Top 10 API Vulnerability Testing Tools (2026): Complete Guide for Securing Modern APIs

APIs now power critical revenue streams across finance, healthcare, and SaaS; everything from customer onboarding to payments to partner integrations. But as teams ship faster through microservices, GenAI-generated code, and constant integrations, most enterprises still struggle to test the sheer volume of APIs they expose. 

When vulnerability testing falls behind, API-led growth doesn’t translate into bottom-line results; instead, it leaks into compliance fines, integration delays, incident response costs, and production firefighting.

That’s why modern enterprises can’t afford to choose between security testing depth, frequency, and coverage. Pen-tests go deep but run quarterly, while scanners run often but skim the surface, neither scales. Tools like Levo unite all three, continuously validating real, exploitable risks across every environment and endpoint so API expansion remains secure, fast, and revenue-positive.

Manual pentesting still finds essential vulnerabilities, but it has not kept pace with continuous delivery or the rapid growth in API counts. Since full engagements consume large parts of security budgets, many organisations settle for infrequent assessments that provide only partial coverage.

The result is a widening gap between development and security. Enterprises now manage hundreds of APIs but rely on security efforts that secure only the top 1% of them, which is as good as none as even a single misconfigured API can cause massive data breaches.  

This is precisely where modern platforms like Levo change the equation. By automating deep API vulnerability analysis, Levo provides nearly 100 times the security coverage of periodic manual pentests at less than one-tenth the cost. Teams gain continuous insights throughout every build and release cycle, steadily improving their security posture without slowing delivery or increasing headcount.

API Vulnerability Testing Tools help teams stay ahead by detecting business-logic, access control misconfigurations logic flaws, sensitive data exfiltration pre-production and enabling their remediation.

Below are the Top 10 API Vulnerability Testing Tools for 2026, selected for their accuracy, automation, and scalability. Each one blends discovery, testing, and analytics to help teams protect APIs from design to production.

TL;DR

The top API vulnerability testing tools to know in 2026 include Levo.ai, Harness / Traceable, Salt Security, 42Crunch, Wallarm, APIsec, StackHawk, Akto, Akamai (formerly Noname Security), and Burp Suite Enterprise.

These platforms help teams detect and fix misconfigurations, broken authentication, and data exposure before APIs go live. The reliance on production controls, such as detection and response, as the primary defence is shifting. Enterprises are now adopting shift-left practices such as API vulnerability testing to supplement production security and close gaps earlier in the lifecycle.

Each tool approaches this challenge differently, but all share one goal: keeping APIs fast, reliable, and secure.

What Are API Vulnerability Testing Tools?

API Vulnerability Testing Tools are specialized solutions that identify and validate security vulnerabilities in APIs, such as access control, business logic issues and sensitive data exfiltration flaws that typical scanners often miss.

Unlike legacy security tools, these platforms are purpose built for modern first applications. They simulate realistic attack patterns to uncover issues in logic or 

Modern API security platforms offer end-to-end coverage across the API lifecycle, with vulnerability testing serving as a key shift-left module alongside discovery, documentation, and monitoring.

By integrating directly with CI/CD pipelines, they help teams catch risks early, maintain consistent standards, and keep releases moving without delay.

In short, they bring real world security testing closer to where code actually lives, i.e. inside the development process itself.

Why API Vulnerability Testing Tools Matter

APIs sit at the heart of most modern software, linking users, services, and data. That same strength also makes them a prime target. As the number of APIs grows, so does the chance of missing one that’s misconfigured or exposed.

That’s where API Vulnerability Testing Tools make a difference. They continuously test how APIs handle authentication, permissions, and data flow. By catching problems early, teams gain the time and visibility to fix them before they escalate.

For businesses, this shift from reactive security to proactive testing has tangible results: fewer incidents, smoother compliance, and faster release cycles.

