Integrity Failures in Cockroachdb

Integrity failures in Cockroachdb APIs often stem from improper row-level security (RLS) implementation and inadequate access controls on distributed data. Cockroachdb's distributed architecture introduces unique attack vectors that traditional SQL databases don't face.

One common pattern involves cross-tenant data exposure in multi-tenant applications. Consider a SaaS application where each tenant's data should be isolated. Without proper row-level security policies, an attacker can manipulate query parameters to access other tenants' records:

SELECT * FROM users WHERE tenant_id = $1; // $1 = 1 OR 1=1

Cockroachdb's crdb_internal functions can also be abused if exposed through APIs. An attacker might exploit functions like crdb_internal.node_statement_statistics to extract system-level information:

SELECT * FROM crdb_internal.node_statement_statistics WHERE user_name = 'admin'

Another Cockroachdb-specific issue arises from transaction isolation level misuse. Cockroachdb defaults to SERIALIZABLE isolation, but APIs might explicitly set READ COMMITTED for performance, creating race conditions:

BEGIN; -- SERIALIZABLE (default)
UPDATE accounts SET balance = balance - 100 WHERE user_id = 123;
COMMIT;

Without proper transaction handling, concurrent requests can lead to balance inconsistencies where users withdraw more than their actual balance across distributed nodes.

Distributed JOIN attacks represent another unique threat. Cockroachdb's distributed query planner might execute JOINs across nodes in ways that expose intermediate results. An attacker could craft queries that force the planner to spill sensitive data during distributed execution:

SELECT u.*, o.* FROM users u
JOIN orders o ON u.id = o.user_id
WHERE u.email LIKE '%@example.com'

Without proper filtering and column-level permissions, this could expose order details for all users with matching emails across the entire cluster.

Detecting integrity failures in Cockroachdb requires both database-level monitoring and API-layer scanning. middleBrick's black-box scanning approach is particularly effective for Cockroachdb APIs because it tests the exposed attack surface without requiring credentials.

Schema analysis is the first detection layer. middleBrick analyzes the OpenAPI specification and maps it against Cockroachdb's data model, identifying potential BOLA (Broken Object Level Authorization) vulnerabilities. For example, if an API endpoint accepts a tenant_id parameter but doesn't verify the requesting user's permissions:

GET /api/tenants/{tenant_id}/data
GET /api/users/{user_id}/profile

middleBrick flags these as high-risk endpoints for integrity testing.

Active scanning tests Cockroachdb-specific injection patterns. The scanner attempts to manipulate SQL queries by injecting Cockroachdb-specific syntax:

SELECT * FROM users WHERE id = $1 -- $1 = 1 OR crdb_internal.node_id IS NOT NULL

middleBrick also tests for distributed query manipulation by attempting to force cross-node data exposure through crafted queries that exploit Cockroachdb's distributed execution engine.

Transaction race condition detection involves sending concurrent requests to test for isolation level vulnerabilities. middleBrick's scanner can detect when APIs fail to handle Cockroachdb's SERIALIZABLE isolation properly, leading to integrity violations.

Row-level security policy analysis examines whether Cockroachdb's RLS features are properly implemented. The scanner checks for missing CREATE ROW LEVEL POLICY statements and tests whether API endpoints respect these policies:

CREATE ROW LEVEL POLICY tenant_isolation ON users
FOR ALL USING (tenant_id = crdb_internal.current_tenant());

middleBrick's LLM security module also scans for prompt injection in AI-powered Cockroachdb interfaces, detecting when system prompts can be extracted or manipulated to access unauthorized data.