Source Code Analysis and SAST Services

In modern software projects, security is not limited to penetration tests carried out after the application reaches production. Detecting vulnerabilities as early in development as possible reduces remediation cost, accelerates release cycles and lowers the risk of critical weaknesses reaching the production environment.

SecureSys Source Code Analysis and SAST Services cover the security review of application source code, the deployment of static analysis tools, the detection of secure coding errors and carrying findings through to remediation together with development teams.

The service can address;

• Static Application Security Testing – SAST,
• Secure Code Review,
• Source Code Security,
• Software Composition Analysis – SCA,
• Secret Scanning,
• Dependency Security,
• CI/CD integration,
• Security Gate,
• Vulnerability Validation,
• Remediation Support

processes together.

Our approach:

Source Code → SAST → SCA → Secret Scan → Validation → Remediation → CI/CD Security Gate

is based on this cycle.

The goal is not merely to produce scanner output, but to build prioritized, technically validated security visibility that software teams can genuinely act on.

What Is Source Code Analysis?

Source Code Analysis is the review of an application's source code against security, quality and secure software development principles.

Source code analysis can be carried out with;

• automated SAST tools,
• manual code review,
• dependency analysis,
• secure coding checks

methods.

This makes it possible to detect potential security problems before the application reaches production.

What Is SAST?

SAST is the abbreviation for Static Application Security Testing.

SAST technologies perform static analysis on source code, bytecode or binaries without running the application.

The aim is;

• insecure code structures,
• injection risks,
• authentication problems,
• authorization errors,
• sensitive data handling,
• insecure API usage

and similar security problems to be detected at an early stage.

How Does SAST Work?

SAST tools parse source code to analyze the application's data flows, function calls and potentially risky code structures.

For example, if input taken from a user is sent directly into an SQL query, the SAST system follows that data flow and can raise an SQL Injection risk.

The basic flow:

User Input → Application Logic → Sensitive Function

is analyzed in this way.

The Difference Between SAST and DAST

SAST and DAST are two complementary Application Security methods.

SAST

Analyzes the source code.

DAST

Tests the running application from the outside.

SAST can detect security problems at an earlier stage, while DAST analyzes the application's actual runtime behavior.

The Difference Between SAST and Penetration Testing

SAST analyzes source code automatically or semi-automatically.

Penetration Testing, by contrast, carries out security testing on the running system from an attacker's perspective.

SAST offers an approach that is;

• repeatable,
• automated,
• CI/CD compatible

by nature.

Pentesting, meanwhile, can surface more complex security problems such as;

• business logic,
• authorization bypass,
• attack chaining,
• runtime behavior

and similar issues.

For this reason, the two approaches should be used together.

Secure Code Review

Secure Code Review is the manual review of source code by expert security analysts.

Manual review can surface problems that automated SAST tools struggle to detect, particularly in;

• business logic,
• authorization,
• custom cryptography,
• privilege management,
• security architecture

areas.

Automated and Manual Source Code Analysis

SecureSys can use both approaches together in source code security:

Automated SAST

Provides rapid analysis across large code bases.

Manual Secure Code Review

Provides deeper analysis of critical and complex functions.

This approach produces stronger results in critical applications in particular.

Why Does Source Code Security Matter?

The remediation cost of vulnerabilities found in production can be far higher than that of defects found during development.

Source code analysis can enable;

• early detection of security defects,
• greater developer awareness,
• reduced release risk,
• prevention of recurring security mistakes

outcomes.

Shift Left Security

Source code analysis is one of the core components of the Shift Left Security approach.

The aim is to move security controls to the beginning of the software development process.

Example:

Developer → Commit → SAST → Fix → Merge

models can be applied.

Secure SDLC and SAST

Within a Secure Software Development Lifecycle, SAST can be integrated into the;

• coding,
• pull request,
• build,
• release

stages.

This stops security controls from being a one-off project activity.

Risks Detectable Through Source Code Analysis

Depending on the technology and the analysis engine used, SAST systems can point to many security problems.

Example risks:

• SQL Injection,
• Cross-Site Scripting,
• Command Injection,
• Path Traversal,
• XXE,
• SSRF,
• insecure deserialization,
• weak cryptography,
• hardcoded credentials,
• insecure random,
• sensitive data exposure,
• unsafe file handling.

