Major Cyber Security Threats & Trends 2026

AI-powered and AI-automated attacks

Attackers are expected to use AI (and “agentic AI” / autonomous agents) to automate reconnaissance, exploit search, phishing, intrusion, lateral movement and even breach orchestration at machine speed.
Use cases include deepfake-based social engineering, automated spear-phishing, prompt-injection attacks (for systems embedding generative-AI), and autonomous malware with adaptive behavior.
That lowers the bar for attackers — small groups or lone actors with AI tools may achieve what previously needed bigger teams or nation-state resources.
Implication: Defenders can no longer rely solely on “slow” manual triage or signature-based defenses — detection, mitigation and containment need to operate at high automation and speed.

Attacks targeting software supply chains — e.g., open-source libraries, dependencies, cloud-hosted platforms — are expected to grow significantly. A compromise at a small or upstream vendor may cascade to hundreds or thousands of downstream organizations.
This includes both “traditional” software supply chains and cloud-native ecosystems, container registries, infrastructure-as-code templates, third-party services, etc.
Implication: Even well-defended orgs are vulnerable if they depend on unverified third-party code. Software supply-chain hygiene and continuous vetting become critical.

According to recent forecasts, 2026 will likely see intensified attacks on industrial control systems (ICS), operational technology (OT) environments, and hybrid systems combining IT + OT.
Critical infrastructure (energy, utilities, manufacturing, transport) remains a top target — the potential impact (service disruption, safety risks, reputational damage) is large.
Implication: Organizations operating or supporting critical infrastructure need to assume “compromise will happen” and adopt robust segmentation, monitoring, and incident response strategies.

As per recent intelligence, attackers increasingly target service accounts, API keys, credentials, OAuth tokens, cloud identities, machine/service-to-service identities — not just human user accounts.
The rise of remote/cloud-native architectures and automated services means identity-centric attacks (misuse of credentials, token theft, identity impersonation) will be especially potent.
Implication: Zero-trust identity management, least-privilege access, credential rotation, audit and anomaly detection must become the baseline — identity is the new perimeter.

Ransomware remains a top threat: with AI-enabled malware and faster propagation, we may see larger, more destructive attacks — often targeting supply chains or critical infrastructure.
Attackers are likely to adopt more subtle, “stealth-first, extortion-later” methods: exfiltrate data, hold it for ransom (or sell), rather than just encrypt.
Implication: Backups, immutable storage, anomaly detection, segmentation and ransomware-resistant architecture remain essential — but now under pressure from faster, AI-enhanced threats.

As more organizations adopt AI-based tools for productivity, automation, or decision making, compromising those AI agents or injecting malicious prompts becomes an attractive route for attackers.
Risks include: unauthorized data extraction, malicious command execution, bypassing of traditional security checks, or serving as “inside agents” inside corporate infrastructure.
Implication: Security must extend into AI/ML pipelines, with strict access controls, prompt validation, logging, and limits on what AI-powered agents can execute — treat them as high-privilege “users.”

Treat AI-driven attacks as business as usual: invest in automation for defense, detection at machine speed, and threat hunting.
Insist on supply-chain hygiene: vet dependencies, isolate third-party code, prefer signed/trusted libraries.
Protect identities first — human and non-human. Implement least-privilege, zero-trust, credential hygiene, audit logging.
Harden infrastructure & OT/ICS: segmentation, network monitoring, regular pentests of hybrid environments (IT + OT).
Assume ransomware/extortion is inevitable — design for resilience: immutable backups, isolation, incident-response drills.
Treat AI agents as privileged entities: secure, log and limit what they can do; review permissions frequently.