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Modern enterprises are undergoing rapid architectural change. More than 70% of large organizations now rely on microservices for critical workloads, which means thousands of internal service calls occur every second across hybrid and multicloud environments. Performance expectations continue to rise, and engineering teams have responded by adopting gRPC for its speed and efficiency. As adoption grows, gRPC endpoints are becoming essential infrastructure that supports core business operations.
This shift introduces a new responsibility for security and technology leaders. Research from the Cloud Native Computing Foundation reports that most organizations adopting microservices experience significant complexity in understanding how their services communicate. As environments scale, teams often lose full visibility into their internal service traffic, especially when protocols like gRPC are introduced to improve performance at scale. This lack of visibility creates strategic risk because even a single insecure gRPC endpoint can expose sensitive data or disrupt dependent services across the organization.
Teams cannot secure what they cannot see. Misconfigured gRPC services may expose data or functionality that was never meant to be public. Authentication and certificate management are inconsistent across teams. Auditing and testing coverage for gRPC traffic is often limited or absent. As companies scale, these gaps create operational drag, regulatory exposure, and in the worst cases direct business disruption.
CISOs and CIOs need an approach that protects performance without slowing innovation. This requires understanding what gRPC endpoints are, how they are discovered, and how to secure them with strong policy and continuous validation.
What are gRPC Endpoints?
A gRPC endpoint is a network interface through which a gRPC service accepts incoming Remote Procedure Call (RPC) requests. In gRPC, services are defined using the Interface Definition Language (typically Protocol Buffers) and compiled into client and server code stubs. A gRPC endpoint specifies the listening host and port on which the server waits for gRPC clients to call its exposed methods.
In effect, gRPC endpoints provide a formal, high performance, language agnostic API surface for internal or external service communication, with clear interface definitions, cross language clients, and support for advanced features such as streaming, efficient serialization, and low latency.
gRPC Endpoints Example
A practical way to understand a gRPC endpoint is to see how it appears in a real production environment. Consider a payment platform that uses a dedicated fraud detection service, similar to the scoring systems used by large financial institutions. The service exposes a gRPC endpoint at fraud service dot internal on port 5051. The service publishes a FraudCheck RPC through its Protocol Buffers contract. This contract defines the request message, which includes fields such as transaction amount, merchant category, and device fingerprint, and the response message, which contains a numeric risk score and decision flags.
The gRPC server binds this contract to a concrete service implementation and listens for incoming calls over HTTP version two with TLS enabled. The payment gateway uses a generated gRPC client to serialize a FraudCheck request into Protocol Buffers, negotiate the TLS session, and stream the request to the server. The server evaluates the transaction using its machine learning model and returns the score with millisecond latency. This is the same pattern used across many large scale environments, including internal scoring engines, routing services, and telemetry pipelines at cloud providers.
This simple endpoint represents concentrated operational and security risk. If certificate validation is disabled, if the endpoint is exposed to unauthorized internal networks, or if the FraudCheck RPC lacks strict authentication, an attacker could submit forged transactions for scoring or probe the service for model behavior.
For executives, the lesson is clear. A gRPC endpoint is not just a technical detail. It is a well defined API surface that carries business critical logic and must be governed with the same level of scrutiny applied to external services. The fraud scoring example shows how a single endpoint can deliver performance gains and architectural efficiency while also requiring disciplined controls to prevent financial exposure and operational disruption.
Finding gRPC Endpoints
Unlike traditional REST APIs that are often documented through gateways or API inventories, gRPC services can be deployed deep inside distributed systems with very little centralized visibility. They may run inside Kubernetes clusters, on virtual machines, in serverless environments, or behind internal load balancers where discovery tools have limited reach.
In a typical enterprise, gRPC endpoints are defined in service configuration files, container orchestration manifests, or Protocol Buffers repositories. Teams often assume these locations represent a complete inventory, yet production environments evolve quickly. Services scale horizontally, endpoints shift during redeployments, and engineering teams introduce new RPC methods without updating documentation. This is why many organizations struggle to maintain a reliable map of their internal gRPC surface area.
Finding gRPC endpoints generally comes down to three technical approaches that complement each other. Each one solves a different part of the visibility problem.
