Static application security testing
In today's rapidly evolving software development landscape, ensuring the security of applications from their inception is no longer just a best practice—it's a critical imperative. This is where static application security testing (SAST) plays an indispensable role.
What is SAST?
SAST, often referred to as static analysis, is a software security testing methodology that meticulously analyzes an application's source code, bytecode, or binary code to uncover potential security weaknesses. Unlike dynamic testing methods that examine a running application, SAST scrutinizes an application from the "inside out," with full access to its internal structure and design, before the code is compiled or executed. This makes SAST a form of white-box testing (i.e., we can "look inside the machine"), providing deep visibility into an application's underlying logic.
At its core, SAST works by parsing an application's code to generate an abstract syntax tree, which represents the structural components of the code, such as functions, variables, and loops. Following this, it performs sophisticated control flow and data flow analyses. Control flow analysis maps potential execution paths through the code, while data flow analysis tracks how data moves between different components. This comprehensive understanding enables SAST to identify insecure data handling, misconfigurations, logical flaws, and other coding mistakes that could lead to vulnerabilities.
SAST tools contain vast databases of predefined security rules and policies, often based on industry standards like the OWASP Top 10 and Common Weakness Enumeration (CWE) lists, which they use to pinpoint patterns associated with known vulnerabilities, such as SQL injection, cross-site scripting (XSS), buffer overflows, and XML External Entity (XXE) vulnerabilities, among others.
Why is SAST necessary?
The need for SAST stems from several fundamental challenges in modern software development:
Developer-to-security staff ratio: Development teams vastly outnumber security personnel in most organizations. Manually reviewing every line of code for security flaws is simply not feasible, especially for large applications. SAST tools automate this process, allowing for the rapid analysis of millions of lines of code in minutes, something impossible for human reviewers.
Early detection and cost efficiency: Finding and remediating vulnerabilities early in the software development lifecycle (SDLC) is significantly less expensive than addressing them later. SAST's ability to operate on uncompiled code means it can be integrated at the very beginning of the SDLC, enabling developers to identify and resolve issues quickly without disrupting builds or pushing vulnerabilities downstream to later stages or, worse, to production.
Enforcing secure coding practices: SAST helps enforce secure coding practices within developers' workflows. By providing near-instant feedback on potential security issues as code is written or committed, SAST helps development teams avoid common risks and learn from their mistakes, fostering a culture of security from the outset.
Preventing data breaches and reputation damage: Unchecked vulnerabilities, once exploited, can lead to serious consequences, including data breaches, significant financial losses, and irreparable damage to an organization's brand reputation. SAST acts as an early warning system, helping to prevent such costly incidents before an application is deployed to the public.
In essence, SAST is an indispensable activity because it represents a proactive, scalable, and cost-effective way to integrate security into the relentless development and updating of software products.
SAST in the SDLC: shifting security left
A cornerstone of modern application security (AppSec), particularly within the DevSecOps approach, is the concept of "shifting left." This refers to the practice of bringing security testing and considerations into the early stages of the SDLC. SAST is an ideal technology for achieving this.
By incorporating SAST into developers' integrated development environments (IDEs) or continuous integration (CI) pipelines, security analysis can occur almost in parallel with code writing or committing. This allows developers to receive rapid feedback on potential security issues, enabling them to address these problems when they are still fresh in their minds, and remediation may be easier. Instead of vulnerabilities being discovered only in the final stages of the SDLC, SAST can ensure continuous security feedback.
The benefits of this "shift left" approach with SAST are substantial:
Accelerated development: By catching vulnerabilities early, developers can fix them quickly, preventing them from accumulating and becoming complex, time-consuming problems later on. This minimizes rework and helps maintain a development velocity.
Reduced remediation costs: The later a vulnerability is discovered in the SDLC, the more expensive and time-consuming it becomes to fix. SAST's early intervention dramatically cuts down these costs.
Improved code quality: Consistent SAST scans encourage developers to write more secure and robust code from the outset, leading to higher overall application quality.
Secure SDLC: Regular SAST scans contribute to a more secure SDLC by ensuring that multiple security considerations are embedded at every stage, from initial coding to final release.
While SAST can be used as a security gateway at various points of the SDLC, including during daily/monthly builds or every code check-in, its maximum value is realized when it is pushed as far left as possible.
SAST's scope: What types of issues does it find?
