What are API Discovery Tools?
API discovery tools automatically identify, catalog, and classify APIs within an organization's network to eliminate security blind spots like "shadow" or "zombie" APIs. These tools are essential for maintaining a real-time inventory of endpoints, ensuring compliance with data regulations (e.g., GDPR, PCI DSS), and preventing developers from recreating existing functionality.
Key discovery methods:
- Traffic-based: Monitors network traffic (north-south and east-west) to identify active API calls. This is best for finding shadow APIs currently in use.
- Source code-based: Analyzes repositories to find API definitions. This "shifts left" by identifying endpoints even if they aren't yet active or receiving traffic.
- Gateway-based: Aggregates logs from API gateways like Kong or Apigee. It provides high visibility into managed APIs but may miss unmanaged endpoints that bypass the gateway.
This is part of a series of articles about API security.
In this article:
API discovery tools provide visibility and control over a growing and often fragmented API landscape. The benefits below focus on how they improve security, governance, and operations:
- Complete API visibility: Automatically finds APIs across environments, including undocumented, shadow, and deprecated endpoints.
- Improved security posture: Identifies exposed endpoints, weak authentication, and misconfigurations.
- Detection of shadow and zombie APIs: Surfaces APIs that are no longer maintained or officially tracked but still accessible.
- Faster compliance and auditing: Maintains an up-to-date inventory of APIs to support regulatory and internal policy requirements.
- Reduced manual effort: Eliminates manual tracking by continuously scanning and updating the API catalog.
- Better API governance: Helps enforce standards for design, versioning, and documentation across teams.
- Operational efficiency: Enables teams to locate and understand APIs, reducing duplication and improving reuse.
1. Automated API Inventory
Automated API inventory continuously scans the environment to identify all APIs, regardless of documentation status or deployment location. By maintaining a real-time catalog, organizations can locate APIs across cloud, on-premises, and hybrid infrastructures. This reduces the risk of unmanaged interfaces becoming security liabilities.
An effective automated inventory system should integrate with data sources such as network traffic, source code repositories, and API gateways. It should provide metadata about each API, including endpoints, protocols, authentication methods, and versioning. With this information, teams can maintain accurate records, track API changes, and respond faster to vulnerabilities or misconfigurations.
2. Shadow and Zombie API Detection
Shadow APIs are undocumented or unauthorized APIs running in an environment. Zombie APIs are deprecated or abandoned APIs that still exist but are no longer maintained. API discovery tools with shadow and zombie detection analyze network traffic, compare inventories against documentation, and flag inconsistencies. Attackers often target these neglected interfaces.
Regular detection allows organizations to update, decommission, or document these APIs. This improves security, reduces compliance risk, and limits exposure from legacy or rogue endpoints. Effective tools should also identify APIs that continue to receive traffic despite being officially retired, since these endpoints may still expose sensitive data or outdated authentication mechanisms.
3. Sensitive Data Classification
Sensitive data classification identifies and tags APIs that handle confidential or regulated data, such as personally identifiable information (PII), financial records, or health information. This feature uses pattern recognition, data flow analysis, and context-aware scanning to flag endpoints transmitting sensitive content.
By classifying sensitive data, organizations can apply targeted security controls, monitor for unauthorized access, and prioritize remediation where exposure risk is highest. This also supports auditing and reporting by showing which APIs process sensitive data and how that data moves across systems.
4. Risk Scoring and Prioritization
Risk scoring assigns quantitative or qualitative risk levels to APIs based on factors such as exposure, authentication strength, data sensitivity, and known vulnerabilities. API discovery tools analyze these factors to help security teams focus on critical issues instead of treating all APIs equally.
A risk scoring system should allow organizations to adjust scoring criteria based on risk tolerance, compliance requirements, and business context. It should integrate with incident response workflows, including automated alerts and ticket creation for high-risk APIs.
5. Runtime Monitoring
Runtime monitoring provides real-time visibility into API activity, including usage patterns, request and response payloads, and anomalous behavior. This enables organizations to detect API abuse, data exfiltration, or denial-of-service attacks as they occur.
Runtime monitoring should include alerting, logging, and integration with security information and event management (SIEM) systems. It may also support anomaly detection through machine learning or behavioral analysis.
6. Compliance Reporting
Compliance reporting automates the generation of reports for regulatory audits and internal governance. These reports document API inventory, security controls, sensitive data handling, and remediation actions.
A compliance reporting capability should offer customizable templates for regulations such as GDPR, HIPAA, or PCI DSS and support scheduled exports. It should provide traceability between discovered APIs and applied controls.
Related content: Apply our top API security best practices for governance and compliance.
Uri Dorot
Uri Dorot is a senior product marketing manager at Radware, specializing in application protection solutions, service and trends. With a deep understanding of the cyberthreat landscape, Uri helps bridge the gap between complex cybersecurity concepts and real-world outcomes.