With Levo, organisations gain continuous validation across thousands of APIs, combining deep analysis with high frequency and broad coverage that manual pentesting cannot replicate. This lets teams ship faster while maintaining a stronger and more consistent security posture. Levo unites depth, frequency, and full coverage in a single, automated process by testing 100x more APIs than manual pen-testing, at 1/10 the cost.

What to Look for in an API Vulnerability Testing Tool

Modern applications have evolved dramatically – from on-premises, monolithic systems to API-first, cloud-native microservices that are updated continuously. Having led enterprise development teams through this evolution, I’ve seen legacy security approaches struggle to keep up. APIs are now the core of digital business, and according to Gartner, by 2026, 80% of data breaches will involve insecure APIs

Finding the right API testing platform is about more than feature checklists; it’s about fit. The best tools strengthen security without slowing developers down. They automate intelligently, integrate naturally, and scale as systems grow.

Here’s what to look for when choosing the right API vulnerability testing tool:

1. Seamless Integration into Development Workflows: In the era of agile and CI/CD, security testing must be integrated into the development lifecycle rather than treated as a separate, disruptive step. Look for a tool that integrates directly with your CI/CD pipelines and DevOps processes. This ensures API security tests run automatically during development and deployment, catching issues early (the “shift left” security approach). For example, a good platform should trigger scans on every build or release, and feed results back into the tools your developers already use (such as CI dashboards or issue trackers). When security testing is incorporated from the beginning, teams can identify and fix vulnerabilities in each sprint without derailing velocity.
2. Intelligent and Automated Testing (with Minimal Noise): Automation is essential when you’re dealing with dozens or hundreds of microservice APIs that change daily. However, not all automation is equal. “Intelligent” automation means the tool smartly prioritizes and validates findings so you aren’t drowning in false positives or trivial issues. Look for solutions that leverage context-aware testing – for example, using machine learning or traffic analysis to focus on real, exploitable risks instead of theoretical ones. Advanced API testing tools now simulate real-world attack scenarios and even learn from actual API behavior. Some platforms (for instance, those with AI-driven analysis) will monitor real API traffic patterns and user behavior to understand what “normal” looks like, then generate tests to probe for abnormal or dangerous conditions.
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3. Comprehensive Coverage of API Threats: APIs introduce a wide range of potential vulnerabilities, so the tool you choose must offer broad and deep coverage of security risks. At a minimum, it should cover the OWASP API Security Top 10 vulnerabilities (such as injection flaws, broken authentication, excessive data exposure, and lack of rate limiting). But beyond the basics, it should also detect API-specific issues that plague modern architectures. For example, Broken Object Level Authorization (BOLA) – where an API exposes data from one user to another due to ID manipulation – has caused many high-profile breaches and must be tested. Broken authentication or token misuse, misconfigured CORS, business logic abuses, and other subtle flaws are now common targets. The testing tool should be able to identify these API-specific exploitation paths, not just generic web app bugs.‍
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4. Scalability and Performance at Enterprise Scale: Enterprise APIs proliferate quickly – you might have hundreds of microservices with thousands of endpoints across dev, test, and production environments. Scalability is therefore a critical factor. The testing tool must scale with your API landscape so that as you deploy new services and endpoints, it can seamlessly include them in its security scans. This involves both organizational scalability (ability to manage many APIs, perhaps with tagging or grouping features) and technical scalability (ability to execute many tests efficiently). Pay attention to how the tool performs when testing at scale. Security testing should not grind your systems to a halt. Leading tools are designed to run in parallel, using efficient testing methods that won’t overwhelm the API or cause excessive load. For example, some cloud-based API security platforms leverage cloud elasticity to run large numbers of test cases quickly, and they use throttling or scheduling to avoid impacting your production performance.
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5. Detection of Business Logic Flaws and Advanced Threats: Today’s API attacks frequently involve abusing legitimate functionality in unintended ways, not just exploiting a coding mistake. For example, an attacker might manipulate an API workflow (e.g., by calling steps out of order or reusing tokens) to escalate privileges or extract data. Legacy testing tools that only look for known signatures (like a specific SQL injection pattern) will miss these scenarios. Therefore, it’s essential that your API testing tool can detect business logic flaws and other advanced threats specific to your application’s design.

