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HYDRA NDR
BlueWave AI Kft. · Budapest, Hungary
Hybrid Unified Detection & Response Architecture 6-Head FourierKAN · Network-native · Edge-deployable

Stop network threats
before they reach your endpoints.

AI-powered Network Detection & Response built on a 6-head FourierKAN architecture. Detects DNS tunneling, C2 beaconing, fast-flux evasion, DGA malware, IDN homograph attacks, and DNS spoofing — in real time, with full interpretability.

<5 min
Mean Time to Detect
per threat class
6 heads
FourierKAN analysis
streams, parallel
5 TTPs
MITRE ATT&CK DNS
coverage (T1048–T1584)
Edge
On-device deploy
Juniper SRX / MX / EX
🌐

Network threats hide in plain sight — inside DNS traffic

Over 90% of malware uses DNS for command & control. Because DNS is universally allowed through firewalls, attackers abuse it to exfiltrate data, beacon to C2 servers, and generate new evasion domains on the fly. Traditional signature-based tools are always behind the curve.

  • DNS tunneling — data exfiltration invisibly encoded in query payloads
  • C2 beaconing — low-volume periodic callbacks to attacker infrastructure
  • Fast-flux DNS — rapid IP rotation evades IP blocklists and reputation systems
  • DGA malware — algorithmically generated domains rotated daily, unblockable by static lists
  • IDN homograph attacks — Unicode lookalike domains trick users and mail filters alike
  • DNS spoofing / poisoning — redirects traffic to attacker-controlled infrastructure
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HYDRA NDR: six specialized heads, one unified verdict

HYDRA monitors all DNS traffic at the resolver level — no agents, no blind spots, no performance impact. Six FourierKAN heads analyze every query in parallel, each specialized for a different threat class. Their outputs are fused into a single, explainable verdict.

  • Full-spectrum coverage: all six DNS threat classes detected simultaneously
  • Interpretable by design: every verdict is auditable — no black-box decisions
  • Edge-deployable: runs on Juniper SRX / MX appliances or a co-located sidecar
  • Works with Zeek, J-Flow, IPFIX, and Juniper Security Director Cloud
  • DORA & NIS2 compliant audit trail with full query-level evidence chains
6-Head FourierKAN Architecture
Head 1
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DNS Tunnel Detection

T1048.003 · T1071.004

Analyses query payload length distributions, base32/base64 encoding patterns, and subdomain entropy. Catches data exfiltration hidden inside seemingly legitimate DNS traffic — including low-and-slow variants designed to evade volume-based detectors.

Head 2
⏱️

C2 Beaconing

T1071.004 · T1090

Identifies periodic, regular DNS lookups characteristic of malware heartbeat callbacks. Uses FourierKAN's frequency-domain representation to detect precise timing regularity — even when attackers add jitter to evade time-windowed detection.

Head 3

Fast-flux Evasion

T1568 · T1584.001

Detects domains with abnormally short TTLs, high A-record churn, and geo-dispersed IP rotation — the hallmarks of fast-flux infrastructure used by botnets and phishing kits to evade IP-based blocking.

Head 4
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DGA Domain Detection

T1568.002

Classifies Domain Generation Algorithm output using n-gram frequency analysis, character entropy scoring, and lexical feature extraction. Catches DGA families including dictionary-based variants that fool simpler entropy-only approaches.

Head 5
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IDN Homograph & Lookalike

T1583.001 · T1566

Detects Unicode homograph attacks (Cyrillic/Latin lookalikes), typosquatting, and brand impersonation in domain names. Combines visual similarity scoring with threat intelligence correlation to catch phishing infrastructure before HTTP traffic appears.

Head 6
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DNS Spoofing & Poisoning

T1557 · T1584

Detects anomalous response patterns: unexpected TTL changes, mismatched authoritative nameservers, response inconsistencies across resolvers. Identifies cache poisoning attempts and on-path DNS hijacking in real time.

