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# When to use SAST versus an LLM security scanner
- URL: https://www.stirup.si/when-to-use-sast-versus-an-llm-security-scanner-ccc39302/
- Published: 2026-10-11T14:51:50.000Z
- Updated: 2026-10-11T14:51:50.000Z
- Description: SAST and LLM-based security scanners each have distinct strengths and use cases. SAST provides deterministic, cost-effective scanning for pattern-based vulnerabilities, while LLMs excel at reasoning-based checks for business logic flaws. Understanding when to use each ensures comprehensive security
- Author: Satish Das
- Tags: Development, Stirup Research

## Choosing Between SAST and LLM Security Scanners

Static Application Security Testing (SAST) and Large Language Model (LLM)-based security scanners serve different roles in a modern software development pipeline. While both tools aim to identify vulnerabilities, their approaches, costs, and effectiveness vary significantly. Understanding these differences is essential for making informed decisions about where and how to deploy each tool.

## Cost and Predictability

SAST is a deterministic scanner that operates on fixed rules and patterns. It is highly predictable in cost, with scanning costs typically measured in fractions of a cent per scan. This makes it ideal for continuous scanning across every commit in a codebase, ensuring consistent coverage without budgetary surprises.

In contrast, LLM-based scanners rely on inference calls, which are paid per scan. The cost of these scanners scales with the volume of code being scanned, making it more difficult to forecast expenses, especially at enterprise scale. While LLMs may be cost-effective for reviewing individual merge requests, they are not well-suited for scanning every commit due to the compounding cost and unpredictability.

## Consistency and Audit Evidence

SAST provides consistent results across multiple runs, making it a reliable tool for audit trails. Because it follows fixed rules, rerunning a scan will yield the same findings every time, which is crucial for compliance and independent verification by auditors.

LLM-based scanners, on the other hand, may produce varying results when the same code is scanned multiple times. This variability is not due to errors in the model but rather the nature of probabilistic reasoning. As a result, LLMs are less suitable for use as standalone audit evidence, though they can complement SAST in a layered security strategy.

## Vulnerability Detection

SAST is particularly effective at identifying pattern-based vulnerabilities such as injection flaws, hardcoded secrets, and insecure cryptographic practices. These are structural issues that can be detected through rule-based scanning.

LLM-based scanners, by contrast, are better suited for detecting intent-based and novel vulnerabilities. They can analyze the context of the code, including epics, issues, and documentation, to identify business logic flaws such as missing authorization checks or broken ownership logic. These are types of vulnerabilities that traditional SAST tools may not detect without additional configuration.

## Validation of Findings

While SAST can flag potential vulnerabilities, it cannot confirm whether a finding is exploitable. LLM-based scanners, however, can generate test cases to attempt exploitation of identified flaws, reducing the number of false positives and increasing the confidence in the findings.

This capability makes LLMs particularly valuable for triaging findings and ensuring that only valid vulnerabilities reach the security team for further investigation.

## Complementary Use Cases

Modern security programs are moving toward a hybrid approach that combines both SAST and LLM-based scanners. SAST remains the baseline for continuous scanning, ensuring deterministic coverage at a predictable cost. LLMs are used for reasoning-heavy checks, typically at the merge request level, where they can detect vulnerabilities that SAST cannot.

This layered approach ensures comprehensive coverage, leveraging the strengths of each tool while mitigating their respective limitations. It allows teams to maintain a secure codebase without compromising on cost, consistency, or auditability.

**Source:** [GitLab](https://about.gitlab.com/blog/sast-vs-llm-security-scanner/?ref=stirup.si). Analysis based on publicly available information; no hands-on testing is claimed.