Top 10 API Vulnerability Testing Tools (2026)

APIs now power most of the digital economy, linking data and services across industries. But every new API also expands the potential attack surface. Continuous testing helps keep that growth safe.

Below are the 10 most trusted API Vulnerability Testing Tools of 2026, chosen for accuracy, automation, and enterprise scalability. Each platform brings its own strengths, from runtime observability to contract validation and helping teams stay secure at every stage of development.

1. Levo.ai — Best Overall API Vulnerability Testing Platform

Overview:

Levo.ai delivers a modern, unified approach to API security by combining vulnerability testing, runtime visibility, and compliance into a single workflow. Its eBPF powered engine observes API behavior at the kernel level, allowing teams to detect access issues, sensitive data exposure, and configuration drift based on how APIs actually behave in production. This creates a testing model that aligns with real runtime context rather than static assumptions.

Integrations:

GitHub, GitLab, Jenkins, Jira, AWS API Gateway, AWS Fargate, Akamai Edge-worker,  Slack, Postman, Burp Suite.

Pros:

• Runtime informed testing engine that detects only exploitable vulnerabilities.
• Discovers every API and maps sensitive data flows directly from live traffic
• Builds custom payloads for each endpoint across all major security testing frameworks
• Accurately tests access control issues including privilege escalation, IDOR, and BOLA.
• Automates authentication for OAuth2, JWT, API keys, and mTLS across environments
• Provides full testing coverage for internal and imported APIs, including Swagger and OpenAPI
• Supports continuous security validation with configurable schedules and endpoint level reruns
• Offers real time debug logs with single click retesting
• Identifies only browser exploitable CORS misconfigurations to reduce noise
• Simulates BOLA without requiring multiple user accounts
• Recommends optimal test users based on real runtime access patterns

Cons:

• Requires some initial runtime traffic to map API behavior fully
• Advanced features may be underutilized by teams 
• Runtime informed testing may challenge existing workflows that rely heavily on static scans

Features:

• Discovers and documents every API from live traffic, so testing is based on real behavior rather than intended design.
• Maps all sensitive data flows and access paths directly from runtime activity, creating an accurate foundation for security testing.
• Generates custom payloads for every endpoint across all major testing frameworks, including the OWASP API Top 10, injection attacks, CVEs, and business logic abuse.
• Performs access control testing that mirrors real world role abuse, including privilege escalation, IDOR, and BOLA. This uses role mapped logic, parameter mutation, token manipulation, and real user data detected automatically from traffic.
• Automates authentication across all schemes and environments, including OAuth2, JWT, API keys, and mTLS, with automatic token generation, renewal, and injection.
• Provides full testing coverage for internal and imported APIs, allowing teams to parameterize Swagger and OpenAPI specifications when traffic instrumentation is not available.
• Supports continuous security testing for constant deployment, including scheduled runs, editable test plans, configurable intervals, and the ability to rerun specific endpoints directly from the UI.
• Offers real time debug logs for failed tests so configuration and environment issues can be identified quickly, with one click retesting.
• Identifies only exploitable CORS misconfigurations using browser aware detection to reduce false positives.
• Simulates BOLA testing without requiring multiple user accounts by using parameter profiles.
• Suggests optimal test users based on runtime access coverage, ensuring payloads reflect accurate context while maintaining a privacy first approach.

Pricing: Custom enterprise pricing; typically lower than agent based tools

G2 Rating: 4.9 

Levo is often used as a “single view” of API behaviour, giving teams quiet, continuous assurance without slowing development.