Tips from the Expert:
In my experience, here are tips that can help you better operationalize API discovery and reduce hidden API risk:
1. Correlate discovery data from multiple layers: Traffic-only discovery misses dormant APIs, while code-only discovery misses unmanaged deployments. Combine runtime traffic, repositories, gateways, DNS, and cloud metadata for accurate coverage.
2. Track “API lineage” over time: Maintain relationships between versions, services, owners, schemas, and environments. Attackers often target forgotten legacy versions still reachable in production.
3. Treat undocumented APIs as security incidents: Shadow APIs should trigger ownership assignment, risk review, and expiration deadlines rather than simply being added to inventory dashboards.
4. Monitor east-west traffic aggressively: Internal service APIs frequently outnumber public APIs and are commonly overtrusted. Discovery inside the network is critical for zero-trust architectures.
5. Fingerprint APIs by behavior, not just paths: Similar request patterns, schemas, and authentication flows can reveal duplicate or renamed APIs that evade inventory tracking.
Traffic-Based
Traffic-based API discovery monitors network traffic to identify APIs in use. This method analyzes HTTP/S requests and responses to extract endpoint definitions, authentication methods, and data payloads. It uncovers undocumented and shadow APIs and shows real-time usage patterns.
Considerations:
This approach detects APIs regardless of documentation or registration status. However, it may require network integration points such as span ports or proxies and can miss APIs that are idle or rarely used.
Source Code-Based
Source code-based API discovery analyzes application source code and configuration files to identify API endpoints and properties. This approach is effective during development and deployment because it catalogs APIs before they are exposed to production.
Considerations:
While it provides visibility into API design, it may not capture runtime behavior or dynamically generated APIs. It also requires access to source code repositories, which may not be feasible for third-party or legacy applications.
Gateway-Based
Gateway-based API discovery uses API gateways, centralized management points for API traffic, to enumerate and monitor registered APIs. Gateways provide metadata on endpoints, usage statistics, and security policies.
Considerations:
This method is limited to APIs managed through the gateway and may miss shadow or legacy APIs that bypass it. Organizations should combine gateway-based discovery with traffic and source code analysis.
API Security and Runtime Protection Platforms
1. Radware API Security Service
Radware API Security Service is an API security platform that provides continuous API discovery, runtime posture management, contextual API testing, and real-time API threat protection. It discovers APIs across environments, including shadow, third-party, outdated, and deprecated APIs, and uses live production traffic to build a high-fidelity view of API behavior, workflows, risks, and exposure. By combining runtime visibility with AI-driven protection, Radware helps organizations detect and mitigate business logic attacks, embedded attacks, bot activity, automated abuse, HTTP DDoS attacks, and sensitive data exposure.
Key features include:
- Continuous API discovery across environments: Discovers APIs across modern application environments, including third-party, outdated, shadow, and deprecated APIs.
- Runtime API catalog and visibility: Provides a centralized view of API inventories, schemas, usage, workflows, configurations, and risk exposure based on live production traffic.
- Shadow and deprecated API detection: Identifies unmanaged, outdated, and deprecated APIs that may otherwise remain outside formal security controls.
- Runtime posture management: Prioritizes API risk using real-time analysis of production traffic, attacker behavior, business logic, and actual exposure.
- AI-driven runtime protection: Detects and mitigates business logic attacks, embedded attacks, API-focused bot attacks, automated abuse, and HTTP DDoS attacks.
2. Salt Security
Salt Security is an API security platform that focuses on continuous API discovery to expose the full API landscape and remove visibility gaps. It identifies documented and undocumented, internal, external, and third-party APIs and builds an inventory with context such as traffic behavior, parameters, and sensitive data exposure.
Key features include:
- Continuous and automated API discovery: Discovers APIs across internal systems, external services, and third-party integrations.
- API inventory with granular details: Captures metadata for each API, including parameters and usage patterns.
- Detection of undocumented APIs: Identifies APIs not registered in gateways or defined in specifications like OpenAPI.
- Shadow and zombie API identification: Finds deprecated, unknown, or untracked APIs.
- Sensitive data exposure visibility: Detects APIs that handle or expose sensitive data such as PII.
3. Traceable AI
Traceable AI is an API security platform that combines continuous API discovery with runtime visibility to provide a view of API ecosystems and risk posture. It discovers and catalogs APIs while mapping sensitive data flows across systems. By analyzing runtime behavior, user activity, and data movement, Traceable generates risk scores and highlights vulnerabilities in real time.
Key features include:
- Automatic and continuous API discovery: Discovers and inventories internal and external APIs in a centralized catalog.
- API catalog with data context: Builds an inventory that includes endpoints, usage details, and service relationships.
- Shadow and orphaned API detection: Identifies unmanaged APIs and alerts teams to changes.
