Protecting GraphQL APIs against OWASP Top 10 Vulnerabilities

APIs are now central to digital business. They power customer experiences, partner ecosystems and AI driven automation. In 2024, analysts reported that API calls made up more than 71% of all web traffic, and 65% of organizations generate revenue directly from APIs. A single data breach now averages nearly $4.9 million globally and more than $9 million in the United States. For security leaders, this makes API protection a priority, directly tied to business continuity and revenue preservation.

API security is no longer something that can be approached with traditional web security tools. Most legacy controls cannot interpret the business logic that APIs expose and therefore fail to detect the authorization flaws, misconfigurations and logic abuses that dominate modern attacks. As companies adopt GraphQL, the challenge intensifies. GraphQL introduces flexibility and efficiency for development teams, but it also increases the risk of over exposure of data and unintended access paths. Without appropriate safeguards GraphQL endpoints can become attractive targets for attackers who seek to exploit structural weaknesses or query complexity.

This is where the OWASP API Security Top Ten becomes essential. It provides a focused framework for understanding the most critical risk categories affecting modern APIs, including GraphQL. The list highlights systemic issues such as broken object level authorization, excessive data exposure, unrestricted resource consumption and unsafe dependencies. These vulnerabilities have contributed to real world breaches across industries, and they represent the core threats that security leaders must address to protect business value.

As organizations modernize their software delivery, they need security solutions that can keep pace with the scale and speed of API driven architectures. Protecting GraphQL APIs through the OWASP API Security Top Ten lens establishes a clear, actionable foundation for reducing risk and strengthening operational resilience.

What is a GraphQL API?

A GraphQL API is a query language and runtime designed to give clients more control over the data they request. Instead of relying on fixed endpoints, a client sends a structured query that specifies precisely what information is needed. The server responds with a single, predictable result that matches the query's shape. This approach reduces over fetching and under fetching, improves performance for modern applications and allows development teams to evolve APIs without creating a large number of new versions.

GraphQL has become popular because it simplifies integration across mobile apps, web applications, microservices and AI driven systems. It allows teams to expose complex data models through a unified schema and to iterate quickly as business requirements change. With GraphQL, clients can retrieve multiple resources in a single request and tailor responses to the needs of specific user experiences or workloads.

While this flexibility is valuable, it also introduces new security considerations. A single GraphQL endpoint can touch many backend systems and datasets, which means a single query can access more information than intended if proper controls are not in place. Query customization, schema introspection and resolver complexity create opportunities for attackers to discover sensitive paths or craft expensive queries that strain infrastructure. As a result, GraphQL requires deliberate governance, authorization checks and resource controls to ensure that its benefits do not introduce unintended exposure.

Does OWASP API Security Top Ten apply to GraphQL Endpoints?

GraphQL introduces a modern and flexible way to retrieve data, but it also amplifies several of the risks outlined in the OWASP API Security Top Ten. 

Because a single GraphQL endpoint can reach many backend systems and return large volumes of data, weaknesses in authorization, validation or configuration can have broader impact than in traditional REST services.

1. Object level authorization remains the most critical concern. OWASP identifies this issue as the top API vulnerability, and it appears in GraphQL when resolvers return data without verifying that the requester has the necessary permissions for the object. A simple query for a customer record by ID can return another user’s information if these controls are missing. 
2. Property level authorization also matters. Since GraphQL lets clients shape the response, sensitive fields may be exposed unless explicitly restricted in the schema or the resolver logic.
3. Resource exhaustion is another critical category. GraphQL allows deeply nested or computationally expensive queries that can overwhelm backend systems if complexity limits and depth controls are not enforced. This aligns with OWASP’s focus on unrestricted resource consumption and highlights the need for strong governance of query behavior.
4. In addition, misconfigurations and unsafe integrations can surface when schemas proliferate or when resolvers rely on upstream services that have not been validated. These issues align directly with OWASP categories such as security misconfiguration and unsafe API consumption.

