The Expanding Importance of Attack Surface Management

As cyber threats become more sophisticated, the concept of an ‘attack surface’ has shifted from a static checklist to a living, breathing ecosystem that requires constant attention. Protecting sensitive data now demands comprehensive visibility into every asset because you can’t protect what you can’t see.

Yet, many organizations still lack full awareness of their attack surface and nearly a third of large businesses see less than 75% of their assets. Meanwhile, small and medium enterprises (SMEs) are becoming more frequent targets for cyber criminals, making Attack Surface Management (ASM) a critical consideration for all.

Looking ahead, ASM will continue to evolve — potentially under new names like Continuous Threat Exposure Management. Key features such as exploit intelligence, dynamic risk scoring, and real-time telemetry sharing are already streamlining and prioritizing remediation activities. The future will likely see even greater integration between ASM and SIEM/SOAR services, which could help provide organizations with a unified view of risk appetite and response.

The ongoing shortage of cyber skills is driving more organizations to leverage managed service providers for data analysis and prioritization. This situation enables internal security teams to focus on high-impact mitigation, thereby reducing risk and improving overall security posture. We expect to see a rise in managed services that handle patch management by automatically addressing non-critical vulnerabilities and freeing up teams to tackle more complex, high-risk exposures. As the market matures, vendor consolidation should make robust ASM solutions more affordable and accessible.

The ever-expanding attack surface

Modern environments are dynamic, with cloud adoption, SaaS reliance, IoT, and OT deployments all contributing to a constantly expanding attack surface. Business activities like mergers and acquisitions add further complexity and unknowns. Automated exploitation techniques, sophisticated malware, and AI-enabled adversarial tools are broadening potential entry points for attackers. It’s not uncommon for organisations to discover assets they believed were decommissioned, only to find these forgotten systems increase their exposure.

AI’s role in monitoring and managing the attack surface

Effective ASM relies on automated tools to discover, identify, and assess risk across assets. Integrating threat intelligence and context-based prioritisation enables tailored remediation planning. AI plays a dual role; while it empowers adversaries with speed and complexity, it also enhances ASM tooling by enabling rapid cross-correlation, predictive behaviour monitoring, and automation of both response workflows and reporting. The emergence of agentic AI, machine learning models capable of making independent decisions, promises even greater automation, although human oversight will remain essential for real-time remediation.

Addressing shadow IT, shadow AI, and shadow MCP

Shadow IT continues to be a significant breach vector, implicated in a third of data breaches. The rise of generative AI embedded in SaaS applications deepens the challenge, as unsanctioned AI use (Shadow AI) increases risks around compliance, data leakage, and decision-making.

Model Context Protocol (MCP) introduces further complexity, potentially exposing sensitive data and enabling unauthorized automation. Addressing these risks requires rigorous asset inventories, continuous monitoring, and advanced governance. Expect regulatory scrutiny to increase, along with the adoption of AI-enabled discovery and control tools.

Zero Trust adoption

Zero trust principles, such as strict access management and micro-segmentation, are fundamental to reducing risk by limiting lateral movement and enforcing least privilege. While zero trust alone cannot solve all ASM challenges, it is a vital component of a layered defense. Combining ASM with zero trust and Identity Access Management (IAM) is likely to become standard practice as demand grows for data segregation by organizational security teams.