42Crunch is well-known for its focus on API security, particularly in terms of enforcing API contracts and validating OpenAPI specifications. It helps to detect misconfigurations early and helps teams in incorporating security into the development process from the beginning. However, it may not be suitable for organizations that require features like dynamic testing, runtime protection, or closer CI/CD integration. As APIs become complex, security teams look for tools that provide deeper visibility, real-time threat detection, and smarter, AI-driven protection. If you're looking for options, here are some alternatives of 42Crunch, with their features, pros, and cons to help you make the right choice.

Top 10 Alternatives and Competitors to 42Crunch.

1. Akto

Akto is an Agentic AI-based API security platform built for modern DevSecOps teams. It automatically discovers internal, external, and shadow APIs across REST, GraphQL, SOAP, and gRPC environments. With over 1,000 built‑in tests mapped to OWASP API Top 10, covering auth, BOLA, SSRF, XSS, and data exposure. It offers both CI/CD integration and runtime posture assessment. By analyzing live traffic, Akto reduces false positives and prioritizes business‑critical findings.

Features:

• Auto‑discovers all API endpoints (internal/shadow) within 60 seconds.

• 1,000+ pre‑built tests focusing on OWASP API Top 10 and more.

• Live traffic analysis to discover data leaks.

• Connects with CI/CD using connectors like Burp, Postman, etc.

• Allows YAML-based tests and configurable deployment options.

Advantages:

• Open-source core promotes transparency.

• Quick onboarding and API scanning in under a minute.

• Scales from free to enterprise level, with transparent pricing.

• Reduces noise with context‑aware business‑logic testing.

• Supports both staging and production environments easily.

2. Noname Security

Noname Security (now part of Akamai) is a comprehensive API security solution that combines continuous discovery, runtime protection, and active testing. It inventories APIs using both traffic sensors and infrastructure connectors, capturing managed, unmanaged, and shadow APIs. It offers real‑time threat prevention with AI‑based anomaly detection and automated remediation workflows integrated with WAFs and SIEMs.

Source: Noname

Features:

• Continuous API discovery using traffic and infrastructure connectors.

• AI-enabled anomaly detection and threat response.

• Automated remediation by modifying WAF/gateway rules.

• 150+ active tests are incorporated into CI/CD pipelines.

• Provides interactive training and a Learning Center.

Advantages:

• Proactive threat prevention with behavior‑based AI detection.

• Easy to deploy in hybrid/cloud via remote engine architecture.

• Integration-friendly with WAF, SIEM, ticketing, and gateway tools.

• Strong support and learning guidance for fast adoption.

• Scalable to large organizations.

Disadvantages:

• Initial setup can be hard and also takes time.

• Rely on traffic data, so may miss inactive or shadow APIs.

• Alerts and false positives require continuous tuning and active monitoring.

3. Salt Security

Salt Security is a data-based API protection tool that focuses on real-time threat detection and extensive behavioral analysis. It quietly captures and analyzes traffic in your environment to establish a baseline for typical API usage. It uses machine learning to detect malicious activities, BOLA attacks, and abuse of business logic.

Source: Salt Security

Features:

• Passive discovery with deep traffic inspection and schema correlation.

• Behavior profiling based on AI and machine learning.

• Sends real-time threat alerts and attack replays.

• Provides security insights by visualizing sensitive data flows.

• Scalable cloud-based architecture for enterprise environments.

Advantages:

• Detects business logic attacks using ML baselines.

• Detailed, replayable timeframe for forensic investigation.

• Allows non-intrusive deployment.

• Helps meet compliance goals.

• Integrates with SIEMs, ticketing, and WAF solutions.

Disadvantages:

• Limited shift-left features.

• May have false positives without ML tuning.

• Expensive for small or mid-sized teams.

4. Traceable AI

Traceable AI is built for deep API security, combining observability with real-time threat detection. It maps the entire API environment automatically to help teams find shadow APIs, which are APIs exposing sensitive data, and anomalous behavior. It uses user/API interaction to detect threats at high levels and remove noise. The alerts reduce false positives and optimize monitoring.

Source: Traceable Ai

Features:

• API queries and user flows are fully observable across the stack.

• Real-time detection of OWASP Top 10 and business logic vulnerabilities.

• API risk grading is based on behavior and data exposure.

• Schema validation and compliance enforcement.

• Dynamic testing across CI/CD, with actionable feedback.

Advantages:

• Context-rich alerts based on user behavior and roles.

• Deep analytics can help prioritize actual dangers over noise.

