What is API Security

API security has shifted from a specialist concern to a board-level risk topic because APIs increasingly carry the most valuable assets in modern software: identity context, business operations, and sensitive data. When breaches occur, the economics are rarely abstract. IBM’s Cost of a Data Breach Report 2024 estimates the global average total cost of a breach at USD 4.88 million, driven heavily by business disruption and post-breach response activities.

At the same time, the operational environment around APIs is changing. Postman’s State of the API 2025 highlights a security concern that is specifically tied to how APIs are being used in production today: 51% of developers worry about unauthorized or excessive API calls from AI agents, alongside concerns about improper sensitive data access and leaked credentials. These patterns matter because they increase the volume, speed, and automation of API interactions, including interactions that look legitimate at the transport and authentication layers.

For more than a decade, analysts have also warned that API abuse would become a dominant breach pathway for enterprises. Gartner’s strategic planning assumption that API abuse would move from infrequent to a primary attack vector is widely cited in industry analyses and has proven directionally accurate as APIs expanded across customer-facing products, partner ecosystems, and internal platforms.

This is why API security is best understood as a control discipline rather than a product category. It is the combination of governance, engineering practices, and enforcement mechanisms that prevent unauthorized access, reduce data exposure, constrain abuse, and provide evidence when incidents occur.

What API Security Means in Modern Enterprises

In modern enterprises, API security refers to the controls and practices used to protect APIs as execution surfaces for business logic and data, rather than as simple integration points. APIs increasingly sit at the center of digital platforms, enabling customer transactions, partner access, internal service communication, and automation at scale. Securing them requires more than transport encryption or authentication alone.

An API typically exposes a narrowly scoped operation, such as retrieving account details, updating an order, or triggering a workflow. While these operations appear technical, they directly correspond to business actions. As a result, failures in API security often lead to concrete outcomes such as unauthorized fund transfers, exposure of personal data, manipulation of records, or abuse of operational processes. The security objective is therefore not only to block access, but to ensure that only the right actor can perform the right action on the right data, under the right conditions.

API security operates across several dimensions simultaneously. It includes identity and access controls to verify who or what is calling an API, authorization logic to determine what that caller is permitted to do, and data protection measures to limit what information is returned or modified. It also includes protections against misuse patterns that are not strictly malicious, such as excessive automation, scraping, or logic abuse that exploits how an API was designed to behave.

Unlike traditional web applications, APIs are designed for machine consumption. They are invoked programmatically, often at high frequency, and frequently without a human in the loop. This characteristic makes APIs highly scalable, but it also reduces the effectiveness of controls that rely on user interaction or visual inspection. As enterprises adopt microservices, event-driven architectures, and AI-powered systems, the number of APIs grows rapidly, along with the complexity of their interactions.

For this reason, API security should be understood as an ongoing operational discipline. It spans design decisions made during development, enforcement mechanisms applied at runtime, and monitoring practices that validate how APIs are actually used in production. Treating API security as a one-time configuration task or as a feature of a single tool leaves critical gaps, particularly as APIs evolve faster than traditional security review cycles.

Why APIs Introduce Unique Security Risks

APIs introduce security risks that differ fundamentally from those found in traditional user-facing applications because they expose direct, programmatic access to business functions and data. While web applications mediate user behavior through interfaces, APIs accept structured requests that are often trusted by design to represent legitimate system interactions.

One of the primary risk factors is the reliance on machine-to-machine communication. API calls are typically authenticated using tokens, keys, or certificates and then processed without additional human validation. Once an API accepts a request as authenticated, it often executes the requested operation in full. This model creates a narrow margin for error. Small flaws in authorization logic, parameter validation, or object ownership checks can be exploited repeatedly and at scale.

APIs also tend to expose fine-grained business operations rather than coarse application flows. An individual endpoint might retrieve a single record, update a specific field, or trigger a downstream workflow. Attackers do not need to compromise an entire application to cause harm. They only need to identify one endpoint where access controls are incomplete or assumptions about caller behavior do not hold. This makes APIs particularly susceptible to logic abuse that appears valid at the protocol and authentication layers.