FourierKAN Fusion Layer — Unified Verdict + Audit Trail
FourierKAN — Why Fourier?
Standard KAN learns B-spline activations. FourierKAN replaces them with learnable Fourier series — ideal for DNS analysis because DNS threat signals are inherently periodic (beaconing), frequency-structured (DGA entropy), and waveform-like (tunnel payload patterns). Every head's decision is mathematically auditable: regulators and SOC teams can inspect exactly which frequency components triggered the alert, with no black-box inference.
Interpretable
Edge-native — runs where your network gear lives

HYDRA is being co-developed with Juniper Networks infrastructure in the BlueWave AI × HPE lab in Szeged. Three deployment architectures are supported — from on-device to cloud-hybrid.

Option 1 — On-device
Junos EVO / cRPD Container

HYDRA runs as a containerized sidecar directly on Junos Evolved devices. DNS telemetry is intercepted at the forwarding plane via dnstap or J-Flow. Zero additional hardware. Best for MX / EX environments with available compute budget.

🖥 Juniper MX / EX series (Junos EVO) · cRPD
Option 2 — Sidecar Appliance
Co-located Mini Appliance

HYDRA engine runs on a compact appliance (Intel NUC / Nvidia Jetson) placed adjacent to Juniper SRX gear. DNS traffic is passively mirrored via SPAN/port mirroring. No latency impact on the forwarding path. Ideal for SRX branch deployments.

🖥 Juniper SRX + Intel NUC / Jetson Orin · SPAN tap
Option 3 — Cloud Hybrid
Security Director Cloud + HYDRA Backend

Juniper Security Director Cloud (or Mist AI) forwards DNS event telemetry to a HYDRA inference backend via API. Centralized detection across distributed branch offices. Best for large enterprise with existing Juniper Security Director deployments.

☁️ Juniper Security Director Cloud · Mist AI API
Input formats supported: Zeek dns.log / conn.log · Juniper J-Flow / IPFIX · dnstap (RFC 8427) · Juniper ATP Cloud telemetry · Juniper JSA (STRM) syslog · Passive DNS (pDNS) feeds
Built for regulated environments with zero tolerance for blind spots
🏦

Financial Institutions

DORA Articles 9 & 10 require continuous ICT threat monitoring and 24-hour initial incident notification. HYDRA provides DNS-layer detection with a complete, query-level audit trail ready for DORA incident reports. Works with existing Juniper / Cisco / Infoblox DNS infrastructure.

DORA ECB TIBER PCI DSS

Critical Infrastructure

NIS2 Directive mandates advanced threat detection for energy, water, transport, and health sectors. HYDRA deploys passively at the DNS resolver level with no disruption to OT/SCADA environments — and no endpoint agents to maintain. Edge deployment keeps DNS data on-premise.

NIS2 ICS/SCADA OT-safe
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Enterprise SOC Teams

Replace noisy rule-based DNS security with AI detection that surfaces real threats with full context. Native SIEM connectors for Splunk, Microsoft Sentinel, Elastic, and IBM QRadar. Alerts are MITRE ATT&CK-tagged with per-head confidence scores and evidence chains for analyst review.

SIEM Integration SOC Automation MITRE ATT&CK

Cost of DNS-Based Threats — Mid-Size Bank (DORA scope)

ItemEstimate
Average cost of undetected data breach€4.5M
DORA non-compliance penalty exposure€10M+
Mean dwell time — DNS threats without NDR~180 days
Mean dwell time with HYDRA NDR<5 minutes
HYDRA NDR annual licence€150K–€400K
Risk-adjusted ROI10–30×

* IBM Cost of a Data Breach Report 2024 · Mandiant M-Trends 2024 · DORA penalty estimates per EBA guidance. Estimates for illustrative purposes only.

Compliance Coverage

  • DORA Art. 9–10 — continuous ICT threat monitoring with full DNS query-level audit trail for 24h incident reporting
  • NIS2 Directive — advanced threat detection and incident notification for essential and important entities
  • GDPR Art. 5 & 32 — no payload data stored; metadata processed in-stream; configurable retention policies
  • EU AI Act — FourierKAN interpretability satisfies High-Risk AI explainability and oversight requirements
  • ISO 27001 / SOC 2 — aligns with A.12.6 technical vulnerability management and continuous monitoring controls

Request a live demo or PoC proposal

We can deploy a 30-day Proof of Concept on your DNS infrastructure.
Agentless. No disruption. Full DORA/NIS2 compliance report included.

👤Németh Gyula — Founder & Lead AI Engineer
Request PoC →