AI SAST
Security Testing Agent's AI SAST scans agent-generated code the moment it's written, catching vulnerabilities at the speed of the autonomous SDLC.
Not built for autonomous coding
Scanning at commit or PR breaks down when agents ship code around the clock
Secure AI coding
Scan agent-generated code the moment it's written, wherever your agents work
Even more noise
You already have too many FPs. Agents shipping code nonstop means even more.
Stop chasing false positives
Reduce false positives by 10x with our Code Property Graph and AI reasoning
AI just makes the toil worse
Triaging findings was always manual. More code from AI just means more work.
Better security with agents
AI built into the platform sharpens results; agents and skills handle the toil
Automatically scan AI-generated code in Cursor, Windsurf, and Claude Code for vulnerabilities and other security risks.
Code property graph. Uses a CPG to evaluate data flow and control flow, not just syntax, delivering 10x fewer false positives.
AI confidence scoring. Scores every finding by true positive likelihood, so teams can focus on real risks instead of chasing noise.
Deep vulnerability detection. Identifies business logic flaws like IDOR and multi-file attack paths that pattern-matching tools miss entirely.
Security Worker Agents. Fully autonomous agents handle orchestration, triage, prioritization, and remediation end-to-end.
AI skills for your team. Claude and MCP skills tackle time-consuming security tasks to increase efficiency and scale out your team.
Agent marketplace. Browse and deploy agents and skills purpose-built for security teams - all in one place.
Find and fix vulnerabilities inside Cursor, Windsurf, and Claude Code without leaving the AI coding tool.
Spend less time chasing false positives. Harness delivers 10x fewer than legacy scanners.
Get AI-generated fix suggestions alongside every finding and fix security issues 95% faster.
Static Application Security Testing (SAST) is a security testing methodology that analyzes application source code to identify vulnerabilities without executing the program. SAST examines code from the inside out, giving developers visibility into potential security flaws during the earliest stages of the software development lifecycle (SDLC).
SAST tools scan code as it's written, identifying common vulnerabilities such as SQL injection, cross-site scripting (XSS), buffer overflows, and insecure cryptographic implementations. By catching these issues before compilation or deployment, SAST enables developers to fix security problems when they're least expensive to remediate, saving both time and money while reducing the risk of breaches in production. This proactive approach makes SAST an essential component of modern DevSecOps practices.
AI SAST (AI-powered Static Application Security Testing) analyzes source code for vulnerabilities before it ever runs, and applies AI to do it faster and more accurately than traditional approaches. Unlike legacy SAST tools that flood developers with false positives, AI SAST uses AI agents to automatically validate findings and eliminate noise, delivering up to 10x fewer false positives so developers can focus on what actually matters. It also applies AI-powered remediation to suggest precise, context-aware fixes, accelerating resolution without requiring deep security expertise. And with coverage extending to AI-generated code, it catches risks introduced by tools like GitHub Copilot or ChatGPT that traditional scanners often miss.
SAST plays a crucial role in meeting regulatory and industry compliance requirements by providing documented evidence of secure software development practices.
Key compliance standards:
Compliance benefits:
By integrating SAST into your SDLC, you create verifiable evidence that your organization follows secure coding practices, essential for passing audits and maintaining compliance certifications.
Advantages:
Limitations:
For optimal security coverage, combine SAST with DAST, Software Composition Analysis (SCA), and regular penetration testing.
SAST tools can identify a wide range of security vulnerabilities and coding flaws aligned with industry standards like the OWASP Top 10 and CWE/SANS Top 25. Here are the primary vulnerability types:
SAST tools detect these issues by analyzing code structure, data flow, and control flow patterns. The most advanced tools can also identify business logic flaws, code quality issues that impact security, and violations of secure coding standards. However, SAST cannot detect runtime-specific vulnerabilities like server misconfigurations or infrastructure issues, which is why it's most effective when combined with DAST and other security testing methods.
Static code analysis works by examining source code without executing the application. The process begins when a SAST tool parses your code and breaks it down into tokens: individual elements like keywords, operators, and identifiers. These tokens are then used to construct an Abstract Syntax Tree (AST), which represents the hierarchical structure of your code.
Once the AST is built, SAST tools may perform several types of analysis: control flow analysis maps all possible execution paths through your code, data flow analysis tracks how data moves from inputs to outputs, and pattern matching compares code structures against known vulnerability signatures. The tool checks for issues like unsanitized user input flowing into database queries, hardcoded credentials, insecure API usage, and violations of secure coding standards.
SAST tools vary significantly in programming language support, with most covering popular languages while some specialize in specific ecosystems.
Commonly supported languages (most tools):
Frequently supported (major tools):
Less common (specialized tools):
Multi-language environment challenges: Teams working with polyglot codebases face a critical decision: use a single SAST tool with broad language coverage (potentially sacrificing depth) or deploy multiple specialized tools (adding complexity but improving accuracy).
Integrating SAST into CI/CD pipelines enables automated security scanning with every code change, catching vulnerabilities before they reach production.
Choose your integration point:
Implementation best practices:
Successful SAST integration requires balancing security thoroughness with developer velocity. Start with critical projects, tune false positives, and gradually expand coverage across your organization.
SAST and DAST are complementary testing methodologies that examine applications from different perspectives. SAST analyzes code at rest during development, while DAST tests running applications in production-like environments.
| Aspect | SAST | DAST |
|---|---|---|
| Testing approach | White-box (inside-out) | Black-box (outside-in) |
| When it runs | During coding / build | Against built application |
| Code access | Requires source code | No source code needed |
| Detects | Code errors, logic flaws | Runtime vulnerabilities, configuration issues |
| Speed | Fast, can scan continuously | Slower, tests at runtime |
| False positives | Higher rate | Lower rate |
For comprehensive security coverage, leading organizations use both SAST and DAST together as part of a layered application security strategy.
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