Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:NSummary
CVE-2026-34748 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Payloadcms Payload. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 21th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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-2026-34748 is a stored Cross-Site Scripting (XSS) vulnerability, classified under CWE-79, affecting Payload, a free and open-source headless content management system. The issue resides in the admin panel of the @payloadcms/next package prior to version 3.78.0. It allows malicious scripts to be embedded in saved content within collections, with a CVSS v3.1 base score of 8.7 (AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:N), indicating high severity due to network accessibility, low attack complexity, and significant impacts on confidentiality and integrity after scope change.
An authenticated attacker with write access to a collection can exploit this by injecting and saving malicious payloads. When another authenticated user, such as an admin, views the affected content in the admin panel, the script executes in their browser context. This enables potential theft of session cookies, keystroke logging, or further client-side attacks, though it requires user interaction to view the content.
The vulnerability has been patched in Payload version 3.78.0. Security practitioners should upgrade to this version or later. Additional details are available in the GitHub Security Advisory at https://github.com/payloadcms/payload/security/advisories/GHSA-mmxc-95ch-2j7c.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18015
Vulnerability Data
Payload is a free and open source headless content management system. Prior to version 3.78.0 in @payloadcms/next, a stored Cross-Site Scripting (XSS) vulnerability existed in the admin panel. An authenticated user with write access to a collection could save content…
more
that, when viewed by another user, would execute in their browser. This issue has been patched in version 3.78.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
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.