Taken together, these patterns show why the OWASP API Security Top Ten is a critical guide for evaluating GraphQL environments. It surfaces the structural weaknesses that matter most and gives security leaders a clear path for strengthening controls before they affect customers or operations. For organizations expanding their use of GraphQL, this framework helps ensure that growth remains secure, predictable and aligned with business priorities.

Applying the OWASP API Security Top Ten to GraphQL

Since the relevance of the OWASP API Security Top Ten to GraphQL is clear, the next step is to use the framework to evaluate real risk across schemas, resolvers, and backend integrations. 

GraphQL introduces unique patterns that require organizations to think beyond endpoint security and instead focus on how data is modeled, requested and executed across the entire API landscape. Applying the OWASP framework helps teams identify where the most meaningful weaknesses may exist and what controls should be prioritized to protect sensitive operations.

A practical way to apply the OWASP categories is to examine how GraphQL structures access control. GraphQL consolidates many operations into a single interface, which means authorization, data exposure, resource usage and integration hygiene must be validated at a more granular level. Object access, property exposure, mutation behavior, query cost and upstream dependencies all become points where OWASP vulnerabilities can surface. Using the OWASP Top Ten as a lens gives security leaders a structured way to pinpoint these intersections and evaluate whether current policies and checks are sufficient.

The table below summarizes how several of the OWASP categories typically appear in GraphQL environments and where organizations should focus their assessments. It provides a starting point for teams to build internal standards, security reviews, and automated controls.

Common GraphQL APIs Vulnerabilities and Attacks identified by OWASP

GraphQL reduces the number of endpoints that organizations must maintain, but this consolidation also means that weaknesses in authorization, schema design or resolver behavior can have wide reaching impact. The OWASP GraphQL Security Cheat Sheet highlights several categories of vulnerabilities that map directly back to the OWASP API Security Top Ten. The following issues are among the most common and should be prioritized in any GraphQL security review.

1. Excessive Data Exposure and Property Level Access Issues: Because GraphQL allows clients to request the exact fields they want, sensitive attributes may be exposed unless explicitly protected. Attackers often experiment with field combinations to see what else the schema will return.

Example:

A customer calls a GraphQL query for their account details, but includes additional fields such as isAdmin, creditLimit, or internal support notes. If the resolver does not filter or authorize these fields, the response may reveal unintended information.

This aligns with OWASP category API3, where sensitive properties are accessible even when object access is correctly enforced.

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2. Broken Object Level Authorization (BOLA): Even when field exposure is restricted, attackers may still gain access to another user’s data by manipulating identifiers. Since many GraphQL operations rely on IDs passed directly in the query, resolvers must enforce authorization at every access point.

Example:

A malicious user submits a query such as

query { order(id: "87501") { item price status } }

If the resolver returns this order without checking ownership, the attacker may gain access to another customer’s transaction history. OWASP identifies BOLA as the most frequent API vulnerability across all API styles.

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3. Query Abuse and Resource Exhaustion: GraphQL allows nested and expansive queries that can generate a large amount of backend work. Attackers often craft intentionally complex queries to overload databases or application servers.

Example:

An attacker issues a deeply nested query such as retrieving a customer’s orders, each order’s items, each item’s supplier, and so on. Without limits on complexity or depth, the system may experience degraded performance or even downtime.

This behavior maps directly to OWASP API4, which concerns unrestricted resource consumption.

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4. Function and Business Logic Abuse: GraphQL mutations can perform sensitive operations. If role checks or business rules are missing, attackers can trigger unauthorized actions or alter important records.

Example:

A mutation such as

mutation { updateUser(id: "42", role: "Admin") }, should only be accessible to privileged users. If a resolver executes this without verifying permissions, attackers may escalate privileges or modify core business data. This aligns with OWASP API5.

