8 Types of Application Security Testing & 6 Critical Best Practices

What Is Application Security Testing? 

Application security testing (AST) is the process of identifying, analyzing, and remediating security vulnerabilities in software throughout the development lifecycle. By utilizing a mix of automated tools and manual methods, organizations can detect risks early, saving costs and preventing breaches.

Modern software requires continuous security testing because applications change constantly. Developers release new code frequently, dependencies are updated, cloud infrastructure evolves, and APIs expose new attack surfaces. A one-time security assessment is no longer enough. Effective AST combines multiple testing approaches throughout the software development lifecycle and continues to monitor applications in production to detect newly introduced risks and verify that security controls remain effective.

Types of application security testing by methodology:

• SAST (Static Application Security Testing): Analyzes uncompiled or source code to find insecure coding patterns, syntax errors, and flaws before the software is built.
• DAST (Dynamic Application Security Testing): Interacts with running applications from the “outside in” to find runtime vulnerabilities like SQL injection and cross-site scripting (XSS).
• SCA (Software Composition Analysis): Scans open-source dependencies and third-party libraries to identify known vulnerabilities and license compliance issues.
• IAST (Interactive Application Security Testing): Combines SAST and DAST, monitoring application behavior and data flow from within the application while it runs.

Types of application security testing by use case:

• Penetration testing: Simulates real attackers to uncover exploitable vulnerabilities, business logic flaws, and attack chains that automated tools often miss.
• Mobile application security testing (MAST): Identifies security issues unique to iOS and Android applications, including insecure storage, weak certificate validation, and reverse engineering risks.
• Web application security testing: Evaluates browser-based applications for vulnerabilities such as injection, XSS, broken authentication, and access control flaws using automated and manual testing.
• Cloud application security testing (CAST): Assesses cloud-native applications, infrastructure, identities, and configurations to identify cloud-specific security risks and misconfigurations.

Application security testing best practices:

• Start with high-risk applications: Prioritize testing for applications that process sensitive data or support critical business functions to reduce the highest risks first.
• Combine multiple testing methods: Use complementary techniques such as SAST, DAST, SCA, penetration testing, and IaC scanning to improve vulnerability coverage.
• Integrate testing into developer workflows: Embed security checks into IDEs, version control, pull requests, and CI/CD pipelines to identify issues earlier in development.
• Reduce false positives with tuning and triage: Customize detection rules and validate findings to improve accuracy and focus remediation on meaningful risks.
• Add secrets detection before code is merged: Scan for exposed credentials during development to prevent sensitive information from reaching shared repositories or production.
• Include Infrastructure as Code security: Scan IaC templates to identify insecure cloud configurations before infrastructure is deployed.

Why Application Security Testing Matters

Application Security Testing (AST) helps organizations identify and remediate security weaknesses before they can be exploited. By integrating security testing throughout the software development lifecycle, AST reduces cyber risk, supports secure development, protects sensitive data, and helps organizations meet regulatory and business security requirements.

• Reducing exploitable vulnerabilities: AST identifies weaknesses in application code, configurations, and runtime behavior before deployment, reducing the attack surface. Continuous testing throughout development helps detect newly introduced vulnerabilities while minimizing false positives and missed issues.
• Supporting secure software development: Integrating AST into developer workflows encourages secure coding practices and provides early feedback on security issues. This shift-left approach reduces remediation costs, limits security-related technical debt, and improves long-term software quality.
• Protecting customer data: AST helps prevent vulnerabilities that could expose sensitive information, including personal, financial, and business data. Reducing the likelihood of data breaches also helps preserve customer trust and avoid legal, regulatory, and financial consequences.
• Meeting compliance and risk management requirements: Regular application security testing supports compliance with standards such as PCI DSS, HIPAA, and GDPR by providing evidence of security assessments and remediation efforts. AST also helps organizations prioritize vulnerabilities based on risk, making remediation efforts more effective.

Common Vulnerabilities Found by Application Security Testing Tools 

Injection Flaws

Injection flaws, such as SQL, OS, or LDAP injection, occur when untrusted data is sent to an interpreter as part of a command or query. Attackers exploit these flaws by inserting malicious input that the application executes, potentially allowing unauthorized access, data manipulation, or system compromise. AST tools detect these vulnerabilities by analyzing code paths and input validation mechanisms, highlighting areas where user input is not properly sanitized.

