What CISOs Must Know About gRPC APIs
APIs are now the backbone of modern digital infrastructure. Over 55% of enterprises manage at least 500 APIs, and 60% of those APIs are updated weekly or monthly. For 21% of companies, APIs contribute more than 75% of total revenue.
At the same time, microservices and cloud-native architectures have gone mainstream, with 74% of organizations already using microservices and 89 % adopting containerized or serverless technologies.
But with this shift comes new challenges latency from chatty internal APIs, growing complexity across distributed systems, and limitations of traditional REST-based communication. As services multiply, performance and reliability start to suffer.
To meet these demands, more teams are turning to gRPC. Originally developed at Google, gRPC enables faster, more efficient service-to-service communication using a binary protocol over HTTP/2. It is built for the realities of modern software; low latency, high throughput, and strict contracts.
What is gRPC API?
gRPC is an open-source framework developed by Google that enables fast, efficient communication between distributed services. It uses the Remote Procedure Call (RPC) model to let applications call functions across different systems as if they were local.
Unlike traditional REST APIs that rely on JSON over HTTP/1.1, gRPC uses Protocol Buffers (Protobuf) for message serialization and HTTP/2 as the transport protocol. This combination reduces payload size, supports multiplexing, and enables features like streaming and bi-directional communication. gRPC is exceptionally well suited for high-performance internal APIs in microservices, where low latency, strong typing, and contract enforcement are critical.
Understanding Remote Procedure Calls (RPCs)
Remote Procedure Calls (RPCs) are a method of communication where one system executes a function on another system as if it were local. Instead of managing HTTP requests, parsing URLs, and handling status codes like with REST, RPC abstracts these complexities. The client simply calls a procedure and receives a response. This makes RPC ideal for structured, high-speed communication between services.
In the gRPC model, the server defines a service and its methods using Protocol Buffers, and the client uses generated code to call these methods directly. This tightly coupled design enforces clear contracts between services and ensures that both client and server understand the expected inputs and outputs. For modern microservice applications, RPC models like gRPC offer faster, more predictable inter-service communication with better developer ergonomics than traditional RESTful approaches.
Security platforms like Levo help ensure this communication remains secure by continuously validating behavior and detecting vulnerabilities across these tightly integrated services.
How does gRPC API work?
gRPC works by letting one service call another as if it were calling a local function, using a predefined contract. It simplifies how microservices talk to each other while ensuring speed, security, and consistency.
Here’s how it works, step by step:
1. Define the Contract Using Protocol Buffers
The process starts with a .proto file. This file defines the service, its methods, and the message types used by those methods. It acts as a shared contract between the client and the server.
Example: Imagine a payment service where one service needs to check a user’s account balance. The .proto file would define a method called CheckBalance with input and output messages.
2. Generate Code from the Contract
Using tools provided by gRPC, both the client and the server automatically generate code in their respective programming languages (e.g., Java, Go, Python) from the .proto file. This reduces human error and ensures consistency across teams.
Example: The CheckBalance method gets translated into a function the client can call and the server can implement, using strongly typed request and response objects.
3. Client Makes a Call Using gRPC Stub
The client uses the generated code (stub) to call CheckBalance just like a local function. Behind the scenes, gRPC uses HTTP/2 to send a binary-encoded request.
4. Server Processes the Request
The gRPC server receives the request, processes the logic (e.g., reads from the account database), and returns the result, typically much faster than REST thanks to HTTP/2 and compact message sizes.
5. Response is Delivered Over the Same HTTP/2 Connection
The server sends the response using the same persistent connection. HTTP/2’s multiplexing enables multiple gRPC calls to share a single connection, reducing latency and resource usage.
6. Security, Streaming, and Monitoring Options Apply
gRPC supports TLS encryption, request authentication, and observability integrations. It also supports streaming in both directions, which is helpful for real-time updates such as stock prices or chat apps.
gRPC Architecture: Components of gRPC APIs
Imagine a fintech platform with multiple microservices powering features such as payment processing, fraud detection, and transaction history. These services must communicate with high speed and precision. In a gRPC-powered setup, instead of relying on REST APIs with text-based JSON and manual contract validation, the platform uses gRPC to streamline service-to-service communication across secure, structured channels.
