,70,2,0,4,0,1,0.1268,0.8732,0.022222,4,4,0
+ATK0002_C0015,ATK0002,script_kiddie,soc_management_plane,transfer_attack_chain,44,39,2,0.051282,0.666667,1.0,0.186929,0.374906,70,0,0,0,0,1,0.2852,0.7148,0.045455,4,0,0
+ATK0002_C0016,ATK0002,script_kiddie,soc_management_plane,gradient_evasion_whitebox,40,18,1,0.055556,0.555556,1.0,0.208411,0.531869,70,0,0,0,0,1,0.1652,0.8348,0.025,16,2,0
+ATK0002_C0017,ATK0002,script_kiddie,cloud_workload,gradient_evasion_whitebox,44,33,3,0.090909,0.636364,1.0,0.194361,0.476438,70,0,0,0,0,0,0.1268,0.8732,0.068182,8,0,0
+ATK0002_C0018,ATK0002,script_kiddie,endpoint_fleet,coordinated_multi_agent,44,39,2,0.051282,0.641026,1.0,0.176267,0.399809,70,1,1,0,0,1,0.2036,0.7964,0.045455,5,0,0
+ATK0002_C0019,ATK0002,script_kiddie,zero_trust_network,adaptive_threshold_hunting,45,41,0,0.0,0.756098,1.0,0.179778,0.384993,70,0,0,0,0,1,0.1268,0.8732,0.0,4,1,0
+ATK0002_C0020,ATK0002,script_kiddie,cloud_workload,boundary_probe_blackbox,39,33,1,0.030303,0.69697,1.0,0.203264,0.41826,70,0,0,0,0,1,0.1652,0.8348,0.025641,5,0,0
+ATK0003_C0001,ATK0003,script_kiddie,soc_management_plane,gradient_evasion_whitebox,37,31,2,0.064516,0.612903,1.0,0.177517,0.444398,70,0,1,0,0,0,0.1268,0.8732,0.054054,3,6,0
+ATK0003_C0002,ATK0003,script_kiddie,endpoint_fleet,gradient_evasion_whitebox,43,35,1,0.028571,0.771429,1.0,0.200967,0.4724,70,0,1,0,0,0,0.1268,0.8732,0.023256,7,0,0
+ATK0003_C0003,ATK0003,script_kiddie,ot_ics_environment,model_extraction_reuse,42,30,1,0.033333,0.566667,1.0,0.186126,0.383108,70,0,0,0,0,0,0.1652,0.8348,0.02381,9,0,0
+ATK0003_C0004,ATK0003,script_kiddie,zero_trust_network,gradient_evasion_whitebox,50,31,1,0.032258,0.741935,1.0,0.180994,0.388965,70,0,1,0,0,0,0.1268,0.8732,0.02,13,3,0
+ATK0003_C0005,ATK0003,script_kiddie,soc_management_plane,gradient_evasion_whitebox,44,37,1,0.027027,0.810811,1.0,0.206688,0.464124,70,0,0,0,0,0,0.1652,0.8348,0.022727,6,2,0
+ATK0003_C0006,ATK0003,script_kiddie,cloud_workload,boundary_probe_blackbox,42,36,3,0.083333,0.583333,1.0,0.190443,0.414548,70,0,1,0,0,0,0.1652,0.8348,0.071429,6,0,0
+ATK0003_C0007,ATK0003,script_kiddie,endpoint_fleet,concept_drift_injection,41,32,0,0.0,0.625,1.0,0.202642,0.552808,70,0,0,0,0,1,0.1268,0.8732,0.0,4,0,0
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+ATK0007_C0014,ATK0007,opportunistic,zero_trust_network,adaptive_threshold_hunting,50,43,3,0.069767,0.465116,1.0,0.20601,0.492653,70,0,0,0,0,0,0.0764,0.9236,0.06,4,5,0
+ATK0007_C0015,ATK0007,opportunistic,zero_trust_network,lateral_movement_evasion,36,33,0,0.0,0.69697,1.0,0.17876,0.37904,70,1,0,0,0,1,0.1028,0.8972,0.0,2,0,0
+ATK0007_C0016,ATK0007,opportunistic,cloud_workload,gradient_evasion_whitebox,40,32,2,0.0625,0.6875,1.0,0.19135,0.530637,70,1,0,0,0,0,0.1292,0.8708,0.05,7,0,0
+ATK0007_C0017,ATK0007,opportunistic,soc_management_plane,lateral_movement_evasion,44,42,1,0.02381,0.642857,1.0,0.191882,0.400305,70,0,0,0,0,0,0.1556,0.8444,0.022727,1,0,0
