Dependency Scanning Tools: Compare Top Security Solutions

A single vulnerable dependency buried five layers deep in your project can expose your entire application to attack. Most developers know they’re using third-party packages, but few realize their code is often 70-90% open source, with each library pulling in dozens more through transitive dependencies. Dependency scanning tools automate the hunt for security flaws and license risks hiding in this sprawling supply chain. This guide compares five proven solutions, from GitHub’s free Dependabot to enterprise platforms like Black Duck, so you can pick the scanner that fits your team’s workflow and risk tolerance.

What Dependency Scanning Tools Do and Why Your Software Needs Them

Dependency scanning tools check the third-party libraries your app uses against known vulnerabilities and licensing issues. They look at both the packages you explicitly installed and the ones those packages pull in, giving you visibility across your entire software supply chain. These tools plug into package managers like npm, Maven, pip, and NuGet to scan your dependency files and flag problems when they pop up.

This isn’t optional anymore. In 2024, 84% of codebases had at least one known open source vulnerability. Even worse, 74% contained high-risk flaws that could actually lead to breaches or system compromises. One in eight open source downloads now ships with a security problem. Modern software is 70-90% open source according to the 2020 FOSS Contributor Survey by Linux Foundation and Harvard. When most of your code comes from external sources, you’re trusting thousands of third-party maintainers with your security.

The tools above take different approaches. Understanding which capabilities you’ll actually use helps you pick the right scanner without paying for features that sit unused.

Understanding Software Composition Analysis and Dependency Management

Software Composition Analysis covers more ground than just dependency scanning. SCA tools analyze complete component profiles, tracking who maintains them, how often they’re updated, community health, security posture. Dependency scanning zeroes in on security and compliance, checking each component against vulnerability databases and license registries. Think of SCA as the full inventory of what’s in your software, with dependency scanning as the risk assessment layer.

Transitive dependencies create the sneakiest risks. When you run npm install, pip install, or mvn package, you’re not just grabbing what you specified. You’re inheriting everything those packages depend on, and everything their dependencies depend on, often 4-5 levels deep. SCA tools catch vulnerabilities in transitive dependencies you never directly installed or even knew existed. A security flaw in some logging utility buried five layers down can compromise your entire application.

SBOM generation has become a regulatory requirement. The US Executive Order on Improving the Nation’s Cybersecurity mandates Software Bill of Materials for federal procurement, and private companies are adopting the same standards fast. Modern scanners generate SBOMs in formats like CycloneDX or SPDX, creating machine-readable inventories of every component. These documents track what’s installed now and create a permanent record you can check against future vulnerability disclosures years after deployment.

Core Capabilities That Define Effective Dependency Scanning Solutions

Not all scanners offer the same depth or breadth. The gaps between basic tools and comprehensive platforms often determine whether you catch critical vulnerabilities before production or discover them through a security incident.

Vulnerability prioritization uses standardized databases and scoring to help teams focus on what matters most. The National Vulnerability Database and GitHub Security Advisory Database provide CVE identifiers and descriptions, while CVSS scoring assigns severity ratings from 0 to 10. Dependency-Track detected 302 vulnerabilities across 120 components and calculated a total risk score of 1238 based on aggregated CVSS metrics. This cumulative approach shows overall project risk rather than just counting findings. A project with 50 low-severity issues might pose less actual risk than one with 5 critical vulnerabilities.

Reachability analysis cuts through false positive noise. Modern scanners check whether vulnerable code actually gets called in your application, not just whether a vulnerable library exists in your dependency tree. If a package contains a security flaw in a function your code never invokes, the actual risk is way lower than a vulnerability in code that executes on every request. This analysis reduces alert fatigue by focusing on genuine threats to your specific codebase rather than theoretical risks.

Effective prioritization considers:

• CVSS severity score from 0 to 10
• Exploit availability showing active attacker use
• Reachability in your codebase
• Production versus development dependencies
• Regulatory and compliance impact

Configurable severity thresholds let you enforce different policies for different contexts. Snyk CLI can fail builds only for high or critical vulnerabilities while allowing lower severity issues to pass with warnings. This prevents blocking development on minor findings that pose minimal risk while ensuring dangerous vulnerabilities never reach production. The threshold configuration turns scanning from a reporting tool into active enforcement integrated directly into your build.

