AI-Ready Security: Adapting to New Threats in Cyber Defence

AI Gives Attackers the Same Superpowers It Provides to Your Business

While you’re using AI to analyse data faster, attackers are using AI to create polymorphic malware that changes its appearance every time it strikes. While you’re deploying AI chatbots to improve customer service, cybercriminals are using AI to craft convincing phishing campaigns that adapt in real time.

This creates an impossible choice for organisations. Deploy AI and expand your attack surface. Skip AI and fall behind competitors.

We see this challenge every day in the CyberOne Security Operations Centre (SOC). The solution isn’t choosing between innovation and security. It’s understanding that AI security requires a fundamentally different approach.

The Burglar Who Changes Disguises

Traditional security tools work like security cameras that recognise known criminals by their faces. They maintain databases of malware signatures and known attack patterns. AI-powered attacks make this approach obsolete.

Imagine a burglar who changes clothes, hairstyle and even facial features every time they break in. Traditional cameras would miss them completely. That’s exactly how polymorphic malware works—constantly changing to avoid detection.

Microsoft’s Defender XDR and Sentinel platforms counter this by monitoring behaviour rather than appearance.

They don’t ask, “Does this look like malware?” They ask, “Is this behaving like an attack?”

We recently caught an attack that demonstrates this perfectly. An attacker compromised user credentials through phishing. The login itself looked completely normal; correct username, correct password, no red flags.

But Microsoft’s behavioural analytics connected 3 subtle signals:

1. The login came from an unusual location
2. Within minutes, the account accessed SharePoint files it had never touched
3. Then it attempted to set up email forwarding rules

Each action appeared legitimate in isolation. Together, they revealed account compromise.

Our SOC analysts immediately deactivated the account and contained the breach. Traditional signature-based tools would have missed this completely.

Healthcare’s Big AI Integration Challenge

Healthcare organisations face particularly dangerous AI security challenges. AI models in healthcare settings without proper oversight represents the most significant health technology hazard for 2025.

The statistics are alarming. The 2024 Ponemon Healthcare Cybersecurity Report revealed that 92% of healthcare organisations experienced cyberattacks in 2024, up from 88% the previous year.

AI systems in healthcare require access to vast amounts of sensitive data, including patient records, diagnostic images and scheduling systems. To function effectively, they integrate with multiple backend systems and data stores.

Attackers see these integrations as bridges to broader infrastructure.

We’ve seen attempts where attackers target AI system APIs designed to pull patient records for analysis. If security controls are weak, they exploit these APIs to extract data or pivot, meaning they use that initial access to move into other critical systems like electronic health records, billing platforms or scheduling services.

Unlike traditional segmented systems, AI integrations often prioritise data flow over security. The feature that makes them powerful becomes the attacker’s pathway deeper into the network.

The Change Healthcare ransomware attack in 2024 exemplifies this risk. The attack exposed data for 190 million users because multi-factor authentication wasn’t enabled on external-facing systems.

Microsoft’s Behavioural Advantage

Microsoft’s integrated security ecosystem addresses AI-era threats through advanced correlation capabilities that traditional point solutions can’t match.

Microsoft Sentinel and Defender XDR not only collect security data but also provide actionable insights. They analyse patterns across identities, endpoints, email and cloud applications to spot subtle anomalies that indicate compromise.

The key advantage is context. When a user logs in from an unusual location, accesses unfamiliar data and modifies system settings within minutes, each action might seem normal. The sequence reveals malicious intent.

This behavioural approach proves especially effective against AI-enhanced attacks.

In the Financial Services sector, successful card testing attacks at Stripe have decreased by 80% by utilising AI technology. JPMorgan Chase has introduced “NeuroShield,” an AI-driven fraud detection system that has reduced scam-related losses by 40%, signalling a major leap in financial security (Source: The Silicon Review).

CyberOne helps organisations implement intelligent tools without requiring enterprise-scale security teams. Our approach focuses on building security capabilities that grow with the business. Across industries, we see similar patterns.

IRIS: Automation That Works

Microsoft Security solutions generate a vast amount of data. For organisations without a SOC team, this creates a new problem: too much information, not enough context.

CyberOne's IRIS solution solves this challenge through intelligent automation.

IRIS acts as the connective tissue in our SOC, automatically triaging alerts and applying correlation rules we’ve refined through countless real incidents. Instead of flooding security teams with hundreds of low-value alerts, IRIS surfaces high-confidence, actionable threats with clear context.

The system integrates seamlessly with Microsoft Sentinel, running custom playbooks that automate containment steps, enrich alerts with threat intelligence and streamline incident management.

For organisations without internal SOC capabilities, this means getting enterprise-grade threat detection and response without the complexity or overhead.

IRIS represents our performance-led approach to security. We don’t just deploy tools. We deliver measurable outcomes that enable safe and innovative solutions.

Building Security Muscles

The biggest misconception we encounter is that AI security comes “built-in.” Leaders often assume that if an AI tool comes from a reputable vendor, security is automatically handled.

But AI systems are only as secure as the ecosystem in which they operate.

We shift the conversation from “Is this AI secure?” to “How do we secure what this AI can access?” This reframing changes everything.

Our approach starts with visibility. You can’t secure what you can’t see. We help organisations understand their environment holistically: who has access to what, how data moves, where AI systems connect and where security blind spots exist.

From there, we prioritise practical, high-impact improvements: enforcing least-privilege access, enabling multi-factor authentication and implementing continuous monitoring across endpoints and cloud applications.

We frame this as building security muscles, not just buying more tools.

The cultural transformation occurs when security stops being reactive and becomes an integral part of strategic planning. Instead of asking, “Do we have the right policy to pass an audit?” organisations start asking, “How do we make our new AI initiative secure by design?”

Performance-Led Security Outcomes

Success in AI-enabled environments requires measurable security outcomes, not security theatre.

We track Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) as core metrics. Seeing these times decrease as our SOC and Microsoft-powered tools catch threats faster provides clear evidence of improvement.

We monitor the quality of correlated alerts. Fewer false positives and more true positives mean our behavioural analytics correctly identify suspicious activity without overwhelming staff with noise.

For clients, we demonstrate secure AI integration by ensuring that sensitive data whether customer financial records, manufacturing IP or retail transaction data—is accessed only by authorised workflows, monitoring for anomalous API usage and validating that least-privilege principles are consistently enforced.

Success means clients can adopt AI confidently across all sectors.

• Financial services firms can deploy AI-powered fraud detection without exposing customer data.
• Manufacturing companies can implement predictive maintenance AI without compromising the security of operational technology.
• Retail organisations can utilise AI to deliver personalised customer experiences while safeguarding payment information.

Security enables innovation rather than blocking it.

Security as Competitive Advantage

• Financial Services organisations can scale digital channels securely while maintaining customer trust.
• Manufacturing businesses can implement Industry 4.0 initiatives without compromising operational technology security.
• Retailers can deliver personalised customer experiences while protecting transaction and personal data.

Success means every organisation, regardless of size, has access to the tools, expertise and automation needed to thrive securely in an AI-native world.

Ultimately, security isn’t about choosing between risk and innovation, it’s about enabling both through intelligent, adaptive defence. That’s why at CyberOne, our MXDR as a Service offering helps organisations of all sizes turn security into a competitive advantage by delivering 24x7 threat detection, rapid response and continuous risk reduction to keep your AI-powered future secure.