+ATK0007_C0018,ATK0007,opportunistic,cloud_workload,model_extraction_reuse,43,31,0,0.0,0.709677,1.0,0.20328,0.47355,70,0,0,0,0,1,0.0764,0.9236,0.0,11,0,0
+ATK0007_C0019,ATK0007,opportunistic,soc_management_plane,boundary_probe_blackbox,46,44,1,0.022727,0.613636,1.0,0.185927,0.449863,70,0,1,0,0,0,0.1292,0.8708,0.021739,2,0,0
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+ATK0008_C0001,ATK0008,script_kiddie,endpoint_fleet,adaptive_threshold_hunting,41,38,3,0.078947,0.657895,1.0,0.184887,0.35937,70,0,1,0,0,0,0.0884,0.9116,0.073171,2,0,0
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+ATK0008_C0004,ATK0008,script_kiddie,enterprise_network,lateral_movement_evasion,44,40,1,0.025,0.625,1.0,0.188253,0.509632,70,0,0,4,0,0,0.0884,0.9116,0.022727,3,0,0
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+ATK0008_C0012,ATK0008,script_kiddie,ot_ics_environment,coordinated_multi_agent,49,45,1,0.022222,0.555556,1.0,0.179698,0.402951,70,0,0,6,0,1,0.1268,0.8732,0.020408,4,0,0
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+ATK0008_C0014,ATK0008,script_kiddie,ot_ics_environment,adaptive_threshold_hunting,44,33,0,0.0,0.787879,1.0,0.188963,0.391811,70,0,0,0,0,1,0.1268,0.8732,0.0,7,0,0
+ATK0008_C0015,ATK0008,script_kiddie,enterprise_network,coordinated_multi_agent,41,36,3,0.083333,0.583333,1.0,0.187526,0.418725,70,0,0,0,0,0,0.2036,0.7964,0.073171,1,0,0
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+ATK0008_C0019,ATK0008,script_kiddie,ot_ics_environment,concept_drift_injection,42,36,0,0.0,0.722222,1.0,0.184873,0.512531,70,0,0,0,0,0,0.1652,0.8348,0.0,4,0,0
+ATK0008_C0020,ATK0008,script_kiddie,soc_management_plane,lateral_movement_evasion,39,24,0,0.0,0.666667,1.0,0.175215,0.368761,70,0,0,0,0,0,0.1652,0.8348,0.0,7,0,0
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+ATK0009_C0002,ATK0009,advanced_persistent_threat,soc_management_plane,concept_drift_injection,44,36,7,0.194444,0.472222,1.0,0.188341,0.394645,70,1,1,0,0,0,0.194,0.806,0.159091,7,0,0
+ATK0009_C0003,ATK0009,advanced_persistent_threat,endpoint_fleet,adaptive_threshold_hunting,42,39,5,0.128205,0.333333,1.0,0.192196,0.461457,70,0,2,0,0,1,0.062,0.938,0.119048,2,0,0
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+ATK0009_C0006,ATK0009,advanced_persistent_threat,soc_management_plane,transfer_attack_chain,49,42,4,0.095238,0.357143,1.0,0.178904,0.48386,70,0,0,0,0,0,0.074,0.926,0.081633,6,0,0
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+ATK0009_C0008,ATK0009,advanced_persistent_threat,cloud_workload,model_extraction_reuse,48,33,3,0.090909,0.30303,1.0,0.169869,0.461746,70,0,2,0,0,0,0.074,0.926,0.0625,11,4,0
+ATK0009_C0009,ATK0009,advanced_persistent_threat,endpoint_fleet,concept_drift_injection,44,42,5,0.119048,0.309524,1.0,0.1906,0.411585,70,0,1,0,0,1,0.086,0.914,0.113636,1,0,0
+ATK0009_C0010,ATK0009,advanced_persistent_threat,endpoint_fleet,coordinated_multi_agent,47,38,6,0.157895,0.315789,1.0,0.198073,0.42791,70,0,0,0,0,0,0.074,0.926,0.12766,6,0,0