SQL Injection Source Code Analysis

SQL Injection problems generally arise from user input being used insecurely inside an SQL query.

The risky approach:

User Input → Dynamic SQL Query

In the secure approach, parameterized queries or prepared statements can be used.

SAST can analyze these data flows automatically.

XSS Source Code Analysis

Cross-Site Scripting problems can arise when user-controlled data is written to HTML output without appropriate encoding or sanitization.

By analyzing input-to-output data flows, SAST can identify potential XSS risks.

Command Injection

Passing user input into operating system commands can create Command Injection risk.

SAST can analyze risky command execution functions.

Path Traversal

Building file paths from user input without control can allow users to reach files they are not permitted to access.

SAST can detect these file system access patterns.

SSRF

Server-Side Request Forgery risks can arise when an application sends server-side requests to user-controlled URLs.

By analyzing data flows, SAST can identify potential SSRF points.

XXE

Insecure XML parser configuration can lead to XML External Entity attacks.

Source code analysis can detect risky XML parser usage.

Insecure Deserialization

Deserializing untrusted data without control can create critical security risks in some technologies.

SAST can analyze these usage patterns.

Authentication Security

Source code analysis can help detect security problems in authentication processes.

For example;

• insecure session management,
• password handling,
• weak authentication flow,
• unsafe token validation

can be checked.

Authorization Analysis

Authorization problems cannot always be detected with an automated scanner alone.

Critical role and permission checks can be examined through Secure Code Review.

Hardcoded Credentials

The presence of;

• passwords,
• database passwords,
• API keys,
• access tokens,
• private keys

inside source code creates serious security risk.

SAST and Secret Scanning systems can detect this information.

Secret Scanning

Secret Scanning looks for sensitive credentials, particularly across Git repositories and commit history.

For example;

• AWS keys,
• API tokens,
• private certificates,
• database credentials

can be detected.

Git History Analysis

Even if a secret has been removed from the current code, it can remain in older Git commits.

For this reason, secret scanning can be applied not only to the latest source code version but also across commit history.

Credential Rotation

A credential found in source code must not simply be deleted.

It should be rotated on the assumption that it may already be compromised.

Secure Secret Management

Credential information can be held in secure mechanisms such as;

• Vault,
• secret manager,
• environment variable,
• workload identity

rather than in source code.

Cryptography Analysis

Weak or incorrect cryptographic implementations can be present in source code.

For example;

• deprecated algorithm,
• hardcoded key,
• weak random,
• insecure cipher mode

risks can be evaluated.

Password Storage

Storing passwords in plaintext or with reversible encryption is a serious security risk.

Secure password hashing algorithms must be used.

Sensitive Data Exposure

Source code analysis can identify the risk of sensitive data being unintentionally exposed through;

• logs,
• error messages,
• debug output,
• API responses

channels.

Logging Security

Writing sensitive information such as;

• passwords,
• tokens,
• personal data,
• credit card data

into application logs must be prevented.

Error Handling

Overly detailed error messages can reveal information about system architecture to attackers.

Secure Code Review can evaluate error handling processes.

Input Validation

Treating user input as trustworthy is the root cause of many application security problems.

Input validation must be applied centrally and consistently.

Output Encoding

In web applications in particular, output encoding appropriate to each context must be applied.

File Upload Security

In file upload functions;

• extension,
• MIME type,
• file size,
• storage path,
• malware scanning

controls must be applied.

Source code analysis can review upload functions from a security perspective.

API Security Code Review

In modern applications, the security of API endpoints is critical.

Within code review, controls such as;

• authentication,
• authorization,
• input validation,
• object ownership,
• rate limiting

can be evaluated.

REST API Source Code Analysis

In REST APIs, IDOR/BOLA and authorization errors in particular can create high risk.

These problems can be analyzed in more detail through manual code review.

GraphQL Security

In GraphQL projects, risks such as;

• authorization,
• introspection,
• query depth,
• resource exhaustion

can be examined.

Mobile Backend Source Code Analysis

The backend API services of mobile applications can also be included in SAST scope.

Web Application Source Code Analysis

In web applications, frontend and backend components can be analyzed according to the technology used.

Microservice Source Code Analysis

In a microservices architecture, each service may have its own repository or code base.

SecureSys can establish a central SAST policy covering all services.

Monorepo SAST

In monorepo structures where all applications live in a single repository, SAST scope can be configured on a per-project basis.

