Artificial Intelligence and Cybersecurity

Identity is the essential control plane for agentic AI security, redefining enterprise defenses amid rising credential-based breaches.

Security leaders must become AI cheerleaders, risk experts, data stewards, teachers, and researchers. Here’s how to lead your organization toward more secure and effective AI use.

LLM agents with too much agency may act on unclear or adversarial inputs, risking unauthorized actions and harming security integrity.

As companies move from narrow to generative to agentic and multi-agentic AI, the complexity of the risk landscape ramps up sharply. Existing AI risk programs—including ethical and cyber risks—need to evolve for organizations to move fast without breaking their brand and the people they impact. 

Without new frameworks, agentic AI threatens to overwhelm identity systems with complexity and risk.

As AI becomes the weapon of choice for cybercriminals, defenders must rethink their own approach to artificial intelligence. Automation alone is no longer enough. The future lies in agentic AI—intelligent systems capable of planning, learning, adapting, and acting on behalf of human operators.

AI acts like Pac-Man—devouring sensitive data across clouds, apps, and copilots. Varonis analyzed 1,000 orgs and found 99% have exposed data AI can access, exposing them to data risks.

Blocking access to public AI applications is not enough to stop employees from putting data at risk

AI automation is a top priority for CISOs, though data quality, privacy, and a lack of in-house expertise are common hurdles

CISOs are advised to apply the same evaluation discipline to AI as they do to any other app in the enterprise.

Agentic AI can be a great tool for many of the ‘gray area’ tasks that SOC analysts undertake

There are a wide range of concerns beyond phishing that should have your attention—and that you should be sharing with colleagues so they can help protect your company.

By embedding trust, traceability, and control into AI deployment, CISOs can balance innovation with accountability, keeping hallucinations in check without slowing progress

Understand the major threats that large language models pose and apply effective defensive measures to deploy AI securely.

The critical question is no longer whether AI will be weaponized, but how soon organizations can adapt to counter it.

Agentic AI redefines how to secure digital ecosystems, where data pattern recognition and decision-making need to happen in real time.

As AI systems become increasingly complex, companies must continually refresh security components to ensure infrastructure security and employee training remain top priorities.

A new report from the Paladin Global Institute, The AI Tech Stack: A Primer for Tech and Cyber Policy, breaks down how AI systems are built and where the biggest security risks live.

This is a practical look at how agentic AI is entering the enterprise and what every CISO should know to stay secure.

AI is already transforming the cybersecurity landscape. The question is whether we can secure that transformation in time. The intelligence layer is here. It’s powerful. And it’s vulnerable.
Now is the moment to reimagine what security looks like when intelligence is everywhere.

Supercharging your data analysis strategy with machine learning, data science, and custom-trained LLMs can unlock a higher level of threat detection and a deeper understanding of organizational risks.

Here are five ways the industry can more effectively secure AI.

While AI agents hold immense potential to reshape industries, their ability to operate autonomously makes them highly attractive hacking tools to adversaries and threat actors.

To rebuild trust, CISOs must push their organizations to rethink AI governance. That starts not with policy, but with infrastructure.

AI-enabled cybercrime has increased in volume and effectiveness since ChatGPT's inception. An RSAC panel shared what they've learned in the past two years.