Another contributing factor is excessive data exposure. APIs are often designed to be flexible and reusable, returning structured responses that include more data than a specific client strictly requires. Over time, as new consumers are added and requirements change, responses may expand without corresponding reviews of data sensitivity. This increases the likelihood that personal, financial, or internal data is unintentionally exposed to callers who should not have access to it.

Finally, APIs evolve rapidly and are frequently deployed independently of traditional release cycles. New endpoints, parameters, and versions may be introduced without comprehensive security review, particularly in organizations practicing continuous delivery or operating large microservice environments. This velocity makes it difficult to maintain an accurate understanding of which APIs exist, who uses them, and how they behave in production. As a result, security controls can lag behind real-world usage.

These characteristics combine to create a risk profile where attacks are less noisy, harder to distinguish from legitimate traffic, and capable of causing significant business impact before they are detected.

API Security Control Objectives

At an enterprise level, API security is most effective when it is framed around control objectives rather than individual tools or vulnerabilities. Control objectives define what an organization is trying to protect and enforce, regardless of how APIs are implemented or which technologies are in use.

The first objective is identity assurance. Every API call must be attributable to a known and verifiable actor, whether that actor is a human user, a service account, or an automated agent. This includes validating credentials, tokens, or certificates and ensuring that identity information cannot be forged, replayed, or misused across contexts.

Closely related is authorization enforcement. Authentication alone is insufficient if APIs do not consistently verify what an authenticated caller is allowed to do. Authorization controls must ensure that each request is evaluated against object ownership, role permissions, and contextual constraints. This is particularly important for APIs that operate on individual records or trigger business actions.

Another core objective is data exposure minimization. APIs should return and accept only the data required for a specific operation, and nothing more. This applies to response payloads, request parameters, and metadata. Excessive data exposure increases both the blast radius of a breach and the likelihood of unintentional data leakage during normal operation.

Integrity and abuse prevention form a fourth objective. APIs must be protected against manipulation that alters business outcomes without violating technical rules. This includes preventing mass assignment, parameter tampering, replay attacks, and automated abuse that exploits how workflows are designed to function. These risks often emerge only when APIs are exercised at scale.

Finally, enterprises require observability and evidence. Effective API security includes the ability to understand how APIs are actually used in production, to detect anomalous or policy-violating behavior, and to produce reliable evidence during incident response, audits, or regulatory inquiries. Without this visibility, organizations may meet design-time requirements while remaining exposed to runtime failures.

Together, these control objectives provide a stable framework for evaluating API security posture across different architectures, teams, and stages of the software lifecycle.

Common API Attack Classes

API attacks tend to exploit gaps in authorization logic, data handling, and business rule enforcement rather than weaknesses in transport or cryptography. Many of the most damaging incidents involve requests that are syntactically valid, authenticated, and processed exactly as designed, but in ways the system did not intend.

Broken Object Level Authorization (BOLA) is one of the most prevalent API attack classes. It occurs when an API exposes object identifiers, such as user IDs, order numbers, or document references, without consistently verifying that the caller is authorized to access the referenced object. In these cases, changing a single parameter in a request can grant access to another user’s data or actions. BOLA exploits are difficult to detect because each request often appears legitimate in isolation.

Insecure Direct Object Reference (IDOR) is closely related and is sometimes used interchangeably with BOLA, though IDOR is often discussed more broadly across web applications. In API contexts, IDOR typically manifests when endpoints rely on client-supplied identifiers without enforcing ownership or role-based checks at runtime. This can result in unauthorized reads, updates, or deletions of sensitive resources.

Mass assignment vulnerabilities arise when APIs automatically bind client-provided input to internal data models without restricting which fields can be set. Attackers can manipulate request payloads to modify attributes that were not intended to be user-controllable, such as account roles, pricing fields, or status flags. Because mass assignment often leverages standard serialization behavior, it can persist unnoticed across multiple endpoints.

Schema abuse and parameter tampering involve sending requests that technically conform to the API’s schema but violate business expectations. This includes supplying unexpected values, abusing optional parameters, or chaining requests in ways that expose edge cases. These attacks frequently bypass perimeter defenses because they do not violate protocol-level rules or trigger signature-based detections.

Beyond these categories, APIs are increasingly targeted for automation-driven abuse, including scraping, credential stuffing against token endpoints, and high-frequency logic exploitation. These patterns blur the line between misuse and attack, especially when they originate from authenticated clients or internal services.