The impact of injection vulnerabilities can be severe, ranging from data leaks to loss of application control. Early detection and remediation are critical, as these flaws are often easy to exploit and frequently targeted. Implementing input validation, parameterized queries, and regular AST scans reduces the risk posed by injection flaws.

Cross-Site Scripting

Cross-site scripting (XSS) vulnerabilities occur when an application includes untrusted data in a web page without proper validation or escaping, enabling attackers to execute malicious scripts in users’ browsers. XSS can be used to steal session cookies, impersonate users, or redirect victims to malicious sites. Tools for application security testing identify XSS issues by scanning for unsafe data handling in client-side and server-side code.

There are different types of XSS, including stored, reflected, and DOM-based, each with distinct attack vectors and remediation approaches. Comprehensive AST solutions detect these variations and provide guidance for fixing them. Preventing XSS requires input validation, output encoding, and, where appropriate, the use of security headers like Content Security Policy (CSP).

Broken Authentication

Broken authentication vulnerabilities arise when application mechanisms for validating user identity are improperly implemented, allowing attackers to compromise user accounts. Common issues include weak password policies, predictable session IDs, or flawed multi-factor authentication processes. AST tools uncover these weaknesses by examining authentication logic and session management flows.

The consequences of broken authentication include unauthorized access to sensitive data, privilege escalation, and account takeover. Remediation involves enforcing strong authentication standards, securely managing credentials, and ensuring session tokens cannot be easily guessed or stolen. Regular security testing of authentication processes is necessary to maintain protection against evolving attack methods.

Broken Access Control

Broken access control occurs when applications fail to enforce restrictions on what authenticated users can do, leading to unauthorized actions such as viewing or modifying data they should not access. AST tools detect these flaws by simulating user roles and permissions and identifying where access boundaries are not respected.

These vulnerabilities can result from overlooked logic paths or misconfigured rules. Attackers can exploit broken access control to escalate privileges or exfiltrate sensitive information. Mitigation requires secure design, code reviews, and dynamic testing to ensure access rules are consistently enforced.

Security Misconfiguration

Security misconfiguration refers to improper settings or defaults in applications, frameworks, servers, or platforms that leave systems open to attack. Examples include verbose error messages, unnecessary services, or outdated components. AST tools identify misconfigurations by checking for deviations from recommended security baselines and best practices.

Misconfigurations are common and often easy to exploit. They often result from rushed deployments or lack of security awareness. Addressing these issues involves hardening configurations, automating security checks, and maintaining up-to-date deployment documentation.

Vulnerable and Outdated Components

Using components with known vulnerabilities, such as outdated libraries or plugins, exposes applications to publicly disclosed and often exploited risks. AST tools, particularly those focused on Software Composition Analysis (SCA), scan dependencies and flag those with security advisories or missing updates.

The threat landscape for open-source and third-party components changes rapidly, making timely patching and monitoring critical. Failing to update components can lead to compromise even if custom code is secure. Organizations should establish processes for tracking and updating dependencies.

Hardcoded Secrets

Hardcoded secrets, such as API keys, passwords, or cryptographic keys embedded in source code, present a risk if exposed. Attackers who gain access to the codebase can use these secrets to bypass authentication or access external services. AST tools with secrets detection scan for patterns that indicate sensitive information in the code.

Hardcoded secrets often reach production through overlooked development practices or insufficient code review. Organizations should use environment variables or secure vaults to manage secrets and enforce automated scanning before code is merged or deployed.

Related content: Read our guide to malicious code

[Interactive Diagram] Core Types of Application Security Testing 

Application Security Testing Methods at a Glance

The following table summarizes the primary methods and techniques used in modern application security testing. We explore each of the methods in more detail below.

By Testing Methodology

1. Static Application Security Testing (SAST)

SAST analyzes application source code, bytecode, or binaries for security vulnerabilities without executing the program. This method identifies issues such as insecure coding practices, buffer overflows, and improper input validation by tracing data flows and control paths within the codebase. SAST tools integrate early in development, allowing developers to detect and fix vulnerabilities before they progress further down the pipeline.