• Supports hybrid and cloud-native microservice architectures.

• Detects internal risks and misuse scenarios efficiently.

• Effective dashboard visualization and tracing tools.

Disadvantages:

• High learning curve for tuning observability logic.

• Needs consistent traffic volume for best performance.

• Resource-intensive for large data pipelines.

5. Imperva API Security

Imperva API Security offers API protection as part of its application and data security suite. It automatically identifies exposed APIs and applies continuous protection by WAF integration and behavioral analysis. The platform defends against known and unknown threats, like injection, DDoS, and auth bypass.

Source: Imperva

Features:

• Discovers APIs and schema enforcement automatically.

• Allows behavioral threat detection and risk scoring.

• WAF-based enforcement of API-level rules.

• Bot mitigation and rate-limiting protection.

• Centralized dashboards for policy and threat monitoring.

Advantages:

• Easily integrate with existing Imperva users and infrastructure.

• Real-time threat prevention at the edge.

• Less impact on app performance and latency.

• Includes bot and DDoS protection together.

• Simplifies compliance monitoring with a unified console.

Disadvantages:

• Limited testing or CI/CD shift-left integration.

• All features are tightly coupled to other Imperva services.

• Limited flexibility for non-Imperva settings.

6. Cequence Security

Cequence Security is an API security platform that offers bot defense, runtime protection, and pre-prod testing. It provides clear visibility into API traffic and inventory throughout any environment, and anomaly detection and detection of malicious patterns. The Cequence platform ultimately focuses on the reduction of fraud, abuse, and business logic exploitation through AI and custom policies.

Source: Cequence Security

Features:

• Real-time traffic analysis and behavioral detection.

• API risk scoring with fraud and abuse indicators.

• Inventory and classification of APIs with attack mapping.

• Combines API discovery with runtime threat detection.

• Includes shift-left testing and bot mitigation tools.

Advantages:

• Identifies business logic abuse in real time.

• Prevents fraud and automated attacks.

• Integrates with firewalls, SIEMs, and gateways.

• Provides clear, contextualized risk insights.

• Flexible deployment in the cloud and on-premises.

Disadvantages:

• Complex policy contexts.

• Some features require adjustment to reduce false positives.

• Smaller firms may find the enterprise model too costly.

7. Data Theorem

Data Theorem provides automated security testing in mobile, web, and API attack surfaces. It continuously scans for vulnerabilities in deployed APIs and refreshes its test cases using threat feeds. This platform primarily focuses on pre-production analysis and compliance validation for API contracts. It works easily with mobile app development and ensures that APIs used by apps are not left vulnerable.

Source: Data Theorem

Features:

• Discovers and scans external APIs continuously.

• Contract validation using OpenAPI specifications.

• Mobile app scanning for backend API security.

• Integrates with CI/CD and sends notifications.

• Compliance testing, including exportable security reports.

Advantages:

• Strong connection with mobile app security.

• Recognizes shadow APIs with mobile deployments.

• Contract testing allows design consistency.

• Fast setup via ready-to-use templates.

• Cloud-friendly and lightweight architecture.

Disadvantages:

• The limited amount of runtime protection in comparison with traffic-based tools.

• The dashboard does not give the analytics needed for larger teams.

• Limited ability to detect business logic attacks.

8. Wallarm

Wallarm combines dynamic API discovery, automatic vulnerability detection, and inline protection. Its hybrid architecture detects OWASP Top 10 vulnerabilities, as well as SSRF, RCE, and other threats, using traffic-based intelligence and active scanning. It works with CI/CD pipelines and provides blocking and passive modes for production APIs. Wallarm supports gRPC, GraphQL, REST, and WebSockets, making it a perfect fit for current API stacks.

Source: Wallarm

Features:

• Active vulnerability scanning in staging and production.

• Traffic-based attack detection with automated blocking.

• Broad protocol support, including gRPC and WebSockets.

• API schema enforcement with behavior profiling.

• Integrates with CI/CD for early-stage testing.

Advantages:

• Handles a variety of API types with precision.

• Combines passive and active detection modes.

• Built-in threat feeds and automatic upgrades.

• Real-time assault dashboards with traceability.

• Easy to deploy across Kubernetes and VMs.

Disadvantages:

• UI can be overwhelming for smaller teams.

• Extensive blocking mode produces some false positives.

• Reporting might be granular.