SAST is adept at identifying a wide array of security issues within an application's static structure. It excels at detecting problems that stem from insecure coding practices, logical errors, and misconfigurations within the code itself. Specifically, SAST tools can identify:
Injection flaws: Such as SQL injection, command injection, and server-side injection, where untrusted input is processed as part of a command or query.
Buffer overflows: Memory-related issues where a program attempts to write data beyond the boundaries of a fixed-length buffer, potentially leading to crashes or arbitrary code execution.
Cross-site scripting (XSS) vulnerabilities: Where malicious scripts are injected into trusted websites to steal user data, hijack sessions, deface pages, or redirect users to malicious sites.
XML external entity (XXE) vulnerabilities: Which can allow for arbitrary file reading, denial of service, or server-side request forgery.
Insecure data handling: Including improper input validation, where data coming from insecure sources is not properly cleansed before consumption.
Weak cryptographic implementations: Such as the use of outdated algorithms or hardcoded passwords, which can allow attackers to easily decrypt sensitive data or gain unauthorized access to systems.
Misconfigured settings: Flaws within application configuration files (e.g., XML, YAML) that could expose the application to unauthorized access, data breaches, or denial of service.
Control flow problems: Issues with the order of program operations that could lead to dangerous sequences and, as a result, allow security controls to be bypassed, unauthorized access, or application crashes.
Semantic errors and structural flaws: Inconsistencies with secure programming practices, weaknesses in class design, and improper declaration or use of variables and functions.
Compliance with standards: SAST tools can check code for compliance with a wide array of security requirements based on international industry standards like OWASP, PCI DSS, GDPR, and HIPAA.
By analyzing data flow, control flow, and semantic information within the code, SAST provides a deep understanding of potential vulnerabilities, even pointing out the exact lines of code where each problem resides.
What are the differences between SAST and DAST?
While SAST is a powerful approach, it's crucial to understand its place within a broader AppSec strategy. Often, discussions about SAST lead to questions about dynamic application security testing (DAST) and how these two methodologies differ.
Feature | SAST | DAST |
Testing method | White-box testing (inside-out) | Black-box testing (outside-in) |
Analysis | Analyzes source code, bytecode, or binaries without executing the application. | Analyzes a running application by simulating attacks. |
Visibility | Complete visibility into the application's source code and internal logic. | No visibility into the internal operations or source code; treats the application as a black box. |
When applied | Early in the SDLC, as soon as code is written or committed. | Later in the SDLC, once there's a working application (e.g., in a test environment or even production). |
Vulnerability types | Code-level vulnerabilities, logic flaws, insecure coding practices (e.g., SQLi, buffer overflows, XXE). | Runtime vulnerabilities, configuration issues, authentication flaws, server-side issues (e.g., XSS, broken auth). |
Programming language dependent? | Yes, the tool needs to support the specific language(s) and frameworks used. | No, it interacts with the application externally, regardless of its underlying language. |
False positives | Tends to produce more false positives as it lacks runtime context. | Tends to have fewer false positives as it tests real-world execution. |
Remediation details | Pinpoints the exact line of code, making remediation straightforward. | Reports that a vulnerability exists, but not the exact line of code. |
Speed of scan | Generally faster, as it doesn't require a running application. | Can take longer, as it requires the application to be executable and involves simulating interactions. |
Do you need both SAST and DAST?
Absolutely. SAST and DAST are complementary, not mutually exclusive. They largely detect different types of vulnerabilities and provide distinct insights. SAST excels at identifying code-level flaws early, enabling precise remediation guidance. However, it cannot detect runtime configuration errors, environment-specific issues, or vulnerabilities that only manifest when the application is actively interacting with external systems.
DAST fills this gap by testing the live application much as an attacker would, uncovering issues that SAST might miss due to its nature. Employing both SAST's early intervention and DAST-type testing in pre-production and production environments ensures a much broader and deeper approach to application security, maximizing vulnerability coverage throughout the SDLC.
What are the differences between SAST and SCA?
Another important distinction is between SAST and software composition analysis (SCA). While both techniques are crucial for comprehensive application security, they focus on different aspects of the codebase.
SCA primarily focuses on third-party code dependencies, such as open-source libraries, frameworks, and other components used within an application. SCA tools scan these components to identify known security vulnerabilities (often from public vulnerability databases like CVEs), outdated versions, and licensing compliance issues. As modern applications heavily rely on open-source libraries, SCA has become increasingly vital for understanding and managing the risks associated with these external components. Like SAST, SCA is often programming language-dependent because it needs to understand the structure of the libraries.
