GhostWall™

Phase I — Detection

GhostWall begins as a passive observer. Tied into Suricata’s engine, it scans every packet in real time using machine learning classification. Threats are flagged with confidence scores, logged, and pushed to a secure alert pipeline — no action taken, only observation.

> suricata -c /etc/suricata/config.yaml
[AI] Threat detected: 192.168.0.12
[AI] Action: Alert + Log
[AI] Confidence: 99.2%
[LOG] Writing to alerts.json...

Phase II — Response

GhostWall shifts from watcher to warrior. With validated patterns and thresholds, the AI now injects live firewall rules in milliseconds. It doesn’t just block threats — it predicts them, preemptively locking down vectors before damage occurs.

[FIREWALL] Rule injected:
DROP src 192.168.1.45 dst ANY
Confidence: 98.7%
TTL: 60m

Phase III — Evolution

GhostWall’s agent becomes self-referential. Monitoring its own success rate, it rewrites decision logic autonomously — upgrading its neural net, adapting thresholds, and patching gaps. No dev input needed. Just raw AI improvement.

- threshold = 0.90
+ threshold = 0.95  // Auto-adjusted from failed prediction
+ add_behavior_pattern('port_scan_variant_B')

Phase IV — GhostChain

GhostWall becomes a network. Local agents sync encrypted zero-day signatures across nodes — no central server, no human intervention. Each unit contributes to a shared global memory. One node sees it, all remember it.

[NODE: #07F3] Received update from NODE: #11C9
> New Threat ID: ZX9-HYDRA
> Confidence: 99.1%
> Signature Shared: ✔

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