Machine learning anomaly detection trained on your own traffic. Detects threats signature-based tools miss. Pushes block rules directly to your firewall — automatically, in real time.
AI firewall monitoring is a network security methodology that replaces static signature databases with machine learning models trained on your network's own traffic patterns. Rather than asking "does this packet match a known-bad signature?", AI monitoring asks "is this connection statistically abnormal for this network?"
Traditional intrusion detection systems (IDS) rely on signatures — lists of known bad IPs, known exploit payloads, known malware hashes. They're effective against known threats, but blind to zero-day exploits, low-and-slow reconnaissance, insider threats, and novel attack patterns. An attacker who is slightly patient or slightly creative evades them entirely.
The GoTech AI Firewall Monitoring Platform applies Isolation Forest — a proven, production-grade unsupervised ML algorithm — to firewall logs, syslog, server auth logs, DNS query logs, and NetFlow/IPFIX data. The model is trained per-client, so it learns what "normal" looks like for your specific environment: your server talking to its usual databases, your employees connecting from their usual subnets, your firewall seeing its usual traffic mix.
When traffic deviates from that learned baseline — a new outbound destination that's never appeared before, a login from an unexpected country, a server process suddenly making DNS queries it's never made — the anomaly scores spike and an alert fires. High-confidence threats can trigger Auto-Apply mode, which pushes block rules directly to your firewall (OPNsense, pfSense, iptables, nftables) in real time.
The model ingests weeks of your baseline log data — firewall connections, server auth events, DNS queries, bandwidth patterns.
Isolation Forest randomly splits the feature space. Normal data points require many splits to isolate; anomalies are isolated quickly with fewer splits.
Each new connection or event gets an anomaly score. Low scores = normal. High scores = flag for review or auto-block, depending on your settings.
No labeled attack examples are needed. The model learns what "normal" is and flags deviations — meaning it catches brand-new attack types that no signature list has seen yet.
The platform combines rule-based detection for known threat categories with ML anomaly detection for unknown threats. Both run in parallel.
Detects sequential port sweeps, service banner grabbing, and slow-scan techniques designed to evade rate-based detection rules.
SSH, RDP, VPN, and web application login brute force — including distributed attacks spread across multiple source IPs.
SYN floods, UDP amplification, and ICMP flood detection with automatic rate-limit and geo-block rule generation.
Outbound connections to command-and-control infrastructure — detected via ML anomaly scoring on destination IPs/ports and DNS query patterns.
Unusual outbound bandwidth spikes, large file transfers to unknown destinations, or high-volume DNS responses that indicate DNS-based data exfiltration.
Detection of DNS queries used to exfiltrate data or establish covert C2 channels — catches iodine, dnscat2, and similar tools.
Automatic blocking of Shodan, Censys, Masscan, and other internet scanner infrastructure — stops reconnaissance before it generates noise.
Block inbound traffic from specific countries or regions. Rule is pushed directly to your firewall. Easily adjustable per-device or globally.
Any traffic that deviates significantly from your network's learned baseline — catches novel attack patterns before any signature list has ever seen them.
Full API integration means the platform can push block rules directly to your firewall — not just read logs.
| Firewall | Integration | Status |
|---|---|---|
| OPNsense | Full API + syslog | Full Support |
| pfSense | Full API + syslog | Full Support |
| Linux (iptables) | fw-agent + API | Full Support |
| Linux (nftables) | fw-agent + API | Full Support |
| Linux (ufw) | fw-agent + API | Full Support |
| Cisco ASA | Syslog ingestion | Partial (read-only) |
| Fortinet FortiGate | Syslog ingestion | Partial (read-only) |
| Palo Alto Networks | Syslog ingestion | Partial (read-only) |
| SonicWall | Syslog ingestion | Partial (read-only) |
| Cisco Firepower | Planned | Planned |
| Sophos XG | Planned | Planned |
| Ubiquiti UniFi | Planned | Planned |
curl -sSL https://ai077.gotech.us/install | sudo bash
Communicates outbound over HTTPS port 443 only — no inbound firewall rules needed on your server.
| Distribution | Status |
|---|---|
| Ubuntu (18.04+) | Supported |
| Debian (10+) | Supported |
| RHEL / CentOS (8+) | Supported |
| Rocky Linux | Supported |
| Arch Linux | Supported |
| Alpine Linux | Supported |
| Amazon Linux (2/2023) | Supported |
| openSUSE Leap / Tumbleweed | Supported |
| Generic Linux (any systemd) | Supported |
From zero to AI-monitored in under 30 minutes.
Submit the quote form — we provision your isolated tenant on the platform within one business day. You get a login at ai077.gotech.us and access to your dashboard.
For OPNsense or pfSense: configure the syslog UDP destination to point to the platform collector, or provide API credentials. For Linux firewalls: point your existing syslog facility at us.
Run a single curl | sudo bash command on each Linux server or workstation you want monitored. The agent ships logs outbound over HTTPS/443 — no inbound holes needed.
The Isolation Forest model ingests your actual traffic. After 24–48 hours it begins scoring connections against your specific normal patterns. Rule-based detection (port scans, brute force, known scanners) fires immediately from day one.
Threats appear in your dashboard with severity scores, source IPs, and context. Approve manually to push block rules, or enable Auto-Apply for high-confidence threats. Every action is logged with full audit trail.
No long-term contracts. No setup fees. Add or remove devices any time. Discounts available for home users and education/non-profit organizations.
Per firewall device. Full API integration — rule push, log ingestion, auto-block.
Per Linux server. fw-agent installed, auth log + syslog + iptables monitoring.
Per endpoint. Lightweight fw-agent monitoring for Linux workstations.
Per device. IoT, NAS, specialty appliances — via syslog or custom log shipping.
Home user and education/non-profit discounts available. Contact [email protected]