Collectively, these attack classes highlight a central challenge of API security: many failures are not the result of missing encryption or authentication, but of incomplete or inconsistent enforcement of authorization and business rules at runtime.

How API Security Is Traditionally Implemented

Enterprises typically implement API security by layering controls across infrastructure, identity systems, and application logic. These controls are often distributed across multiple teams and tools, each addressing a specific aspect of API exposure.

A common foundational control is the use of API gateways. Gateways act as centralized entry points for API traffic and are responsible for routing requests, enforcing basic policies, and integrating with authentication mechanisms. They often provide rate limiting, request validation, and logging capabilities. In many organizations, gateways also serve as the primary mechanism for publishing and versioning APIs.

Web Application Firewalls (WAFs) are frequently deployed alongside gateways or at the network edge. WAFs focus on filtering malicious traffic patterns, blocking known attack signatures, and enforcing protocol-level correctness. When configured for APIs, they may validate request formats, inspect headers, and apply rules designed to detect common exploitation techniques. Their effectiveness depends heavily on the quality of rules and the visibility they have into API semantics.

Identity and access management systems play a central role in API security by issuing and validating credentials such as OAuth tokens, API keys, or certificates. These systems establish who or what is calling an API and provide claims or attributes that downstream services can use for authorization decisions. In practice, authentication is often centralized, while authorization logic is implemented within individual services.

At the application layer, service-level authorization checks enforce business rules. Developers are responsible for ensuring that each endpoint validates object ownership, role permissions, and contextual constraints before executing an operation. These checks are typically embedded in code and may vary significantly across teams and services, depending on development practices and frameworks.

Finally, organizations rely on logging and monitoring tools to track API activity and investigate incidents. Logs may capture request metadata, response codes, and error conditions, while monitoring systems alert on availability or performance issues. Security-relevant insights are often inferred indirectly from these signals rather than observed explicitly.

While these mechanisms form the backbone of traditional API security programs, they are often implemented independently and evaluated in isolation. This fragmentation makes it challenging to understand how APIs behave as a system, particularly as environments scale and evolve.

API Security Across the Lifecycle: Design, Build, Run 

Effective API security cannot be confined to a single phase of development or operation. In enterprise environments, APIs are designed, implemented, deployed, and evolved continuously. Security controls must therefore span the entire lifecycle, with clear ownership and accountability at each stage.

Design Phase

During the design phase, API security focuses on defining contracts and expectations. This includes specifying authentication requirements, authorization models, and data schemas, as well as documenting which consumers are permitted to access which operations. Design-time decisions determine how granular endpoints are, how object identifiers are exposed, and how errors are handled. Weaknesses introduced at this stage often persist throughout the life of an API and are difficult to remediate later.

Build Phase

The build phase translates design intent into code. Developers implement authentication integration, authorization checks, and input validation within individual services. Static analysis, code reviews, and security testing can identify certain classes of issues, such as missing authorization logic or unsafe data binding. However, these activities rely on assumptions about how APIs will be used once deployed and cannot fully anticipate real-world traffic patterns or abuse scenarios.

Run Phase

The run phase is where APIs are exercised under production conditions. Requests originate from a mix of clients, services, partners, and automated systems, often at volumes and velocities that differ significantly from test environments. New consumers may be added, usage patterns may shift, and APIs may be repurposed in ways that were not originally anticipated. Security controls at this stage must account for actual behavior rather than intended behavior.

In practice, many organizations place disproportionate emphasis on design and build controls while treating runtime security as a monitoring problem rather than an enforcement one. This creates blind spots when APIs behave correctly from a code perspective but are misused, abused, or combined in ways that introduce risk.

Understanding API security as a lifecycle discipline highlights the need for continuity between design assumptions, implementation choices, and observed production behavior.

Why Visibility and Context Matter

Many API security failures occur not because controls are absent, but because they operate without sufficient visibility into how APIs behave in production. Design-time specifications, code-level checks, and perimeter defenses are all based on assumptions about usage. When those assumptions diverge from reality, security gaps emerge that are difficult to detect using traditional methods.