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5. Insufficient Input Validation and Injection Risks: Although GraphQL reduces some forms of injection risk, resolvers may still pass unvalidated data to backend systems. Attackers can craft malicious inputs that reach databases, search engines or third party services.

Example:

A search query that forwards user input to an Elasticsearch backend may allow query manipulation if the resolver does not properly sanitize the value.

This is related to OWASP API10, which states that unsafe consumption of APIs or services exposes the system to injected payloads.

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6. Schema Introspection Exposure: Introspection is a useful development feature because it lets clients inspect available types and operations. When enabled in production, it provides attackers with a full map of the API including sensitive fields, internal mutations or administrative operations.

Example:

An attacker runs a query like { __schema { types { name fields { name } } } } to identify a mutation that resets user passwords or accesses internal account data.

This is a form of misconfiguration, aligning with OWASP API8.

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7. Resolver Chaining and Hidden Access Paths: GraphQL allows resolvers to call other resolvers or backend systems. If internal relationships are not secured, attackers may reach data through indirect paths that developers did not anticipate.

Example:

A user should not be allowed to see payroll data. However, by querying a related object, such as a department or manager, the user may indirectly retrieve salaries if the resolver for that related object exposes more than expected.

This aligns with issues described in OWASP categories around insufficient authorization and unsafe consumption of internal services.

Finding GraphQL endpoints and securing them.

For many organizations the first challenge in securing GraphQL is simply knowing where it exists. GraphQL often appears as part of new product features, internal tools, partner integrations or front end modernization efforts. Because it typically runs behind a single endpoint and can be embedded within multiple services, it is easy for teams to deploy GraphQL without formal discovery or inventory processes. A structured approach to identifying and securing these endpoints helps prevent blind spots that attackers can exploit.

Step 1: Establish Visibility Across All Environments

GraphQL endpoints may exist in production, staging, legacy systems or shadow environments created during rapid development cycles. Discovery should include traffic analysis, codebase inspection and API gateway review. GraphQL patterns, such as POST requests with query or mutation fields, can help identify endpoints even when documentation is incomplete. Visibility is critical because many attacks succeed by targeting APIs that were never formally cataloged.

Step 2: Map Schemas and Data Exposure

Once endpoints are identified, organizations should map the GraphQL schema and understand the objects, fields and relationships it exposes. Schema introspection, when enabled, provides a full view for defenders, but it should be restricted in production to prevent attackers from gaining the same insight. Mapping schemas allows security teams to identify sensitive fields, high value business operations and data flows that require stronger controls.

Step 3: Evaluate Authorization and Access Controls

GraphQL consolidates many operations into a single interface, so access control cannot be applied once at the endpoint level. It must be validated across objects, fields and mutations. Organizations should assess how resolvers enforce authorization and whether sensitive data can be reached through alternate paths. This step aligns directly with OWASP categories such as broken object level authorization, property level access issues and broken function level authorization.

Step 4: Implement Resource Governance

Because GraphQL allows complex nested queries, rate limits and resource controls are essential. Security teams should evaluate whether query depth, cost metrics, and rate limiting policies have been applied consistently. This protects availability and ensures that intentionally heavy queries cannot degrade performance for users or downstream systems.

Step 5: Secure Backend Integrations and Dependencies

GraphQL resolvers often interact with multiple databases, microservices or external APIs. Organizations should review these integrations for proper input validation, error handling and dependency security. This protects against misconfigurations, unsafe API consumption, and lateral exposure, all of which OWASP highlights.

Step 6: Monitor Runtime Behavior

Even with strong design controls, attackers often probe GraphQL endpoints with unusual queries, field combinations or access patterns. Continuous monitoring helps detect these behaviors early. Tracking resolver activity, query frequency, access patterns and anomaly indicators enables teams to respond before issues escalate.