Multi-Repo SAST

In organizations with a large number of repositories, a central SAST platform can be established.

Languages Supported by SAST

Depending on the tool used, a large number of programming languages can be analyzed.

For example;

• Java,
• C# / .NET,
• JavaScript,
• TypeScript,
• Python,
• PHP,
• C/C++,
• Go,
• Kotlin,
• Swift

languages can be supported.

Java Source Code Analysis

In Java applications, areas such as;

• Spring Security,
• serialization,
• SQL access,
• file operations,
• cryptography

can be analyzed.

.NET Source Code Analysis

In C# and .NET applications;

• authentication,
• Entity Framework,
• SQL queries,
• ASP.NET security,
• configuration

can be checked.

JavaScript and TypeScript SAST

In Node.js and frontend/backend JavaScript projects;

• dependency,
• input handling,
• server-side logic,
• secret

risks can be analyzed.

Python Source Code Analysis

In Python applications, areas such as;

• Django,
• Flask,
• FastAPI,
• file operations,
• command execution,
• database access

can be evaluated.

PHP Source Code Analysis

In PHP applications, injection, file handling and authentication risks can be examined with automated and manual methods.

Go Source Code Analysis

Go applications used in cloud-native and microservice projects can be included in SAST analysis.

Mobile Source Code Analysis

In Android and iOS applications, security topics such as;

• insecure storage,
• API keys,
• cryptography,
• certificate validation,
• sensitive data handling

can be evaluated at source code level.

Android Source Code Analysis

In Android Java/Kotlin projects;

• SharedPreferences,
• local database,
• exported component,
• WebView,
• intent handling

checks can be carried out.

iOS Source Code Analysis

In Swift and Objective-C projects, areas such as;

• Keychain,
• local storage,
• ATS,
• URL scheme,
• certificate handling

can be analyzed.

Software Composition Analysis – SCA

Modern source code projects use a large number of third-party dependencies.

While SAST analyzes first-party code, SCA analyzes third-party components.

For this reason, in application security;

SAST + SCA

should be used together.

Dependency Vulnerability

A vulnerability in an open source library in use can affect the application itself.

Vulnerable dependencies can be identified with SCA.

Transitive Dependency

The packages a package itself uses can also create security risk.

SCA can analyze transitive dependencies through the dependency tree.

Dependency Update

Safe version recommendations can be produced for vulnerable dependencies.

Producing an SBOM

Following source code and dependency analysis, a Software Bill of Materials can be produced.

An SBOM makes the third-party components an application uses centrally visible.

CycloneDX and SPDX

SBOM output can be produced in CycloneDX or SPDX format according to need.

Licence Analysis

For open source components, not only vulnerabilities but also licence risks can be analyzed.

Source Code Licence Compliance

Some open source licences can affect the software distribution model.

SCA solutions can provide licence visibility.

End-of-Life Dependency

Frameworks or packages whose development has ended and which no longer receive patches can be detected.

SAST CI/CD Integration

One of the most important advantages of SAST is that it can be integrated into the CI/CD pipeline.

Example:

Developer Commit → Build → SAST → Security Gate → Deployment

Pull Request SAST

Each time a Pull Request is opened, security analysis can be run only on the changed code.

This approach gives the developer rapid feedback.

Merge Request Security

When a critical vulnerability is found, merging the Merge Request can be blocked.

Security Gate

An automatic security gate can be applied according to risk level.

For example;

Critical → Block

High → Approval

Medium → Track

Low → Report

SAST and GitLab CI/CD

In environments using GitLab, SAST analyses can be run as pipeline jobs.

SAST and GitHub Actions

In GitHub repositories, security scans can be integrated into GitHub Actions pipelines.

SAST and Azure DevOps

Within Azure DevOps Pipelines, source code security scans can be automated.

SAST and Jenkins

SAST tools can be integrated into existing Jenkins CI/CD environments.

Quality Gate and Security Gate

Software quality and security results can be evaluated within the same pipeline.

While the Quality Gate checks;

• code quality,
• coverage,
• duplication

the Security Gate evaluates;

• vulnerability,
• secret,
• dependency

risks.

SAST as a Service

For organizations that do not want to build their own SAST platform, analysis can be delivered through a service model.

Within SecureSys SAST as a Service;

• source code scanning,
• finding validation,
• false positive analysis,
• reporting,
• remediation support

services can be provided.