+ATK0009_C0011,ATK0009,advanced_persistent_threat,soc_management_plane,gradient_evasion_whitebox,35,28,8,0.285714,0.178571,1.0,0.192492,0.467679,70,1,1,0,0,0,0.098,0.902,0.228571,7,0,0
+ATK0009_C0012,ATK0009,advanced_persistent_threat,zero_trust_network,coordinated_multi_agent,50,47,7,0.148936,0.297872,1.0,0.19692,0.55976,70,0,5,0,0,0,0.086,0.914,0.14,3,0,1
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+ATK0009_C0014,ATK0009,advanced_persistent_threat,soc_management_plane,concept_drift_injection,41,37,4,0.108108,0.297297,1.0,0.176709,0.510115,70,0,0,3,0,0,0.086,0.914,0.097561,4,3,0
+ATK0009_C0015,ATK0009,advanced_persistent_threat,cloud_workload,gradient_evasion_whitebox,45,42,11,0.261905,0.190476,1.0,0.190926,0.473121,70,0,4,0,0,0,0.098,0.902,0.244444,1,0,0
+ATK0009_C0016,ATK0009,advanced_persistent_threat,soc_management_plane,coordinated_multi_agent,46,36,3,0.083333,0.333333,1.0,0.1818,0.47236,70,0,1,0,0,0,0.086,0.914,0.065217,5,0,0
+ATK0009_C0017,ATK0009,advanced_persistent_threat,enterprise_network,concept_drift_injection,40,35,8,0.228571,0.285714,1.0,0.192273,0.500012,70,1,4,0,0,1,0.098,0.902,0.2,4,0,1
+ATK0009_C0018,ATK0009,advanced_persistent_threat,enterprise_network,coordinated_multi_agent,43,39,5,0.128205,0.282051,1.0,0.178074,0.357579,70,0,2,0,0,1,0.074,0.926,0.116279,4,0,1
+ATK0009_C0019,ATK0009,advanced_persistent_threat,enterprise_network,gradient_evasion_whitebox,43,38,11,0.289474,0.342105,1.0,0.198836,0.472027,70,1,5,0,0,0,0.098,0.902,0.255814,4,0,0
+ATK0009_C0020,ATK0009,advanced_persistent_threat,endpoint_fleet,lateral_movement_evasion,46,43,10,0.232558,0.162791,1.0,0.17399,0.440989,70,0,4,0,0,0,0.074,0.926,0.217391,2,0,0
+ATK0010_C0001,ATK0010,script_kiddie,endpoint_fleet,gradient_evasion_whitebox,40,31,0,0.0,0.83871,1.0,0.188658,0.498151,70,1,0,0,1,1,0.1652,0.8348,0.0,8,0,0
+ATK0010_C0002,ATK0010,script_kiddie,ot_ics_environment,model_extraction_reuse,46,39,3,0.076923,0.512821,1.0,0.193052,0.485624,70,0,1,0,1,0,0.0884,0.9116,0.065217,6,0,0
+ATK0010_C0003,ATK0010,script_kiddie,cloud_workload,gradient_evasion_whitebox,39,33,4,0.121212,0.606061,1.0,0.172785,0.497986,70,0,2,0,0,0,0.1268,0.8732,0.102564,5,0,0
+ATK0010_C0004,ATK0010,script_kiddie,zero_trust_network,gradient_evasion_whitebox,46,43,2,0.046512,0.697674,1.0,0.182612,0.443883,70,0,2,3,0,0,0.1268,0.8732,0.043478,2,0,0
+ATK0010_C0005,ATK0010,script_kiddie,cloud_workload,gradient_evasion_whitebox,40,36,2,0.055556,0.638889,1.0,0.188969,0.572507,70,0,0,0,0,1,0.1268,0.8732,0.05,1,5,0
+ATK0010_C0006,ATK0010,script_kiddie,ot_ics_environment,gradient_evasion_whitebox,43,40,0,0.0,0.675,1.0,0.192011,0.422898,70,2,0,0,0,0,0.1652,0.8348,0.0,1,0,0
+ATK0010_C0007,ATK0010,script_kiddie,ot_ics_environment,gradient_evasion_whitebox,40,31,0,0.0,0.709677,1.0,0.204256,0.480536,70,0,0,0,0,0,0.1268,0.8732,0.0,6,0,0
+ATK0010_C0008,ATK0010,script_kiddie,enterprise_network,model_extraction_reuse,41,29,2,0.068966,0.655172,1.0,0.173868,0.339855,70,0,0,0,0,1,0.2036,0.7964,0.04878,8,0,0
