Understand how your application behaves Not just how it’s written
Traditional tools see code. SMART understands how it behaves. By building a semantic model of control flow, data flow, APIs, and workflows, and layering AI on top, SMART uncovers security weaknesses that traditional tools miss.
Traditional Tools
Pattern matching. Fragmented visibility. High noise.
SMART
Semantic understanding. Full context. AI-guided insight.
Traditional tools see code. SMART understands how it behaves.
Most tools analyze code in isolation. They detect patterns, raise findings, and often leave teams to decide what is real.
SMART takes a different approach. It semantically understands code, control flow, data flow, APIs, and workflows, then uses that context to uncover security weaknesses that traditional tools miss.
Higher-confidence findings with more context.
Better visibility into logic and authorization flaws.
Clearer root cause guidance for faster fixes.
From code structure to contextual weakness discovery
SMART goes beyond code pattern matching. It semantically understands code structure, control flow, data flow, APIs, and workflows, then uses that context to uncover security weaknesses with much greater depth and precision.
Understands functions, routes, components, and how the application is actually put together.
Maps execution paths, branching behavior, APIs, and workflow transitions to understand how logic really unfolds.
Tracks how data, objects, and sensitive inputs move through the system so weaknesses can be evaluated in context.
Uses semantic understanding plus AI to surface logic, authorization, and exploitability issues traditional tools often miss.
Traditional tools see fragments
Traditional security tools analyze code like an X-ray. They detect patterns, flag issues, and generate findings, but often lack the depth to understand how the system actually works.
From surface-level detection to behavioral understanding
Traditional Tools
Analyze code patterns or endpoints in isolation, with limited context of execution and intent. The result is more noise and less understanding of deeper logic and authorization weaknesses.
SMART
Semantically understands code and behavior, uses control flow and data flow context, and layers AI on top for higher-signal analysis that reaches beyond pattern matching.
Outcome
Higher-confidence findings, deeper coverage, and clearer root cause context so teams can remediate faster and focus on what actually matters.
What semantic modeling reveals that scanners miss
Broken Object Level Authorization
Detects when one user can access another user’s records through predictable identifiers, workflow gaps, or hidden object relationships.
Broken Object Property Level Authorization
Finds unauthorized exposure or mutation of sensitive object fields that are missed when testing only endpoint-level access.
Business Logic Abuse
Uncovers exploitable sequences across multi-step workflows, including privilege bypass, misuse of state transitions, and invalid order of operations.
Chained Runtime Risk
Reveals SSRF, injection, or policy bypass only when multiple services, parameters, and states interact in combination.
Built for modern software delivery at enterprise scale
CI/CD to Runtime
Use SMART across the SDLC, from pull requests and pre-release validation to runtime-oriented assurance.
Signal Over Noise
Focus teams on validated, high-impact weaknesses instead of overwhelming them with theoretical findings.
Developer-Ready Output
Turn semantic understanding into actionable guidance that supports faster remediation and secure-by-design delivery.
Frequently asked questions about SMART
What is SMART?
SMART stands for Semantic Modeling for Application & API Risk Testing. It builds a behavioral model across code, APIs, identities, objects, and workflows.
How is SMART different from SAST or DAST?
Instead of analyzing code or probing endpoints in isolation, SMART understands how the system behaves with deeper semantic context, allowing it to uncover weaknesses more precisely.
What kinds of issues does SMART detect best?
SMART excels at business logic flaws, authorization gaps such as BOLA and BOPLA, and multi-step exploit paths that traditional tools frequently miss.
Why does semantic modeling matter?
Because real risk is defined by behavior, not patterns. Semantic modeling gives teams the context needed to prioritize and fix what actually matters.
Stop chasing findings. Start eliminating risk.
SMART powers a stronger model of application security where every issue is understood in context, every fix is more actionable, and every release moves you closer to secure-by-design software.
Identify the weaknesses that matter in your environment.
Give developers clearer, context-aware root cause guidance.
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