Managed SAST Service

Owning a SAST product is not sufficient on its own.

Scanner results need continuous analysis.

Within SecureSys Managed SAST;

• scan scheduling,
• rule tuning,
• finding triage,
• false positive management,
• developer reporting

processes can be managed.

False Positive Management

SAST tools can produce findings that are not genuine security problems.

Too many false positives can lead developer teams to disregard security tooling altogether.

SecureSys can have critical findings validated by expert analysts.

True Positive Validation

High and Critical findings can be analyzed manually to determine whether they represent real risk.

Exploitability Analysis

The presence of a vulnerability in code does not always mean it is directly exploitable.

Risk must be assessed together with;

• application exposure,
• data flow,
• authentication,
• existing controls

factors.

Risk-Based Prioritization

SecureSys does not evaluate findings on the scanner severity score alone.

In prioritization;

• vulnerability severity,
• application criticality,
• internet exposure,
• exploitability,
• data sensitivity

can be weighed together.

Vulnerability Triage

During triage, findings can be classified as;

• genuine risk,
• false positive,
• accepted risk,
• remediation required

categories.

Remediation Guidance

Technical remediation guidance a developer can act on can be prepared for each security finding.

For example, rather than simply saying:

“SQL Injection found.”

the report can present;

• the risky line of code,
• the data flow,
• an example of the secure approach,
• a remediation explanation

together.

Developer-Friendly Reporting

It matters that SAST reports are understandable to the development team.

The report can hold;

• file,
• line,
• function,
• vulnerability,
• severity,
• recommendation

information.

Executive SAST Report

For senior management, instead of technical code-line detail;

• total applications,
• critical vulnerabilities,
• remediation trend,
• open risks,
• security coverage

can be summarized.

Ticketing Integration

SAST findings can be transferred automatically into ticketing systems such as;

• Jira,
• Azure Boards,
• ServiceNow

and similar platforms.

Vulnerability Ownership

Each finding can be assigned to the relevant developer or application owner.

Remediation SLA

Remediation timeframes can be set according to risk level.

For example:

Critical → 7 days

High → 30 days

Medium → 60 days

can be configured according to corporate policy.

Remediation Tracking

Findings can be tracked centrally until they are closed.

Retest

After the developer completes remediation, the relevant code can be re-analyzed to verify the vulnerability has been resolved.

Delta Scan

Rather than analyzing the entire source code on every scan, only the changed sections can be scanned.

This approach can shorten developer feedback time.

Baseline Scan

At the first stage, the whole code base can be scanned to establish the existing security debt.

Legacy Application SAST

Applications in use for many years can produce thousands of security findings.

In such cases, resolving all findings at once may not be possible.

SecureSys can build a risk-based remediation roadmap.

Security Technical Debt

Software developed for a long time without security controls can accumulate security technical debt.

SAST can help measure that debt.

Application Security Maturity

An organization's source code security maturity can be assessed under the;

• secure coding,
• SAST,
• SCA,
• DevSecOps,
• remediation,
• metrics

headings.

Secure Code Review Checklist

For critical projects, technology-specific manual code review checklists can be created.

OWASP Top 10 and Source Code Analysis

SAST controls can be mapped to OWASP Top 10 risks.

For example, risk areas such as;

• Injection,
• Cryptographic Failures,
• Security Misconfiguration,
• Identification and Authentication Failures

can be analyzed.

OWASP ASVS

The OWASP Application Security Verification Standard can be used in source code and architecture reviews of critical web applications.

OWASP API Security

OWASP API Security risks can be taken into account in API source code analysis.

CWE Mapping

SAST findings can be mapped to Common Weakness Enumeration – CWE identifiers.

This allows security problems to be classified in a standard way.

The Difference Between CVE and CWE

CWE defines types of software weakness.

CVE, by contrast, refers to specific known vulnerability records.

SAST mostly detects coding weaknesses of the CWE type.

SCA, meanwhile, analyzes dependencies carrying CVEs.

NIST SSDF and SAST

The NIST Secure Software Development Framework recommends integrating secure software development processes into the SDLC.

SAST can be used as one of the technical implementations of that approach.

ISO/IEC 27001 and Source Code Security

The secure development and vulnerability management processes within ISO/IEC 27001 can be supported by source code analysis.