Automated Testing of GraphQL Endpoints

As organizations expand their use of GraphQL, manual security testing becomes difficult to scale. GraphQL schemas change frequently, new fields and mutations are introduced at high velocity and backend integrations evolve as products mature. Automated testing provides a consistent and repeatable way to validate security controls and identify vulnerabilities before they reach production. It also helps security and engineering teams maintain coverage across complex GraphQL environments without slowing development.

Step 1: Automate Schema and Field Level Analysis

Automated tools can parse the GraphQL schema to identify sensitive fields, high risk operations and unexpected exposure paths. This includes detecting fields that should not be publicly available, mutations that alter business critical data and relationships that allow indirect access to sensitive resources. Automated schema analysis helps teams catch exposure issues early and ensure that new additions do not introduce unreviewed risk.

Step 2: Test for Authorization Weaknesses

Because GraphQL consolidates many operations into a single endpoint, automated testing should verify authorization at the object, property and function levels. This includes checking whether unauthorized users can access IDs, request restricted properties or invoke sensitive mutations. Automated tests are especially effective at detecting broken object level authorization and broken property level authorization, two of the most common issues identified by OWASP.

Step 3: Evaluate Query Behavior and Resource Limits

Automated testing can simulate realistic and malicious queries to determine whether the endpoint properly enforces depth limits, cost thresholds and rate limits. This helps identify opportunities for resource exhaustion, excessive backend calls or denial of service. Testing query behavior under load provides insight into how GraphQL will operate under real world traffic patterns or attack scenarios.

Step 4: Validate Input Handling and Error Responses

GraphQL resolvers frequently interact with databases, legacy systems and external APIs. Automated testing can check whether inputs are properly validated, sanitized and handled across these boundaries. Tools can also analyze error messages to ensure they do not leak sensitive information or reveal internal system details that could help attackers map the environment.

Step 5: Test Resolver Paths and Business Logic

Automated workflows can explore the different execution paths within resolvers, validating that business rules and contextual checks are enforced consistently. For example, a mutation that updates financial data should confirm the user's role, account ownership, and transaction context. This type of testing helps identify business logic flaws that traditional vulnerability scanners are not designed to detect.

Step 6: Integrate Testing Into CI and CD Pipelines

To keep pace with modern development, automated GraphQL security tests should be triggered for each code change and deployment. This ensures new schemas, resolvers or third party integrations are evaluated before they reach production. CI driven testing reduces reliance on periodic audits and provides immediate feedback to developers, improving both speed and security.

Remediation and Testing Strategies for securing GraphQL APIs against OWASP Vulnerabilities

Identifying vulnerabilities is only the first step. Securing GraphQL requires organizations to adopt consistent remediation practices and testing workflows that align with how GraphQL structures data, handles requests and interacts with backend systems. 

The strategies below map directly to the OWASP API Security Top Ten and illustrate how to strengthen GraphQL security with clear, practical examples.

1. Strengthen Object Level Authorization (OWASP API1)

GraphQL gives clients the ability to reference objects by ID, but resolvers cannot assume that a valid identifier equals valid access. Authorization decisions must be enforced for every object returned, regardless of how the query is constructed.

Remediation Example:

Suppose a user sends a query such as:

query { order(id: "1002") { total status } }

To prevent unauthorized access, the resolver should:

• Verify that the authenticated user is associated with order 1002
• Ensure the requester’s role permits viewing order information.
• Validate that the ID refers to an existing record belonging to the requester’s scope.

This prevents attackers from modifying the ID value to retrieve another customer’s data.

Testing Strategy:

Automated tests should attempt ID enumeration, referencing orders or objects belonging to other accounts. Any resolver that returns data without confirming object ownership should be flagged immediately.

2. Restrict Property Level Exposure (OWASP API3)

GraphQL’s flexibility allows clients to request any field available in the schema. This becomes risky when sensitive fields are unintentionally exposed or when internal attributes are not properly restricted.