Here are the key components that make this architecture work:
1. Protocol Buffers (Protobuf)
Protobuf is the language-neutral schema definition format used by gRPC. Developers define services and message structures in .proto files, which are compiled into client and server code for multiple languages. Compared to JSON, Protobuf is smaller and faster, making it ideal for low-latency systems. For security and governance leaders, this means schemas are enforceable and standardized across all teams.
2. gRPC Client
In gRPC, the client behaves like a local function calling a remote service. It uses the generated Protobuf stubs to package requests and manage serialization automatically. In our fintech example, the payment gateway service might invoke a CheckFraud method on the fraud detection service with just a single line of code, and gRPC handles the rest behind the scenes.
3. gRPC Server
This is the backend service that implements the logic defined in the Protobuf interface. It receives serialized requests from clients, processes them, and sends responses back. The server enforces strict contract adherence, improving runtime safety. Levo helps secure these interactions by identifying authorization issues, misconfigurations, and vulnerabilities in gRPC request handling before production.
4. HTTP/2 Transport Layer
Unlike REST, which typically runs over HTTP/1.1, gRPC uses HTTP/2 for transport. This enables multiplexed streams, binary framing, and lower overhead, which significantly boost performance in distributed systems. It also supports bi-directional communication, making gRPC ideal for real-time features like streaming analytics or fraud alerts.
5. Interceptors (Middleware)
gRPC interceptors are like middleware, they allow teams to add custom logic (such as logging, monitoring, or authentication) before a call is sent or received. This is especially useful for enforcing security policies across services. Levo integrates into this layer to run real, attack-simulating payloads during development and runtime to proactively uncover weaknesses.
gRPC API Example
Imagine a customer applies for a personal loan through a bank’s mobile app. Behind the scenes, this action triggers a cascade of inter-service communication between various microservices such as:
- Loan Application Service: Collects the request and customer data.
- KYC Verification Service: Validates the applicant’s identity.
- Credit Scoring Service: Assesses financial risk using external APIs.
- Fraud Analysis Service: Screens for suspicious patterns in real time.
- Approval Engine: Makes a decision based on inputs from upstream services.
- Notification Service: Sends alerts about the application status.
In a REST-based system, each call would use verbose JSON payloads, with separate HTTP/1.1 connections and the overhead of parsing and processing. This creates latency, increases CPU cycles, and complicates error handling across chained dependencies.
With gRPC, each of these internal calls is executed as a remote procedure call over a single, persistent HTTP/2 connection. Data is exchanged in compact Protobuf format, and the .proto schema ensures that both the sender and receiver interpret data consistently. If the Fraud Analysis Service streams updates based on third-party risk feeds, gRPC enables efficient server-side streaming without polling.
Now let’s look at the architecture components that enable this flow:
- Client Stub: Auto-generated from the .proto file, the stub abstracts service logic and allows the Loan Application Service to call VerifyIdentity() or CheckCredit() as if they were local functions.
- Server: Each service (like KYC or Fraud Analysis) implements the server-side methods defined in the .proto file. The gRPC server receives requests, executes logic, and sends structured responses.
- Protocol Buffers (Protobuf): A highly efficient binary serialization format used to define message schemas and service contracts. Smaller and faster than JSON, Protobuf reduces payload size and improves performance.
- gRPC Channel: A long-lived HTTP/2 connection between client and server. It enables multiplexed calls, flow control, and header compression, minimizing network latency across all services.
- Interceptors and Middleware: gRPC supports hooks for authentication, logging, and telemetry. For regulated industries, this helps inject compliance checks and enrich security logs without rewriting core services.
