Semantic Code Analysis that understands application behavior.
Understand how code, data, APIs, authorization, and business logic work together. SMART builds a semantic model of the application, then applies AI reasoning to uncover deeper security weaknesses and help developers fix the right path.
Understand what code means—not just what it matches.
Semantic Code Analysis examines how code behaves in application context rather than relying only on vulnerability signatures or isolated syntax patterns.
SMART models control flow, data flow, APIs, objects, authorization, trust boundaries, and business workflows so security analysis can reason about how components interact and where real application risk may emerge.
Traditional tools see code. SMART understands how it behaves.
Rules and pattern matching remain useful, but complex application risk often depends on how code, data, authorization, APIs, and workflows interact.
SMART builds that context first, then uses it to surface higher-signal weaknesses and give engineering better root-cause guidance.
Understand application behavior before judging risk.
SMART combines deterministic analysis with AI to understand how code behaves in context—so security decisions are based on execution paths, data movement, authorization, APIs, and business logic rather than isolated code patterns.
Understand the code path.
Understand how components interact.
Identify higher-signal security issues.
Security meaning depends on relationships—not isolated lines of code.
SMART reasons across the application context that determines whether a security decision is correct.
Identity + role
Object + workflow
Code enforcement
Use context to decide what deserves action.
SMART carries a potential weakness through semantic analysis, contextual prioritization, remediation, and where appropriate runtime validation.
Identify the weakness.
Rules, semantic analysis, flows, and AI reasoning surface a security signal.
Add application context.
Reachability, authorization, objects, trust boundaries, workflows, and likely impact.
Fix the right path.
Give developers root cause, affected path, and context-aware remediation guidance.
Prove the control holds.
Connect to Semantic Runtime Validation where runtime proof materially improves confidence.
Weaknesses that require understanding application logic and context.
BOLA + object access
Identify code and workflow paths where ownership, role, tenant, or object-level authorization may fail.
Logic abuse
Reason about invalid sequences, state transitions, privilege conditions, and application-specific rules.
Injection + sensitive data
Trace untrusted input and sensitive data through reachable execution paths and security-sensitive functions.
Boundary violations
Understand where data, identity, or control crosses a trust boundary without the intended validation.
Route + service relationships
Connect code paths to APIs, services, objects, and downstream behaviors instead of treating endpoints separately.
Multi-step weakness paths
Identify security impact that emerges only when several individually valid code paths interact.
Give developers context they can use—not another generic finding.
SMART translates semantic understanding into the information engineering needs to act: where the weakness originates, how the risky path works, why it matters, and how to correct the relevant control.
Explore Continuous Vulnerability Management →Connect code risk to the rest of your application.
SMART works alongside dependency analysis, API and runtime validation, and autonomous penetration testing so teams can connect code-level weaknesses to broader application risk.
Semantic Code Analysis
Control flow, data flow, authorization, business logic, AI reasoning, and developer remediation.
Explore AI SAST →SCA + SBOM
Dependencies, reachability, CVE/OSV, EPSS, KEV, containers, IaC, and licenses.
Explore Software Composition Analysis →Semantic Runtime Validation
Authorization, objects, workflows, business logic, runtime behavior, and exploitability proof.
Explore Semantic Runtime Validation →Autonomous Pen Testing
Adversarial exploration, attack chaining, exploit proof, and remediation retesting.
Explore Autonomous Pen Testing →Semantic Code Analysis questions.
What is Semantic Code Analysis?
Semantic Code Analysis examines how code behaves in application context by modeling control flow, data flow, APIs, objects, authorization, trust boundaries, and business workflows. Aptori SMART applies this approach and layers AI reasoning on the resulting application context.
What is the difference between Semantic Code Analysis and SAST?
Traditional SAST commonly uses rules, signatures, pattern matching, and program-analysis techniques to identify potential weaknesses. Semantic Code Analysis goes further by modeling relationships across control flow, data flow, APIs, identities, authorization, objects, and workflows to understand the security meaning of application behavior. Aptori SMART combines these semantic models with deterministic analysis and AI reasoning.
Does SMART rely only on AI?
No. SMART uses deterministic program and semantic analysis to build application context, then layers AI reasoning on top where it improves weakness discovery, prioritization, or remediation.
Can SMART find business logic and authorization vulnerabilities?
Yes. SMART can reason about application-specific authorization relationships, object access, workflow state, business rules, and multi-step code behavior that simple pattern matching may miss.
How does SMART reduce false positives?
SMART evaluates findings using semantic context, control and data flow, reachability, authorization relationships, and where useful runtime exploitability evidence, providing stronger signals for prioritization.
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