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CVE-2026-33538 is a denial-of-service vulnerability in Parse Server, an open-source Node.js backend framework, caused by unindexed database queries triggered by authentication requests with arbitrary, unconfigured provider names. It affects all Parse Server versions prior to 8.6.58 and versions 9.0.0 through 9.6.0-alpha.51 (inclusive of numerous alpha releases). The vulnerability was published on March 21, 2026, with patches released the same day. It carries a CVSS v3.1 base score of 7.5 (High) and a CVSS v4.0 base score of 8.7 (High) (GitHub Advisory).
The root cause is classified as CWE-400 (Uncontrolled Resource Consumption). In the vulnerable findUsersWithAuthData function in src/Auth.js, the server called config.authDataManager.getValidatorForProvider(provider) to retrieve the adapter but did not check whether a validator was actually configured before proceeding to execute a database query. Because no database index exists for unconfigured authentication provider fields, each such request triggered a full collection scan ($or query) on the user database. The fix adds an early-return guard: if validatorConfig?.validator is absent, the function returns null immediately, skipping the database query entirely and deferring rejection to the handleAuthDataValidation stage with an UNSUPPORTED_SERVICE error (GitHub Advisory, Commit 40eb442).
Successful exploitation allows an unauthenticated attacker to cause denial of service by saturating database resources. Each crafted authentication request (via signup or the /challenge endpoint) forces a full collection scan on the user database; by parallelizing many such requests, an attacker can exhaust database CPU and I/O, rendering the Parse Server unavailable to legitimate users. There is no confidentiality or integrity impact — the vulnerability is limited to availability of the affected service (GitHub Advisory).
No public proof-of-concept exploit code is known to exist, and there is no evidence of in-the-wild exploitation at this time. The attack requires no authentication, no special privileges, and no user interaction, making it trivially automatable from the network. The EPSS score is approximately 0.122%, reflecting a currently low but non-negligible probability of exploitation. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog (GitHub Advisory).
/parse/users or /parse/challenge) running versions prior to 8.6.58 or between 9.0.0 and 9.6.0-alpha.51./parse/users) or the /parse/challenge endpoint, including an authData field with an arbitrary, non-existent provider name (e.g., {"authData": {"nonExistentProvider": {"id": "test123"}}}).curl, ab (Apache Bench), or custom scripts to send a high volume of these requests concurrently, maximizing the number of simultaneous full collection scans on the user database.$or query against the user collection. As requests accumulate, database CPU and I/O are exhausted, causing query latency to spike and legitimate requests to time out or fail, effectively taking the service offline (GitHub Advisory, Commit fbac847)./parse/users or /parse/challenge endpoints from one or more source IPs; requests containing authData fields with unknown or arbitrary provider names.UNSUPPORTED_SERVICE errors or 400-series responses for authentication requests with unrecognized provider names; unusually high request rates to authentication endpoints.collscan in slow query logs or explain() output showing no index used); elevated database CPU utilization and query execution times correlating with incoming authentication traffic.Upgrade Parse Server to version 8.6.58 (for the 8.x LTS branch) or 9.6.0-alpha.52 (or later, including the stable 9.6.0 release) to apply the fix. There is no known configuration-based workaround other than upgrading. As interim measures while patching, operators should implement rate limiting on authentication endpoints (e.g., via a reverse proxy or WAF) and monitor database query performance for signs of resource exhaustion (GitHub Advisory, PR #10271, PR #10270).
Source: This report was generated using AI
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