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I Built an Autonomous AI SIEM With 10 Neural Networks

DEV Community·Миша Ефремов·23 days ago
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What if your server could defend itself? That's the question that drove me to build SHARD — a fully autonomous cybersecurity system that detects attacks, generates real-time defense rules, blocks hackers, and predicts their next move. All without a security team. All without human intervention. The Problem Every day, thousands of servers are attacked. SQL injections, brute force attempts, DDoS floods, ransomware. Small businesses can't afford enterprise SIEM solutions like Splunk or Palo Alto ($50,000+/year). They need something that just works — automatically. I decided to build it. What SHARD Does When an attacker hits your server: 13 honeypots detect the connection (SSH, MySQL, Redis, MongoDB, FTP, etc.) XGBoost ML model classifies the attack type (13 types, 100% accuracy) Seq2Seq Transformer (5.35M parameters) generates unique iptables/WAF rules RL DQN Agent decides: block permanently? block temporarily? throttle?…

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