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threat-prediction

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mayank02raj / MITRE-ATTACK-based-Attack-Chain-Prediction

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Hybrid LSTM-Markov attack chain forecasting for MITRE ATT&CK. Learns from 4,849 campaign chains + 8,437 real intrusion traces. Generates 26,051 risk-ranked multi-step attack futures via constrained beam search. 86% next-step accuracy, 0.76 Pearson correlation with NCISS severity. SECRYPT 2026 submission.

machine-learning deep-learning markov-chain pytorch cybersecurity lstm beam-search stix risk-assessment threat-intelligence mitre-attack attack-graph cyber-defense threat-prediction research-code
  • Updated Apr 17, 2026
  • Python

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