+ATK0010_C0009,ATK0010,script_kiddie,zero_trust_network,coordinated_multi_agent,44,38,2,0.052632,0.815789,1.0,0.170901,0.366801,70,0,0,4,0,0,0.2036,0.7964,0.045455,5,0,0
+ATK0010_C0010,ATK0010,script_kiddie,endpoint_fleet,coordinated_multi_agent,44,37,3,0.081081,0.540541,1.0,0.198698,0.463049,70,0,2,0,0,0,0.0884,0.9116,0.068182,6,5,0
+ATK0010_C0011,ATK0010,script_kiddie,ot_ics_environment,transfer_attack_chain,45,34,0,0.0,0.676471,1.0,0.180444,0.59408,70,1,0,0,0,0,0.0884,0.9116,0.0,8,6,0
+ATK0010_C0012,ATK0010,script_kiddie,zero_trust_network,transfer_attack_chain,46,41,2,0.04878,0.731707,1.0,0.179755,0.433615,70,0,2,0,0,0,0.2036,0.7964,0.043478,5,4,1
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+ATK0010_C0014,ATK0010,script_kiddie,ot_ics_environment,transfer_attack_chain,43,31,1,0.032258,0.612903,1.0,0.176042,0.431287,70,0,1,6,0,0,0.1268,0.8732,0.023256,8,0,0
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+ATK0010_C0019,ATK0010,script_kiddie,zero_trust_network,adaptive_threshold_hunting,45,36,0,0.0,0.694444,1.0,0.185063,0.496864,70,2,0,0,0,1,0.2036,0.7964,0.0,8,0,0
+ATK0010_C0020,ATK0010,script_kiddie,enterprise_network,boundary_probe_blackbox,42,34,0,0.0,0.764706,1.0,0.204029,0.424348,70,0,0,0,0,1,0.2036,0.7964,0.0,6,0,0

network_topology.csv

@@ -0,0 +1,201 @@
+segment_id,detector_id,segment_type,trust_level,detection_coverage,defender_architecture,feature_space_dim,alert_threshold,retraining_cadence_days,ensemble_size,detection_strength,adversarial_robustness
+SEG00001,DET00001,cloud_workload,0.6965,0.8412,gradient_boosted_tree,75,0.7297,36,1,0.74,0.5
+SEG00002,DET00002,data_exfiltration_target,0.5408,0.7775,rule_based_threshold,99,0.7347,30,2,0.55,0.3
+SEG00003,DET00003,ot_ics_control_network,0.5992,0.8136,ensemble_stacked,89,0.7321,31,4,0.91,0.74
+SEG00004,DET00004,soc_management_plane,0.5755,0.6654,autoencoder_anomaly,53,0.6531,36,2,0.71,0.55
+SEG00005,DET00005,ot_ics_control_network,0.6506,0.7284,autoencoder_anomaly,94,0.5824,29,1,0.71,0.55
+SEG00006,DET00006,cloud_workload,0.8111,0.7736,rule_based_threshold,74,0.5633,24,2,0.55,0.3
+SEG00007,DET00007,zero_trust_segment,0.6136,0.8485,gradient_boosted_tree,107,0.6776,26,2,0.74,0.5
+SEG00008,DET00008,data_exfiltration_target,0.6966,0.7028,ensemble_stacked,73,0.6803,35,3,0.91,0.74
+SEG00009,DET00009,cloud_workload,0.2925,0.8125,neural_network_dense,73,0.753,30,2,0.79,0.58
+SEG00010,DET00010,zero_trust_segment,0.5927,0.7181,gradient_boosted_tree,94,0.738,32,1,0.74,0.5
+SEG00011,DET00011,cloud_workload,0.4735,0.7359,transformer_sequence,98,0.6394,35,2,0.85,0.67
+SEG00012,DET00012,soc_management_plane,0.4172,0.8495,lstm_behavioural,93,0.5505,27,2,0.82,0.63
+SEG00013,DET00013,zero_trust_segment,0.4683,0.5108,ensemble_stacked,54,0.6245,36,5,0.91,0.74
+SEG00014,DET00014,ot_ics_control_network,0.5499,0.5944,rule_based_threshold,94,0.6674,33,2,0.55,0.3
+SEG00015,DET00015,soc_management_plane,0.7374,0.5721,ensemble_stacked,66,0.6338,20,3,0.91,0.74
+SEG00016,DET00016,cloud_workload,0.401,0.47,rule_based_threshold,89,0.6038,41,1,0.55,0.3
