Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:LSummary
CVE-2026-20139 is a medium-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Splunk Splunk. Its CVSS base score is 4.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked in the top 9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-2 (Flaw Remediation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8197
Vulnerability Data
In Splunk Enterprise versions below 10.2.0, 10.0.2, 9.4.8, 9.3.9, and 9.2.12, and Splunk Cloud Platform versions below 10.2.2510.3, 10.1.2507.8, 10.0.2503.9, and 9.3.2411.121, a low-privileged user that does not hold the "admin" or "power" Splunk roles could craft a malicious payload…
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into the `realname`, `tz`, or `email` parameters of the `/splunkd/__raw/services/authentication/users/username` REST API endpoint when they change a password. This could potentially lead to a client‑side denial‑of‑service (DoS). The malicious payload might significantly slow page load times or render Splunk Web temporarily unresponsive.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Authenticated low-priv user can abuse password-change REST endpoint to trigger resource exhaustion (CWE-400) resulting in application DoS on Splunk Web.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces validation and sanitization of user-supplied values in realname/tz/email before they reach the authentication/users endpoint, blocking the crafted payloads that trigger uncontrolled resource consumption.
Requires prompt application of the vendor patches that close the input-handling flaw in the listed Splunk versions, eliminating the root cause of the client-side DoS.
Limits the ability of non-admin/power roles to invoke or influence the /authentication/users/username endpoint, reducing the attack surface available to low-privileged accounts.
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.