Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-48494 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Forceu Gokapi. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Drive-by Compromise (T1189); ranked at the 4th 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 AC-3 (Access Enforcement) 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-2025-16640
Vulnerability Data
Gokapi is a self-hosted file sharing server with automatic expiration and encryption support. When using end-to-end encryption, a stored cross-site scripting vulnerability can be exploited by uploading a file with JavaScript code embedded in the filename. After upload and every…
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time someone opens the upload list, the script is then parsed. Prior to version 2.0.0, there was no user permission system implemented, therefore all authenticated users were already able to see and modify all resources, even if end-to-end encrypted, as the encryption key had to be the same for all users using a version prior to 2.0.0. If a user is the only authenticated user using Gokapi, they are not affected. This issue has been fixed in v2.0.0. A possible workaround would be to disable end-to-end encryption.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored XSS via malicious filename in Gokapi web app enables drive-by compromise (T1189) and exploitation of public-facing application (T1190), facilitating JavaScript execution (T1059.007) in victims' browsers when viewing upload lists.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly blocks the stored XSS by validating and sanitizing untrusted filename input before storage and display.
Enforces per-user access restrictions on resources and the upload list, eliminating the pre-2.0.0 absence of any permission system that let every authenticated user trigger or view the payload.
Limits the scope of damage by ensuring authenticated users receive only the minimum privileges needed, reducing the blast radius of both the missing permission model and the XSS trigger.
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 standards require proper neutralization of alternate script syntax, directly eliminating CWE-87.
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.
Application security requirements explicitly call for neutralization of untrusted input to block XSS variants.