1. Static discovery through source and configuration analysis
Engineering and security teams review Protocol Buffers definitions, service configuration files, and deployment descriptors such as Kubernetes manifests or Terraform modules. This reveals the endpoints a service intends to expose and the RPC methods it declares. Static discovery is valuable for understanding design intent, but it does not confirm whether an endpoint is currently deployed, reachable, or configured correctly in production.
2. Runtime discovery using platform level telemetry
To identify what is truly active in the environment, teams rely on cluster introspection tools, service mesh metadata, and workload level observability. These tools surface real listening ports, active TLS certificates, service identities, and live RPC methods. This is the model used by modern service mesh platforms that automatically detect running gRPC endpoints as workloads come online.
3. Traffic based discovery through network and application analytics
Even with static and runtime data, organizations often need to analyze actual traffic flows to understand how services interact. By inspecting RPC call patterns, teams can determine which clients call which methods, how frequently they call them, and whether any undocumented or deprecated endpoints are still in use. Cloud providers and distributed tracing systems rely heavily on this method to build accurate real time service inventories.
Together, these three approaches give organizations a complete view of their gRPC footprint. One shows what should exist, one shows what does exist, and one reveals how it is really being used. For leaders, this combined visibility is essential for governance, incident response, and risk reduction.
Securing gRPC Endpoints: Approaches
Securing gRPC endpoints requires controls that match both the performance characteristics of gRPC and the business critical nature of the services they expose. Because gRPC endpoints often handle internal system to system communication, teams sometimes assume implicit trust. In practice, this assumption has proven risky as environments scale, teams decentralize, and trust boundaries blur across cloud, hybrid, and partner networks.
Effective security programs typically rely on three complementary mechanisms. Each addresses a different layer of risk, and together they form a defensible control model.
Access Control Lists (ACLs)
Access Control Lists are one of the earliest and most widely understood mechanisms for restricting service access. In a gRPC context, ACLs define which clients, service identities, or network segments are allowed to invoke specific endpoints or RPC methods. These rules are often enforced at the infrastructure layer through service meshes, API gateways, or network policy engines rather than inside application code.
From a business perspective, ACLs support segmentation and least privilege. A fraud detection service, for example, may allow calls only from the payment gateway and settlement systems while denying all other internal traffic. This reduces blast radius if credentials are compromised or a downstream service is misconfigured. However, ACLs alone do not provide strong identity assurance. They control who can connect, not necessarily who is making the request.
As organizations grow, ACLs can also become difficult to manage consistently. Without centralized governance, rules tend to drift, creating gaps that weaken the intended security posture.
JSON Web Tokens (JWTs)
JSON Web Tokens are commonly used to authenticate and authorize gRPC clients at the application layer. In this model, a client presents a signed token as part of the gRPC metadata with each request. The server validates the token, verifies its issuer and signature, and evaluates claims such as service identity, role, or scope before executing the requested RPC.
JWT based authentication provides strong identity context and scales well across distributed systems. It allows organizations to enforce fine grained access controls tied to business logic rather than just network location. For example, a fraud scoring endpoint may accept calls only from clients with a specific role claim, regardless of where they run.
The operational challenge lies in token lifecycle management. Expired tokens, misconfigured issuers, or inconsistent validation logic can introduce outages or security gaps. From an executive standpoint, JWTs are powerful but require disciplined key management and standardized enforcement to avoid fragmentation across teams.
TLS certificates
Transport Layer Security is foundational to securing gRPC endpoints. Because gRPC runs over HTTP version two, TLS is the standard mechanism for encrypting traffic and authenticating servers and clients. Most production deployments rely on mutual TLS, where both sides present certificates and verify each other’s identity before any RPCs are exchanged.
TLS certificates provide confidentiality, integrity, and strong service identity. They are widely used in regulated industries and are supported natively by gRPC frameworks, cloud platforms, and service meshes. In practice, certificate based authentication is often the first line of defense against unauthorized access to internal services.
The business risk emerges when certificate management is treated as a one time setup rather than an ongoing process. Expired certificates, shared private keys, or disabled verification settings have contributed to multiple service outages and security incidents. Executives should view certificate governance as an operational control that directly affects uptime, trust, and compliance.
Testing gRPC Endpoints
Testing gRPC endpoints focuses on validating how real clients interact with real services under realistic conditions. Unlike traditional web APIs, gRPC endpoints expose strongly typed RPC methods rather than URLs, which means effective testing must operate at the protocol and business logic level rather than relying on surface level scanning.