Where Levo Adds Value
Because gRPC enables rapid inter-service communication, misconfigured authorization or data exposure can cascade quickly. Levo helps close that gap. Its API security testing engine analyzes .proto definitions, generates smart payloads, and tests each gRPC call across internal, external, and third-party APIs. It uncovers broken access controls, insecure data flows, and logic flaws that static policies miss, especially useful in fast-moving architectures like this one.
Characteristics of gRPC APIs
gRPC APIs offer a modern approach to service communication, purpose-built for speed, precision, and scalability. Below are the defining traits that distinguish gRPC from legacy protocols:
1. Protocol Buffers (Protobuf) as the Interface Language
Instead of JSON or XML, gRPC uses Protocol Buffers for defining API contracts. This ensures compact, fast, and strongly typed data exchange. Every field is validated against a shared .proto schema, reducing ambiguity and parsing errors across services.
2. HTTP/2 Transport Layer
gRPC runs over HTTP/2, enabling persistent, multiplexed connections between client and server. This allows multiple API calls to be sent over a single connection, reducing overhead and improving throughput.
3. Bi-Directional Streaming Support
gRPC enables real-time communication by supporting four API interaction types, including client streaming, server streaming, and full-duplex. This is essential for use cases such as telemetry collection, fraud monitoring, and chat systems.
4. Code Generation and Strong Typing
gRPC auto-generates client and server code in multiple languages from the .proto file. This accelerates development and enforces strict typing, reducing runtime errors and improving test predictability.
5. Contract-First Development
Every gRPC service starts with a .proto definition. This forces upfront clarity on what each API does, its input and output types, and its structure. As a result, gRPC APIs are easier to test, version, and govern, making them more secure by design.
6. High Performance at Scale
With binary serialization and persistent connections, gRPC consistently outperforms REST in terms of latency and payload size. In microservice architectures where hundreds of calls happen per request, these performance gains compound.
gRPC Method Types
gRPC supports four communication patterns that give engineering teams precise control over how services interact. These method types allow gRPC to support dynamic, real-time use cases with reduced complexity and performance overhead. Each type serves a distinct purpose in microservices and API infrastructure, especially where efficiency and observability are key for security leaders.
For modern enterprise security teams, adopting gRPC can reduce blind spots in service-to-service communication and enable faster, more contextual decision-making across APIs.
1. Unary RPC
A single request and a single response similar to a traditional REST API call.
Example: A payment gateway checks whether a customer has sufficient funds. The request includes the user ID and transaction amount, and the response confirms approval or denial. For CISOs, this pattern is common in policy validation, where high-frequency calls must be fast and deterministic.
2. Server Streaming RPC
The client sends a single request, and the server streams multiple responses back.
Example: A security operations platform queries threat intelligence from an upstream feed. Instead of waiting for the entire data set, it begins streaming results in real time. This reduces latency and enables teams to act faster on urgent threats, such as zero-day exploit indicators.
3. Client Streaming RPC
The client sends a stream of data to the server, followed by a single response.
Example: A telemetry agent sends security event logs (e.g., user logins, config changes) to a central analysis service. After receiving the full stream, the server returns a summary risk score or alert. For CISOs, this pattern helps consolidate signals from distributed sources without overwhelming the backend.
4. Bi-Directional Streaming RPC
Both client and server send messages continuously over a single connection.
Example: A fraud detection engine and a transaction processor exchange user behavior data in real time. The engine flags suspicious activity, and the processor immediately adjusts authentication flows. This is critical in sectors like banking, where milliseconds matter and preemptive defense is key.
Why use gRPC APIs?
gRPC is gaining adoption in enterprises because it addresses real challenges in building, scaling, and securing modern applications. From a security and performance standpoint, gRPC delivers clear advantages in critical areas.
1. High Performance and Low Latency
gRPC uses HTTP/2 and binary serialization (via Protocol Buffers), which significantly reduces payload size and speeds up communication. Unlike REST, which transmits verbose JSON over HTTP/1.1, gRPC streams compact messages over a single connection.