- Runtime-based risk scoring: Assigns risk scores based on runtime data such as usage behavior and sensitive data flows.
- Sensitive data flow visibility: Maps how sensitive data moves across APIs, services, and data stores.
DevSecOps and API Testing-Oriented Discovery Tools
4. Akto
Akto is an API discovery platform that uses AI to identify and track APIs from source code to runtime. It provides visibility into internal, external, and third-party APIs, including REST, GraphQL, gRPC, and SOAP, across cloud and on-prem environments. By combining code analysis with traffic visibility, Akto builds a continuously updated API inventory.
Key features include:
- API discovery (code to runtime): Discovers APIs across source code and runtime traffic.
- API inventory across API types: Identifies internal, external, partner, and third-party APIs.
- AI-powered discovery: Uses automation to uncover APIs and adapt to changes.
- Detection of shadow APIs: Finds APIs created and used outside formal processes.
- Identification of zombie APIs: Detects outdated or abandoned API versions.
5. StackHawk
StackHawk is an API discovery solution that focuses on source code analysis to map the application attack surface before deployment. By integrating with code repositories, it identifies APIs, application components, and security-relevant changes during development.
Key features include:
- Source code–driven API discovery: Connects to repositories like GitHub, GitLab, and Bitbucket to analyze source code.
- Continuous repository scanning: Scans repositories and updates the inventory with each code commit.
- Comprehensive attack surface mapping: Identifies APIs, applications, and exposed components.
- Support for multiple API types and architectures: Detects REST, GraphQL, gRPC, and WebSocket endpoints.
- Early detection of shadow APIs: Discovers endpoints directly from code before production release.
6. Pynt
Pynt is an API security platform that combines automated API discovery with context-aware security testing. It identifies internal, external, and third-party APIs by aggregating data sources, including live traffic, and builds an up-to-date inventory.
Key features include:
- Automated and continuous API discovery: Discovers and tracks APIs across environments.
- Unified API inventory from multiple data sources: Combines inputs from sources including live traffic.
- Live traffic–based discovery: Uses traffic data collected through eBPF, mirroring, and proxies.
- Detection of shadow and unknown APIs: Identifies untracked or unmanaged APIs.
- Context-aware API security testing: Performs testing based on actual API behavior and context.
Enterprise API Management and Governance Platforms
7. Noname API Security
Noname API Security, now Akamai API Security, is an API security platform that delivers continuous API discovery, risk analysis, and runtime protection. It inventories APIs, including shadow and zombie endpoints, and provides visibility into API behavior, traffic flows, and data exposure.
Key features include:
- Automatic and continuous API discovery: Discovers and inventories APIs across environments.
- Comprehensive API inventory and classification: Tags and categorizes APIs, including shadow and zombie endpoints.
- AI and genAI API visibility: Identifies APIs connected to genAI models, LLMs, and MCP servers.
- Detection of shadow and unmanaged APIs: Uncovers APIs that are not properly tracked or documented.
- API vulnerability assessment (OWASP Top 10): Scans APIs for vulnerabilities and misconfigurations defined in the OWASP API Top 10.
8. MuleSoft Anypoint Platform
MuleSoft Anypoint Platform is an API management and governance solution that provides visibility, control, and lifecycle management for APIs and AI services. It enables organizations to discover and catalog APIs across environments while enforcing governance and security policies from a centralized control plane.
Key features include:
- API discovery and cataloging: Discovers and catalogs APIs across the organization.
- Unified API and AI governance: Applies governance policies to APIs, LLMs, and agent interactions.
- Centralized API management control plane: Manages and monitors APIs and agent traffic through a unified interface.
- Support for multiple architectures and protocols: Works across monolithic, microservices, and hybrid architectures.
- API catalog integration with CI/CD pipelines: Updates APIs through CI/CD workflows.
9. Apigee API Management
Apigee API Management is Google Cloud's platform for building, securing, and managing APIs with a proxy-based architecture. It places an API proxy layer between backend services and consumers, allowing organizations to control traffic and enforce security policies without modifying backend systems.
Key features include:
- API proxy layer for abstraction and control: Uses a proxy layer between clients and backend services.
- Granular security and traffic management policies: Applies controls such as authentication, rate limiting, quotas, and threat protection.
- Support for multiple API protocols: Supports REST, gRPC, SOAP, and GraphQL APIs.
- Decoupling of frontend and backend services: Separates API consumers from backend services using the proxy layer.
- API analytics and monitoring: Provides insights into API traffic, usage patterns, and performance.
Conclusion
API discovery tools are increasingly important as organizations expand their API ecosystems across cloud, hybrid, microservices, and AI-driven environments. Without continuous discovery, undocumented or outdated APIs can create major visibility and security gaps that are difficult to manage manually. Automated discovery helps organizations maintain an accurate inventory, strengthen governance, improve compliance, and reduce operational risk.