Remediation Example:

Consider an object type that includes fields such as internalNotes, creditLimit, or isAdmin. These fields may support internal workflows, but should not be returned through public APIs. Remediation involves:

• Removing sensitive fields from the publicly exposed schema
• Applying field level authorization in resolvers
• Designing allowlists that return only approved properties

This ensures the API cannot accidentally leak sensitive attributes.

Testing Strategy:

Automated tests should query objects with all known fields and confirm that sensitive or internal only attributes are either removed from the schema or blocked by authorization rules.

3. Enforce Query Depth and Complexity Limits (OWASP API4)

Because GraphQL allows nested queries, attackers often create intentionally heavy requests to exhaust system resources. Depth and complexity controls are critical to preventing these performance based attacks.

Remediation Example:

A malicious actor might attempt a query that recursively requests relationships, such as retrieving users, their orders, each order’s items and the suppliers for every item. Without controls, such a query can overload database and application layers.

Effective remediation includes:

• Setting a maximum query depth
• Applying cost based scoring rules
• Limiting query batching and concurrency
• Implementing rate limits for expensive operations

These guardrails ensure that unexpected or malicious queries cannot degrade service.

Testing Strategy:

Automated tests should generate deeply nested and high cost queries to confirm that the system rejects or throttles them before they reach backend services.

4. Protect Sensitive Mutations With Role and Context Checks (OWASP API5)

Mutations can create, update or delete data, which makes them high value targets for attackers. Robust authorization must extend beyond roles to include context, business logic and data ownership.

Remediation Example:

Consider a mutation such as:

mutation { updateUserRole(id: "42", role: "Admin") }

Before executing this action, the resolver should:

Validate that the requester is authorized to assign roles

• Confirm that the requester has the correct hierarchy or scope to modify the target user.
• Enforce business rules, such as requiring approval flows for privileged changes.
• This prevents unauthorized privilege escalation and protects business critical operations.

Testing Strategy:

Automated mutation testing should attempt to perform sensitive changes with insufficient roles or incorrect context. Any mutation that succeeds without proper validation represents a significant risk.

5. Harden Schema Configuration and Environment Settings (OWASP API8)

Misconfigurations frequently create exploitable openings in GraphQL systems. Because GraphQL exposes schema details and resolver behaviors, configuration hygiene must be tightly controlled.

Remediation Example:

An organization using GraphQL in production should:

• Disable schema introspection unless explicitly required
• Minimize detailed error responses that reveal resolver paths or backend models
• Validate schema stitching or federation rules to ensure internal services are not unintentionally exposed
• Review default behaviors in GraphQL libraries that might create permissive access

These steps reduce the amount of information attackers can gather and prevent accidental exposure.

Testing Strategy:

Automated tests should verify whether introspection is accessible, confirm that error messages are sanitized and check whether internal schema details can be inferred from external queries.

6. Validate Data From Backend and Third Party Services (OWASP API10)

GraphQL resolvers often rely on data from microservices, external APIs or partner systems. If these inputs are not validated, they can introduce vulnerabilities such as injection risks, data corruption or unexpected behavior.

Remediation Example:

If a resolver retrieves product data from a third party service:

• Validate the structure and type of the returned data.
• Sanitize any fields that may influence database or search queries.
• Implement fallback logic for malformed or unexpected responses.
• Confirm that the upstream service has its own authentication and rate limiting.

This closes gaps that arise when GraphQL trusts external systems too broadly.

Testing Strategy:

Automated tests should simulate unexpected or malformed responses from upstream services and verify that resolvers handle them safely and consistently.

Best Practices to Implement Complete GraphQL Security

To build a robust, production-grade GraphQL API, organizations must go beyond ad-hoc fixes and embed security as a foundational part of the API lifecycle. The practices below combine authorization, input validation, schema design, resource controls and operational hygiene, wrapped in real-world examples that make the abstract concrete.

