Top Code Security Scan Tools of 2025

Code security. Code scanning. Static analysis. DevSecOps. No matter what you call it, the goal is the same: building a more secure application. The main point of code security is to detect and resolve vulnerabilities at the source before they reach production. As a codebase expands (and boy, do they expand when you toss AI coding agents into the mix) and changes, manually combing through thousands of lines of code and tracking how information flows across hundreds of functions is completely unrealistic at scale. In the age of AI and vibe coding, this problem becomes exponentially more pronounced.

This is when organizations realize their potential security gaps and begin to rely on code security scan tools—specifically static application security testing (SAST) and software composition analysis (SCA) tools. These represent one critical piece of the broader application security testing toolbox, which includes SAST for source code analysis, DAST for runtime testing, and SCA for identifying vulnerabilities in third-party libraries and dependencies. 

Code security scanning emerged in the early 2000s as basic pattern-matching tools that flagged obvious security issues, such as hardcoded passwords. Early solutions required extensive manual configuration and produced overwhelming false positives. Today’s tools have evolved dramatically, leveraging AI, semantic analysis, and continuous integration to provide real-time, actionable security feedback directly within developer workflows. 

These tools automatically scan your repositories, highlight risky code, secrets, third-party dependencies, infrastructure as code, and other code components to flag vulnerabilities and risks. With some tools, you can even plug them into your IDE so security checks happen as you write your code.

In 2025, these tools will be put to the test in terms of code generation speed and the velocity of multi-file changes. In minutes, applications can be built and refactored to the nth degree. This means that tools need to be held to a certain standard to keep up; mainly, these tools must be: 

1. Totally automated
2. Customizable
3. Embedded in dev tools (IDEs, PRs, CI/CD)
4. Give developer and agent-friendly remediation guidance/feedback loops

In this guide, we’ll break down the top five code security scan tools of 2025, covering both paid and open-source options, their key features, and best practices. Let’s start by examining these tools in more detail and understanding how they work.

What are code security scan tools?

Code security scan tools are automated solutions that analyze your application’s security posture across multiple dimensions. They identify vulnerabilities such as SQL injection points, buffer overflows, cross-site scripting, exposed secrets, hardcoded API keys, sensitive data leaks, insecure configurations, and vulnerable third-party dependencies. 

These tools encompass several testing approaches: 

• Static Application Security Testing (SAST): Analyzes source code without execution to find vulnerabilities early in development 
• Software Composition Analysis (SCA): Scans third-party libraries and dependencies for known vulnerabilities and license issues 
• Secret Detection: Identifies exposed credentials, API keys, and sensitive data in code repositories 
• Infrastructure as Code (IaC) Scanning: Reviews cloud configuration files for security misconfigurations 

The best part is how seamlessly these tools fit into modern DevSecOps workflows. Many integrate directly into CI/CD pipelines, running automated checks for every build and delivering actionable insights in real time. This shift-left approach means you resolve security issues during development rather than discovering them after release, reducing remediation costs compared to fixing vulnerabilities in production.

What to look for in code security scan tools

Here are the key factors to consider when selecting a code security scan tool:

Strong preset rules

Customization matters, but a strong tool should also come with out-of-the-box preset rules. Look for built-in checks that cover compliance frameworks like SOC 2, PCI DSS, and HIPAA, plus security standards like the OWASP Top 10, and common flaws like hardcoded passwords or exposed API keys. These give you a solid security baseline before you layer on custom rules. Note that while SAST tools support compliance by catching issues early, organizations must combine them with process controls, policies, and runtime testing to meet full regulatory requirements.

Accuracy and risk prioritization

Every vendor claims “low false positives,” but real accuracy comes from intelligent prioritization. Look for tools that provide exploitation paths, consider data sensitivity, score based on exploitability (not just severity), and offer confidence scores for each finding. The best security testing tools prioritize high-confidence and high-impact findings. Modern platforms also use AI and machine learning to improve accuracy and flag only the issues that truly matter. Before committing, run a proof-of-concept on your actual codebase—false positive rates vary dramatically by tech stack.

Automation

A good code security scan tool automates checks at critical points such as builds, pushes, and merges, and runs continuously in CI/CD pipelines. When issues appear, it blocks deployments and offers actionable feedback. Some tools provide developers with code-fix suggestions or quick-fix pull requests, although human review remains essential for accuracy. Beyond CI/CD integration, consider how tools fit your security ecosystem. Modern Application Security Posture Management (ASPM) platforms aggregate findings from multiple scanners, while combining SAST with DAST creates comprehensive coverage. When static analysis identifies a potential vulnerability and dynamic testing confirms it’s exploitable, you know it’s critical.

