Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:N/A:NSummary
CVE-2025-20367 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Splunk Splunk. Its CVSS base score is 5.7 (Medium).
Operationally, ranked at the 26th 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 SI-10 (Information Input Validation) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-32715
Vulnerability Data
In Splunk Enterprise versions below 9.4.4, 9.3.6 and 9.2.8, and Splunk Cloud Platform versions below 9.3.2411.109, 9.3.2408.119 and 9.2.2406.122, a low-privileged user that does not hold the 'admin' or 'power' Splunk roles could craft a malicious payload through the `dataset.command`…
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parameter of the `/app/search/table` endpoint, which could result in execution of unauthorized JavaScript code in the browser of a user.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Validates the dataset.command parameter on /app/search/table to reject or sanitize JavaScript payloads before they reach other users' browsers.
Filters or encodes output returned by the search/table endpoint so that injected script from a low-privileged user cannot execute in another user's browser.
Restricts low-privileged accounts (non-admin/power) from accessing or invoking the dataset.command functionality that enables the reflected XSS vector.
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.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.