Scenario: In a microservices-based fraud detection system, where each transaction triggers dozens of API calls, gRPC ensures that these interactions happen in milliseconds. This keeps fraud checks fast without delaying user experience or increasing compute costs.
2. Strongly Defined Contracts
Using Protocol Buffers, gRPC enforces strict data contracts. This eliminates the ambiguity often seen in REST APIs, where JSON schemas may be loosely defined or missing altogether. For CISOs, this ensures consistency across environments and prevents accidental data exposure due to type mismatches.
Scenario: A healthcare provider must transmit patient records across services. gRPC’s type-safe contracts reduce the risk of serialization issues that might expose sensitive PHI.
3. Bi-Directional and Streaming Communication
gRPC supports full-duplex streaming, which is critical for real-time applications. Unlike REST, which handles one request and one response at a time, gRPC allows persistent connections and continuous data flow.
Scenario: A security incident response tool can stream threat detection events to a central platform while simultaneously receiving real-time remediation instructions. This shortens attackers' dwell time within systems.
4. Smaller Payloads, Less Overhead
gRPC messages are binary and highly efficient, reducing network strain and lowering cloud costs. For globally distributed apps, this makes a measurable difference in bandwidth consumption.
Scenario: An e-commerce platform with customers across regions uses gRPC between its inventory, pricing, and order systems to reduce latency and improve checkout speed without increasing network load.
5. First-Class Support for Polyglot Systems
gRPC is supported in multiple programming languages. It simplifies development across diverse teams and helps unify security policies across a mixed-language tech stack.
Scenario: A financial services firm has microservices written in Java, Go, and Python. gRPC lets them enforce consistent API definitions and authentication logic across services without complex translation layers.
When to use gRPC APIs: Use Cases
gRPC is not a one-size-fits-all solution, but it excels in environments where speed, efficiency, and precision are critical. Below are common enterprise-grade use cases where gRPC is the clear choice:
1. Internal Microservices Communication: In large-scale distributed systems, internal services often talk to each other hundreds or thousands of times per second. gRPC is built for this.
Example: A real-time analytics platform processes user behavior across dozens of services. gRPC enables these services to exchange compact, binary-encoded data rapidly, minimizing latency and infrastructure cost.
2. Low-Latency Financial Transactions: High-frequency trading, digital wallets, and payment processors rely on ultra-fast communication. gRPC’s binary format and multiplexing over HTTP/2 dramatically reduce request overhead.
Example: A fintech app uses gRPC between its authentication, risk scoring, and transaction services. This architecture keeps user approval times under 200 milliseconds, ensuring conversion without compromising security.
3. Streaming Data Applications: Applications that involve chat, telemetry, or media streaming benefit from gRPC’s bi-directional streaming.
Example: A cybersecurity operations center collects live logs and event data from endpoint agents. Using gRPC, the platform streams events continuously while sending back detection updates in real time.
4. Polyglot Environments: For enterprises with services written in different languages, gRPC offers a consistent API surface across the board.
Example: An insurance company with a claims service in Java, a billing engine in .NET, and a fraud detection module in Python adopts gRPC to maintain a single source of truth through a shared protobuf schema.
5. IoT and Edge Devices: gRPC’s lightweight payloads are ideal for devices with constrained bandwidth or CPU.
Example: A logistics company uses gRPC to relay telemetry from delivery trucks to a central fleet dashboard. This reduces data transmission costs while maintaining up-to-the-minute visibility.
gRPC API vs REST API
Here’s a quick comparison between gRPC and REST APIs across performance, usability, and operational dimensions to help assess which is better suited for your architecture:
Is gRPC API better than REST API?
Whether gRPC is “better” than REST depends entirely on the application context and the priorities of the business and engineering teams.
For internal microservices and performance-critical systems, gRPC is typically the better fit. A financial platform running fraud detection, transaction logging, and scoring engines can benefit from gRPC’s speed and efficiency. Its compact messages and HTTP/2 support reduce latency and resource usage, which are critical at scale.
