What is application vulnerability scanning?
Application vulnerability scanning is the automated process of detecting security weaknesses in software applications. This means specialized tools continuously analyze your apps, APIs, and cloud workloads to find flaws that attackers could exploit.
These automated tools work differently than manual security reviews. They compare your application's code, configurations, and runtime behavior against databases of known vulnerabilities and security best practices. The goal is simple: find and fix security holes before hackers can use them against you.
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Why application vulnerability scanning matters in modern environments
The shift to cloud-native architectures has fundamentally changed how you need to think about application security. Traditional perimeter-based security no longer works when your applications are distributed across multiple clouds, containers spin up and down dynamically, and infrastructure is defined as code.
Modern applications face unique challenges that make vulnerability scanning essential. Cloud environments introduce new attack vectors through misconfigured storage buckets, exposed APIs, and overly permissive identity policies. The speed of DevOps means code ships faster than ever, potentially introducing vulnerabilities at an unprecedented pace.
Here's the real problem: individually minor issues can combine to create critical attack paths. For example, a medium-severity SQL injection vulnerability becomes critical when that application runs with admin database credentials, is exposed to the internet, and connects to customer payment data. This interconnected risk is why modern scanning must understand context, not just identify individual flaws.
Attack path focus: Rather than chasing individual CVEs in isolation, modern vulnerability management focuses on attack paths—chains of exposures that attackers can exploit to reach critical assets. For example, an attacker might exploit a medium-severity vulnerability in a web application, use that foothold to access cloud credentials, then leverage overly permissive IAM roles to reach production databases. Effective scanning must identify these multi-step paths, not just individual weaknesses.
What are Application Vulnerabilities? Types & Prevention Strategies
Application vulnerabilities are security weaknesses in software code, design, or configuration that attackers can exploit to compromise systems or data.
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Types of application vulnerability scanning
Understanding the different scanning approaches helps you build comprehensive coverage across your application lifecycle. Each type of scanner is designed to find specific kinds of weaknesses at different stages of development and deployment.
Static Application Security Testing (SAST) analyzes source code without executing the application, catching vulnerabilities early in development like hardcoded secrets or insecure coding patterns.
Dynamic Application Security Testing (DAST) tests running applications from the outside, simulating real attacks to find runtime vulnerabilities like authentication bypasses or injection flaws. This approach doesn't need access to the source code, making it valuable for testing third-party applications or when source code is unavailable.
Interactive Application Security Testing (IAST) combines static and dynamic approaches by instrumenting applications to analyze code execution paths during testing. IAST agents monitor application behavior in QA or pre-production environments, providing real-time feedback about vulnerabilities as code executes through test scenarios.
Software Composition Analysis (SCA) identifies vulnerabilities in third-party libraries and dependencies that make up modern applications. This is crucial since most apps are built using numerous open-source components.
Infrastructure as Code (IaC) Scanning analyzes Terraform templates, AWS CloudFormation, and Kubernetes manifests for security misconfigurations before deployment. This prevents security gaps from ever reaching your production environment.
Container Image Scanning examines container images for vulnerable packages, misconfigurations, and embedded secrets across all layers. This is essential for securing the building blocks of your containerized applications.
API Security Testing specifically targets REST, GraphQL, and gRPC APIs for authentication issues, excessive data exposure, and injection vulnerabilities. APIs are a primary target for attackers because they expose business logic and data directly to external consumers, making specialized testing essential for modern application security.
Here's a quick comparison to help you choose the right scanning approach for each stage:
| Scanning Type | What It Finds | What It Runs | Best For | Typical Owner | Limitations |
|---|---|---|---|---|---|
| SAST | Coding flaws, hardcoded secrets | Source code, IDE, CI/CD | Early detection, compliance | Developers, AppSec | High false positives, no runtime context |
| DAST | Runtime vulnerabilities, config issues | Running applications | Production-like testing | QA, Security | Requires deployed app, limited code visibility |
| IAST | Code execution vulnerabilities | Instrumented test environments | Accurate detection with context | AppSec, QA | Requires instrumentation, not for production |
| SCA | Vulnerable dependencies, licenses | Source code, build systems | Open-source risk management | Developers, Legal | Doesn't catch custom code flaws |
| IaC Scanning | Infrastructure misconfigurations | IaC templates, CI/CD | Preventing cloud security gaps | DevOps, CloudOps | Only catches config issues, not runtime |
| Container Scanning | Image vulnerabilities, malware | Container registries, runtime | Container security | DevOps, Security | Needs continuous scanning for new CVEs |
How application vulnerability scanning works
The scanning process follows a systematic workflow designed to identify, validate, and prioritize security issues across your applications. This automated process is far more efficient than manual testing and provides the continuous coverage you need for modern development.