Data flow analysis

The best tools scan the entire application flow. They map how data moves through your code, from inputs (sources) to potentially dangerous functions (sinks). This reveals vulnerabilities such as SQL injection or information leaks that simple pattern matching cannot detect.

Wide language support

Your team likely works with multiple languages and frameworks across different projects. So, your code security scan tool must support a wide range of programming languages. Different tools (which are covered in detail later in this post) excel with specific tech stacks:

Language/Framework	Best Tools	Key Strengths
JavaScript/TypeScript	Semgrep, Snyk Code	Modern framework support (React, Vue, Node.js)
Java/Spring	Checkmarx, SonarQube	Enterprise Java, Spring-specific vulnerabilities
Python	Semgrep	Django/Flask, Python-specific patterns
C/C++	Checkmarx, Veracode	Memory safety, deep taint analysis
Go	Semgrep	Go-specific antipatterns
Infrastructure as Code	Checkmarx, Snyk	Terraform, CloudFormation, Kubernetes

Reporting & dashboards

Good reporting turns scanning into strategy. Automated dashboards give an overview of code health, highlight vulnerabilities that need urgent attention, and track progress across releases. The right tool identifies which repositories and modules pose the greatest risk and visualizes trends over time.

Top 5 code security scan tools

We selected these tools based on the core factors you should expect in a modern code scanner.

1. Semgrep

Semgrep is a lightweight static code analysis tool built for speed and customization. It utilizes semantic pattern matching to identify security threats, enabling fast analysis while preserving an understanding of code structure. The open-source version gives teams control over their security standards through custom rules. While Semgrep excels at pattern matching, its data flow and taint analysis capabilities are more limited than those of enterprise tools.

Best for: Teams wanting fast, customizable scanning with minimal false positives
Pricing: Free for open source; Team tier starts at $40/developer/month

Key features:

• Semantic pattern matching using abstract syntax trees (ASTs)
• Supports more than two dozen languages
• Custom rule creation for domain-specific vulnerabilities
• Open-source version available (Semgrep OSS)

2. GitHub Advanced Security

GitHub Advanced Security brings enterprise-grade protection directly into the GitHub platform. It includes Code Scanning powered by CodeQL, a semantic analysis engine that identifies vulnerabilities. Since it’s built into GitHub, security checks start from the first commit. GitHub Advanced Security is available with GitHub Enterprise or as an add-on for GitHub.com organizations.

Best for: Teams already using GitHub who want native security integration
Pricing: Included with GitHub Enterprise; $49/user/month for GitHub.com

Key features:

• Native GitHub integration with PR annotations and security alerts
• CodeQL for semantic code analysis across 10+ languages
• Secret scanning to prevent credential leaks
• Dependency scanning for vulnerable packages

3. Checkmarx

Checkmarx specializes in deep static code analysis. It maps data flow across multiple functions and tracks vulnerabilities through application logic. The standout feature is CxQL (Checkmarx Query Language), which lets teams write custom rules for their specific codebase. Newer versions include an AI-powered query builder that converts natural language into security rules. While Checkmarx has expanded to include SCA (Software Composition Analysis) and IaC (Infrastructure as Code) scanning, SAST remains its core strength.

Best for: Organizations needing deep code analysis with customizable security rules
Pricing: Enterprise-level pricing, typically starting in the tens of thousands annually

Key features:

• All-in-one security testing suite (SAST, IAST, DAST, SCA, and more)
• AI-powered query builder (in newer versions) for creating custom security rules
• Supports a broad set of programming languages and frameworks

4. Endor Labs 

Endor Labs provides supply chain security that combines SCA with function-level reachability analysis and dependency health metrics. It gives visibility into open-source and AI‐model risks (including phantom dependencies and license issues), and helps prioritize vulnerabilities based on whether their vulnerable code paths are actually used in your specific codebase.

Best for: Organizations that want to reduce noise, enforce custom dependency governance, and focus on actionable risk. 

Pricing: Enterprise pricing available on request 

Key features: 

• Reachability analysis to reduce false positives and prioritize exploitable vulnerabilities 
• Custom policies via policy-as-code (using Rego / OPA) for dependency governance, license risk, etc. 
• Dependency health and open source risk assessment (maintainership, community/risk metadata) 
• Integrations with source repositories, CI/CD, IDE tools etc., to surface real risks early in workflows. 