PCI DSS and Source Code Analysis

In payment applications, secure coding and application security controls matter within PCI DSS requirements.

SAST can support these processes technically.

KVKK and Source Code Security

Vulnerabilities in software processing personal data can lead to a data breach.

Source code analysis supports a secure development approach in applications processing personal data.

DORA and Software Security

Secure development and vulnerability management of critical applications used in the financial sector matter for operational resilience.

SAST and DevSecOps

SAST is one of the core security tools of a modern DevSecOps pipeline.

However, it is not sufficient on its own.

A mature DevSecOps model can use the;

SAST + SCA + Secret Scan + IaC Scan + Container Scan + DAST + Pentest

controls together.

SAST and Software Supply Chain Security

While SAST analyzes the source code the organization writes, Software Supply Chain Security also assesses third-party dependencies and the build chain.

These two areas must be managed together.

SAST and SBOM

SAST and SBOM serve different purposes.

SAST: Source code weaknesses.

SBOM: Inventory of the software components in use.

Both data sets can be shown together on a central Application Security dashboard.

SAST and Platform Engineering

On an Internal Developer Platform, SAST can be made a default service for all developer teams.

SAST can run automatically within the Golden Path.

Secure by Default Development

For every newly created repository, automatic;

• SAST,
• SCA,
• secret scanning,
• branch protection

can be enabled.

Source Code Access Security

Source code is one of an organization's most important intellectual property assets.

Repository access must be protected with;

• MFA,
• RBAC,
• least privilege,
• audit

controls.

Private SAST Environment

Where it is not appropriate for source code to leave the organization, SAST can be deployed entirely on-premise or in a private cloud.

Air-Gapped SAST

In defence, public sector or critical system projects, source code can be analyzed in an environment without internet connectivity.

SecureSys can build an air-gapped SAST architecture.

Source Code Analysis Inside the Red Network

In critical software development environments, a;

Private Git → Private SAST → Private SCA → Private CI/CD

architecture can be built within the Red Network.

Source Code Confidentiality

Before uploading source code to third-party SaaS SAST systems;

• data residency,
• source code confidentiality,
• vendor access

must be evaluated.

On-Premise SAST

On-premise SAST platforms can be deployed so that source code remains entirely within the organization.

Cloud SAST

In more flexible projects, cloud-based SAST services can be used.

Hybrid SAST

Some repositories can be analyzed in a private environment while less critical projects use cloud services.

SAST Tool Integrations

SecureSys can support the integration of different SAST platforms according to the organization's existing licensing and technology preferences.

The core goal here is to establish a sustainable Application Security process rather than to promote a particular tool.

SonarQube and Code Quality

Code quality platforms such as SonarQube can provide visibility into;

• code smell,
• duplication,
• maintainability,
• some security issues

areas.

However, for comprehensive AppSec requirements they may need to be evaluated alongside specialized SAST technologies.

Application Security Dashboard

Output from multiple SAST, SCA and security tools can be shown on a central dashboard.

Security Finding Correlation

The same vulnerability being reported repeatedly by different tools can be prevented.

Vulnerability Deduplication

By normalizing findings, duplicate results can be reduced.

Application Risk Score

For each application, a central risk score can be produced from;

• SAST,
• SCA,
• DAST,
• pentest,
• criticality

data.

Security Coverage

The percentage of applications within the organization covered by SAST can be measured.

For example:

SAST Coverage: 90%

SAST KPIs

Measurable metrics can include;

• number of applications scanned,
• Critical/High finding count,
• Mean Time to Remediate,
• false positive rate,
• security gate failures,
• scan coverage

and similar.

Mean Time to Remediate – MTTR

The time from detection of a vulnerability to completion of remediation can be measured.

Vulnerability Trend

The number of vulnerabilities newly discovered and closed each month can be compared.

Developer Security Scorecard

An application-level security scorecard can be presented to development teams.

The aim is not to penalize teams but to make security improvement measurable.

Integration with Secure Coding Training

SAST results can be used to personalize developer training.

For example, if SQL Injection problems keep appearing in a team, dedicated secure coding training can be planned for those developers.

Just-in-Time Security Training

While a developer reviews a finding, short training content about that specific vulnerability can be shown directly.

AI Generated Code Security

Growing use of AI coding assistants makes source code analysis more important.

Code produced by AI can also contain;

• insecure API,
• vulnerable pattern,
• hardcoded secret,
• weak authentication

issues.

