Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2026-47999 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Adobe Commerce. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 6% 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-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-2026-44422
Vulnerability Data
Adobe Commerce is affected by a stored Cross-Site Scripting (XSS) vulnerability that could be abused by a high-privileged attacker to inject malicious scripts into vulnerable form fields. Malicious JavaScript may be executed in a victim's browser when they browse to…
more
the page containing the vulnerable field. Scope is changed.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored XSS (CWE-79) in a web application directly enables exploitation of public-facing apps (T1190) and execution of attacker-supplied JavaScript in victim browsers (T1059.007).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Validates all form-field inputs to reject or sanitize script payloads before they are stored and later rendered.
Filters or encodes dynamic content on output so that stored malicious JavaScript cannot execute in victim browsers.
Restricts the number of high-privileged accounts that can reach the vulnerable form fields, reducing the attack surface for stored XSS.
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.