Discovery and inventory phase: Scanners first map all application assets including endpoints, APIs, dependencies, and infrastructure components. This creates a comprehensive inventory for analysis.
Scanning and analysis phase: Tools probe applications using various techniques—pattern matching for SAST, fuzzing for DAST, or behavioral analysis for runtime scanning. Each method is designed to uncover different types of vulnerabilities.
Vulnerability detection phase: Identified issues are matched against vulnerability databases like CVE and OWASP patterns to classify security weaknesses. This helps categorize the types of risks present in your environment.
Context enrichment phase: Modern scanners add cloud context—understanding if vulnerable applications are internet-exposed, have access to sensitive data, or connect to critical systems. This is what separates basic scanning from truly effective vulnerability management.
Risk prioritization phase: Vulnerabilities are scored based on severity, exploitability, and business impact to focus remediation efforts. Modern prioritization augments CVSS scores with exploit signals from CISA's Known Exploited Vulnerabilities (KEV) catalog, EPSS (Exploit Prediction Scoring System) likelihood models, and environmental context like internet exposure and data sensitivity.
Validation phase: Advanced scanners validate exploitability through reachability analysis (checking if vulnerable code paths are actually called), runtime evidence (confirming vulnerable libraries are loaded), and environmental checks (verifying if exploitation prerequisites exist). This reduces false positives by confirming vulnerabilities are exploitable in your specific configuration.
Remediation guidance phase: Actionable fix recommendations are provided, often with code snippets or configuration changes. This empowers your team to resolve issues quickly without guesswork.
Bidirectional traceability phase: Advanced platforms trace vulnerabilities from running cloud workloads back to the originating source code repository, commit, and developer. This enables you to fix the root cause in code rather than just patching deployed instances. For example, when a vulnerable library is detected in production containers, traceability shows which microservices use it, which repositories contain it, and which teams own those repositories—accelerating remediation from weeks to days.
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Key capabilities and evaluation criteria
When evaluating application vulnerability scanning solutions, focus on capabilities that directly address modern security challenges. A simple CVE scanner is no longer enough—you need a tool that provides deep context and integrates seamlessly into your workflows.
Comprehensive coverage across technologies: Support for multiple programming languages, frameworks, cloud services, and deployment models including serverless and containers. Your scanner needs to work with everything you use.
Agentless scanning capabilities: Prefer agentless methods for cloud workload and infrastructure scanning to reduce operational overhead and increase coverage across ephemeral resources. Note that application-level testing like SAST requires access to source code repositories, while IAST needs runtime instrumentation in test environments.
Cloud-native context awareness: Understanding of cloud permissions, network exposure, and data flows to identify toxic combinations. This is the only way to see true attack paths in your environment.
Developer-friendly integration: Native integration with IDEs, CI/CD pipelines, and developer workflows to enable shift-left security. Security should be a natural part of development, not a roadblock. Tools that provide inline feedback in VS Code, GitHub pull requests, and Jenkins pipelines see higher developer adoption than those requiring context switching.
Context-driven prioritization: Combine vulnerability severity with cloud context—network exposure paths, identity permissions, and sensitive data access—to identify exploitable attack paths. For example, a medium-severity vulnerability in an internet-exposed application with admin database credentials becomes critical, while the same vulnerability in an isolated development environment remains low priority. This approach reduces remediation queues by 80% compared to CVSS-only prioritization.
Low false positive rates: Accurate detection with validation to avoid alert fatigue and wasted remediation efforts. Your team needs to trust the findings they receive.
Automated remediation guidance: Specific, actionable fix recommendations with code examples and one-click fixes where possible. This accelerates your mean time to remediation.
Compliance mapping: Automatic mapping to common frameworks including SOC 2, ISO 27001, PCI DSS (requirements 6.3 and 6.5), HIPAA, NIST 800-53, NIST SSDF, and OWASP Top 10. This simplifies compliance reporting by showing which vulnerabilities violate specific control requirements.
What is application vulnerability management?
