CVE-2026-93637 in Collaboration Suite
Summary
by MITRE • 10/14/2026
An authentication rate-limit bypass in Zimbra Collaboration Suite 10.1.0 through 10.1.21 allows unauthenticated attackers to make repeated password guesses through GraphQL without incrementing Zimbra’s source-IP failure counter. GraphQL aliases allow multiple authentication attempts in one HTTP request.
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Analysis
by VulDB Data Team • 10/15/2026
The vulnerability identified as an authentication rate-limit bypass in Zimbra Collaboration Suite versions 10.1.0 through 10.1.21 represents a critical flaw in the application's access control mechanisms, specifically within its GraphQL interface. This issue stems from how the server processes incoming requests that utilize GraphQL aliases to batch multiple operations into a single HTTP transaction. In standard authentication flows, systems typically track failed login attempts per source IP address and enforce rate limiting by temporarily blocking or slowing down further attempts after a threshold of failures is reached. However, in this specific implementation, the logic responsible for incrementing the failure counter fails to account for the multiplexed nature of GraphQL aliases. Consequently, an attacker can construct a single HTTP request containing multiple authentication queries, each with different credentials, and submit them simultaneously. The server processes these distinct attempts but does not correctly attribute or count them against the source IP's cumulative failure total, effectively allowing unlimited password guessing within that single request envelope.
From a technical perspective, this flaw exploits the fundamental design of GraphQL, which allows clients to define exactly what data they want and how it is structured in the response. By leveraging aliases, an attacker can name multiple instances of the same authentication mutation differently, tricking the backend into treating them as separate operations that do not trigger the shared state variables used for rate limiting. This bypass renders traditional brute-force mitigation strategies ineffective because the protective counter remains static despite numerous successful or failed login attempts being processed in one go. The operational impact is severe, as it enables unauthenticated attackers to perform rapid credential stuffing or dictionary attacks against user accounts without triggering account lockouts or IP-based blocks. This significantly lowers the barrier for unauthorized access, potentially leading to full compromise of email accounts, exposure of sensitive corporate communications, and further lateral movement within the network if valid credentials are obtained.
This vulnerability aligns with CWE-287, which describes Improper Authentication, specifically regarding the failure to enforce proper rate limiting or account lockout policies during authentication attempts. It also maps directly to MITRE ATT&CK technique T1110.004, known as Brute Force: Password Spraying, where attackers use a small number of commonly used passwords against many different accounts to avoid detection by traditional security controls that rely on per-account failure thresholds or simple IP-based rate limiting. The ability to bypass these controls via GraphQL aliases highlights the need for more granular request validation and state management in modern web application frameworks.
To mitigate this risk, administrators must immediately apply the vendor-provided patches available for Zimbra Collaboration Suite versions 10.1.0 through 10.1.21. Until patching is complete, it is advisable to restrict access to the GraphQL endpoint using network-level controls such as Web Application Firewalls that can detect and block requests containing multiple aliases or unusually large payload sizes associated with batched authentication attempts. Additionally, implementing multi-factor authentication for all user accounts adds a critical layer of defense that remains effective even if password-based brute force attacks succeed in guessing credentials. Monitoring logs for high volumes of authentication requests from single IP addresses using non-standard GraphQL patterns can also aid in early detection and response to ongoing exploitation attempts.