Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-33538 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Parseplatform Parse-Server. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked at the 34th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SC-6 (Resource Availability) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-33538 is a denial-of-service vulnerability in Parse Server, an open-source backend deployable on any Node.js-compatible infrastructure. In versions prior to 8.6.58 and 9.6.0-alpha.52, the server processes authentication requests containing arbitrary, unconfigured provider names by executing a database query for each one before rejection. Without a database index for unconfigured providers, each request triggers a full collection scan on the user database, enabling resource exhaustion.
An unauthenticated network attacker can exploit this vulnerability with low complexity and no privileges, as indicated by its CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H). By sending repeated authentication requests with fabricated provider names, the attacker forces multiple full-table scans, which can be parallelized across threads or instances to saturate database CPU and I/O resources, leading to service unavailability. This aligns with CWE-400 (Uncontrolled Resource Consumption).
The Parse Server security advisory (GHSA-g4cf-xj29-wqqr) and related GitHub pull requests (#10270, #10271) detail the patch, available in versions 8.6.58 and 9.6.0-alpha.52 via commits 40eb442e02672986730007d0a1edb22c1c4bd357 and fbac847499e57f243315c5fc7135be1d58bb8e54. Security practitioners should upgrade immediately and monitor for unusual authentication traffic patterns as an interim measure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-14975
Vulnerability Data
Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Prior to versions 8.6.58 and 9.6.0-alpha.52, an unauthenticated attacker can cause denial of service by sending authentication requests with arbitrary, unconfigured provider…
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names. The server executes a database query for each unconfigured provider before rejecting the request, and since no database index exists for unconfigured providers, each request triggers a full collection scan on the user database. This can be parallelized to saturate database resources. This issue has been patched in versions 8.6.58 and 9.6.0-alpha.52.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
SC-5 directly limits the effects of resource-exhaustion events that constitute uncontrolled consumption.
SC-6 enforces explicit allocation limits on resources, structurally preventing the weakness from occurring.
Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.
Hardened configuration baselines can include resource quotas and limits that constrain consumption.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.
By continuously monitoring utilization, stress-testing peak loads, and maintaining documented plans to scale or throttle resources, the control directly limits an attacker’s ability to drive a system into uncontrolled resource exhaustion.
Pre-agreed severity-based prioritization and resource allocation during incident triage reduce the likelihood that an attacker-induced resource exhaustion will overwhelm the organization before corrective action is taken.
Business-continuity plans that include resource-management controls reduce the likelihood that an attacker can trigger uncontrolled resource consumption by forcing the system into a degraded or fallback state.
Defining RTOs and capacity requirements for ICT services during business-impact analysis forces organizations to provision sufficient resources and throttling mechanisms, reducing the likelihood that an attacker can induce denial-of-service through uncontrolled resource consumption.
Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.