Commercial Dependency Scanning Platforms and Their Distinguishing Features

Commercial platforms compete on developer experience, automation, and enterprise features rather than basic vulnerability detection. Checking dependencies against CVE databases is table stakes. The real differences are in how tools present findings, integrate into workflows, and reduce manual work.

Snyk

Snyk emphasizes developer experience through tools that shift security earlier. The Snyk Advisor website helps you pick better-maintained packages before adding them to projects, showing security history, maintenance frequency, community health. IDE integration provides contextual security info directly in VS Code, IntelliJ, and other editors as you write code. Pull request commenting shows exactly which dependency changes introduced new vulnerabilities, and the free tier makes these capabilities accessible to individual developers and small teams.

Mend (formerly WhiteSource)

Mend focuses on automated remediation that minimizes manual work. The Renovate bot provides highly configurable dependency updates across GitHub, GitLab, and Bitbucket, going beyond alerts to actually generate pull requests with fixes. In testing with a Node.js repository, Mend flagged 15 security vulnerabilities including critical CVEs and created automated PRs with the exact version changes needed. The checkbox controls in PR descriptions let you manage automerge behavior without leaving GitHub, reducing context switching and making security fixes feel like natural parts of code review.

Synopsys Black Duck

Black Duck specializes in enterprise scenarios and M&A due diligence where comprehensive component discovery matters more than development speed. The platform maintains a proprietary knowledge base covering millions of components with extensive license information. Fortune 500 adoption in regulated industries like finance, automotive, and healthcare demonstrates Black Duck’s strength in audit trails and comprehensive documentation needed for compliance. When a bank acquires a fintech startup or an automotive manufacturer evaluates a software vendor, Black Duck provides the component and license discovery that legal teams require.

GitHub Advanced Security

GitHub Advanced Security uses native platform advantages for zero-friction security. Dependabot automatically opens pull requests with CVE information, severity ratings, changelog details, and remediation guidance without any setup. The integration with existing GitHub workflows means scanning happens automatically for every repository without developers adopting new tools. GitHub users get dependency scanning free in public repositories, and Advanced Security extends this to private repos with features like secret scanning and code analysis.

Enterprise features across commercial platforms include SSO for centralized authentication, RBAC for team-based access control, and centralized policy enforcement that applies security standards consistently. Pricing models range from per-developer seats to consumption-based scanning volumes.

Open Source Alternatives and Their Operational Trade-offs

Open source scanners provide viable alternatives for teams willing to accept operational responsibilities in exchange for avoiding vendor lock-in and licensing costs. The main trade-offs involve maintenance burden, database updates, and support availability. Community tools offer full transparency and customization but require in-house expertise.

OWASP Dependency-Check

OWASP Dependency-Check is completely free with no restrictions or feature limitations. The operational characteristic that matters most is manual vulnerability database updates. The tool downloads data from the National Vulnerability Database, and you need to manage when updates occur. Maven and Gradle plugin integration provides convenience for Java projects. The tool generates reports in HTML, JSON, CSV, and XML for integration with ticketing systems and dashboards. In testing with a Java project, Dependency-Check detected 8 vulnerabilities across 3 dependencies and produced detailed HTML reports with CVE identifiers and severity ratings.

Anchore Syft and Grype

Anchore takes a container-specialized approach with Syft generating Software Bills of Materials and Grype performing vulnerability matching against those SBOMs. This two-stage design gives you flexibility to generate component inventories once and scan them multiple times, or share SBOMs with customers. Container scanning depth showed when Grype identified 63 vulnerabilities including multiple instances of CVE-2021-44228 Log4Shell across log4j-core and log4j-api versions in different container layers. Written in Go for performance, both tools execute quickly enough for CI/CD integration without causing build delays.

OSV-Scanner

OSV-Scanner uses the Open Source Vulnerability database rather than relying solely on NVD. This provides potentially better coverage for modern languages like Rust and Go where the community contributes vulnerability data directly to OSV. Community-contributed information often appears in OSV before making it into the formal CVE/NVD process, giving you earlier warning. The focus on broader ecosystem support makes it valuable for polyglot environments where traditional NVD-based scanners might miss language-specific vulnerabilities.

The primary cost of open source tools involves database updates, version upgrades, and self-managed infrastructure. You need processes for keeping vulnerability data current, upgrading scanner versions when fixes or features are released, and maintaining the servers or CI runners where scanning executes.

