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Tenant Isolation, Access Control, and Data Segregation Testing

Understanding API-Level Security Vulnerabilities

Tenant isolation and data segregation vulnerabilities are fundamentally API-level security concerns. Whether testing occurs through API DAST or WebApp DAST, the underlying vulnerabilities being detected originate from the API layer of the application architecture.

Why Isolation Is an API-Level Concern:

Modern applications are architecturally composed of presentation layers (web interfaces, mobile applications) and data access layers (REST APIs, GraphQL endpoints, RPC services). Data segregation is enforced at the API level through authorization logic that validates whether a given authenticated user can access a specific resource. When this authorization logic is absent, insufficient, or incorrectly implemented, the vulnerability exists within the API itself, regardless of which client interface is used to trigger the request.

A web application's UI may visually hide data that should not be accessible to a user, but if the underlying API endpoint returns that data without proper authorization checks, the vulnerability is present in the API. Similarly, a mobile application might not display certain features to unprivileged users, but if the API endpoints backing those features lack authorization enforcement, the security boundary has been violated at the API layer.

Configuration Support Across Testing Modes:

Escape's multi-user testing configurations are supported across both API DAST and WebApp DAST modes. However, the security issues identified—Broken Access Control (BAC), Tenant Isolation failures, Insecure Direct Object References (IDOR), and Cross-User Data Breaches—are invariably manifestations of API-level authorization deficiencies.

  • API DAST: Direct testing of REST, GraphQL, SOAP, and other API protocols, where requests are constructed and sent directly to API endpoints
  • WebApp DAST: Browser-based testing where user interactions generate API traffic, which is then intercepted, analyzed, and replayed with modified authentication contexts

In WebApp DAST scenarios, the primary user is utilized for exploration and crawling to discover API endpoints through browser interactions. Secondary users are then employed to replay the captured API traffic with different authentication credentials, validating that the underlying APIs properly enforce authorization boundaries.

The Nature of Tenant Isolation Vulnerabilities

Tenant isolation vulnerabilities manifest when authentication and authorization mechanisms fail to prevent unauthorized cross-tenant or cross-user data access. These vulnerabilities typically exhibit one or more of the following characteristics:

Authorization Bypass Through Direct Object Reference:

Resource identifiers (IDs, UUIDs, keys) are accepted by API endpoints without validating that the authenticated user has authorization to access the referenced resource. This allows an attacker to enumerate or guess identifiers belonging to other users or tenants and retrieve their data.

Data Leakage Through Insufficient Response Filtering:

API responses contain data belonging to multiple users or tenants without proper filtering based on the requesting user's authorization context. This occurs when queries or data aggregation operations fail to apply tenant-scoping predicates.

The UUID Fallacy: High-Entropy Identifiers and False Security

A common misconception in API security is that UUIDs (Universally Unique Identifiers) or other high-entropy identifiers provide inherent protection against unauthorized access due to their unpredictability.

Why This Is Insufficient:

While a 128-bit UUID cannot be feasibly brute-forced, security boundaries fail when any single API endpoint leaks identifiers across tenant or user boundaries. An attacker who obtains a UUID through information disclosure (error messages, API responses, web scraping, social engineering, or insider knowledge) can then pivot to attempt access to the referenced resource.

The Attack Chain:

  1. Discovery: An API endpoint leaks UUIDs of resources belonging to other tenants (e.g., in a user listing, error message, or analytics endpoint)
  2. Pivoting: The attacker extracts these UUIDs and constructs requests to resource-specific endpoints
  3. Exploitation: Without proper authorization checks, the API returns the protected resources

UUIDs create a false sense of security that can lead to systemic authorization failures. Security must be enforced through explicit authorization validation, not identifier obscurity.

Escape's testing methodology accounts for this by performing both ID reinjection attacks (pivoting discovered identifiers across user contexts) and direct data presence analysis (detecting when responses contain data that should be filtered based on authorization scope).

How Escape Validates Authorization Boundaries

Once multiple users are configured in the scan's authentication settings, Escape automatically orchestrates authorization testing through credential replay and response analysis:

Credential Replay Testing:

API requests discovered or generated during exploration are systematically replayed with the authentication credentials of different users. Responses are compared to detect authorization failures.

Response Analysis and Fingerprinting:

Escape employs sophisticated response fingerprinting algorithms to detect when different users receive substantively identical responses, indicating potential authorization bypass. The analysis accounts for expected variations (timestamps, session identifiers, user-specific metadata) while identifying semantically equivalent data access.

Tenant Isolation Security Testing

In multi-tenant architectures where multiple customers share a common software instance, tenant isolation represents a critical security boundary. When two or more users are configured in a scan profile, Escape's authorization testing engine automatically validates tenant isolation by systematically comparing API responses across different authenticated contexts.

Automated Testing Methodology:

Escape's business logic analysis algorithms perform cross-user request replay while applying response similarity detection and endpoint sensitivity classification. This automated approach identifies authorization breaches without requiring manual test case definition for each endpoint.

GraphQL-Specific Challenges:

GraphQL APIs present unique tenant isolation challenges due to their flexible query structures and type systems. Consider a GraphQL schema that exposes a User type with an email field. Without proper field-level authorization, queries that legitimately return user objects may inadvertently leak email addresses across tenant boundaries—a privacy violation that could constitute a compliance breach under GDPR, CCPA, or HIPAA regulations.

The GraphQL type system's interconnected nature means that authorization failures in one type can cascade through relationship traversals, enabling deep information disclosure through multi-hop queries. Escape's Tenant Isolation testing validates that distinct users cannot access identical GraphQL objects or retrieve the same scalar field values when such access would violate tenant boundaries.

Additional Resources

For comprehensive information on tenant isolation vulnerability classification, remediation guidance, and real-world exploitation scenarios, consult the Tenant Isolation Vulnerability Documentation.