pith:4JHZUWES
Context-Aware Web Attack Detection in Open-Source SIEM Systems via MITRE ATT&CK-Enriched Behavioral Profiling
Context features from prior events raise web attack detection F1 in open-source SIEM from 0.705 to 0.967.
arxiv:2605.13337 v1 · 2026-05-13 · cs.CR · cs.LG
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Context features improve all tested gradient boosting algorithms from ~0.705 macro F1 to 0.947-0.967 (Stage 1) and 0.876-0.914 (Stage 2); the hybrid cascade achieves F1 of 0.967 (binary) and 0.914 (six-class). Wazuh's native rule engine detects 0% of Brute Force and Broken Authentication events; the AI module detects 100% and 98.3% respectively.
The purpose-built dataset of 46,454 Wazuh security events accurately reflects the distribution and behavioral patterns of real-world web attacks and normal traffic.
Smart-SIEM adds context-aware ML profiling to Wazuh SIEM, lifting binary attack detection F1 to 0.967 and six-class categorization to 0.914 while recovering from concept drift via retraining.
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| First computed | 2026-05-18T02:44:48.454704Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
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(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
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Canonical record JSON
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