SAST, on the other hand, focuses on the application's custom-written code. It analyzes the unique logic and implementation flaws introduced by the development team. When used together, SCA and SAST provide a comprehensive assessment of an application's security posture: SCA secures third-party components, while SAST covers in-house code.
Advantages and disadvantages of SAST
Like any AppSec testing methodology, SAST has its strengths and weaknesses. Understanding these helps in its effective deployment.
Advantages of SAST
Early detection ("Shift Left"): Identifies vulnerabilities at the earliest stages of development, often before code is compiled, significantly reducing remediation costs and effort.
Comprehensive code coverage: Can analyze 100% of the codebase, ensuring every line of code and every potential execution path is tested for security flaws.
Speed and automation: Scans millions of lines of code in minutes, far exceeding the capabilities of manual code reviews. Additionally, automates consistent security checks across large codebases.
Pinpoints root cause: Provides precise details, including file name, location, and line number, for each detected vulnerability, simplifying understanding and remediation for developers.
Reinforces secure coding practices: Integrates into developer workflows (e.g., IDE plugins), providing rapid feedback that helps developers learn from mistakes and write more secure code proactively.
Variety of languages supported: Many modern SAST tools support a wide range of programming languages and frameworks, allowing consistency across diverse projects.
Supports compliance: Helps organizations meet regulatory requirements (e.g., PCI DSS, GDPR) by demonstrating due diligence in identifying and addressing software vulnerabilities.
Disadvantages and challenges of SAST
False positives: SAST tools make assumptions based on code patterns and frequently flag harmless or healthy pieces of code as vulnerabilities, which are known as false positives. This often leads to wasted time in investigation and reduces trust in the tool.
False negatives: Conversely, SAST can miss many actual vulnerabilities, classified as false negatives, particularly those that depend on runtime context, complex configuration, or external environmental factors.
Lack of runtime context: SAST analyzes code in isolation, meaning it cannot determine if a potential vulnerability is truly exploitable in a live environment. It's "blind" to runtime interactions and network-related issues. For example, it might flag unsanitized input on the front end even if it's properly sanitized on the backend, leading to a false positive if the SAST tool doesn't have visibility across different repositories.
Language dependency: While many tools support multiple languages, if an organization uses many different or less common programming languages, finding a single SAST tool that covers all of them effectively can be a challenge.
Scan time and report freshness: While generally faster than DAST, comprehensive SAST scans can still take a significant amount of time for very large codebases. The resulting reports represent a snapshot of the code at that moment and can quickly become outdated as development continues, necessitating frequent re-scans.
Requires tuning and maintenance: SAST is not a "set-it-and-forget-it" solution. Rules need to be reviewed, refined, and updated over time to reduce noise (false positives), reflect changes in the codebase, and account for evolving attack patterns. Without ongoing care, tools can become obsolete or overly noisy.
Context-blindness (cloud/runtime): Without integration with cloud or runtime visibility tools, SAST treats all findings equally, regardless of whether a vulnerable piece of code is running in a locked-down internal service or an internet-facing workload with access to sensitive data. Prioritization based on actual risk becomes difficult without this context.
Despite these challenges, modern SAST tools are continuously evolving to address these issues, notably through the integration of AI and machine learning, which helps improve accuracy and reduce false positives.
Key steps to run SAST effectively
Implementing SAST effectively goes beyond simply acquiring a good tool. It involves a strategic approach that actively engages development and security teams and also brings key add-ons such as risk management platforms and generative AI models into play.
Tool selection
Choose a SAST tool that supports the programming languages and underlying frameworks used by your development teams. Key features to look for include:
Accuracy: High true positive rates (identifying real vulnerabilities) and low false positive rates (minimizing irrelevant alerts).
Speed: Fast scanning capabilities to avoid slowing down development workflows.
Integration: Optimal integration with CI/CD pipelines, version control systems, IDEs, and other development tools.
Developer-friendly: Continuous scans to deliver near real-time reports and integration with an easy-to-use platform for vulnerability prioritization and remediation.
Automated remediation: Compatibility with a GenAI model capable of generating accurate and secure code suggestions or even applying fixes automatically.