REST remains ideal for public-facing APIs. A retail company that exposes product data or checkout endpoints benefits from REST’s compatibility with browsers, its ease of use with JSON payloads, and widespread tooling. It’s simpler to test, document, and integrate across teams.
Security also plays a role. REST works well with standard API gateways and WAFs. gRPC requires more tailored integration with observability and runtime protection tools.
Many organizations use both REST externally for accessibility and gRPC internally for performance. The right choice depends on the system’s architecture and communication needs.
gRPC API vs GraphQL
Here’s a quick comparison between gRPC and GraphQL APIs across performance, usability, and operational dimensions to help assess which is better suited for your architecture:
Is gRPC API better than REST API?
gRPC is often better for back-end service communication where speed, predictability, and streaming are priorities. For example, an identity verification platform calling real-time scoring, analytics, and database services can use gRPC to minimize latency and maximize throughput across services.
GraphQL shines when client flexibility is key. For instance, a media platform or mobile app team might use GraphQL to request exactly the data needed, nothing more, nothing less, streamlining UI performance and reducing over-fetching.
From a security and governance standpoint, GraphQL’s dynamic nature can increase complexity. Access control must be tightly scoped to avoid data leaks, and API protection tools need to understand query patterns deeply. gRPC, by contrast, operates on a strict service contract, making it easier to enforce access policies but harder to introspect with traditional tools.
In practice, many organizations use both GraphQL for frontend customization, gRPC for backend service calls. Choosing the right tool depends on the audience, performance needs, and the system's architecture.
gRPC API vs SOAP
When evaluating API protocols for different use cases, it is helpful to compare gRPC and SOAP in terms of performance, security, and operational fit to determine where each aligns best.
Is gRPC API better than SOAP API?
In modern cloud-native environments, gRPC is generally better than SOAP. It offers faster message exchange, better support for streaming, and a lighter payload structure. This makes it well-suited for performance-sensitive systems, such as financial trading backends or internal API calls across microservices, in high-load environments.
However, SOAP still holds ground in sectors like banking, government, and healthcare, where message reliability, transactional guarantees, and compliance with WS-* standards are non-negotiable. SOAP’s verbose structure and built-in features like WS-Security and XML encryption make it easier to pass audits in those contexts.
For example, a fintech firm modernizing its internal infrastructure may choose gRPC to replace SOAP-based inter-service calls, improving latency and scalability. But if it needs to interact with a government payment gateway still operating over SOAP, the team would continue using SOAP for that integration.
Ultimately, gRPC is a forward-looking technology built for modern distributed systems, while SOAP remains relevant in legacy ecosystems where strict compliance and structure matter more than speed. Organizations often maintain both, phasing out SOAP where feasible and introducing gRPC to accelerate internal innovation.
Key Features of gRPC APIs
gRPC’s design emphasizes speed, structure, and scalability, making it well suited for modern, distributed systems.
Below are its key features that help enable secure and efficient inter-service communication:
- High Performance with HTTP/2
gRPC uses HTTP/2, which allows multiplexing multiple requests over a single connection. This reduces network latency especially useful in high-throughput environments like digital banking platforms.
- Compact Binary Serialization (Protocol Buffers)
Unlike JSON, gRPC uses Protocol Buffers for message encoding, which shrinks payload sizes and speeds up transmission. In bandwidth-sensitive scenarios like IoT or mobile financial apps, this optimization matters.
- Strongly Typed Contracts
gRPC APIs are defined using .proto files, ensuring strict request/response formats. This minimizes integration issues between teams and services, supporting better governance in regulated environments.
- Bi-Directional Streaming
gRPC allows clients and servers to send and receive data streams simultaneously over one connection. For example, in fraud detection systems, real-time bidirectional updates between services improve response accuracy.
- Built-In Authentication Support
gRPC supports TLS encryption and can integrate with authentication systems like OAuth2 or mTLS. This enables secure communication, a critical requirement in sectors such as healthcare and fintech.
