As we kick off 2026, cybersecurity is undergoing rapid transformation. In just the past year, we’ve seen a surge in attacks driven by advances in AI, automation, and the subsequent increased sophistication of social engineering techniques. This year promises new challenges and exploits.
Below are several predictions for the top threats in 2026, along with actionable recommendations to help strengthen defenses:
1. Exploits facilitated by agentic AI, shadow AI, and AI-driven social engineering methods.
Almost everyone has experienced an AI-related attack this year, as documented in this post from OpenAI, this post describing IDesaster, and this post from Fortune on AI coding tools vulns. While stronger cloud defenses could have helped prevent many of these attacks, monitoring local networks would also have helped to detect shadow AI and address risks in agentic tool usage.
Recommendation: Start by improving hybrid network visibility and monitoring to help detect malicious activity early. One of the more important ways to defend against AI-related attacks is to add network detection and response (NDR) tools that can identify issues early on using a combination of deep packet analysis, network threat detection, and other mechanisms.
2. The rise of deepfakes and synthetic media as part of phishing campaigns.
By generating ever more realistic content, these techniques and technologies can compromise various identity and authentication checks. Or, they can be used to manipulate insiders into establishing trust with adversaries and sharing sensitive or privileged data which could ultimately allow attackers to compromise systems or exfiltrate data. CrowdStrike reported that 75% of intrusions involved compromised identities or valid credentials rather than malware.
Recommendation: Implement stronger ZTNA-based policies and deploy digital identity verification along with AI-based content authenticity tools, such as passwordless and biometric authentication.
3. The escalation of ransomware powered by offensive AI orchestration and automation.
CrowdStrike, in a survey last fall, said AI is increasingly used to accelerate and automate ransomware attacks, making them more difficult to respond to and neutralize. This orchestration is enabling more realistic phishing lures, helping to more quickly compromise systems, driving faster encryption and exfiltration of data, and sending out threats of public release of data in an accelerated and coordinated manner.
Recommendation: Strengthen defenses with comprehensive network security that includes detections for precursors to ransomware attacks, and watches for anomalous command & control and exfiltration of data. AI and other automation tools can also be used defensively to find and prevent the exploits that lead to ransomware attacks.
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4. Attackers are getting better at finding security loopholes, unprotected infrastructure, and ways to hide their network communications.
Thanks to AI-driven tools, finding vulnerabilities has accelerated to warp speed: vulnerabilities can be exploited in minutes not hours. Network scans that previously required human review can be analyzed, and attacks can be launched by automated agents. Now, even attacker communications can more easily hide by creating new tools and exploiting known blindspots in tunnels and through LoTL of network devices.
Recommendation: Improve risk scoring across your entire catalog of assets — such as what can be accomplished with NDR systems — which can help to locate and prioritize vulnerabilities more effectively. Focus on AI-driven incident response methods to complement these systems as well.
5. Static and scheduled network scans leave gaps in time where threats can be deposited and take hold.
Network infrastructure is dynamic: thanks to virtual machines, containers and cloud computing, servers and services come and go in a moment, often creating vulnerable entry points for attackers. As a result, nearly every static scan becomes outdated because it doesn’t capture the real-time status of your infrastructure.
Recommendation: Implement a continuous vulnerability scanning practice along with real-time threat detection. Both can help monitor more of your network infrastructure, decrease attack response times and close detection gaps. This can reduce the potential time windows and opportunities available to adversaries.
6. Multicloud blind spots and evasion of EDR and CNAPP
Catching multicloud threats is getting harder as adversaries get more sophisticated in bypassing existing siloed security tools such as CNAPP and EDR. Having multiple clouds is today’s norm, and that means that tools have to do a better job at having the visibility to understand how networks are constructed across clouds and how data is consumed.
Recommendation: NDR systems can help to analyze cloud data flows and exploits, and create a normalized security data format to facilitate incident response across these multicloud environments.
These are just a few of the scenarios security teams are likely to encounter in the year ahead. As automated and AI-driven exploits advance, defenders will need to keep pace. Organizations that evaluate these six strategic moves for their SOC can put themselves on stronger footing in the face of faster, smarter threats.