Step One: Identify the gRPC Endpoint and Its Contract
Testing begins with understanding what the endpoint exposes. Each gRPC endpoint is defined by a Protocol Buffers contract that specifies available RPC methods, required inputs, and expected responses. For example, a fraud detection service may expose a FraudCheck method that accepts transaction details and returns a risk score.
From a security perspective, this contract defines the attack surface. It tells testers which fields can be manipulated, which data types are expected, and which methods represent sensitive business actions. Reviewing this definition is essential before any meaningful testing can begin.
Step Two: Establish Authenticated Client Context
Most production gRPC endpoints require authentication through TLS certificates, tokens, or both. Testing must mirror this reality. A test client should be configured with the same credentials and identity types used by legitimate services.
Using the fraud scoring grpc endpoint example, a tester may authenticate as the payment gateway service and submit a valid FraudCheck request. This confirms baseline functionality and establishes a reference point for further testing. From there, the same request can be sent using different identities or reduced permissions to validate that access controls are enforced correctly.
Step Three: Send Realistic and Manipulated Payloads
Effective testing of gRPC endpoints requires sending payloads that reflect real business usage. This includes valid requests as well as intentionally manipulated inputs. Fields such as transaction amount, account identifiers, or customer metadata should be altered to test how the service handles edge cases and unexpected values.
For example, a tester might submit a FraudCheck request with mismatched account identifiers or extreme transaction values to observe how the service responds. This approach surfaces logic flaws and validation gaps that protocol level scans cannot detect.
Step Four: Test Multi Call Workflows
Many gRPC endpoints are part of larger workflows rather than isolated operations. Testing must reflect this by executing sequences of calls that mirror real business processes. A single fraud check may be followed by an authorization decision, a settlement request, or an audit log update.
Security testing should validate whether access control decisions remain consistent across these steps. By replaying workflows with different identities, testers can uncover hidden authorization weaknesses that only appear when state is carried across calls.
Step Five: Validate Enforcement and Failure Behavior
Testing gRPC endpoints is not only about successful responses. It is equally important to observe how endpoints fail. Testers should confirm that unauthorized requests are rejected cleanly, sensitive data is not leaked in error messages, and rate limits or abuse protections activate as expected.
From an executive viewpoint, this step provides assurance that failures are controlled and predictable rather than chaotic or exploitable.
Step Six: Automate and Repeat Continuously
Finally, testing gRPC endpoints must be automated and repeated as services evolve. Each deployment, schema change, or access control update should trigger the same set of tests. Automation ensures that security validation keeps pace with delivery velocity and does not depend on manual effort.
Organizations that operationalize this approach gain continuous visibility into the security posture of their gRPC endpoints. Testing becomes a routine part of service delivery rather than a reactive exercise after incidents or audits.
gRPC Endpoints Testing Best Practices to follow
Testing gRPC endpoints effectively requires more than validating availability or protocol compliance. Because gRPC is commonly used for business critical internal services, testing practices must reflect how these endpoints are built, deployed, and used in production environments. The following best practices represent what mature organizations apply at scale.
Test gRPC Endpoints Continuously
gRPC endpoints change as often as the services behind them. New RPC methods are introduced, existing ones evolve, and access controls are adjusted as business logic grows. Testing gRPC endpoints only once a quarter or during periodic assessments leaves long gaps where vulnerabilities can exist unnoticed.
Best practice is to test gRPC endpoints continuously as part of the deployment lifecycle. Each build or release should automatically trigger security testing so changes are evaluated immediately. This approach aligns security validation with how modern engineering teams deploy software and significantly reduces exposure windows.
Use Offensive Testing With Real Payloads
Basic scans and crawlers can confirm that a gRPC endpoint exists, but they are not capable of uncovering most real world vulnerabilities. Effective testing must be offensive in nature and reflect how attackers interact with APIs.
This means sending actual payloads that are customized to the Protocol Buffers schema and API parameters. Requests should include valid data, malformed data, and edge case values that stress business logic. This approach exposes validation flaws, logic errors, and authorization weaknesses that passive techniques consistently miss.
Test Access Control Across Multi Call Workflows
Access control failures in gRPC environments rarely appear in a single call. Business operations often span multiple RPCs where each step relies on state established by earlier interactions. Vulnerabilities such as Broken Object Level Authorization and Broken Authentication and Function Level Authorization only surface when full workflows are exercised.