- Multi-Language Support
Developers can generate client/server code in multiple languages from a single .proto definition. This accelerates delivery across polyglot engineering teams without sacrificing consistency or security.
- Error Handling and Status Codes
gRPC standardizes error responses, making it easier to track and debug issues in distributed systems. This clarity improves reliability for both developers and incident response teams.
Benefits of using gRPC APIs
As modern architectures scale, organizations are adopting gRPC to solve performance and communication challenges across internal services.
Below are key benefits that make gRPC an attractive option for security and engineering leaders alike:
- High Performance with Lower Latency
gRPC uses HTTP/2 and binary serialization via Protocol Buffers, which makes message exchange faster and more efficient than JSON over HTTP. For example, a fintech platform handling hundreds of trades per second can reduce latency and improve user experience with gRPC.
- Bi-directional Streaming Support
Unlike REST, gRPC supports client-side, server-side, and full duplex streaming. This is essential for real-time apps like live dashboards, video conferencing, or telemetry systems where continuous data exchange is critical.
- Strong API Contracts via Protocol Buffers
gRPC enforces strict contracts through .proto files. This ensures better consistency and validation between services, reducing bugs caused by mismatched data formats, which is an important aspect when scaling securely across multiple teams.
- Built-in Code Generation for Multiple Languages
With gRPC, developers can automatically generate client and server code in multiple languages (Java, Go, Python, etc.), accelerating development in polyglot environments without compromising on consistency.
- Efficient Communication for Internal Microservices
In complex microservices environments where hundreds of internal calls are made for a single business transaction, gRPC minimizes communication overhead and ensures reliable performance.
- Better Use of Network and CPU Resources
gRPC’s compact binary messages reduce payload size, which means lower bandwidth usage and less CPU consumption. This is especially useful for edge deployments or services with high throughput demands.
- Support for Deadlines and Cancellation
gRPC includes built-in mechanisms for setting timeouts and canceling calls. This helps prevent cascading failures and resource hogging in distributed environments, which is critical for maintaining availability.
Limitations of using gRPC APIs
While gRPC brings impressive advantages, it is not a universal solution.
Below are some limitations that organizations should consider before adopting it, especially in complex, compliance-heavy, or public-facing environments:
- Browser Compatibility Is Limited
gRPC is not natively supported by most web browsers. This limits its use in public-facing web apps unless a gateway or REST proxy is introduced, which can add operational overhead.
- Steeper Learning Curve
Engineers unfamiliar with Protocol Buffers or strongly typed contracts may face an initial learning curve. This can slow onboarding and adoption across teams without prior RPC experience.
- Tooling and Debugging Complexity
Traditional REST tools like Postman or browser-based consoles are not fully compatible with gRPC out of the box. Teams must use specialized tools like grpcurl or BloomRPC, which can complicate debugging for security or QA teams.
- Limited Human Readability
Since gRPC uses a binary format, logs and payloads are not human-readable by default. This can impact threat analysis, monitoring, and forensics unless decoded or integrated into observability tools.
- Increased Setup Requirements for HTTP/2 and TLS
Deploying gRPC securely often requires explicit configuration of HTTP/2 and TLS across services, especially in on-prem or hybrid environments. This adds setup time compared to conventional REST services.
- More Complex Versioning and Backward Compatibility
Maintaining backward compatibility with gRPC services requires careful handling of .proto changes. This puts added pressure on version control, especially in regulated environments where breaking changes can disrupt dependent systems.
Challenges with gRPC Testing and its solutions
While gRPC delivers clear performance and architectural benefits, testing gRPC services poses unique challenges distinct from those of REST or traditional APIs. Security and engineering teams must plan accordingly to ensure gRPC APIs are robust, secure, and production-ready.
- Lack of Human-Readable Formats
gRPC uses Protocol Buffers instead of JSON, which are compact but not human-readable. This makes it harder for testers to inspect request and response payloads during debugging.
