Gartner’s How to Achieve the Minimum Viable AI Governance
Report
Attack Surface Risk Reduction
The Top 10 Device Exposures of 2026
Map the Mayhem to Remedy Risk
Most enterprise breaches begin with known exposures that are allowed to remain – whether it’s identity drift, Shadow AI, device misconfigurations, legacy protocols, or unmanaged software.
By understanding the prevalence, exploitability, and business impact of those persistent exposure points, security leaders can better focus their efforts to reliably eliminate risk.
Inside the Report
This report examines the ten device exposures most likely to be present across enterprise environments.
Each is ranked according to prevalence, exploitability, business impact, and remediation complexity.
Download the report to learn:
- The 10 exposures creating the greatest attack surface risk in modern enterprises
- Why familiar security gaps continue to drive successful attacks years after they were identified
- Practical strategies for reducing exposure through continuous remediation & validation
Attack Surface Risk Reduction Starts With Exposure Intelligence
Reducing the enterprise attack surface is not simply a matter of finding more vulnerabilities. It requires a holistic understanding of exposure, how attackers exploit them, and why they persist despite years of security investment.
Knowing the ins and outs of the most common pitfalls allows security leaders to make more informed decisions.
Testimonials Section
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FAQs to Mull Over Before You Get Started
What is an attack surface?
An attack surface is the collection of systems, identities, applications, devices, cloud resources, and configurations that attackers can target to gain unauthorized access or move laterally within an environment. As organizations adopt cloud services, AI tools, and remote work technologies, the enterprise attack surface continues to grow.
What is attack surface risk reduction?
Attack surface risk reduction is the process of identifying, understanding, prioritizing, and reducing the security exposures that attackers are most likely to exploit. It extends beyond vulnerability management to include identity exposures, cloud misconfigurations, legacy protocols, unmanaged software, Shadow AI, and other weaknesses that expand an organization’s attack surface.
Why do known security exposures remain unresolved?
Many security exposures persist because remediation introduces operational risk. Configuration changes can disrupt business services, legacy systems may depend on outdated technologies, and enterprise environments change constantly. As a result, organizations often know about exposures long before they are able to eliminate them.
What are device exposures in cybersecurity?
Device exposures are configuration weaknesses, outdated technologies, excessive permissions, or unmanaged assets that increase the likelihood of compromise. Examples include overprivileged identities, publicly exposed cloud resources, legacy protocols, remote access services, default credentials, unmanaged software, and insufficient audit logging.
How does Shadow AI increase attack surface risk?
Shadow AI introduces unmanaged applications, excessive permissions, unapproved integrations, and new data flows that security teams often cannot see or govern. Without continuous visibility into AI tools and their configurations, organizations can unknowingly expand their attack surface and expose sensitive information.