2. Harness / Traceable — Best for Runtime Threat Detection

Overview:

Traceable.ai provides a runtime focused approach to API security built around traffic collection, threat detection, and forensic investigation. The platform captures full API payloads, correlates attack patterns, and supports SOC teams with analytics and incident response workflows. Its primary value is reactive protection in production environments rather than proactive prevention across the SDLC.

Integrations:

AWS, GCP, Azure, Kubernetes, Splunk, Datadog

Pros:

• Strong production detection and blocking capabilities.
• Full payload visibility that supports fraud analysis and forensic investigations.
• Customizable dashboards that help SOC teams correlate and investigate threats.
• On prem deployment option available for enterprises that require it.
• Useful for runtime threat analytics and post incident response.

Cons:

• Depends on capturing full API traffic which creates significant compute and storage overhead
• Traffic dependent discovery misses inactive, low traffic, internal, and third party APIs
• Testing is supported mainly only in runtime and does not provide meaningful pre production coverage
• Requires more manual effort from SOC teams to manage alerts, dashboards, and investigations
• On prem deployments are difficult because the architecture depends on traffic ingestion and a centralized data lake
• API documentation is limited to what traffic reveals which often results in drift and gaps
• Misconfigurations and data exposures can reach production before detection due to reactive workflows

Features:

• Traceable focuses on detecting and blocking attacks in production by collecting and analyzing full API payloads.
• Discovery is based entirely on observed traffic. Active and internet facing APIs are identified, but inactive or internal endpoints remain undiscovered without ongoing traffic.
• API specifications are created from traffic only, which provides limited context and does not capture pre production behavior. This results in documentation drift and compliance challenges.
• The platform provides dashboards, visualizations, and forensic tools that enable SOC teams to analyze attacks, investigate anomalies, and review runtime behavior.
• Traceable supports on prem deployment, although the architecture requires full traffic ingestion and storage, which increases operational complexity for regulated or air gapped environments.
• Testing is generated from traffic patterns and focuses primarily on common OWASP API Top 10 risks for active APIs. Depth is limited because testing cannot extend beyond what has been observed at runtime.

Pricing: Enterprise pricing based on API volume

G2 Rating: 4.7

Harness / Traceable suits large teams that want a single view across delivery and security.

Read More: Top 10 Traceable AI Alternatives

3. Salt Security — Best for Production API Monitoring

Overview:

Salt Security provides a production focused approach to API protection by collecting traffic at the edge through API gateways and WAFs. The platform centers on runtime anomaly detection and incident response, with limited visibility into how APIs behave across environments. Because it lacks a native API security testing engine, most vulnerabilities reach production before they can be identified or prevented.

Integrations:

API gateways, WAFs, cloud platforms, SIEM solutions, and common observability tools.

Pros:

• Provides runtime anomaly detection for production environments
• Supports SOC teams with traffic based investigation and incident analysis
• Integrates with existing gateways and WAFs already deployed in enterprises

Cons:

• No native API vulnerability testing engine. Salt cannot generate or execute API-specific test cases.
• Relies entirely on a legacy DAST integration, which is built for web apps, not APIs.
• Cannot test authentication, authorization, or business logic flows, making most API attack paths invisible.
• No pre-production or CI/CD testing, so vulnerabilities ship straight to production.
• High false positives and missed critical API issues because DAST lacks runtime context or API semantics.
• No ability to simulate realistic attack payloads, replay traffic, or validate exploits.
• Testing depth is negligible, limited to whatever the external DAST can scan from the outside-in.
• Shift-left is impossible, despite marketing claims, because there is no actual testing capability behind it.