SAST provides early feedback to developers, supporting a shift-left approach to security. However, SAST can generate false positives and may not catch issues that appear only during runtime. For best results, SAST should be complemented by other testing methods and tuned to the languages and frameworks in use.

2. Dynamic Application Security Testing (DAST)

DAST evaluates running applications by simulating attacks and monitoring responses, focusing on vulnerabilities that appear during execution. Unlike SAST, DAST does not require access to source code; instead, it interacts with the application as an external attacker would, probing for issues like injection flaws, XSS, and misconfigurations. DAST is useful for identifying runtime and environment-specific vulnerabilities.

AI-powered Dynamic Application Security Testing tools test the application in a real-world context and can uncover issues that static analysis might miss. However, DAST can be slower for complex applications and may struggle to reach all code paths without thorough test coverage. Integrating DAST into continuous integration pipelines helps maintain security throughout the software lifecycle.

3. Software Composition Analysis (SCA)

Software Composition Analysis (SCA) identifies and manages risks introduced through third-party and open-source components used within an application. Modern software often relies on external libraries, frameworks, and packages, making it necessary to track dependencies and monitor them for known vulnerabilities, licensing issues, and outdated versions. SCA tools inventory components and compare them against vulnerability databases.

SCA continuously monitors dependencies throughout the software lifecycle. When new vulnerabilities are disclosed, organizations can determine whether they are affected and prioritize remediation. While SCA does not analyze custom code for security flaws, it provides visibility into supply chain risks.

4. Interactive Application Security Testing (IAST)

IAST combines elements of SAST and DAST by analyzing applications from within the running environment. It uses instrumentation agents deployed alongside the application to monitor code execution, data flows, and security-relevant events during testing. Because IAST has visibility into source code context and runtime behavior, it can identify vulnerabilities with greater accuracy and provide information about root causes.

IAST reduces false positives and offers remediation guidance. It detects vulnerabilities such as injection flaws, insecure configurations, and authentication weaknesses as the application is exercised through functional or security tests. However, IAST requires application instrumentation and test coverage to be effective.

By Use Case

5. Penetration Testing

Penetration testing is a manual or semi-automated security assessment in which security professionals attempt to identify and exploit vulnerabilities in an application, simulating real attackers. Unlike automated AST tools, penetration testers use human expertise to discover complex vulnerabilities, chained attack paths, and business logic flaws that automated scanning may overlook.

Penetration testing evaluates security from an attacker’s perspective and validates the real-world impact of identified weaknesses. It often uncovers issues related to authorization, workflow manipulation, and application design that require contextual understanding. While typically performed periodically rather than continuously, it complements automated AST methods by providing insight into an application’s overall security posture.

6. Mobile Application Security Testing (MAST)

Mobile Application Security Testing (MAST) focuses on identifying security vulnerabilities in iOS and Android applications, as well as the APIs and backend services they rely on. Mobile applications introduce risks that are less common in traditional web applications, including insecure local data storage, weak certificate validation, improper use of platform security features, and reverse engineering. MAST combines static analysis, dynamic testing, and device-specific techniques to evaluate the application’s behavior and resilience.

Teams often combine MAST with SAST, DAST, and API security testing to gain complete visibility into the mobile ecosystem. While MAST identifies issues specific to mobile platforms and devices, other testing methods help assess backend services, shared code, and third-party components that also contribute to the application’s security.

7. Web Application Security Testing

Web Application Security Testing focuses on identifying vulnerabilities in browser-based applications and the services that support them. It evaluates common web security issues such as injection attacks, cross-site scripting (XSS), broken authentication, access control flaws, and security misconfigurations. Testing typically combines automated scanning with manual validation to assess both client-side and server-side behavior.

Teams rarely rely on a single testing method for web applications. SAST helps identify coding issues before deployment, DAST evaluates the running application, IAST provides runtime insight during testing, and penetration testing uncovers complex attack paths and business logic flaws. Combining these approaches provides broader coverage across the software development lifecycle.

8. Cloud Application Security Testing (CAST)

Cloud Application Security Testing (CAST) focuses on securing applications running in cloud environments by evaluating application code, cloud configurations, infrastructure, identities, APIs, and deployed services. Cloud-native applications rely on services such as containers, serverless functions, managed databases, and identity platforms, creating risks that extend beyond application code. CAST helps identify vulnerabilities, insecure configurations, excessive permissions, exposed resources, and other cloud-specific security issues.