Application vulnerability management is a continuous process of discovering, assessing, prioritizing, and remediating security weaknesses in your software code, APIs, and dependencies across the entire development lifecycle.
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Implementation challenges and best practices
You'll face several hurdles when implementing application vulnerability scanning. However, with the right strategies and tools, you can effectively manage these challenges.
Challenge: Alert fatigue from overwhelming vulnerability counts
Implement risk-based prioritization focusing on exploitable vulnerabilities with actual business impact. Prioritize vulnerabilities that meet multiple criteria: listed in CISA's Known Exploited Vulnerabilities (KEV) catalog, have public exploit code available, affect internet-exposed services, provide access to sensitive data (PII, payment info, credentials), or exist in applications with elevated cloud permissions (admin roles, cross-account access).
Challenge: Lack of developer adoption and security friction
Integrate scanning into existing developer workflows and IDEs. Provide developers with clear ownership and actionable remediation guidance to fix issues without extensive security expertise. Implement automatic ownership mapping that assigns vulnerabilities to the correct team based on code repository ownership, cloud resource tags, or service ownership metadata. This eliminates the manual triage process where security teams spend hours determining who should fix each issue.
Challenge: Incomplete coverage across hybrid environments
Deploy agentless scanning that works across cloud, on-premises, and containerized environments. Ensure scanning covers the entire application lifecycle from code to runtime.
Challenge: Manual correlation across multiple security tools
Consolidate to platforms that provide unified visibility across all security domains. Automate vulnerability correlation with infrastructure and identity context.
Challenge: Keeping pace with rapid deployment cycles
Embed scanning in CI/CD pipelines with automated policy enforcement. Implement graduated policies: fail builds on critical vulnerabilities in KEV catalog, block deployments for high-severity issues in internet-exposed services, warn on medium-severity findings, and run full scans on main branch while doing incremental scans on feature branches. Add exception workflows so teams can document accepted risks with expiration dates rather than disabling checks entirely.
Challenge: Managing vulnerability noise from third-party components
Generate and maintain Software Bill of Materials (SBOM) for all applications to create an accurate inventory of components. Use Vulnerability Exploitability eXchange (VEX) documents from vendors to identify which CVEs don't affect your specific usage of a library. For example, if a vulnerability exists in a database driver's connection pooling feature but your application uses single connections, VEX documents can mark that CVE as not applicable, reducing your remediation queue.
Platform consolidation advantage: Organizations using separate tools for SCA, SAST, IaC scanning, container scanning, and cloud security typically face tool sprawl—managing 5-10 security products with different interfaces, policies, and data models. This fragmentation increases mean time to remediation by 3-5x because teams must manually correlate findings across tools. Unified platforms that combine code security, cloud security, and runtime protection with a single policy engine and security graph reduce operational overhead by 60% while improving detection accuracy through cross-domain correlation.
Wiz's approach to cloud-native application vulnerability management
Wiz Unified Vulnerability Management (UVM) transforms application vulnerability scanning by bringing together code, cloud, and runtime context into a single platform. This unified approach moves beyond traditional point solutions to provide complete visibility across your entire application security posture—from source code to production workloads.
Wiz UVM combines multiple scanning capabilities that traditionally required separate tools. Wiz Code integrates SCA directly into developer workflows, scanning dependencies in IDEs and CI/CD pipelines to prevent vulnerabilities from reaching production. Wiz Cloud provides agentless vulnerability scanning across all cloud workloads including VMs, containers, and serverless functions without performance overhead or operational complexity.
The Wiz Security Graph correlates vulnerabilities with cloud context like network exposure, identity permissions, and data access to surface toxic combinations that represent real attack paths. The Wiz Runtime Sensor uses lightweight eBPF-based instrumentation to validate which vulnerabilities are actually exploitable in production environments. By observing actual library usage and code execution paths, it reduces false positives by up to 95% and focuses remediation on vulnerabilities that pose real risk.
Wiz UVM's bidirectional traceability connects vulnerabilities found in running workloads back to the specific code commit and developer, accelerating remediation workflows from weeks to days. Attack path analysis shows how application vulnerabilities combine with misconfigurations and excessive permissions to create exploitable chains leading to critical assets—giving you the context needed to prioritize what matters most.
Ready to transform application vulnerability management with unified code-to-cloud visibility? Request a demo to see how Wiz UVM delivers comprehensive vulnerability insights with the context you need for faster, more effective remediation.
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