Implementing Dependency Scanning in CI/CD Pipelines and Development Workflows

Dependency scanning must run at two critical points: during active development when new code is committed, and in CI/CD pipelines before deployment. Automated scanning on every code change catches vulnerabilities immediately when dependencies are added or updated, while pre-deployment scanning provides a final gate. Manual periodic scans fail to catch vulnerabilities quickly enough. By the time someone remembers to run a scan, vulnerable code may have shipped.

Platform-specific integration varies. GitHub Actions workflows can invoke Snyk, Dependency-Check, or other scanners through marketplace actions. GitLab CI provides pipeline template includes that add scanning jobs with minimal config. Jenkins uses plugins where tools provide dedicated configuration UIs. Azure DevOps uses pipeline tasks from the marketplace, CircleCI uses orbs, Bitbucket Pipelines uses pipe components, and Bamboo typically requires custom scripts. The integration quality determines whether scanning feels natural or bolted on.

For more details on security tool integration patterns, check out Understanding CI/CD Integration for Security Tools.

Performance optimization through incremental scanning makes the difference between sub-minute checks and pipeline delays that frustrate developers. Modern tools analyze only changed dependencies rather than rescanning the entire project. If a build changes one package in a project with 200 dependencies, incremental scanning checks just that one package and its transitive dependencies instead of revalidating all 200.

Integration practices that balance security with productivity:

• Scan on every commit and pull request to catch issues immediately
• Use incremental scanning for performance
• Implement policy-based build gating that fails builds for violations
• Configure severity thresholds for build failures
• Enable reachability analysis to reduce false positives
• Set up automated notifications to Slack channels or ticketing systems
• Maintain separate policies for development versus production branches

Balancing rigor with workflow efficiency prevents alert fatigue and builds that fail so frequently developers stop paying attention. If every minor vulnerability blocks development, teams start creating exceptions or ignoring results. The goal is catching genuinely dangerous vulnerabilities without treating every theoretical risk as a crisis.

Package Manager Coverage Across Programming Languages and Ecosystems

Comprehensive language coverage matters for polyglot environments combining Node.js frontends, Java backends, Python data processing, and Go microservices. A scanner that only understands npm packages misses vulnerabilities in the rest of your stack, creating security blind spots.

Language-specific scanners like Retire.js for JavaScript and Safety for Python often maintain more current advisory databases than general-purpose tools. The specialized tools monitor ecosystem-specific disclosure channels, security mailing lists, and project issue trackers that might not immediately feed into broader CVE databases. This means ecosystem-focused scanners can alert you about vulnerabilities days or weeks before they appear in multi-language platforms.

OSV-Scanner provides enhanced coverage for modern languages where community-contributed data supplements official CVE information. The Open Source Vulnerability database aggregates security advisories from language-specific sources, GitHub Security Advisories, and traditional CVE feeds. This helps ensure that vulnerabilities disclosed through language community channels don’t slip through while waiting for formal CVE assignment.

License Compliance Detection and Policy Enforcement

Scanners track both security vulnerabilities and legal risks through automated license detection. Legal exposure from improperly used open source licenses can be just as damaging as security vulnerabilities, potentially leading to IP disputes, forced code disclosure, or contract violations. When FOSSA scanned 77 dependencies and identified 8 license types with 2 critical compliance issues in NPM project testing, it showed that license problems are common and often invisible without automated detection.

License categories carry different legal implications. Permissive licenses like MIT and Apache 2.0 allow broad usage including in proprietary commercial software with minimal restrictions. Copyleft licenses like GPL variants require that derivative works be distributed under the same license, which can force disclosure of proprietary code. Commercial and proprietary licenses may restrict usage, require payment, or impose incompatible terms. Understanding which licenses appear in your dependency tree prevents legal surprises during product launches or M&A due diligence.

The comprehensive license database maintained by tools like WhiteSource and Black Duck covers millions of components with curated information verified by legal experts. Black Duck’s design specifically addresses Fortune 500 compliance needs where license failures can derail product launches or acquisitions.

Common compliance use cases:

• Preventing GPL in proprietary software where copyleft would force source disclosure
• M&A due diligence requiring complete license inventories
• Regulatory audit requirements in industries with strict documentation needs
• IP risk management identifying potential patent or licensing conflicts

Policy enforcement blocks builds automatically when forbidden licenses appear. You can configure rules that fail CI/CD pipelines if GPL-licensed packages are detected in proprietary applications, or require manual approval for any component using non-standard licenses. This prevents accidental inclusion of incompatible licenses rather than discovering them during legal review after development is complete.