Solution: Use tools that support .proto files to automatically decode and visualize gRPC traffic. Platforms like Postman, BloomRPC, or language-specific libraries can bridge the gap for developers and QA teams.
- Limited Browser and Network Visibility
Unlike REST, gRPC over HTTP/2 is not natively supported by most browsers or traditional proxies. This limits visibility during manual testing and impedes network-based security inspection.
Solution: Use gRPC clients and proxy-compatible testing tools that can mirror real traffic. Teams should also integrate runtime observability platforms that track gRPC call paths, timing, and anomalies.
- Testing Stateful and Streaming Scenarios
gRPC supports streaming and bi-directional communication, which introduces challenges for validating stateful transactions or long-lived sessions.
Solution: Incorporate unit tests and contract tests that simulate streaming behavior. Load testing frameworks that support persistent connections (e.g., ghz or Gatling) are essential for validating real-time scenarios.
- Authentication and Authorization Testing
Many gRPC APIs implement token-based or mTLS authentication. Verifying correct handling of roles, privileges, and failed access scenarios is complex.
Solution: Use test harnesses that replicate different user roles and scenarios. Levo, for instance, enables continuous testing of authorization boundaries in gRPC APIs, detecting broken access controls and privilege escalation paths.
- Schema Drift and Undocumented APIs
Since gRPC relies on .proto files, outdated or missing files can cause schema drift between services and reduce test coverage.
Solution: Enforce version control and schema linting during CI. Runtime testing solutions like Levo can validate actual service behavior against contract definitions to surface mismatches early.
Best Practices for securing gRPC APIs
As gRPC adoption grows, so does its appeal to attackers. While gRPC introduces performance benefits, its use of HTTP/2 and binary payloads adds complexity for traditional security tools. To stay ahead, security leaders must ensure gRPC APIs are protected across development and production. The following best practices help build resilient, secure gRPC environments without sacrificing velocity.
- Enforce Strong Authentication and Authorization
Use mutual TLS (mTLS) to authenticate services and clients, preventing impersonation. At the application level, implement granular access controls that validate user roles for each service method. For example, in a fintech environment, a TransferFunds method should strictly check if the calling user is authorized for the destination account.
- Validate Protocol Buffers and Input Payloads
Never assume input safety. gRPC messages should be validated against the .proto schema to prevent deserialization attacks or malformed data from propagating through services. Schema validation should be implemented on both the client-side and the server-side to prevent misuse.
- Implement Logging and Observability at Method Level
Since gRPC messages are binary, standard HTTP logs do not provide visibility into them. Teams should instrument gRPC calls to capture metadata, status codes, and anomalous behaviors. For instance, an excessive number of failed CreateUser calls may indicate enumeration or abuse attempts.
- Enable Rate Limiting and Throttling
To prevent abuse, apply request rate limits at method level. gRPC's streaming nature makes it vulnerable to persistent connections that consume server resources. Rate limiting helps ensure system availability even under misuse.
- Harden Internal APIs Just Like External Ones
Many organizations assume gRPC APIs are “safe” because they are internal. This creates blind spots. All gRPC endpoints, regardless of exposure, should be tested for logic flaws, improper access, and data leakage risks. In regulated sectors, even internal misconfigurations can trigger compliance failures.
- Integrate Security Testing in CI/CD
Security should start early. gRPC APIs must be tested during development for vulnerabilities like insecure defaults, logic flaws, or broken authorization. Tools like Levo allow continuous testing of internal, partner, and public gRPC APIs using real payloads and user-role scenarios ensuring security evolves with the codebase.
- Use Centralized Service Governance
Establish a registry of all active gRPC services, their contracts, and permissions. A clear inventory prevents orphaned services and unmanaged dependencies. In a microservice environment, tracking who owns each gRPC service helps speed up response in case of vulnerabilities or incidents.
Implement complete API Security for gRPC API with Levo
gRPC APIs increase performance and efficiency, but they also demand security controls that match their speed and complexity. Traditional tools struggle to secure binary protocols, internal APIs, and dynamic inter-service communication. That’s where Levo steps in with purpose-built for modern API environments.
