NetMoniAI explores AI-driven network defense for SOC teams

A new open-source research project, NetMoniAI, developed by Texas Tech University, aims to revolutionize network monitoring and security by combining distributed AI agents with centralized analysis. The framework is designed to help CISOs and SOC teams detect and respond to threats more effectively.

How NetMoniAI Works

The system operates on a two-layer architecture:

1. Node-level agents: Lightweight AI monitors on individual machines analyze local network traffic, detect anomalies, and generate human-readable summaries using language models.
2. Central controller: Correlates data from multiple agents to identify cross-network patterns and coordinated threats.

Early Testing Shows Promise

• Small-scale physical testbed: Detected anomalies and classified traffic within 5 seconds.
• Simulated attacks (DoS, reconnaissance): Scaled to 50 nodes, with agents identifying threats and the controller linking observations.

The framework emphasizes speed, scalability, and interpretability, offering a dashboard and chatbot for clear explanations.

Potential Impact on SOC Operations

NetMoniAI addresses longstanding challenges in network monitoring:

• Packet-level inspection vs. flow-based monitoring trade-offs.
• Reducing false positives and redundant alerts.
• Surfacing distributed attacks that traditional methods miss.

Corey Nachreiner, CISO at WatchGuard, noted: "An AI-based hybrid system could detect early anomalies on a single system and correlate follow-on attacks, giving defenders multiple chances to break the chain."

Challenges Ahead

While promising, NetMoniAI faces hurdles:

• Enterprise-scale testing: Untested in high-traffic, regulated environments.
• Cost and latency: Dependence on large language models raises concerns.
• Autonomy vs. control: Security teams may hesitate to grant AI agents too much independence.

Pallavi Zambare, co-author, emphasized: "This is not about replacing humans. Analysts retain final authority, while AI provides structured reports and recommendations."