Trellix Deploys AI Security Operations Inside Customer Environments

Trellix released Trellix Wise for Private Cloud, enabling enterprises to execute artificial intelligence security operations entirely within their own infrastructure. This deployment model addresses primary barriers preventing large organizations from assigning security operations center tasks to AI agents, according to SiliconANGLE.

Why did Trellix shift AI operations to private cloud?

David Soto, Trellix chief information security officer, stated that large organizations are not resistant to the technology but rather to the tradeoffs involved. These tradeoffs include transmitting sensitive security telemetry to a public cloud and absorbing unpredictable token costs. Additionally, enterprises have struggled with a lack of visibility into how AI decisions are made, which complicates governance efforts.

What concerns do security leaders have about AI?

Research firm Vanson Bourne Ltd. polled 600 chief information security officers on insider risk in August and September. The resulting “Mind of the CISO” report indicates that 40% of respondents named a lack of trust in automated decision-making as a barrier. Soto argued that companies not governing AI agents with the same rigor as human employees are operating with an unmonitored insider at scale.

How does the new platform handle auditability?

Every outcome generated by the private cloud edition includes a confidence level. Trellix stated that each result is explained in plain language so it can be audited for governance purposes. This approach aims to provide the transparency that enterprises require while maintaining control over their security data and avoiding public LLM interactions.

What does this mean for operational risk?

The Vanson Bourne survey found that AI-driven or autonomous systems were behind 28% of insider incidents over the past year. The average organization took seven hours to spot an insider incident and eight more hours to respond. Soto described this window as an invitation to attackers who use AI to speed up every stage of an attack, highlighting the need for faster, governed defense mechanisms.

Background: AI agents

AI agents are software systems that perceive their environment, make decisions, and execute actions to achieve specific goals. They move beyond generating text to performing tasks like coding, scheduling, or data analysis. You must treat them as active participants in your network, not passive tools.

Read the full guide: AI Agents Examples: How Autonomous Software Changes Security

What to do and how to stay safe: Trellix

• Review current AI security tool deployments to ensure sensitive telemetry remains within your defined security boundary.
• Establish clear governance policies for AI agents that match the rigor applied to human employee monitoring.
• Audit AI decision outputs for transparency and confidence levels to satisfy compliance and governance requirements.
• Monitor insider risk metrics specifically related to autonomous systems and automated decision-making processes.

Step-by-step guide: AI Usage Policies at Work: How to Prevent Data Leakage

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

Frequently asked questions

Does Trellix Wise for Private Cloud send data to the public cloud?

No, the solution operates fully inside the customer’s environment, ensuring data remains within the security boundary and is never sent to a public LLM.

What percentage of insider incidents involved AI systems?

According to the Vanson Bourne survey, AI-driven or autonomous systems were behind 28% of insider incidents over the past year.

How is cost structured for this new release?

Customers using Trellix Wise for Private Cloud are not billed by the token, addressing concerns about unpredictable costs associated with public cloud AI usage.