Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2025-48954 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Discourse Discourse. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 49th 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.
Discourse, an open-source discussion platform, is affected by CVE-2025-48954, a cross-site scripting vulnerability (CWE-79) present in versions prior to 3.5.0.beta6. The flaw manifests specifically when the content security policy is disabled and social logins are in use, allowing attacker-controlled content to execute in users' browsers. The issue carries a CVSS 3.1 score of 8.1, reflecting network attack vector, low complexity, no required privileges, and required user interaction.
An unauthenticated attacker can exploit the vulnerability by crafting a malicious social-login flow that injects scripts into the Discourse instance. Successful exploitation grants the ability to read sensitive data and perform actions on behalf of the victim user, resulting in high impact to confidentiality and integrity without affecting availability.
The official advisory at https://github.com/discourse/discourse/security/advisories/GHSA-26p5-mjjh-wfcf states that version 3.5.0.beta6 contains the fix. As a workaround, administrators are advised to enable the content security policy until the update can be applied.
EPSS for the CVE reached a peak of 0.1558 after disclosure before settling at the current value of 0.1012, indicating emerging exploitation interest that warrants renewed attention.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-28274
Vulnerability Data
Discourse is an open-source discussion platform. Versions prior to 3.5.0.beta6 are vulnerable to cross-site scripting when the content security policy isn't enabled when using social logins. Version 3.5.0.beta6 patches the issue. As a workaround, have the content security policy enabled.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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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.