1. Enforce Strong Authentication and Authorization

GraphQL should only be accessible to authenticated clients, and every resolver must verify that the requester has the right to access or modify the data involved. Aligning authorization with both user identity and business context prevents accidental exposure through GraphQL’s flexible query structure.

Practical Example:

A login mutation issues a short lived token that encodes user roles. Every resolver then reads this token and verifies whether the requester can view or modify the object in question. For example, a user should only see their own orders and only administrators should access user-management mutations.

2. Apply Input Validation and Use Strict Schemas

GraphQL inputs can influence underlying systems, so validation must be explicit. Defining strict input types and expected formats helps ensure that only well formed data flows into backend services.

Practical Example:

If a mutation accepts an email or age value, enforce custom scalar validation to check formatting, range, or integrity. Invalid or malformed inputs should be rejected outright rather than passed through to databases or downstream systems.

3. Limit Query Complexity, Depth and Rate

GraphQL’s ability to nest queries creates opportunities for attackers to overload backend systems. Controls that manage query cost and execution help protect availability.

Practical Example:

Set a maximum depth on all queries, calculate the estimated cost of each request based on field complexity and limit the rate of requests per user or token. This prevents a single high cost query from degrading service or causing avoidable downtime.

4. Minimize Exposure Through Careful Schema Design

Schemas evolve, but they should never expose fields or operations that are not intended for public access. Treat your schema as a contract and rigorously separate the internal from the external.

Practical Example:

Fields such as auditTrail, internalNotes, or riskScore should not appear in public schemas. Disable schema introspection in production to prevent attackers from mapping the entire API. Expose only what client applications need for business functionality.

5. Secure Backend Integrations and Dependencies

GraphQL often consolidates data from multiple services. Each backend or third party integration becomes part of the trust boundary and must be validated accordingly.

Practical Example:

If a resolver calls a pricing service or recommendation engine, validates the structure and types of the returned data, ensures errors are handled safely and enforce authentication on any internal service GraphQL depends on. Avoid passing user supplied values directly to external URLs or queries.

6. Monitor and Audit GraphQL Activity Continuously

Since all GraphQL operations pass through a single endpoint, visibility becomes essential. Logging and runtime monitoring help detect anomalies early.

Practical Example:

Track the types of queries users send, their depth, their cost and their response times. Alert on unusual activity, such as repeated failed mutations, high cost queries, or attempts to request restricted fields. Periodically review schema changes and access rules to ensure consistency over time.

7. Integrate Security into CI and CD Workflows

GraphQL evolves rapidly, so manual reviews alone cannot keep up. Embedding automated security tests into development pipelines ensures each schema update or resolver change is evaluated before reaching production.

Practical Example:

Trigger automated authorization tests, input validation tests and complexity checks whenever a developer modifies the schema. Enforce known query allow-lists for public clients so only approved operations can run in production.

Implement complete GraphQL API Security beyond OWASP with Levo

Protecting GraphQL APIs requires more than meeting the OWASP API Security Top Ten baseline. Because a single GraphQL endpoint can access many objects, fields and backend systems, organizations need continuous visibility, rigorous testing and real time protection across the entire API lifecycle. Levo delivers this by combining automated discovery, comprehensive security testing, sensitive data mapping, runtime threat detection and inline protection to secure GraphQL environments at scale.

Below is a practical view of how Levo strengthens GraphQL security across each OWASP API Top Ten category.

API1:2023 Broken Object Level Authorization (BOLA)

GraphQL resolvers are especially vulnerable to BOLA because attackers can manipulate object identifiers in queries or nested fields.

How Levo Secures This:

Levo automatically tests the authorization scheme for every object and field exposed through GraphQL. It simulates real attack patterns, such as ID manipulation, sequential enumeration, and nested object traversal, to confirm that resolvers enforce proper access controls. If an object appears accessible through any query path without the correct permissions, Levo flags it immediately.