Features:

• Production anomaly detection based on traffic collected from gateways and WAFs
• Traffic dependent API discovery with limited visibility into internal and low traffic APIs
• Runtime monitoring only, with no pre production security testing engine
• Hybrid deployment available, but no fully on prem option
• Traffic ingestion into the vendor SaaS, including sensitive data
• Limited documentation generation, covering only a small subset of API parameters
• Edge based visibility without behavioral or context aware insights

Pricing: Enterprise pricing on request

G2 Rating: 4.7

‍Read More: Top 10 Salt Security Alternatives

4. 42Crunch — Best for API Contract & OpenAPI Validation

Overview:

42Crunch focuses on contract based API security by validating OpenAPI specifications and scanning definitions for schema level issues. The platform relies entirely on developer maintained documentation rather than observing real API behavior, which means many vulnerabilities move into production unchecked. Since it does not validate live traffic or runtime behavior, security accuracy depends on constant manual updates to OpenAPI files and offers limited protection for real world attack surfaces.

Integrations:

CI pipelines, developer tooling, IDE plugins, and OpenAPI specification repositories.

Pros:

• Fast to begin scanning by pointing the platform at existing OpenAPI files
• Useful for basic contract validation and detecting mismatches between schemas and implementations
• Provides CI integrations for static documentation checks
• Offers a lightweight way to enforce documentation quality within development workflows

Cons:

• Time to market slows because the platform validates only developer maintained specs without stress-testing actual API behavior.
• Operational costs rise as teams must manually maintain OpenAPI documents and reconcile them with real APIs.
• Provides no validation of live API behavior which allows most vulnerabilities to reach production.
• Customization is limited to spec extensions and cannot adapt tests to real business logic.
• High manual burden on security teams to update specs for every endpoint change.
• Runtime protection applies only to traffic flowing through the provided proxy.
• Many APIs remain invisible because discovery depends entirely on supplied docs.

Features:

• Spec based contract validation for OpenAPI files to detect schema and conformance issues.
• Static CI scanning that checks definitions during pipeline runs but does not validate runtime behavior.
• Limited runtime proxy for traffic protection, restricted to traffic routed through the Docker based component.
• Spec dependent API discovery, which surfaces only documented endpoints and misses dynamically generated routes.
• Manual remediation workflow with reports listing spec violations but lacking actionable fix guidance.

Pricing: Free tier; paid from $49/month

G2 Rating: NA

5. Wallarm — Best WAAP for Production Layer Protection

Overview:

Wallarm Security focuses on Web Application and API Protection with a strong emphasis on detecting and blocking attacks in production environments. The platform relies on edge based traffic ingestion and in line processing, which places most of its value in reactive defense rather than preventing vulnerabilities before release. Because security is tied to production modules and retrofitted shift left components, organizations receive limited visibility into API behavior and cannot reliably detect insecure code before it reaches production.

Integrations:

API gateways, WAFs, cloud providers, and incident response tooling.

Pros:

• Useful for WAAP use cases that require blocking of suspicious traffic in production
• Integrates with edge and gateway infrastructure already present in many environments
• Provides basic alerting for newly discovered endpoints or sensitive data flows
• Supports hybrid deployment modes

Cons:

• The platform does not provide a true pre-production vulnerability testing capability. Most findings come from analyzing production traffic rather than actively testing APIs before release.
• Test cases are not generated automatically or contextually. The system does not analyze API behavior, sensitive data paths, or authentication flows to craft meaningful payloads.
• Security tests require significant manual configuration. Teams must create rules, tune parameters, and maintain their own testing workflows.
• Authentication and authorization logic is not tested reliably. Session handling is inconsistent, resulting in incomplete coverage of access control vulnerabilities.
• Vulnerabilities are not reproduced automatically. Teams need to manually reconstruct exploit paths, which slows down investigation and remediation.
• Attack simulations have limited depth. The testing engine does not build advanced payloads that reflect real misuse scenarios, business logic attacks, or chained exploits.
• Customization options are minimal. There is no straightforward way to tailor test logic or data types to match in-house API requirements.
• Remediation guidance is not automated. Findings are not mapped to specific services, developers, or code locations, and no fix recommendations are generated.
• Visibility into API behavior during testing is limited. Because tests are not grounded in a deep understanding of the API, it is difficult to identify root causes or confirm the extent of an issue.
• Coverage across the SDLC is minimal. Earlier environments such as development, staging, and QA receive little to no testing support, leaving most issues to surface only in production.