Automated Remediation and Dependency Update Workflows

96% of known vulnerabilities have existing fixes available, typically requiring simple version updates rather than complex code changes. Most security issues in dependencies are resolved by upgrading to a patched version maintainers already released. The challenge isn’t finding fixes. It’s implementing them quickly enough that vulnerable code doesn’t linger in production for weeks or months.

Automated update bots like GitHub Dependabot and Mend’s Renovate monitor dependency files daily and generate pull requests when new versions become available. Dependabot is built directly into GitHub, requiring zero setup for repositories that opt in. It checks package files every day, identifies when newer versions exist, and opens pull requests with detailed information about what changed. Renovate provides highly configurable update automation across GitHub, GitLab, and Bitbucket with granular control over schedules, version ranges, and PR behavior. In some years, over 30% of all GitHub pull requests were opened by bots. That’s how much dependency maintenance has shifted to automation.

Configurable auto-merge capabilities allow update PRs to merge automatically when tests pass, creating fully hands-off dependency maintenance for well-tested projects. You can configure bots to automatically merge pull requests for patch-level updates in packages you trust, while requiring manual review for major version changes that might include breaking changes. The checkbox controls in Renovate PR descriptions let you enable or disable automerge on individual PRs without changing global configuration.

Automation practices that prevent update chaos:

• Robust test coverage before enabling auto-merge
• Scheduled update batching to avoid dozens of daily PRs
• Grouping related dependencies so frontend packages update together
• Semantic versioning constraints limiting auto-merge to patch and minor updates
• Breaking change detection requiring manual review for major version bumps

Combining scanning tools with update bots creates a complete workflow where scanners identify vulnerabilities and bots generate fix pull requests automatically. You don’t need separate processes for detection and remediation. The tools work together to find problems and propose solutions. The 30% of GitHub PRs opened by bots demonstrates this workflow across thousands of projects.

Supply Chain Security and Malicious Package Detection

Supply chain security concerns have escalated as attackers shift from finding vulnerabilities to deliberately creating them. Sonatype logged 245,032 malicious packages in 2023, a threefold increase within one year. These aren’t accidental security flaws. They’re packages intentionally created to steal credentials, install backdoors, or execute arbitrary code on developer machines and production servers. Traditional CVE-based scanning misses these threats entirely because malicious packages don’t have CVE identifiers until someone discovers them.

Log4Shell serves as the definitive case study of supply chain impact. CVE-2021-44228 affected thousands of teams despite completely secure application code because the exploit existed in a widely-used logging library. Applications that never directly installed log4j still contained it 3 or 4 levels deep in their dependency trees. The vulnerability’s severity and the number of affected applications showed that your code security is irrelevant if a critical dependency has a remotely exploitable flaw.

To learn more about comprehensive supply chain security strategies, check out Modern Supply Chain Security Practices.

Detection techniques for malicious packages go beyond CVE databases to identify suspicious patterns. Typosquatting identification catches packages with names similar to popular libraries but slight variations like “reqeusts” instead of “requests”. Suspicious maintainer change detection alerts when established packages suddenly transfer to new maintainers who immediately publish updates. Abnormal package behavior analysis flags executables, network connections, or file system access that don’t match the package’s stated purpose.

Supply chain security features that catch deliberate threats:

• Malicious package databases tracking known harmful components beyond CVE listings
• Maintainer reputation tracking showing ownership history and contributor patterns
• Package popularity analysis identifying suspicious packages with few downloads
• Dependency confusion detection preventing private package names from being hijacked
• Real-time threat intelligence receiving alerts when new supply chain attacks are discovered

Proactive defense through dependency selection guidance helps prevent supply chain issues before they enter your codebase. Tools like Snyk Advisor show package health metrics including security history, maintenance activity, and community adoption. Choosing well-maintained packages with active security response from trusted maintainers reduces risk more effectively than scanning alone.

Container and Cloud-Native Application Scanning

Containers package applications with all their dependencies into self-contained units that include application code, runtime libraries, and operating system packages. This bundling creates a unique scanning challenge because vulnerabilities can exist in the base OS layer, system libraries, or application dependencies. Traditional dependency scanners that only analyze package files miss vulnerabilities in the container’s base image or system-level components.