Configuration
Handle licensing, set up access control, and provision necessary resources (servers, databases) for the tool. Fine-tune the tool to your organizational needs, configuring it to reduce false positives or find specific vulnerabilities by updating existing rules or writing new ones.
Integration into workflows
Embed the SAST tool into developer workflows. This includes IDE extensions for rapid feedback as code is written and command-line tools connected to version control systems to run scans automatically during commits, pull requests, or builds. The goal is to catch issues as early as possible.
Application scanning
Prioritize high-risk applications for initial scans, eventually onboarding all applications. Synchronize application scans with release cycles, daily/monthly builds, or code check-ins to ensure continuous security assessment.
Vulnerability prioritization
After scans, triage the results to remove false positives and prioritize identified vulnerabilities based on severity, exploitability, and potential impact. This ensures remediation efforts focus on the most critical risks.
Remediation and verification
Provide detailed issues to development teams for timely remediation. Implement fixes by patching code or applying other measures and re-scan to verify that the remediations have worked and have not introduced new vulnerabilities.
Continuous improvement and governance
Secure coding training: Train developers on secure coding practices and how to use SAST tools effectively.
Regular tool updates: Keep SAST tools updated to identify the latest vulnerabilities and adhere to current coding standards.
Process review: Regularly review and improve SAST processes, tools, and configurations to adapt to evolving threats and organizational needs.
Collaboration: Foster communication and collaboration between development, security, and operations teams to establish a shared understanding of security goals (DevSecOps culture).
Fluid Attacks: a comprehensive approach to SAST and beyond
Among the market-leading solutions, Fluid Attacks offers a powerful SAST tool that integrates seamlessly into modern development workflows. Our static analysis tool, which is continuously optimized, is designed to quickly identify a wide range of vulnerability types from the very beginning of your SDLC.
Our SAST tool supports around 15 programming languages and is continuously benchmarked against other tools to improve its scope and reduce false positive rates. Notably, in 2021, our SAST tool achieved 100% in true positives and 0% in false positives against the OWASP Benchmark version 1.2, demonstrating exceptional accuracy and minimal noise.
Fluid Attacks' scanner findings are delivered through our intuitive vulnerability management platform and API, as well as through convenient IDE extensions, making them highly practical for your development team. Beyond just detection, we also leverage generative artificial intelligence to provide you with automated, custom fix options for specific vulnerabilities in your code, significantly easing the remediation burden.
Perhaps surprisingly, the SAST scanner and other Fluid Attacks tools are open source. What truly sets Fluid Attacks apart is our holistic approach. We combine multiple testing techniques in a single, integrated solution, encompassing SAST, SCA, DAST, cloud security posture management (CSPM), secure code review (SCR), penetration testing as a service (PTaaS), and reverse engineering (RE). Our pentesters are also available to help your development and security teams solve questions about the most complex vulnerabilities, ensuring no issue is left unaddressed. We also actively check remediation success with reattacks and can break the build in your CI/CD pipelines to prevent unsafe deployments, solidifying your security posture.
The future of SAST: AI and automated remediation
SAST is not a static field; it is continuously evolving with advancements in technology. The integration of artificial intelligence (AI) and machine learning (ML) is rapidly transforming SAST tools. AI/ML can significantly improve accuracy, reducing both false positives and false negatives, and enabling SAST tools to adapt faster to new vulnerability patterns.
Capabilities like "autofix" or "autoremediation" are becoming increasingly common: Static analysis, code context, and machine learning models are leveraged to generate precise, secure code suggestions—and sometimes even apply fixes automatically—without developers needing to leave their IDE or break the CI/CD flow. These innovations ease the burden on developers, allowing them to focus more on writing secure code and building innovative applications.
Conclusions
Static application security testing is an indispensable component of a robust application security strategy. By providing deep visibility into an application's codebase early in the development lifecycle, SAST enables organizations to detect and remediate vulnerabilities when they are least expensive to fix and before they can be exploited.
While SAST has its limitations, particularly concerning runtime context, its strengths—including comprehensive code coverage, automation, and the ability to "shift left"—make it a powerful prevention mechanism. When SAST is combined with complementary methods such as DAST and SCA, and integrated into a mature DevSecOps pipeline, it ensures a comprehensive and proactive approach to software security.
Investing in SAST and related technologies not only safeguards applications but also upholds the reputation and reliability of development teams and their companies, who demonstrate an unwavering commitment to excellence and security in software development.