Cloud applications require multiple testing approaches because security depends on both the application and the cloud environment in which it operates. Teams commonly combine CAST with SAST, DAST, SCA, infrastructure as code (IaC) scanning, container security scanning, and cloud security posture management (CSPM) to detect risks across the entire cloud application stack.

Why Mature Programs Combine Methods Rather Than Rely on One Approach

No single application security testing method can identify every type of vulnerability. Some techniques analyze source code before deployment, while others evaluate running applications, third-party components, cloud environments, or platform-specific risks. Each method provides visibility into a different part of the application and its attack surface, with its own strengths and limitations.

Mature application security programs combine multiple testing methods to improve coverage throughout the software development lifecycle. For example, SAST helps developers detect coding issues early, SCA manages risks from third-party dependencies, DAST validates deployed applications, IAST provides runtime context, and penetration testing uncovers complex attack paths and business logic flaws. Using these methods together allows teams to identify a broader range of vulnerabilities, reduce false positives, and prioritize remediation based on real-world risk.

How Application Security Testing Fits Into the SDLC 

The following table shows how the testing methods above fit into each stage of the software development lifecycle (SDLC).

Application Security Testing Best Practices 

1. Start With High-Risk Applications

Application security testing delivers the greatest value when organizations focus first on the applications that create the highest business risk. Systems that process sensitive customer information, financial transactions, regulated data, or critical business operations should receive the highest testing priority because they are the most attractive targets for attackers. 

A risk-based approach also helps security teams allocate limited resources more effectively by focusing on the applications where vulnerabilities would have the greatest operational, financial, or compliance impact.

Action items:

• Identify applications that process sensitive or regulated data.
• Rank applications based on business criticality, internet exposure, and user population.
• Prioritize security testing for externally accessible applications.
• Reassess application risk regularly as systems and business requirements change.
• Allocate testing resources according to business risk rather than application count.

2. Combine Multiple Testing Methods

No single application security testing method can identify every class of vulnerability. Static analysis, dynamic testing, software composition analysis, secrets detection, IaC scanning, and penetration testing each provide visibility into different parts of the attack surface. Combining these techniques throughout the software development lifecycle improves coverage, compensates for the limitations of individual tools, and provides a more complete view of application risk.

Action items:

• Combine SAST, DAST, SCA, and penetration testing in the testing program.
• Include secrets detection and IaC scanning where applicable.
• Use multiple testing methods at different stages of the SDLC.
• Correlate findings from different tools to improve prioritization.
• Review testing coverage regularly to identify security gaps.

3. Integrate Testing Directly Into Developer Workflows

Application security testing is most effective when developers receive security feedback while they are actively writing and reviewing code. Embedding security checks into IDEs, version control systems, pull requests, and CI/CD pipelines allows vulnerabilities to be identified and remediated before they reach later development stages. 

Continuous testing also shortens feedback loops and helps establish security as a shared engineering responsibility rather than a separate review process.

Action items:

• Integrate AST tools into IDEs and source control platforms.
• Run automated security checks during pull requests and CI/CD builds.
• Provide developers with remediation guidance alongside findings.
• Treat security defects similarly to functional defects during development.
• Measure remediation times to improve development workflows.

4. Reduce False Positives With Tuning and Triage

Application security testing produces the best results when findings are accurate, relevant, and prioritized. Excessive false positives reduce confidence in security tools and can overwhelm development teams with low-value work. 

Organizations should regularly tune detection rules, customize policies for their technology stack, and establish a consistent triage process that validates findings before remediation efforts begin.

Action items:

• Customize detection rules for the organization’s applications.
• Suppress findings that have been verified as non-exploitable.
• Validate security findings before assigning remediation work.
• Prioritize vulnerabilities based on exploitability and business risk.
• Provide developers with clear remediation recommendations.

5. Add Secrets Detection Before Code Is Merged

Exposed credentials remain a common cause of security incidents and are often introduced during development. Automated secrets detection identifies API keys, passwords, certificates, access tokens, and other sensitive credentials before they are committed to shared repositories or deployed into production. 

Preventing secret exposure early is significantly easier than rotating compromised credentials after they have been distributed.