Example:

If a malicious user alters a query to order(id: "1002") and the resolver returns another customer’s order, Levo detects the unauthorized access path and classifies it as a critical BOLA issue.

Outcome:

Organizations eliminate the most common and high impact GraphQL vulnerability.

API2:2023 Broken Authentication

Because GraphQL consolidates many operations behind a single endpoint, missing or weak authentication puts large portions of the API at risk.

How Levo Secures This:

Levo discovers and maps the authentication scheme used by every GraphQL endpoint. It highlights endpoints that lack authentication, expose sensitive data without identity checks or rely on misconfigured tokens. Levo also tests authentication behavior such as token expiration, replay handling and credential misuse.

Example:

If a GraphQL endpoint serving account data is accessible without a valid token, Levo identifies the gap and provides remediation guidance.

Outcome:

Authentication failures are detected early, dramatically reducing the attack surface.

API3:2023 Broken Object Property Level Authorization (Excessive Data Exposure)

GraphQL’s flexibility often reveals more fields than intended unless resolvers enforce strict rules.

How Levo Secures This:

Levo performs property level tests across the schema to identify sensitive fields, internal attributes and hidden properties that are exposed through the API. It validates whether role and context checks prevent unauthorized access to specific fields within an object.

Example:

If a user requests fields such as isAdmin, internalNotes or creditLimit that should not be available externally, Levo detects the exposure and pinpoints the resolver responsible.

Outcome:

Sensitive attributes remain protected even when object level access is enforced correctly.

API4:2023 Unrestricted Resource Consumption

Deeply nested or high cost GraphQL queries can overload backend systems.

How Levo Secures This:

Levo conducts automated rate limit and resource consumption testing to identify endpoints that can be stressed by heavy queries. It simulates nested queries, bulk retrievals and expensive mutations to uncover potential denial of service risks.

Example:

If a deeply nested query overwhelms a database or causes unbounded resolver chaining, Levo surfaces the vulnerability along with detailed execution traces.

Outcome:

Organizations reinforce GraphQL performance and availability under malicious or unexpected load.

API5:2023 Broken Function Level Authorization

Mutations that modify data or trigger workflows require strict control.

How Levo Secures This:

Levo maps authentication and authorization schemes for every mutation and tests whether role checks, ownership rules and business conditions are properly enforced. If any mutation can be executed without the correct privileges, Levo catches it both during testing and at runtime.

Example:

A mutation such as updateUserRole(id: "42", role: "Admin") should never be accessible to a basic user. Levo detects the unauthorized execution path and surfaces it as a critical risk.

Outcome:

Unauthorized business actions are blocked before they can impact operations or data integrity.

API6:2023 Unrestricted Access to Sensitive Business Flows

GraphQL often exposes high value flows such as payments, account linking or password resets.

How Levo Secures This:

Levo automatically discovers sensitive data flows across GraphQL fields, resolvers and backend calls. It identifies endpoints that handle PII, financial data or credentials, and validates whether the authentication scheme is appropriate. At runtime, Levo detects and blocks attempts to exfiltrate sensitive data.

Example:

If a resolver moves PII to a third party service without proper controls, Levo alerts the team and provides details on the data, endpoint and misuse pattern.

Outcome:

Critical business flows remain secure, compliant and fully monitored.

API7:2023 Server Side Request Forgery (SSRF)

GraphQL resolvers may call external systems, making them vulnerable to SSRF if user-controlled inputs are passed to backend requests.

How Levo Secures This:

Levo performs preproduction SSRF testing by injecting potential SSRF payloads into relevant fields and validating how backend calls behave. It identifies resolvers that pass untrusted input into URL builders, HTTP clients or cloud metadata endpoints.

Example:

If a resolver fetches product details from a user-supplied URL, Levo simulates SSRF patterns and checks whether internal endpoints become reachable.

Outcome:

Resolvers cannot be exploited to pivot into internal networks or sensitive services.