Strong testing validates how identities and permissions behave across sequences of calls. By executing the same workflow with different roles or service identities, teams can identify hidden authorization paths that would otherwise remain invisible.
Automate Everything End to End
For testing gRPC endpoints to scale, it must be fully automated. This includes endpoint inventory discovery, payload generation, test execution, and result analysis. No part of the process should depend on manual security bandwidth.
Automation ensures coverage keeps pace with deployment velocity and removes human bottlenecks. It also provides leadership with consistent and repeatable assurance that all gRPC endpoints are being tested uniformly across the environment.
Validate Failure and Enforcement Behavior
Testing should confirm not only that authorized requests succeed but also that unauthorized or malformed requests fail safely. gRPC endpoints should reject invalid calls cleanly, avoid leaking sensitive information in error responses, and enforce rate limits or abuse protections where applicable.
This practice helps ensure predictable behavior during misuse or attack scenarios and reduces the risk of cascading failures.
Treat gRPC Endpoints as First Class APIs
A final best practice is cultural as much as technical. gRPC endpoints should be treated with the same rigor as external APIs. They carry business critical logic, process sensitive data, and often sit on key transaction paths. Testing programs should reflect this importance rather than assuming internal usage implies lower risk.
Challenges faced during gRPC Endpoint Testing and its solutions
While the importance of testing gRPC endpoints is increasingly clear, many organizations struggle to implement these practices effectively. The challenges are not theoretical. They stem from the complexity of modern service architectures and the limitations of manual security processes. Understanding where these efforts break down helps clarify why automation is no longer optional.
Challenge: Rapid Change and Service Sprawl
gRPC endpoints evolve continuously as services are deployed, scaled, and updated. New RPC methods appear, schemas change, and endpoints are moved or replicated across environments. Manually tracking these changes is impractical, especially in organizations operating hundreds of services.
Solution: Automated discovery and inventory management are required to maintain an accurate view of all active gRPC endpoints. Automation ensures that new endpoints are detected as soon as they are deployed and included in testing workflows without human intervention.
Challenge: Manual Payload Creation Does Not Scale
Creating realistic test payloads for gRPC endpoints requires understanding Protocol Buffers schemas, field constraints, and business logic. Doing this manually for each service is slow, error prone, and difficult to repeat consistently across teams.
Solution: Automated payload generation based on service contracts allows testing to scale with the environment. By deriving inputs directly from Protocol Buffers definitions, organizations can ensure coverage across all RPC methods while eliminating dependence on manual effort.
Challenge: Multi Call Workflow Testing Is Hard to Replicate
Many of the most serious access control vulnerabilities only appear across sequences of RPC calls. Manually orchestrating these workflows using different identities and permission levels is time consuming and often incomplete. As a result, hidden authorization flaws remain undetected.
Solution: Automated workflow testing enables repeatable execution of multi call sequences with controlled identity variations. This allows organizations to systematically identify issues such as Broken Object Level Authorization and Broken Authentication and Function Level Authorization without relying on ad hoc testing.
Challenge: Continuous Testing Overwhelms Security Teams
Testing gRPC endpoints continuously requires coordination across development, security, and platform teams. When testing relies on manual execution or periodic assessments, security teams quickly become a bottleneck and coverage degrades.
Solution: Fully automated testing pipelines integrate directly into deployment workflows. This removes security bandwidth as a limiting factor and ensures that testing keeps pace with delivery velocity.
Challenge: Inconsistent Enforcement and Visibility
Manual testing often produces fragmented results that are difficult to compare or trend over time. Leadership lacks a clear view of which gRPC endpoints are tested, which controls are enforced, and where risk is accumulating.
Solution: Automation provides consistent execution and centralized visibility. Results can be aggregated across services and environments, giving executives a reliable view of risk posture and progress.
Implement complete gRPC API Security Testing with Levo
Implementing effective gRPC API security testing is difficult not because teams lack intent, but because the requirements exceed what manual processes and traditional tools can support. gRPC endpoints evolve continuously, rely on strongly typed contracts, and often participate in complex multi call workflows. Levo addresses these challenges by grounding security testing in real runtime behavior rather than static assumptions.