9. Firetail

FireTail is a modern, cloud-based API security technology that prioritizes visibility, logging, and access control at the application layer. FireTail relies on OpenAPI specifications and static checks to protect APIs directly in runtime via lightweight SDKs, providing a developer-first paradigm that seamlessly integrates into modern app stacks. It gives teams insight into every API call, like who made it, what data was touched, and whether it complied with policy.

Source: Firetail

Features:

• In-app API security by lightweight SDKs

• Full visibility into every API call with context

• Role-based access control and data classification

• Integration with SIEM and cloud-native tools

• Alerts for sensitive data access and misuse

Advantages:

• Developer-first approach with easy integration

• Ideal for securing APIs in production environments

• No agents or gateways required

• High granularity in monitoring and logging

• Strong support for cloud-native and serverless apps

Disadvantages:

• Limited static testing or design-time analysis

• Requires SDK integration, which may add dev effort

• Less mature than larger vendors in market reach and support

10. Kong Gateway (with API Security Plugins)

Kong Gateway is a fast API gateway with a growing community of plugins that offer API security features. Kong's plugins provide rate limiting, JWT authentication, ACLs, request and response validation, and threat protection. It performs well in traffic control and performance monitoring due to its Lua-based extensibility.

Source: Kong Gateway

Features:

• JWT Authentication, mTLS, and ACL rules in plugins.

• Schema and payload validation.

• Rate limiting and bot management plugins.

• Native and open-source deployment.

• Plugin Hub with extensible Lua scripts.

Advantages:

• Lightweight and quick, with low-latency processing.

• The open plugin system allows for extensive customization.

• Integrate with OPA, Prometheus, and other API analytics tools.

• Combines with microservices-based environments.

• An active and growing open-source community.

Disadvantages:

• Needs external tools for full security coverage.

• Plugin configurations might have issues or errors.

• Limited runtime behavior analysis.

How to Choose the Right API Security Platform

Choosing an API security solution is important to protect an organization’s data, applications, and infrastructure.

Map your complete API inventory

Security engineers must begin by identifying every API in staging and production, including undocumented, deprecated, and internal services. Tools that rely only on specs or gateways will miss shadow and zombie APIs. Select platforms that use traffic mirroring, proxy hooks, or native connectors to surface hidden endpoints. Visibility must be real-time and continuous, not static.

Ensure full OWASP API Top 10 coverage

Static lists and marketing claims are insufficient; engineers should check if the platform allows in-depth detection in various OWASP categories. The platform should validate BOLA, authentication vulnerabilities, excessive data exposure, and other business logic vulnerabilities. It should enable both predefined and bespoke test scenarios that are tailored to your specific environment.

Align shift-left testing with runtime defense

A platform not only detects issues after deployment, but also prevents them during development. Security engineers require both automated CI/CD scanning and production telemetry. Look for tools that integrate into pipelines and also monitor live traffic for logic abuse, broken auth, and sensitive data flow. Runtime visibility identifies unknown risks that scanners miss.

Check for integration and automation readiness

Security tools must embed cleanly into the DevSecOps toolchain to avoid friction. Choose platforms that provide plugins or APIs for Jenkins, GitHub Actions, Azure DevOps, and similar environments. Alerting should integrate with SIEMs or ticketing systems with minimal setup. It should support API gateways, WAFs, and reverse proxies. Automation cuts down on excessive alerts and helps teams respond more quickly to confirmed threats.

Validate scalability and signal-to-noise ratio

Enterprise environments generate high traffic volumes. Noisy tools can quickly erode trust. Engineers should test how platforms manage large datasets without losing performance or accuracy. They should concentrate on platforms that prioritize important alerts while filtering out non-exploitable noise. Role-based dashboards for security teams and developers improve usability. Efficient alerting and stable performance under load are signs of a mature, scalable solution.

Final Thoughts

42Crunch is widely recognized for its focus on shift-left API security, with strengths in OpenAPI contract enforcement, static analysis, and compliance validation. It works well for organizations prioritizing APIsec early in the development cycle. However, its coverage is limited when it comes to runtime protection, business logic abuse detection, and large-scale observability.

Akto is an agentic suite for API security that addresses modern API security needs with a full-lifecycle approach, covering discovery, testing, runtime monitoring, and posture management. It has over 1000 built-in tests for OWASP Top 10, authentication, and sensitive data issues in staging and production. Unlike static solutions, you'll get real-time insights and integration with CI/CD and traffic flows. Scalable, easy to introduce, and for teams that require depth and fast performance.  Schedule a API Security demo and find out how Akto can help secure your organization's APIs.