Trivy and Anchore Grype provide specialized container scanning that analyzes Docker images, filesystem layers, and both OS packages and application dependencies in a single scan. Written in Go for performance, these tools execute quickly enough for CI/CD integration without creating bottlenecks. Anchore Grype identified 63 vulnerabilities including multiple instances of CVE-2021-44228 Log4Shell across log4j-core and log4j-api versions in container image scanning. The detection of multiple Log4Shell instances across different layers shows how container scanning finds vulnerabilities that application-level scans would miss because they exist in base image layers built months earlier.

Infrastructure as Code scanning extends dependency analysis to Terraform modules, CloudFormation templates, and Kubernetes manifests. These infrastructure definitions often reference container images, Helm charts, or external modules that can contain vulnerabilities. Scanning infrastructure code alongside application code provides comprehensive coverage of the entire deployment pipeline.

Container scanning targets that comprehensive tools must cover:

• Base OS packages in Alpine, Ubuntu, Debian, or other base images
• Application dependencies installed via package managers
• Filesystem layers where vulnerabilities might exist in intermediate build stages
• Helm chart dependencies referenced by Kubernetes deployments

Kubernetes security for running workloads requires continuous monitoring beyond initial deployment scanning. Container images scanned six months ago might have new CVEs discovered since deployment. Tools with runtime scanning capabilities monitor running containers in Kubernetes clusters and alert when new vulnerabilities affect already-deployed workloads.

Reporting Capabilities and Dashboard Analytics for Security Teams

Centralized dashboards aggregate security findings across multiple projects and repositories, providing security teams with unified visibility instead of per-project silos. OX Security demonstrated this by providing end-to-end supply chain monitoring across repositories, registries, CI/CD pipelines, and runtime environments, aggregating and prioritizing 179 alerts in a tested implementation. Without centralized visibility, security teams struggle to understand overall organizational risk when findings are scattered across dozens of individual project reports.

Report formats need to accommodate different stakeholders and integration requirements. Dependency-Check generates reports in HTML for human review, JSON for programmatic processing, CSV for spreadsheet analysis, and XML for SIEM ingestion or ticketing system integration. Different audiences need different views. Executives want summary dashboards showing vulnerability trends, security teams need detailed vulnerability information with remediation guidance, and compliance auditors require complete component inventories with license documentation.

Real-time alerting through Slack, PagerDuty, and webhook notifications ensures security findings reach appropriate team members in the tools they already use. Integration with communication platforms means developers see security alerts in their team channels rather than logging into separate dashboards. PagerDuty integration can escalate critical findings to on-call engineers when high-severity vulnerabilities are detected in production. Webhook support allows custom integrations with internal notification systems or workflow automation platforms.

Key reporting features for organizational visibility:

• Vulnerability trending showing whether security posture is improving or degrading
• Compliance report generation for audits with SBOM exports and license documentation
• Audit trail maintenance tracking who acknowledged findings and what remediation actions were taken
• Executive summary dashboards providing high-level metrics without technical details
• Team-specific views filtered to each development team’s repositories

Role-based access control enables different teams to manage their applications independently while central security maintains oversight. Developers see findings for their projects and can acknowledge or remediate vulnerabilities within their scope. Security teams view aggregated dashboards showing vulnerability statistics, compliance posture, and trend analysis across all teams. This separation prevents information overload while ensuring appropriate visibility at each level.

Tool Selection Criteria for Different Organizational Sizes and Needs

Tool selection should match organizational maturity, available resources, and specific requirements rather than defaulting to feature-rich platforms that exceed actual needs. The right tool for a startup differs dramatically from what a Fortune 500 enterprise requires.

Individual Developers and Small Teams

Individual developers and small teams need free tier options with rapid setup measured in minutes. IDE integrations matter more than enterprise dashboards because developers want security feedback directly in their coding environment. GitHub Dependabot provides the easiest starting point for projects already on GitHub, requiring no setup beyond enabling the feature. Snyk’s free tier offers generous scanning limits for open source projects and small commercial teams. OWASP Dependency-Check works well for developers comfortable with command-line tools who want complete control without vendor relationships. The common thread is minimal operational overhead.

