RabbitMQ has patched two vulnerabilities that could expose sensitive data and undermine tenant isolation in enterprise deployments. The most serious flaw, tracked as CVE-2026-57219 and reported by Miggo, allows an unauthenticated attacker to retrieve OAuth 2 configuration details, including a confidential client secret, from the obsolete /api/auth management endpoint. In deployments that use the management interface with OAuth-based identity provider authentication, an attacker could use the leaked secret to impersonate the broker, obtain an administrator token, and gain access to users, messages, queues, exchanges, and broker settings.
A second flaw, CVE-2026-57221, allows authenticated users without proper permissions to infer the existence of other tenants’ queues and exchanges and view related metadata and statistics, creating cross-tenant information leakage. The issues affect versions dating back to RabbitMQ 3.13.0 and have been fixed in 4.3.0, 4.2.6, 4.1.11, 4.0.20, and 3.13.15. Organizations are being urged to patch quickly, restrict or remove internet exposure of the management interface, apply segmentation or other configuration mitigations if patching is delayed, and rotate OAuth client secrets because software updates alone do not invalidate secrets that may already have been exposed.

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3 events from the most recent confirmed update back to the earliest known activity.
Two RabbitMQ flaws were present since 2024, including an OAuth secret disclosure issue that could enable broker takeover and an authorization flaw that exposed queue and exchange metadata to unauthorized authenticated users.
RabbitMQ fixed the vulnerabilities in versions 4.3.0, 4.2.6, 4.1.11, 4.0.20, and 3.13.15. The updates address the high-severity broker takeover risk from leaked OAuth client secrets and the medium-severity cross-tenant information leakage issue.
Miggo reported CVE-2026-57219, which exposes a confidential OAuth client secret through a management endpoint, and CVE-2026-57221, which allows authenticated users to enumerate queues and exchanges and read related statistics or metadata.
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