5. Snyk Code

Snyk Code uses AI-powered scanning to provide real-time feedback as you code. It offers a free plan with 100 tests per month and integrates directly into IDEs and CI/CD tools. The risk scoring helps teams prioritize fixes based on actual impact. Note that Docker container scanning is handled by Snyk Container, a separate product.

Best for: Developer teams wanting AI-driven scanning with minimal setup
Pricing: Free tier (100 tests/month); Team tier starts at $52/developer/month

Key features:

• Easy setup and clean interface
• DeepCode AI engine for vulnerability detection
• Config file scanning for infrastructure misconfigurations
• Real-time scanning with fast feedback

Specialized Tools Worth Considering

Aside from the tools above, there are a few other popular options that can work well. These type of tools include:

Secret Detection

• TruffleHog: Advanced secret scanning with high accuracy and git history analysis 
• GitHub Secret Scanning: Native GitHub integration with partner token verification and automatic remediation

Application Security Posture Management (ASPM)

• Cycode: Complete ASPM platform with built-in SAST, SCA, and secrets detection 
• Legit Security: Supply chain security with policy enforcement 
• Jit: Orchestrated security testing with multiple scanner integrations 
• Apiiro: Risk-based application security with business context 
• ArmorCode: Security findings aggregation and vulnerability management

Best Practices for Code Security

Implementing code security scan tools effectively requires more than just installation. These practices will help you maximize the value of your security scanning investment and build a culture of secure development:

• Automate scans early and often: Configure code security scan tools to run with every code commit or pull request, providing immediate feedback to developers before issues compound.
• Integrate directly into developer workflows: Deploy code security scan tools directly into IDEs so developers receive security guidance as they code, not days later in a report.
• Prioritize based on real risk: Focus on vulnerabilities based on their exploitability and potential business impact, not just CVSS scores.
• Layer your security testing: Ensure complete coverage by combining code security scan tools with DAST and SCA tools, as each catches different vulnerability types.
• Leverage AI capabilities: Utilize AI-powered code security scan tools to minimize false positives and receive contextual remediation advice that accelerates fixes.

Common challenges with code security scan tools

While code security scan tools provide essential protection, teams should understand their limitations:

False positive fatigue: Even modern tools generate noise. Without proper tuning and prioritization, developers waste cycles investigating non-issues, which can lead them to overlook real vulnerabilities.

Context blindness: Static scanners can’t understand business logic or runtime behavior. They might flag secure code as vulnerable or miss complex authorization flaws that only manifest during execution.

Performance overhead: Scanning large codebases can slow CI/CD pipelines. Teams must balance security coverage with development velocity, often requiring selective scanning strategies.

Tool sprawl: Using multiple scanners (SAST, DAST, SCA) creates integration challenges. Without proper orchestration, teams struggle to correlate findings and eliminate duplicates across tools.

Platform selection complexity: For those worried about tool sprawl, choosing between all-in-one security platforms and best-of-breed specialized tools creates decision fatigue, with teams uncertain whether unified solutions will match the detection capabilities of purpose-built tools.

Where does StackHawk fit in?

Not all vulnerabilities are caught at the code level. Security flaws often slip into production, which is why you need a dynamic application security testing (DAST) solution like StackHawk.

While code security scan tools analyze source code for vulnerabilities, StackHawk tests a running version of your application. It simulates real-world attacks and shows exactly how your application responds. This approach identifies threats, such as SQL injection, cross-site scripting, and API security vulnerabilities, before they can reach production environments.

Since most applications rely on APIs, StackHawk’s focus on detecting API vulnerabilities makes it a critical choice for modern development. It addresses the gaps that typical code security scan tools miss, including weak authorization, business logic flaws, and data exposure risks that only occur at runtime.

SAST and DAST are not interchangeable; they are complementary. Together, they provide complete coverage, with code security scan tools securing code early in development and DAST validating real-world security scenarios. Using both ensures you close gaps that either approach would miss on its own.

Conclusion

Code security scanning is now a crucial component for development teams. By catching vulnerabilities at the source, these tools prevent costly production incidents. While no single tool can capture everything, a well-integrated scanner within your workflow provides the foundation for secure software delivery.

Code security scan tools work best when paired with runtime testing. The best DAST tools complement SAST by simulating real attacks and validating how applications behave in production conditions. As AI continues to improve accuracy and reduce false positives, the testing market is expected to grow from $857 million to $3.8 billion by 2032.

The future of software security lies in combining automation, AI, and integrated testing approaches. Ready to see how StackHawk’s dynamic testing complements your code security scan tools? Start a free trial to catch the runtime vulnerabilities that static analysis misses, or schedule a demo to discuss your application security needs.