State of AppSec 2026: Security at Engineering Speed

AI has flipped delivery into continuous code generation and deployment faster than teams can review line by line.

AppSec hasn’t kept up. Most programs still run scan → report → triage → debate , producing more noise, slower decisions, and risk in production. Gartner projects that by 2028, 75% of enterprise engineers will use AI code assistants, raising the bar for trustworthy verification.

This report exposes:

  • Why scan-and-report AST breaks down in continuously changing systems

  • How AI-driven delivery made verification (not detection) the new bottleneck

  • Where modern risk actually lives: authorization, business logic, exploit chains

If your AppSec backlog grows faster than you can validate exploitability, verification is the constraint; not scanning.

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Read the Report

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What You'll Learn

Learn why AppSec teams are hitting a hard scaling limit, how the highest-impact failures evade traditional scanning, and what “security at engineering speed” requires: trusted decisions backed by real validation and reproducible evidence.

The new bottleneck: verification

Why faster code creation pushes pressure into review, testing, governance and AppSec.

Why findings stopped being useful

A finding without context still requires a human to answer: is this exploitable here, right now?

Where risk lives now: authZ + logic

Why many modern failures look like valid requests abusing unintended behavior.

Exploitability proof cuts noise

How evidence-backed validation turns debates into decisions, and backlogs into action.

What “security at engineering speed” requires

Continuous reasoning, memory, and execution across design → code → runtime.

How to evaluate Security AI safely

What to demand: guardrails, deterministic workflows, audit logs, and strict data boundaries.

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Generation got cheap. Understanding got expensive.

The next era of AppSec is not more alerts; it's faster, higher-confidence security outcomes.

Ready to secure at engineering speed?

Download the report to learn why scan-and-report hit a ceiling; and how modern teams move from findings to outcomes.