Runtime Driven Discovery and Context
Levo begins by establishing an accurate testing foundation. It automatically discovers and documents all APIs, including gRPC endpoints, by observing live traffic rather than relying on documentation alone. This allows Levo to map sensitive data flows and access paths as they actually exist in production environments. As a result, testing reflects real service behavior rather than intended designs that may be outdated or incomplete.
For gRPC endpoints, this runtime context is critical. It ensures that Protocol Buffers contracts, RPC methods, and parameter usage are understood in the context of how services truly communicate.
Endpoint Specific Payload Generation for gRPC
Levo generates custom security payloads for every endpoint it discovers, including gRPC endpoints, using runtime derived insights. Payloads are tailored to the specific parameters, data types, and access patterns of each RPC method. This enables testing across common vulnerability classes, injection vectors, and business logic abuse scenarios that generic scanning tools are not capable of detecting.
This approach aligns directly with the need for offensive testing using real payloads that mirror attacker behavior rather than relying on superficial protocol validation.
Access Control Testing Across Roles and Workflows
One of the most difficult aspects of testing gRPC endpoints is validating access control across multi call workflows. Levo automates this process by simulating real world role abuse. It tests for privilege escalation, IDOR, and BOLA by combining role mapped logic, parameter mutation, and token manipulation. Levo can detect real user data from runtime traffic and safely use it to build test payloads that reflect how attackers exploit authorization gaps across service interactions.
This capability allows organizations to uncover hidden access control vulnerabilities without manually orchestrating complex workflows or maintaining multiple test accounts.
Authentication Automation Across Schemes
gRPC environments commonly rely on diverse authentication mechanisms such as JWTs, OAuth2, API keys, and mutual TLS. Levo automatically detects the authentication scheme in use and handles token generation, injection, and renewal. This allows security tests to execute successfully across environments without manual configuration or developer assistance.
For CISOs, this removes a major operational bottleneck and ensures that security testing remains continuous even as authentication models evolve.
Continuous and Comprehensive Coverage
Levo supports continuous security testing aligned with modern deployment velocity. Test schedules, intervals, and scopes can be configured centrally, allowing organizations to validate gRPC endpoints as they change. Levo also provides coverage for internal and imported APIs, ensuring that gRPC services are tested with the same rigor as externally exposed endpoints.
Real time debug logs and simplified retesting enable teams to quickly validate fixes without rerunning entire test suites, improving both efficiency and signal quality.
Conclusion
As gRPC endpoints increasingly power critical internal and external services, organizations can no longer rely on fragmented or periodic security testing. Levo stands out as the most automated and comprehensive API security testing platform by unifying depth, frequency, and coverage into a single continuous system. By testing significantly more APIs than manual approaches at a fraction of the operational cost, Levo removes the traditional tradeoff between speed and security and allows teams to ship confidently at modern deployment velocity.
From a business perspective, this level of automation translates directly into measurable outcomes. Continuous security validation eliminates late stage surprises, reduces incident response costs, and shortens integration timelines. Secure APIs are integrated faster, generate revenue sooner, and avoid the downstream costs associated with compliance failures, remediation delays, and operational disruption. By embedding security testing directly into delivery workflows, Levo turns security from a bottleneck into a growth enabler.
Beyond testing, Levo protects APIs including gRPC APIs end to end through a complete platform approach. Its API inventory and discovery capabilities give organizations a continuously updated view of every gRPC endpoint across internal, external, and partner environments. API documentation and monitoring provide ongoing visibility into how services behave as schemas and traffic patterns evolve. Sensitive data discovery and vulnerability reporting surface real risk where it matters most, grounded in live usage rather than assumptions.
At runtime, Levo adds continuous threat detection and protection to close the gap between visibility and enforcement. It detects anomalous behavior, authorization abuse, and exploit attempts as gRPC traffic flows through production systems, then applies precise, policy driven protections to stop real attacks without disrupting legitimate services. Governance is enforced continuously through runtime aware controls, ensuring access, authentication, and data flows remain aligned with business intent across environments.
Together, Levo’s API protection, API security testing, API detection, inventory, monitoring, documentation, sensitive data discovery, vulnerabilities reporting, modules provide a unified system of record and control for modern APIs. For CISOs and technology leaders, this means stronger security posture, smoother audits, faster delivery, and sustained business resilience as gRPC and API driven architectures continue to scale.
