The 2026 Web Application Security Report, based on a global survey of more than 800 security professionals, quantifies what many teams are already seeing across web application security and API security environments. Only 29% of respondents report confidence in their overall application security posture, dropping to 15% for AI-integrated applications and 12% when defending against AI-generated attacks.

This highlights a gap between how modern web applications and APIs function and how they are being secured. AI is integrated into application logic, workflows, and APIs, but the controls governing these systems still rest on outdated assumptions.

Application Behavior Has Shifted Beyond What Static Controls Can Track

AI-integrated applications generate API calls dynamically, adapt their behavior at runtime, and depend on chains of internal and external services that change depending on the context. Fixed inventories and review-cycle policy updates do not reflect that behavior in modern application security environments.

Most web application security tools were designed for predictable traffic and human-scale interactions. However, they are now expected to analyze model-generated payloads and autonomous service activity across APIs and distributed applications. The result is a gap between how applications behave and what security systems actually monitor. This gap first appears as incomplete visibility across applications and APIs.

Visibility Gaps Are Largest Where Risk Is Highest

According to the report, only 13% of organizations are highly confident that they know all applications and APIs in use across their environment. Meanwhile, APIs are viewed as the highest-risk application category by 67% of respondents and represent one of the largest visibility gaps at 53%. 

AI accelerates changes across application environments. Endpoints are generated dynamically, dependencies are added outside standard workflows, and shadow AI tools operate without normal controls. Inventory-based models for web application and API security assume a stable set of assets, which no longer matches how applications are built or deployed.

Attack Methods Are Familiar, but Execution Has Changed

While credential stuffing, API abuse, and application-layer exploits remain the primary entry points for web application attacks, the methods of attack have evolved. Modern AI-assisted attacks operate continuously, dynamically adapt to defenses in real-time, and seamlessly blend into legitimate traffic. The report shows that 74% of organizations have seen an increase in AI-generated or AI-assisted attacks, and credential-based attacks account for 58% of incidents. 

These attacks succeed because they operate inside normal access paths, enumerating endpoints, testing access, and extracting data in ways that resemble legitimate activity. Authentication doesn't prevent what happens after access is granted. Most critical activity occurs at the API and session levels. To be effective, modern application security controls must function there as well.

Detection and Response Are Not Keeping Pace

Only 20% of organizations detect incidents within hours. More than half take a week or longer, and nearly one-third take over a month. And remediation timelines follow the same pattern. That delay is where most of the damage happens.

Detection breaks down because signals are distributed across different systems. Authentication logs show valid logins, API gateways display expected requests, and application logs record routine transactions, because each system captures only part of the activity, not the entire sequence. Without shared context, threat activity isn’t recognized as a connected pattern in real time. Instead, correlation usually happens later, often manually, during incident response.

Remediation follows the same pattern. Response depends on multiple systems and teams working from partial views, which extends the exposure window further. The result is a mismatch between how attacks operate and how detection and response are carried out.

Tool Fragmentation Is Reinforcing the Problem

Only 5% of organizations report satisfaction with their current application security tools, while 62% are either consolidating or planning to consolidate solutions. This highlights a set of critical operational issues, including inconsistent policy enforcement across tools, duplicated controls, and fragmented telemetry across web application and API security systems. 

The report highlights ongoing issues such as limited visibility, high false positives, and poor integration between tools. These problems worsen when inspection and enforcement are handled by separate systems instead of a shared view.

What Is Needed from Application Security

The report emphasizes that these challenges must be tackled together. Environments are always changing, which requires ongoing discovery across applications and APIs, while attacks increasingly operate within legitimate traffic, making inspection beyond authentication essential. Detection also needs to happen in real time as activity occurs. That requires shared context across enforcement points. And consistent policy enforcement demands reducing fragmentation across application security tools.

Addressing any one of these in isolation does not change the overall outcome.

Where FortiAppSec Cloud Fits

The data highlights consistent gaps in visibility, inspection, detection, and enforcement at both the application and API levels. FortiAppSec Cloud addresses these challenges by integrating web application and API security—combining WAF, API protection, bot mitigation, and application security services into a single platform. This allows it to enforce consistent policies and share telemetry across the entire application surface, including both user-driven traffic and service-generated activity.

This integrated approach reduces the gaps created by separate control points and fragmented application security tools. It also allows inspection and enforcement to operate on the same view of application behavior, which is necessary in environments where APIs are both high-risk and poorly understood.

The Data is Clear

Visibility across applications and APIs remains limited, even as attacks operate at a speed and scale that static controls cannot match. Detection is also slowed by fragmented signals across systems, which delays correlation and response. That is why organizations are seeking to consolidate tools and close the gaps created by managing these functions separately.

This isn't a matter of missing features. The application architecture simply hasn't kept up with the way modern web applications, APIs, and AI-driven workloads are developed or how attacks are now carried out. Bridging that gap involves rethinking how visibility, inspection, and enforcement work together instead of treating them as separate layers.

Read the Full Report

If you’re evaluating how well your web applications and APIs are secured against AI-driven threats, start with the data. Download the 2026 Web Application Security Report to assess how your current application security architecture handles visibility, runtime inspection, and detection across both AI and non-AI traffic.