Network Security

Stop threats from moving across your network
before they become a breach

Network Security

Network Security — Detect and Stop Threats Your Perimeter Can't See

Firewalls and signature-based tools stop known threats at the edge. But once an attacker is inside your network — moving laterally, escalating privileges, exfiltrating data — traditional tools are largely blind. AI-powered network detection and response sees everything, learns what normal looks like, and stops threats before they cause damage.

Why Perimeter Security Is Not Enough

Most network security tools are built to stop known threats at the perimeter — blocking IP addresses, filtering known malware signatures, enforcing firewall rules. Against attackers who are already inside, or threats that have never been seen before, they are largely ineffective.

Ransomware groups spend an average of 11 days inside a network before deploying their payload — mapping systems, escalating privileges, disabling backups, and positioning for maximum damage. None of this activity triggers a firewall rule. It requires a different approach: self-learning AI that understands what normal behaviour looks like in your specific environment — and detects anything that deviates from it.

70% of network threats are novel — never seen before.

Rule-based and signature-based tools can only detect what they have been trained to recognise. Most real-world network threats involve techniques that bypass these controls entirely. AI-driven network detection identifies threats based on behavioural anomaly — not because they match a known pattern, but because they deviate from what is normal for your organisation.

What Our Network Security Service Provides

🧠 Self-Learning AI Detection

Learns the normal behaviour of every device, user, and connection in your network. Detects deviations — unusual traffic patterns, unexpected connections, anomalous data flows — that indicate a threat, even one that has never been seen before.

⚡ Autonomous Response

When a threat is detected, AI responds in real time — isolating affected devices, blocking suspicious connections, forcing re-authentication — without waiting for human intervention. Contained in seconds, not hours.

🌐 Full Network Visibility

Complete coverage across on-premise, cloud, hybrid, and OT environments. Every device, every connection, every data flow — visible in a single platform. Including remote workers and IoT devices that traditional tools miss.

🔌 Lateral Movement Detection

Identifies attackers moving through your network after an initial compromise — credential abuse, privilege escalation, reconnaissance — before they reach critical systems or deploy ransomware.

📈 Reduced Alert Fatigue

AI triage investigates and correlates alerts automatically — reducing the volume of notifications your team receives to only what genuinely requires attention. Security teams focus on response, not noise.

📋 NIS2 & DORA Compliance

Continuous network monitoring with detailed logs of all detected threats and responses — satisfying NIS2 and DORA requirements for network security controls, incident detection, and audit documentation.

Powered by Darktrace — Gartner Magic Quadrant Leader for Network Detection and Response

Our network security service is delivered through Darktrace — the AI cybersecurity company whose Self-Learning AI learns the unique digital fingerprint of your organisation and detects threats that no rule or signature could catch. Named a Leader in the Gartner Magic Quadrant for Network Detection and Response 2025 and 2026. Used by organisations including ABN AMRO, Air France-KLM, and Siemens Energy.

Frequently Asked Questions

We already have a firewall — do we still need network detection?

Yes. A firewall enforces rules at the perimeter — blocking or allowing traffic based on predefined policies. It cannot detect threats that arrive through allowed channels (legitimate credentials, trusted connections, phishing payloads), and it is blind to what happens inside your network once an attacker is in. Network detection and response monitors all internal traffic and detects anomalous behaviour regardless of how the attacker entered.

How does self-learning AI work for network security?

Instead of relying on rules or known threat signatures, self-learning AI builds a behavioural model of your network — what devices normally connect to, what data flows normally look like, what users typically do at what times. When something deviates from this baseline, it flags the anomaly. This means it can detect threats that have never been seen before, including zero-day exploits, novel ransomware variants, and insider threats.

Does this cover cloud and remote workers?

Yes. Modern network security must extend beyond the on-premise perimeter. Our service covers on-premise infrastructure, cloud environments (AWS, Azure, Google Cloud), hybrid networks, OT/IoT devices, and remote worker endpoints — giving you full visibility regardless of where your assets and users are located.

Does network security help with NIS2 compliance?

Yes. NIS2 Article 21 requires organisations to implement network monitoring and detection controls as part of their cybersecurity risk management. Continuous AI-driven network detection directly satisfies this requirement — and the detailed threat logs provide the audit evidence regulators require.

See What's Happening Inside Your Network Right Now.

Book a free network security assessment with Magic Stone. We'll show you what AI-driven detection reveals about your network — and what your existing tools are missing.

Book a Free Network Security Assessment

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Our Partners

We maintain a diverse network of strategic technology alliances to optimise our cyber security solutions, each selected for their proven ability to deliver real cybersecurity outcomes. Every partner we work with is thoroughly vetted to ensure their solutions align with our mission—protecting your business against ransomware, enhancing visibility, and supporting NIS2 compliance.

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