For this reason:

AI Generated Code → Developer Review → SAST → SCA → Security Gate

should be applied as a model.

AI Code Review

AI-based tools can accelerate the code review process.

However, security-critical decisions should not be left to AI output alone.

AI-supported analysis and human expert assessment can be used together.

Secure AI-Assisted Development

When using AI coding assistants, it is not only code security that must be evaluated but also;

• source code privacy,
• prompt leakage,
• credential exposure,
• IP risk

considerations.

LLM Application Source Code Security

Alongside classic web application security risks, the source code of LLM and Generative AI applications carries new risks such as;

• model API key,
• prompt template,
• tool authorization,
• data source access

exposures.

AI Agent Source Code Security

Agentic AI systems can include tool calling and highly privileged API integrations.

During code review;

• tool permissions,
• authorization,
• human approval,
• action boundaries

must be evaluated with particular care.

The SecureSys Source Code Analysis Process

1. Application and Repository Inventory

The applications, languages and repositories in scope are identified.

2. Technology Analysis

Frameworks, dependency managers and build systems are determined.

3. First SAST Scan

A baseline security analysis is carried out on the source code.

4. SCA and Secret Scanning

Third-party component and sensitive credential risks are analyzed.

5. Expert Validation

Critical findings are reviewed manually.

6. Risk Prioritization

Findings are ranked according to application criticality and exploitability.

7. Technical Reporting

Code-level remediation guidance is prepared for the development team.

8. Executive Report

Total risk and application security posture are summarized.

9. Remediation Support

Technical support can be provided to help developer teams resolve findings.

10. Retest

Remediated findings are checked again.

11. CI/CD Integration

SAST processes are moved into the automated pipeline.

12. Continuous Management

Continuous analysis can be applied through a SAST as a Service or Managed SAST model.

Why the SecureSys Source Code Analysis and SAST Service?

A SAST tool producing thousands of findings does not, on its own, make software secure.

The real value lies in managing the;

Detection → Validation → Prioritization → Remediation → Retest → Automation

chain correctly.

SecureSys treats source code analysis not merely as automated scanner output, but as part of DevSecOps, penetration testing and software supply chain security processes.

The aim is to establish a workable security model between an organization's security teams and its developer teams.

Our approach:

Find Earlier → Validate Better → Fix Faster → Prevent Recurrence

is based on this principle.

Frequently Asked Questions

What is SAST?

Static Application Security Testing is the method of analyzing application source code for vulnerabilities without running it.

Are source code analysis and SAST the same thing?

SAST is the automated component of source code analysis. Source code analysis can also cover manual Secure Code Review work.

Does SAST replace penetration testing?

No. SAST analyzes source code weaknesses; penetration testing evaluates real attack paths in the running application.

Can SAST be integrated into the CI/CD pipeline?

Yes. SAST can be run automatically at the commit, Pull Request, build or release stage.

Does SAST send source code outside the organization?

That depends on the product used. Where source code confidentiality is critical, on-premise or air-gapped SAST architectures can be used.

Which programming languages does SAST support?

Depending on the platform used, Java, C#, JavaScript, TypeScript, Python, PHP, Go, Kotlin, Swift and many other languages can be analyzed.

What is the difference between SAST and SCA?

SAST analyzes the source code the organization writes, while SCA analyzes third-party and open source dependencies.

Does SAST produce false positives?

Yes. That is why validation of High and Critical findings by expert analysts matters.

Can mobile application source code be analyzed?

Yes. Android and iOS source code can be analyzed with SAST and manual code review methods appropriate to the technology.

Should AI-generated code go through SAST?

Yes. AI-generated code must pass the same security controls as any other source code.

Strengthen Your Source Code Security During Development with SecureSys SAST

Detecting critical vulnerabilities during development rather than after the application reaches production can improve both security and software delivery speed.

With SecureSys Source Code Analysis and SAST Services, you can manage the;

Source Code → SAST → SCA → Secret Scanning → Expert Validation → Remediation → CI/CD Security Gate

processes under a single Application Security model.

Instead of sending your development teams hundreds of scanner alerts, you can prioritize genuine risks, provide code-level remediation guidance, and stop recurring security mistakes through DevSecOps automation while the code is still being written.

Have your source code security level assessed, move your SAST processes into the CI/CD pipeline, and make security a natural part of software development.