Startups and Growing Teams

Startups need to balance cost constraints with professional-grade capabilities. Tools requiring minimal dedicated security staff allow development teams to own security without hiring specialized roles. Automated workflows reduce manual work that steals development time. Aikido Security targets this segment with rapid setup and immediate value delivery. Snyk Team plans add collaboration features beyond the free tier while remaining affordable. Mend offers startup-specific programs with reduced pricing for early-stage companies. The selection criteria emphasize operational efficiency and cost-effectiveness during the critical growth phase.

Enterprise Organizations

Enterprise organizations require SSO integration with corporate identity providers, role-based access control for different teams and business units, policy enforcement that applies security standards consistently across hundreds of projects, audit trails showing all findings and remediation actions, SBOM generation for compliance and regulatory requirements, and centralized dashboards providing executive visibility. Black Duck addresses M&A due diligence with comprehensive license discovery. Sonatype Nexus Lifecycle provides curated vulnerability intelligence with near-zero false positives. OX Security offers end-to-end supply chain monitoring. Enterprise tools prioritize compliance, governance, and organizational visibility over individual developer convenience.

Total cost consideration must include both licensing fees and developer time. Sonatype Nexus Intelligence achieves near-zero false positives in component identification, potentially saving dozens of hours investigating and dismissing incorrect alerts. A tool with a higher licensing fee but better accuracy can cost less overall than a free tool that generates false positives requiring constant triage. Setup time creates similar hidden costs. Aikido’s minutes-to-value setup differs dramatically from Black Duck’s historically significant configuration requirements. Calculate the fully-loaded cost including implementation time, ongoing maintenance, and false positive management rather than just the license price.

Performance Optimization and Scan Frequency Considerations

Scan frequency must balance comprehensive security coverage with acceptable pipeline performance and developer experience. Scanning on every single commit provides maximum security but can slow builds and frustrate developers if scans take several minutes. The right balance depends on project size, dependency count, and risk tolerance.

Incremental scanning techniques analyze only changed dependencies instead of rescanning entire projects. When a developer updates one package in a project with 150 dependencies, incremental scanning validates just that package and its transitive dependencies rather than revalidating all 150. This optimization keeps scan times under 30 seconds for most projects even when full scans would take several minutes. Snyk scans typically complete in seconds due to incremental analysis and cached vulnerability data.

Scanning frequency recommendations:

• On every commit and pull request for new dependencies being added

Final Words

Dependency scanning tools aren’t optional anymore. With 84% of codebases containing vulnerabilities and modern apps running on 70-90% third-party code, these tools are your first line of defense.

Whether you pick a commercial platform like Snyk or Black Duck, or go open source with OWASP Dependency-Check, the key is getting scans running in your CI/CD pipeline this week, not next quarter.

Start simple. Scan on every commit. Fix critical issues first. Build from there.

The tools exist. The vulnerability databases are updating daily. Your dependencies won’t secure themselves.

FAQ

What is a dependency scanner?

A dependency scanner is an automated tool that analyzes your software’s third-party libraries and modules to detect security vulnerabilities and licensing issues. These tools examine both direct dependencies you explicitly install and transitive dependencies pulled in automatically, generating reports with vulnerability details and remediation guidance.

What’s the best software dependency scanner?

The best software dependency scanner depends on your specific needs: Snyk offers the strongest developer experience with IDE integration and free tiers for startups, OWASP Dependency-Check provides completely free open source scanning without vendor lock-in, and Black Duck delivers enterprise-grade license compliance for large organizations requiring audit trails and M&A due diligence capabilities.

What is the difference between Snyk and OSV scanner?

Snyk and OSV scanner differ primarily in their vulnerability data sources and commercial model: Snyk is a commercial platform with a free tier that uses proprietary vulnerability intelligence plus CVE databases, while OSV scanner is completely free and uses Google’s Open Source Vulnerability database, potentially offering better coverage for newer ecosystems like Rust and Go compared to traditional NVD-based tools.

What are the top 10 OWASP security risks?

The OWASP Top 10 represents the most critical web application security risks, including injection flaws, broken authentication, sensitive data exposure, XML external entities, broken access control, security misconfigurations, cross-site scripting, insecure deserialization, using components with known vulnerabilities (where dependency scanners help), and insufficient logging. Dependency scanning tools specifically address the risk of using components with known vulnerabilities by detecting outdated libraries.