Levo helps enterprises secure their entire gRPC footprint by covering the full API security lifecycle from discovery to remediation. Here’s how:
- Discover and Inventory Every gRPC Endpoint
gRPC services often fly under the radar of conventional API management. Levo’s API Inventory capabilities continuously uncover internal, external, and third-party APIs, including undocumented or low-traffic gRPC services across cloud-native environments.
- Continuous API Detection
Levo’s API Detection automatically discovers and inventories every API endpoint including internal, third-party, partner, shadow, zombie, and undocumented APIs across all environments (dev, staging, production). This ensures full visibility over the entire API attack surface even before workloads are exposed, eliminating blind spots and giving security teams a complete catalog to monitor, secure, and manage.
- Map and Monitor Real-Time Behavior
Once discovered, API Monitoring tracks each gRPC method in production. It captures behavior patterns and flags anomalies like spikes in method calls or unusual data access. Sensitive Data Discovery ensures that gRPC payloads handling PII or regulated data are appropriately classified and monitored for policy violations.
- Auto-Generate and Auto-Update API Docs
Many teams struggle with outdated or missing .proto files. Levo’s API Documentation auto-generates and reconciles gRPC specifications based on live traffic eliminating guesswork and ensuring security policies remain aligned with actual behavior.
- Shift Left with Intelligent gRPC Testing.
Static scanners fall short on binary protocols and logic flaws. Levo’s API Security Testing runs continuous, context-aware security tests across development and staging environments.
It simulates real-world threat scenarios using actual user flows and service dependencies, detecting issues like Broken Object Level Authorization (BOLA) before they ship.
- Stop Attacks in Real Time
If a gRPC method begins leaking sensitive data or receives malformed inputs, Levo’s API Protection enforces behavioral guardrails. It blocks anomalous or high-risk requests with minimal disruption to service availability without relying on brittle signatures.
- Ensure Effective Remediation by Addressing Root Causes
Vulnerability Reporting links every discovered issue to the responsible service, code owner, and impacted data, enabling teams to prioritize based on actual business risk—not just CVE severity. Levo MCP Server enriches this further by correlating behavior across microservices to reveal downstream impact and lateral movement paths. This deep context empowers teams to remediate faster and address the root cause, ensuring vulnerabilities are fully closed rather than repeatedly resurfacing.
Conclusion
gRPC APIs have become the backbone of high-performance, modern applications. Their efficient binary format, strong interface contracts, and support for streaming make them ideal for service-to-service communication in cloud-native systems. But with that power comes new complexity. The same traits that make gRPC fast and scalable, such as protocol buffers, HTTP/2 multiplexing, and bi-directional communication, also make them harder to inspect, govern, and secure using traditional methods.
Legacy scanners and network-based monitoring tools were not designed for the nuances of gRPC. They often miss undocumented endpoints, cannot parse protobuf payloads, and fail to detect business logic or authorization flaws. In environments where API inventory changes frequently and internal APIs handle sensitive data, this creates security gaps and operational blind spots.
This is where Levo changes the equation. Enterprises can now discover, govern, and protect their gRPC APIs with a platform built specifically for modern architectures. Levo provides complete visibility across internal, external, and partner-facing APIs, automatically generating accurate inventories and documentation even when proto files are missing or outdated.
Through its governance modules, Levo maps sensitive data flows, tracks policy violations, and ensures authentication and authorization controls are enforced continuously. With runtime-aware testing and protection, Levo enables enterprises to secure their gRPC APIs across the full software development lifecycle, from CI and CD pipelines to production environments.
By combining shift-left testing with runtime protection and observability, Levo empowers organizations to maintain development velocity without compromising security. For enterprises investing in gRPC, adopting a context-aware and continuous security strategy is not just smart, it is essential. Levo ensures that your fastest services do not become your riskiest ones.
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