API8:2023 Security Misconfiguration

GraphQL is highly configurable, and insecure defaults often go unnoticed.

How Levo Secures This:

Levo continuously detects misconfigurations such as exposed schema introspection, missing TLS enforcement, overly permissive CORS policies, weak authentication configurations or unprotected mutations. It alerts teams with actionable remediation steps.

Example:

If introspection is left enabled in production, Levo flags the exposure and identifies which schema elements attackers can see.

Outcome:

Misconfigurations are corrected before they become exploitable.

API9:2023 Improper Inventory Management

Shadow GraphQL endpoints and undocumented fields pose a long term risk.

How Levo Secures This:

Levo automatically builds a complete API inventory using traffic analysis, code scanning and log correlation. This inventory includes every GraphQL query, mutation, field and resolver, even if undocumented or hidden behind internal services.

Example:

If a legacy GraphQL endpoint still exists behind a service mesh and exposes outdated business logic, Levo discovers it and adds it to the inventory for assessment.

Outcome:

Nothing in the GraphQL ecosystem remains invisible or untested.

API10:2023 Unsafe Consumption of APIs

GraphQL resolvers often rely on upstream microservices or external APIs.

How Levo Secures This:

Levo detects all internal, external and third party APIs consumed by GraphQL resolvers and maps what data is shared with them. It flags insecure dependencies, missing authentication, unvalidated responses and any sensitive data that flows to external systems.

Example:

If a resolver sends customer data to an external recommendation engine without adequate validation or encryption, Levo surfaces the issue and provides remediation guidance.

Outcome:

Organizations gain full control over how GraphQL interacts with internal and third party ecosystems.

Conclusion

Protecting GraphQL APIs against the OWASP API Security Top Ten is not a not a point in time problem. The vulnerabilities outlined by OWASP span discovery gaps, design flaws, misconfigurations, business logic weaknesses, and runtime abuse. Addressing them effectively requires a coordinated approach that operates before deployment, during operation, and at the moment of attack. This is where Levo’s unified security model becomes essential.

Levo’s Proactive module establishes the foundation. By delivering continuous visibility through automated API inventory, rich documentation and sensitive data discovery, organizations gain a complete understanding of their GraphQL attack surface. This is paired with rigorous security testing that identifies broken authorization, authentication gaps, data exposure and resource abuse risks early. Together, these capabilities ensure vulnerabilities are detected and remediated before they reach production.

The Governance module ensures that security does not degrade as GraphQL environments evolve. Continuous monitoring provides real time awareness of how APIs are being used, how data flows across systems, and where configurations or access patterns drift from defined policy. This layer helps teams surface OWASP API Top Ten risks early by enforcing consistent controls and highlighting deviations as they occur, rather than relying on periodic reviews or static controls.

Risks as they emerge, rather than relying on periodic reviews or static controls.

Finally, Levo’s Runtime Detection and Blocking module closes the loop. When attacks occur, Levo detects them in real time and enforces inline protection to block malicious behavior before data is exposed or services are disrupted. This ensures that OWASP vulnerabilities are not only discovered and fixed, but actively prevented from being exploited.

Beyond standard OWASP coverage, Levo also enables organizations to define bespoke security controls that reflect their unique risk profile. Security teams can create custom security tests, threat detection rules, and blocking policies tailored to specific applications, environments, or industries. Using flexible policy definitions, teams can encode internal governance standards and continuously evaluate live API traffic against them. This ensures protection remains current even as APIs, teams and business requirements change.

Taken together, Levo delivers a comprehensive and adaptive approach to GraphQL API security. By unifying visibility, testing, governance and runtime protection, it enables enterprises to detect, remediate and block OWASP API Top Ten vulnerabilities immediately while maintaining the flexibility to address emerging threats and organization-specific risks. This holistic model enables GraphQL innovation to scale securely without compromising trust, resilience, or business outcomes.