Huntress Reports 10 Endpoint Security Trends Shaping 2026

Huntress published a report detailing ten endpoint security trends shaping 2026, highlighting the growing risks of AI agents and evolving ransomware tactics.

The risk

Threat actors are increasingly using living-off-the-land techniques to blend into normal system activity, bypassing traditional antivirus tools that rely on perimeter defenses. Huntress notes that endpoints, identities, and cloud workloads now overlap, creating complex attack surfaces that standard tools struggle to monitor effectively.

Who is exposed

Organizations relying on autonomous AI systems for security operations face new risks, as these agents can miss novel threats or behave unpredictably if attacked. Huntress warns that attackers may target AI agents themselves as non-human identities, attempting to hijack their decision-making processes without human oversight.

Cost and compliance

Ransomware groups are shifting from simple encryption to multi-layered extortion, combining data theft with public pressure to force higher payouts. Huntress states that attackers often harvest credentials and threaten disclosure long before deploying encryption, making rapid detection critical to preventing significant business disruption and public fallout.

What should you do?

Teams should verify that their AI security tools include human validation steps to prevent autonomous errors. Organizations must also ensure their incident response plans are documented and regularly tested to handle multi-front attacks like ransomware effectively.

The background in plain language

Endpoint security protects the devices where data lives, such as laptops and servers. Extended Detection and Response (XDR) combines signals from multiple sources, like email and cloud, into one view. Incident response plans are pre-written guides that tell staff exactly who to call and what steps to take when an attack occurs, ensuring a coordinated reaction rather than chaotic guessing.

Background: AI agents

AI agents are software systems that perceive their environment, make decisions, and execute actions to achieve specific goals. Unlike standard models, they maintain internal state and interact with external tools, creating unique security risks around tool execution, memory retention, and autonomous decision loops that require specialized controls.

Read the full guide: AI Agents Explained: Answers to Security and Architecture Questions

What to do and how to stay safe: Huntress

• Review current AI security configurations to ensure human analysts validate automated decisions before critical actions are taken.
• Audit your incident response documentation to confirm it covers multi-layered threats like ransomware and data extortion.
• Monitor for unusual activity from non-human identities, such as AI agents, which may indicate hijacking attempts.
• Consolidate security tools into platforms that provide unified visibility across endpoints, identities, and cloud workloads.

Step-by-step guide: AI Governance Explained: Building Rules for Autonomous Systems

General security guidance from the Vector Tribune newsroom. It is not confirmed advice from the organisations named in this story.

Frequently asked questions

What is agentic AI in security?

Agentic AI refers to systems that analyze large volumes of data and automate parts of security investigations, requiring strong guardrails to prevent unpredictable behavior.

How is ransomware changing?

Ransomware tactics are evolving from single encryption events to multi-layered extortion, combining data theft, encryption, and public pressure to increase payouts.

Why is incident response planning important?

Without a tested plan, teams waste time determining roles during an attack, allowing incidents to spiral into chaos and increasing the risk of data exposure.