Google’s 2024 zero‑day report sent shockwaves through the cybersecurity world. It revealed that 44 percent of all zero‑day exploits last year targeted enterprises and that 60 percent of those attacks focused squarely on security and networking products. Those are the very lines of defense we rely on to keep our data safe.

Even more alarming, many organizations still don’t monitor their firewalls, routers, and identity systems with the same rigor as endpoints. The result? Gaps that threat actors can,  and do,  exploit, leading to an estimated $44 billion in global losses. Let’s walk through Google’s findings, explore why traditional tools miss these blind spots, and show how AI‑enhanced risk platforms can give you the visibility and speed you need to stay one step ahead.

Google’s 2024 Findings: Enterprises in the Crosshairs

Last year’s data makes it clear: attackers are hunting bigger targets. Google’s threat analysis shows that nearly half of zero‑day exploits hit corporate networks rather than home users.

• 44 percent of exploits focused on enterprise systems, not consumer devices.
  
  
• 60 percent of attacks zeroed in on security and networking products such as firewalls, VPN gateways, and identity‑access management tools.
  
  
• Average dwell time,  the period between compromise and detection,  exceeded 30 days in many cases.
  

Those numbers mean that executives and security teams must treat every unexpected log entry and configuration change as a potential zero‑day clue. Ignoring that data is no longer an option when the losses can total in the tens of billions.

Why EDR Tools Miss Infrastructure Blind Spots

Endpoint detection and response (EDR) solutions do a fine job of monitoring servers and workstations. But Google’s report highlights a key blind spot: your network hardware and security appliances rarely fall under the EDR umbrella.

• No agents on appliances: Most firewalls and routers cannot run endpoint agents, leaving them unmonitored.
  
  
• Log silos: Network device logs often sit in separate systems, never correlated with endpoint alerts.
  
  
• Delayed patch cycles: Vendors release patches slowly, and without real‑time monitoring, unpatched appliances remain exposed.
  

Without continuous insight into these critical layers, your EDR deployment covers only part of the battlefield. Attackers know this and exploit it.

Actionable Insight: Extend your monitoring scope by deploying network‑level sensors that feed appliance logs into your security console. Correlate those logs with endpoint alerts to spot suspicious patterns,  like a sudden spike in dropped packets or unexpected VPN login attempts.

The True Cost of Unpatched Systems

The financial impact of zero‑day exploits is staggering. Industry analysts place global breach costs at over $44 billion for 2024 alone. Beyond direct remediation costs,  hiring emergency contractors, paying ransoms, and restoring backups,  firms lose customer trust and may face hefty regulatory fines.

• SEC penalties for failing to patch critical vulnerabilities can run into the millions.
  
  
• GDPR fines may reach 4 percent of annual global turnover if personal data is exposed.
  
  
• Reputational harm translates into lost business, with surveys showing that 60 percent of customers switch providers after a breach.
  

Every unpatched appliance isn’t just a technical gap; it’s a ticking financial time bomb.

Actionable Insight: Integrate your patch‑management system with your risk platform so that any missed update triggers an immediate high‑risk alert. That way, you can prioritize and track appliance patches alongside your endpoint updates.

From Static Rules to AI‑Driven Risk Scoring

Legacy risk tools rely on static rule sets that require manual updates. In a world where zero‑day exploit patterns evolve daily, those rules fall behind. AI‑enhanced platforms take a different approach:

• Continuous learning: AI examines live telemetry from endpoints, networks, and cloud services to spot outliers.
  
  
• Real‑time risk scores: Each asset,  server, firewall or IAM platform carries a risk score that updates automatically as new threats emerge.
  
  
• Predictive insights: By mapping behaviors to known attacker tactics (using frameworks like MITRE ATT&CK), AI can flag likely zero‑day attempts before they succeed.
  

With AI at the core, you gain a dynamic picture of your security landscape rather than a static snapshot.

Actionable Insight: Pilot an AI risk platform on your top five high‑value assets, including one network appliance. Compare the speed and accuracy of breach detection against your current tools.

Case Study: AI in Action Averts a Network Breach

Earlier this year, a global financial institution suffered an attempted zero‑day attack on its main data‑center firewall. The device’s CPU usage spiked at unusual hours. While the legacy monitoring system dismissed it as normal traffic, the AI platform’s anomaly detector scored it as a likely zero‑day indicator. An automated drill simulated an exploit, triggered a containment playbook and blocked the suspicious traffic,  all in under five minutes. The bank avoided a potential breach that could have cost tens of millions.

That real‑world success shows how AI‑driven risk platforms can fill gaps that traditional tools miss.

Mapping to Industry Frameworks: ISO 27001 and NIST CSF 2.0

You need more than a buzzword. Tie your AI‑enhanced zero‑day detection to established standards:

• ISO 27001: Use the standard’s Annex A.12 controls (Operations security) to guide your network and endpoint monitoring strategy.
  
  
• NIST CSF 2.0: Map your risk‑scoring outputs to the “Detect” and “Respond” functions, showing auditors exactly how you catch and handle anomalies.
  
  
• MITRE ATT&CK: Integrate automated mapping so each detected anomaly links back to known tactics and techniques.
  

Framing AI insights within these familiar models smooths audit paths and gives stakeholders confidence that your approach stands on solid ground.

Trending Threats: Ransomware‑as‑a‑Service and the EU AI Act

Zero‑day exploits rarely exist in isolation. Ransomware‑as‑a‑Service gangs leverage unpatched appliances to gain an initial foothold before deploying encryption payloads. Industry reports estimate RaaS revenues at $200 billion globally for 2025. Meanwhile, the EU AI Act will soon require risk scoring algorithms to undergo transparency reviews, affecting how you deploy AI within your security stack.

• RaaS risks: Treat every unusual encryption request as a potential zero-day vulnerability.
  
  
• AI Act considerations: Ensure your AI risk models include audit logs and explainability features.
  

Staying ahead of these trends means your zero‑day detection efforts also support broader resilience goals and keep you compliant with AI regulations.

Turn Zero‑Day Chaos into Confidence, Contact iRM

When 44 percent of zero‑day attacks hit enterprises and 60 percent strike security appliances, you can’t rely on endpoint tools alone. AI-driven risk platforms close critical visibility gaps,  offering real-time risk scores, predictive analytics, and automated playbooks that stop zero-day exploits before they cause billions in damage.

Contact iRM today to explore our AI‑powered risk frameworks. We’ll help you extend monitoring to every layer of your infrastructure, integrate MITRE ATT&CK for clear breach context, and automate your patch and incident workflows, so you finally sleep easy knowing zero‑day blind spots are a thing of the past.