APIs are often evaluated in isolation. An endpoint may appear secure when reviewed on its own, with proper authentication, parameter validation, and error handling. However, risk frequently arises from how APIs are used together, how frequently they are invoked, and how their behavior changes over time. These patterns are only observable at runtime, when real traffic flows through the system.

Context is equally important. A request that is technically valid may still be inappropriate given the caller’s role, historical behavior, or the sensitivity of the data involved. For example, repeated access to a large number of individual objects may indicate enumeration or scraping, even if each request passes authorization checks. Without visibility into sequence, frequency, and scope, such behavior blends into normal operations.

Another challenge is the dynamic nature of modern environments. APIs are versioned, extended, and integrated with new consumers continuously. Documentation and inventories often lag behind deployments, leaving security teams with an incomplete understanding of which APIs exist and how they are accessed. This gap makes it difficult to apply consistent policies or assess exposure accurately.

Visibility also underpins accountability and response. When incidents occur, enterprises must be able to reconstruct what happened, which data was accessed, and which controls failed or were bypassed. Logs and alerts that lack semantic context about API operations provide limited support for investigation, compliance reporting, or remediation planning.

For these reasons, effective API security increasingly depends on the ability to observe and interpret API behavior as it occurs, rather than relying solely on static definitions or edge-based filtering. Visibility and context transform API security from a configuration exercise into an operational capability.

API Security vs Application Security

API security and application security are closely related, but they address different execution models and risk profiles. Traditional application security focuses on protecting user-facing interfaces and workflows, where user interaction provides natural boundaries and opportunities for validation. API security, by contrast, governs programmatic access to business functions that are often invoked without human oversight.

While many application security principles apply to APIs, such as least privilege and input validation, APIs require additional emphasis on authorization consistency, data minimization, and behavioral analysis. The absence of a user interface means that misuse can scale rapidly and remain undetected if controls are not designed specifically for machine-driven interactions.

The table below highlights key differences between the two disciplines.

Conclusion: Where Enterprise API Security Is Headed 

Enterprise API security is increasingly defined by a gap between what organizations believe their APIs do and what those APIs actually do in production. Design-time specifications, gateway policies, and authentication systems describe intended behavior, but they do not capture how APIs evolve, how they are combined, or how they are exercised at scale by real consumers, services, and automated agents.

As a result, API security is shifting away from static configuration toward runtime verification. Security teams are being asked not only to define controls, but to demonstrate that those controls hold under real conditions. This requires continuous awareness of which APIs are active, how they change over time, and how sensitive data moves across requests and services.

In practice, this means treating API security as an execution problem. Enterprises need to maintain a live inventory of APIs derived from observed traffic rather than documentation alone. They need documentation that reflects real request and response behavior, not aspirational schemas. They also need visibility into which APIs handle regulated or sensitive data, and how access to that data is enforced in production.

Runtime observation becomes especially important for detecting authorization failures and logic abuse. Many of the most damaging API attacks do not violate protocol rules or authentication checks. They exploit valid endpoints in unintended ways, often over time and across multiple requests. Detecting these patterns requires correlating identity context, object access, and behavior at runtime, rather than inspecting requests in isolation.

This is where platforms such as Levo are positioned. Levo does not replace gateways, WAFs, or identity providers. Instead, it operates as a runtime API security layer that observes how APIs are actually used in production and provides continuous evidence across discovery, documentation, detection, and enforcement.

Levo’s API Inventory and API Documentation capabilities establish an accurate, continuously updated view of active APIs based on live traffic. 

Sensitive Data Discovery identifies where regulated data is exposed or transmitted, grounding privacy and compliance controls in observed behavior. 

Runtime API Detection and API Monitoring correlate requests across identities and objects to surface authorization failures, logic abuse, and anomalous access patterns that static controls often miss. 

API Security Testing and Vulnerabilities Reporting close the loop by validating controls and translating runtime findings into actionable remediation signals for engineering teams. 

For environments integrating AI agents or internal automation, Levo’s MCP Server exposes this runtime context programmatically, enabling security signals to be consumed by other systems and workflows.

Taken together, these capabilities reflect a broader shift in enterprise API security. Protection is no longer defined solely by what was configured or reviewed at release time. It is defined by what can be observed, verified, and enforced as APIs operate in real systems. Runtime evidence becomes the foundation for trust, compliance, and sustained control.