Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). EPSS scores by FIRST (EPSS SIG), generated by Empirical Security. Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-35460 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Papra Papra. Its CVSS base score is 4.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 14th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-19653
Vulnerability Data
Papra is a minimalistic document management and archiving platform. Prior to 26.4.0, transactional email templates in Papra interpolate user.name directly into HTML without escaping or sanitization. An attacker who registers with a display name containing HTML tags will have those…
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tags injected into the verification and password reset email bodies. Since emails are sent from the legitimate domain (e.g: auth@mail.papra.app), this enables convincing phishing attacks that appear to originate from official Papra notifications. This vulnerability is fixed in 26.4.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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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.
Secure engineering principles include mandatory output encoding and neutralization of HTML metacharacters to stop injection at the source.
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.
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.