Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:LSummary
CVE-2025-31136 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Freshrss Freshrss. Its CVSS base score is 6.7 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 23th 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-2025-16906
Vulnerability Data
FreshRSS is a self-hosted RSS feed aggregator. Prior to version 1.26.2, it's possible to run arbitrary JavaScript on the feeds page. This occurs by combining a cross-site scripting (XSS) issue that occurs in `f.php` when SVG favicons are downloaded from…
more
an attacker-controlled feed containing `<script>` tags inside of them that aren't sanitized, with the lack of CSP in `f.php` by embedding the malicious favicon in an iframe (that has `sandbox="allow-scripts allow-same-origin"` set as its attribute). An attacker needs to control one of the feeds that the victim is subscribed to, and also must have an account on the FreshRSS instance. Other than that, the iframe payload can be embedded as one of two options. The first payload requires user interaction (the user clicking on the malicious feed entry) with default user configuration, and the second payload fires instantly right after the user adds the feed or logs into the account while the feed entry is still visible. This is because of lazy image loading functionality, which the second payload bypasses. An attacker can gain access to the victim's account by exploiting this vulnerability. If the victim is an admin it would be possible to delete all users (cause damage) or execute arbitrary code on the server by modifying the update URL using fetch() via the XSS. Version 1.26.2 has a patch for the issue.
- 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.