Action items:

• Scan source code for exposed secrets before merge requests are approved.
• Block commits containing verified credentials.
• Store secrets in dedicated secrets management platforms or vaults.
• Replace hardcoded credentials with environment-based configuration.
• Regularly rotate credentials and revoke exposed secrets.

6. Include Infrastructure as Code Security

Modern applications increasingly rely on infrastructure defined through code, making infrastructure security an essential part of application security testing. Infrastructure as Code (IaC) scanning analyzes Terraform, Kubernetes, AWS CloudFormation, and similar templates to detect insecure configurations before cloud resources are deployed. 

Identifying misconfigurations during development reduces operational risk and prevents insecure infrastructure from reaching production.

Action items:

• Scan IaC templates during development and CI/CD pipelines.
• Detect excessive permissions, exposed services, and insecure networking.
• Verify encryption and secure default configurations.
• Apply security policies consistently across infrastructure templates.
• Remediate IaC findings before deployment to production.

How to Choose Application Security Testing Solutions 

Choosing an application security testing solution requires balancing coverage, accuracy, workflow fit, and remediation speed. The right solution should help teams find meaningful risks across the software lifecycle without slowing development or overwhelming teams with low-value alerts.

Key considerations include:

• Coverage across the SDLC: Support for code, dependencies, secrets, infrastructure as code, APIs, containers, and runtime environments.
• Multiple testing methods: Combination of static analysis, software composition analysis, secrets detection, IaC scanning, API security, container security, and dynamic testing.
• Low false positive rates: High-fidelity findings that distinguish exploitable issues from theoretical risks.
• Risk-based prioritization: Findings ranked by severity, exploitability, context, and business impact.
• Developer workflow integration: Integration with IDEs, source control systems, CI/CD pipelines, issue trackers, and collaboration tools.
• Actionable remediation guidance: Clear explanations and fix recommendations close to where code is written and reviewed.
• Automation and AI assistance: Automated triage, prioritization, and fix suggestions to reduce manual work.
• Support for AI-generated code: Evaluation of human-written and AI-generated code with the same scrutiny.
• Unified risk visibility: Single view of risks across applications, dependencies, infrastructure, and runtime signals.
• Scalability for large teams: Support for many applications, repositories, languages, and teams without creating bottlenecks.
• Centralized governance and controls: Centralized policy management, role-based access controls, audit logs, and standardized security gates to enforce consistent security requirements across teams while supporting compliance and reporting.

Conclusion

Effective application security testing relies on combining multiple testing methods rather than depending on a single tool. SAST, DAST, SCA, IAST, penetration testing, and specialized approaches such as mobile, web, and cloud application security testing each provide visibility into different parts of the attack surface. Using these methods together throughout the software development lifecycle helps organizations identify a wider range of vulnerabilities, validate findings, reduce false positives, and address security issues before they can be exploited.

As applications evolve, application security testing should evolve with them. Modern AST programs integrate testing into developer workflows, continuously assess applications and dependencies, and use solutions that fit the organization’s technology stack and development processes. Selecting tools with broad coverage, strong integrations, and actionable remediation guidance enables security and development teams to reduce risk over time while supporting faster and more secure software delivery.

Application Security Testing for the Agentic AI Era with Checkmarx One Platform

Checkmarx One is the unified, cloud-native application security platform for enterprises that need to secure code, applications, and AI-driven development at scale. It brings SAST, SCA, IaC, API, DAST, container, and supply chain security together with ASPM and the Checkmarx One Assist family of agentic AI agents, delivering correlated risk insights and developer-centric remediation from the IDE to production. With a single platform and data model, customers reduce tool sprawl, improve risk visibility, and help developers ship secure software faster.

Key capabilities of the Checkmarx One platform:

• Unify fragmented AppSec tools: Consolidate multiple scanning and point solutions into one platform with a shared data model.
• Gain a single view of application risk: Correlate findings across code, open source, infrastructure, APIs, containers, and supply chain.
• Accelerate remediation: Use agentic AI assistants to provide contextual fixes, prioritization, and guidance where teams work.
• Support enterprise governance and reporting: Align AppSec metrics and posture with business-critical applications and regulatory requirements.
• Enable shift everywhere: Embed security across IDEs, CI/CD pipelines, cloud, and runtime, aligned to modern DevSecOps practices.

Learn more about Checkmarx One