+SEG00017,DET00017,corporate_lan,0.6046,0.6686,transformer_sequence,59,0.6702,25,1,0.85,0.67
+SEG00018,DET00018,corporate_lan,0.5274,0.8399,neural_network_dense,93,0.6097,16,1,0.79,0.58
+SEG00019,DET00019,ot_ics_control_network,0.5508,0.7158,rule_based_threshold,70,0.5998,21,1,0.55,0.3
+SEG00020,DET00020,data_exfiltration_target,0.7504,0.7737,autoencoder_anomaly,61,0.6749,21,2,0.71,0.55
+SEG00021,DET00021,dmz_perimeter,0.6807,0.8807,transformer_sequence,97,0.6178,30,2,0.85,0.67
+SEG00022,DET00022,ot_ics_control_network,0.8006,0.9093,isolation_forest,89,0.6695,27,1,0.68,0.42
+SEG00023,DET00023,soc_management_plane,0.5768,0.7417,neural_network_dense,73,0.6719,27,1,0.79,0.58
+SEG00024,DET00024,dmz_perimeter,0.4956,0.9124,lstm_behavioural,111,0.5588,34,2,0.82,0.63
+SEG00025,DET00025,soc_management_plane,0.5664,0.7611,rule_based_threshold,77,0.6115,32,2,0.55,0.3
+SEG00026,DET00026,cloud_workload,0.6364,0.6495,ensemble_stacked,85,0.765,32,4,0.91,0.74
+SEG00027,DET00027,zero_trust_segment,0.6265,0.6787,autoencoder_anomaly,89,0.557,33,2,0.71,0.55
+SEG00028,DET00028,endpoint_fleet,0.4373,0.5723,rule_based_threshold,73,0.4807,34,2,0.55,0.3
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+SEG00182,DET00182,data_exfiltration_target,0.2995,0.8998,neural_network_dense,92,0.617,31,1,0.79,0.58
+SEG00183,DET00183,data_exfiltration_target,0.8406,0.7197,autoencoder_anomaly,86,0.5367,32,2,0.71,0.55
+SEG00184,DET00184,dmz_perimeter,0.5313,0.7936,ensemble_stacked,61,0.6855,33,6,0.91,0.74
+SEG00185,DET00185,corporate_lan,0.6162,0.4608,autoencoder_anomaly,84,0.6871,19,1,0.71,0.55
+SEG00186,DET00186,corporate_lan,0.7964,0.6112,autoencoder_anomaly,83,0.5275,36,1,0.71,0.55
+SEG00187,DET00187,corporate_lan,0.3597,0.7147,neural_network_dense,117,0.6684,23,1,0.79,0.58
+SEG00188,DET00188,zero_trust_segment,0.4123,0.6213,autoencoder_anomaly,101,0.7088,35,1,0.71,0.55
+SEG00189,DET00189,data_exfiltration_target,0.3598,0.8357,neural_network_dense,85,0.68,29,1,0.79,0.58
+SEG00190,DET00190,dmz_perimeter,0.4809,0.9897,isolation_forest,89,0.7006,18,1,0.68,0.42
+SEG00191,DET00191,soc_management_plane,0.6659,0.6088,ensemble_stacked,85,0.5377,27,7,0.91,0.74
+SEG00192,DET00192,dmz_perimeter,0.6786,0.6495,ensemble_stacked,81,0.6765,32,5,0.91,0.74
+SEG00193,DET00193,cloud_workload,0.6414,0.7783,transformer_sequence,65,0.6258,34,2,0.85,0.67
+SEG00194,DET00194,endpoint_fleet,0.3881,0.9433,isolation_forest,82,0.6114,28,2,0.68,0.42
+SEG00195,DET00195,soc_management_plane,0.2535,0.6033,lstm_behavioural,71,0.7196,42,2,0.82,0.63
+SEG00196,DET00196,zero_trust_segment,0.6082,0.7799,gradient_boosted_tree,62,0.7683,38,1,0.74,0.5
+SEG00197,DET00197,corporate_lan,0.5292,0.9686,isolation_forest,94,0.7935,27,1,0.68,0.42
+SEG00198,DET00198,dmz_perimeter,0.6689,0.5518,gradient_boosted_tree,92,0.7552,36,2,0.74,0.5
+SEG00199,DET00199,cloud_workload,0.7053,0.5963,isolation_forest,52,0.6412,45,2,0.68,0.42
+SEG00200,DET00200,cloud_workload,0.6207,0.6992,lstm_behavioural,82,0.6782,45,2,0.82,0.63