Why is NDR leading the cybersecurity shift – And why now?
By Sharat Nautiyal (pictured), Director of Security Engineering, Vectra AI, Asia Pacific & Japan
Cyberattacks today aren’t loud or obvious – they’re stealthy, surgical and drawn out over days, weeks or even months. Adversaries escalate privileges quietly, move laterally through hybrid environments and strike when the damage will be greatest. Recent breaches like the attack capturing over 31,000 Australian banking credentials, and $500,000 stolen through Australia’s superannuation funds, underscore just how ineffective prevention-only security tools have become. The Australian government’s 2023-2024 Annual Cyber Threat Report states that the financial and insurance service industry is amongst the top 10 reporting sectors, decreasing to 8th place from 6th the previous year.
As threat actors increasingly weaponise Artificial Intelligence (AI) to scale reconnaissance, craft convincing phishing campaigns, and exploit vulnerabilities faster than ever, defenders are under pressure to evolve. Mentions of malicious AI tools on cybercrime forums have surged 200%, and IBM reports that two-thirds of cybersecurity professionals have had to revise their strategies in response to AI-powered threats. In turn, SOC teams are increasingly relying on AI-driven solutions to stay ahead.
NDR Is Mission-Critical for Detecting Threats Hiding in the Gaps
As cloud adoption surges and hybrid environments become the norm, traditional perimeter defences and siloed tools like EDR, SIEM, and cloud security platforms are no longer enough. Today’s attackers are no longer barging through the front door—they’re “living off the land”, exploiting trusted tools and moving laterally under the radar.
Network Detection and Response (NDR) provides the visibility and intelligence needed to detect what others miss. By analysing both north-south (perimeter) and east-west (internal) traffic, NDR surfaces meaningful insights that help stop stealthy activity before it causes damage. In this context, NDR acts as the connective tissue between fragmented tools—turning isolated alerts into coherent incidents, and enabling faster, automated response when every second counts.
Gartner’s latest Magic Quadrant for NDR highlights how leading platforms are raising the bar—integrating seamlessly into broader security ecosystems, reducing false positives, and delivering real-time threat detection across complex environments.
For high-stakes sectors like financial services, healthcare and critical infrastructure, the need is particularly acute. Whether it’s detecting attempts to tamper with election infrastructure or stopping identity-based threats before data exfiltration occurs, NDR is quickly becoming indispensable.
AI: The Engine Behind Effective NDR
AI is the force multiplier behind NDR. It enables platforms to ingest vast volumes of network traffic, learn from attacker behaviour, and prioritise threats with unmatched speed and accuracy. This is particularly important in today’s dynamic environments, where SOC teams are inundated with noise and need fast, actionable insights—not just more alerts.
Advanced NDR solutions use behavioural models and machine learning to identify anomalies in real time, continuously refining detection logic as attacker tactics evolve. When integrated with other tools in the security stack, NDR enhances overall visibility, supports incident triage, and accelerates time-to-response.
Beyond the Perimeter: A New Security Paradigm
Relying solely on prevention is no longer viable. Breaches are inevitable—the critical question is how quickly you can detect and contain them. Headlines may focus on the initial breach, but the true damage often occurs later, when attackers quietly exfiltrate data or disrupt critical operations.
While endpoint protection remains important, it can’t be the sole line of defence. In a world of hybrid environments and decentralised decision-making, organisations need a multi-layered strategy that includes continuous network monitoring and automated response.
Laying the Foundation For XDR
As security strategies mature, the boundaries between NDR and Extended Detection and Response (XDR) are blurring. While XDR pulls data from multiple layers—endpoints, cloud, email, and beyond—NDR provides the deep network visibility essential for spotting threats that evade other tools.
By monitoring traffic patterns, detecting anomalies, and correlating activity across the network, NDR becomes the foundation of any robust XDR strategy. It helps security teams stop lateral movement, contain insider threats, and prevent attackers from exploiting known vulnerabilities—such as those used in the Salt Typhoon campaign—or stealing sensitive data, like the malware attack on FIIG, comprising 18,000 clients’ personal information.
Identity: The Critical Battleground
Identity is often the attacker’s target. This makes Identity Threat Detection and Response (ITDR) is a crucial complement to NDR. By combining native identity signals with native network telemetry, organisations can detect identity-based threats earlier and respond with greater precision.
For buyers evaluating NDR solutions, identity coverage should be non-negotiable. The ability to detect unauthorised access, privilege escalation, and account abuse is essential in today’s landscape.
What to Look for in an NDR Solution
Not all AI-powered security platforms are created equal. When selecting an NDR solution, security leaders should look for:
- Cloud and On-Prem Compatibility: The platform must analyse raw traffic across all environments—cloud, on-premises, and hybrid.
- Behavioural Detection Models: Look for AI that blends human expertise with machine learning, constantly learning and adapting.
- Incident Aggregation: Solutions should consolidate alerts into structured incidents to streamline triage and response.
- Three Core Capabilities:
- Coverage: Detect a wide range of attack techniques.
- Clarity: Prioritise based on what matters to your environment.
- Control: Give SOC teams the power to intervene early and decisively.
Importantly, hold vendors accountable for their AI claims. Ask for proof of efficacy, demand transparency around how models work, and prioritise solutions with robust instrumentation and telemetry.
Looking Ahead: Outpace. Outsmart. Defend.
As cyber threats grow more sophisticated, the future of defence lies in autonomy. AI-driven NDR platforms are already reducing the burden on analysts by detecting and responding to threats in real time with minimal human intervention.
As these systems continue to mature, the ability to detect threats, triage incidents, and initiate responses autonomously will become table stakes. In this context, learning from NDR leaders like those recognised in Gartner’s 2025 Magic Quadrant isn’t just smart—it’s essential.
These platforms set the benchmark for what effective, AI-powered network security looks like. By adopting solutions that deliver visibility, speed, and automation, organisations can better protect their assets, their reputation, and the broader digital ecosystem we all depend on.