Features:

• Production focused WAAP functionality centered on detection and blocking in live environments.
• Edge based traffic ingestion that limits visibility into internal and east west traffic.
• Hybrid deployment support, although full processing remains in the cloud
• Static OpenAPI specification checks with limited documentation depth
• Basic alerting for newly seen endpoints and simple sensitive data flow detection
• Manual rule configuration required for detection, blocking, and response

Pricing: Subscription based

G2 Rating: 4.7

6. APIsec — Best for Spec-Based API Scanning

Overview:

APIsec delivers a static, scan driven approach to API security where tests operate only on manually supplied API catalogs and documentation. Because the platform has no built-in discovery, no runtime context, and no behavioral awareness, most critical endpoints remain untested and many vulnerabilities move into production. Security tests remain episodic and disconnected from real usage, slowing application delivery and weakening the overall security posture as deployments scale.

Integrations:

CI pipelines, OpenAPI file repositories, developer tooling, and basic SaaS connectors.

Pros:

• No vendor induced privacy risk because no traffic instrumentation or payload ingestion occurs
• Simple to begin scanning when API documentation is already available
• Supports basic CI execution for teams that want static contract checks
• Useful for organizations that only need periodic schema validation

Cons:

• Application delivery slows because testing is based solely on one-off scans and never reflects real API behavior
• Total cost grows rapidly because customers pay per endpoint and must manually maintain the entire API catalog
• Time to value is delayed because tests cannot run until complete API documentation is supplied
• Testing remains shallow and misses environment or behavior driven vulnerabilities
• Generic payload libraries reduce test fidelity and demand continuous maintenance
• Significant manual overhead to define, update, and configure every endpoint for scanning
• No on prem option, making the platform unusable in isolated or regulated networks
• Security posture degrades because no visibility or discovery exists for new, changed, or undocumented endpoints
• Remediation is slow because results only include raw schema violations with no mapping or automation
• Critical vulnerabilities go undetected because tests lack real world context, authentication handling, or automated flows

Features:

• Static API scanning based entirely on manually supplied documentation
• Pay per endpoint testing model with no automated discovery to reduce scope
• Manual API catalog management, required before scans can run
• Basic schema validation that identifies mismatches in supplied definitions
• Generic payload libraries that provide surface-level tests without runtime insight
• No authentication automation, leading to limited coverage of real attack paths
• Single request attack models that miss multi-step or chained exploit scenarios

Pricing: Enterprise custom pricing

G2 Rating: 4.7

7. StackHawk — Best for Code-Driven API Scanning

Overview:

StackHawk delivers a code driven scanning approach to API security that relies on parsing code repositories to infer API endpoints. Because the platform does not validate real API behavior or observe live traffic, testing remains shallow and cannot detect the majority of real world vulnerabilities. Security relies on periodic scans that operate on incomplete, statically derived catalogs, which slows time to market and leaves critical gaps in protection as applications evolve.

Integrations:

CI pipelines, Git repositories, code scanners, and developer tooling.

Pros:

• Easy to start scanning when code bases and repositories are already connected
• Useful for basic static checks against code inferred endpoint lists
• Provides CI integration for lightweight testing during development stages
• Offers a Docker based scanner that can run inside private networks

Cons:

• Time to market slows because security is limited to periodic scans that never reflect runtime behavior
• Total cost rises due to pay per scan pricing and extensive manual triage of false positives
• Storing full repositories and configs may expose embedded secrets and sensitive comments
• Setup leaves blind spots because no runtime discovery agent exists
• Customization is extremely limited to static payload templates
• High manual overhead to configure each scan, update endpoint lists, and triage generic alerts
• Docker based scanner analyzes only code and cannot observe live traffic

Features:

• Code inferred API scanning that parses repositories to detect endpoints
• Static payload templates without dynamic or context aware generation
• Manual endpoint list management required for every scan cycle
• No runtime telemetry or traffic based behavior analysis
• Basic CI execution that triggers scans on commit or pull request
• Single request attack models that cannot simulate stateful or multi step workflows
• High false positive rates from static analysis based testing

Pricing: Free tier; paid from $39/month

G2 Rating: 4.5

8. Akto — Best for Traffic-Based API Discovery

Overview:

Akto offers automated endpoint discovery and a broad library of prebuilt tests, but security remains shallow and reactive because testing is limited to generic payloads and surface level scans. Without runtime context or behavior aware analysis, critical vulnerabilities such as complex access control issues and business logic flaws remain undetected. Manual setup across authentication, roles, traffic inputs, and configuration slows DevOps cycles and prevents security from acting as a business enabler.

Integrations:

CI pipelines, cloud traffic connectors, OpenAPI imports, and developer tooling.

Pros:

• Automated discovery of live endpoints based on captured traffic
• Generates basic OpenAPI specifications for organizations lacking documentation
• Broad test library suitable for identifying common API issues
• Supports YAML based test customization and parameter overrides

Cons:

• Security remains a bottleneck because testing is generic and disconnected from actual API behavior
• Costs escalate with per endpoint scan fees and growing manual configuration overhead
• High privacy risk due to traffic captures and test recordings that expose tokens, headers, and PII
• Lengthy deployment cycles because traffic capture requires deep internal review and multi environment setup
• Only high level customization available with limited control over logic and auth path testing
• Heavy manual effort required to configure authentication, define roles, manage tokens, and triage false positives
• On prem connectors increase complexity and compliance overhead because privacy scrubbing is not built in
• Documentation lacks meaningful metadata such as rate limits, error patterns, and auth schemes
• Remediation is slow because the platform provides only raw test results without mapping findings to services or owners

Features:

• Traffic based endpoint discovery that identifies active APIs and produces basic OpenAPI specifications
• Library of prebuilt tests that cover common patterns but lack endpoint specific customization
• Manual authentication setup including tokens, roles, and session data
• Limited YAML based customization for test templates and parameter overrides
• Self hosted connectors for capturing traffic in private and hybrid environments
• Basic OpenAPI generation missing metadata such as status codes, rate limits, and auth schemes

Pricing: Free community version; enterprise from ~$500/month

G2 Rating: 4.5

9. Akamai (formerly Noname Security) — Best Edge-Based Production Visibility

Overview:

Akamai Security provides API protection through edge based detection and WAF style enforcement, with a focus on monitoring and blocking activity in production environments. Because the platform captures traffic after encryption at the CDN and gateway layers, visibility into internal and low traffic APIs is limited, and critical vulnerabilities often progress into production before they are detected. The approach creates noise for security teams, slows application delivery, and fails to enable shift left practices.

Integrations:

API gateways, CDNs, WAFs, cloud logging pipelines, and production monitoring systems.

Pros:

• Useful for production blocking and runtime protection at the edge
• Integrates with gateway and CDN infrastructure already deployed in many enterprises
• Supports global traffic footprints through Akamai’s distributed edge network

Cons:

• No positive impact on product delivery or revenue growth because security occurs only in production
• Extremely high cost due to traffic mirroring and multi point ingestion in the cloud
• High vendor-induced privacy risk because sensitive data is exported to the vendor SaaS from multiple locations
• Deployment approvals often take months because any production side integration requires multi team validation
• Customization is poor and lacks usable controls for in house needs
• High manual overhead as developers must provide documentation and security teams must triage large volumes of alerts
• No insight into internal APIs because agentless discovery at the edge cannot see east west traffic
• Remediation is slow and generic, with no runtime linked prioritization or service mapping without additional integrations

Features:

• Edge based traffic ingestion through CDN and gateway instrumentation
• Production only monitoring and detection with limited metric level insights
• Traffic mirroring for visibility that increases cloud costs
• Generic payload testing requiring full application deployment
• Manual schema uploads for any testing coverage
• No automatic API documentation or behavior enriched discovery

Pricing: Enterprise pricing based on usage and modules

G2 Rating: 4.5

Read More: Top 10 Akamai Security Alternatives

10. Burp Suite Enterprise — Best Traditional Scanner for APIs

Overview:

Burp Suite Enterprise automates one of the most trusted security testing engines in the industry. It brings Burp’s deep scanning capabilities to enterprise teams, supporting both REST and GraphQL APIs. For organisations with mature security programs, it ensures testing consistency across environments.

Integrations:

Jenkins, GitHub, GitLab, Azure DevOps, Jira

Pros:

• Reliable, proven scanning framework
• Supports a variety of API architectures
• Extensive configuration for advanced users

Cons:

• May require tuning for complex API ecosystems
• Not scalable for enterprise API ecosystems

Features:

• Automated API vulnerability scanning
• Seamless CI/CD and ticketing integration
• Detailed reporting and analytics

Pricing: Starts around $5,000 per year

G2 Rating: 4.8

Benefits of Using API Vulnerability Testing Tools

Today, APIs account for more than 90% of modern web traffic. According to Gartner, APIs have become the primary attack surface for modern applications and remain one of the most frequent root causes of data breaches as enterprises expand their use of microservices, cloud workloads, and interconnected systems. 

Most businesses now run hundreds or even thousands of APIs, and security teams often can’t keep up. All it takes is one untested or forgotten endpoint for a breach, outage, or compliance failure to spread across systems.

That’s why API Vulnerability Testing Tools matter. They give security teams the same speed and automation that developers already rely on. Instead of discovering flaws after a release or during an incident, enterpises can find and fix issues earlier, long before customers or regulators notice.

Here’s what enterprises gain:

1. Early Detection of Vulnerabilities: Catch logic errors and broken authentication before release. Less rework, fewer emergency patches.
2. Continuous Security Assurance: Testing runs automatically in pipelines, ensuring every build meets baseline security standards.
3. Improved Compliance and Governance: Prebuilt checks for SOC 2, PCI-DSS, and GDPR turn compliance into a background process rather than a quarterly scramble.
4. Reduced Breach Impact: API related breaches cost enterprises an average of USD 4-5 million, according to IBM’s 2024 breach report. Early detection cuts downtime, response costs, and reputational damage.
5. Better Collaboration Between Teams: Shared dashboards enable dev, QA, and security teams to work from the same data, speeding up remediation.
6. Lower Operational Costs: Automation reduces manual effort and unplanned fixes, improving ROI for both engineering and security.

Greater Customer Trust: Strong Security Posture rarely makes headlines, and that’s the point. Fewer incidents mean more stability and confidence in your brand.

Conclusion — Why Levo.ai Leads API Vulnerability Testing in 2026

For security leaders, the challenge in 2026 is no longer just identifying vulnerabilities. It is keeping pace with systems that evolve faster than traditional scanning tools can follow. APIs now sit at the center of revenue, customer experience, regulatory exposure, and operational resilience.

Levo.ai closes this gap with its runtime informed security testing. This gives CISOs something legacy tools cannot: a real-time, uncompromised view of how every API behaves in production. Misconfigurations, broken access controls, and attempts to sensitive data exfiltrations are detected pre-production, before they cause incidents, compliance fines and data loss.

Levo.ai does more than test APIs. It reinforces the foundation of the digital ecosystem by ensuring that the systems driving revenue, analytics, and customer experience remain secure, consistent, and compliant at all times. For CISOs who want to reduce risk while supporting rapid delivery, Levo.ai provides the visibility and control needed to protect the enterprise without slowing it down.

Get real time clarity into your API vulnerabilities. Book a Levo.ai demo and see how continuous runtime security eliminates blind spots before they become incidents.