Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:NSummary
CVE-2023-31145 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Collabora Online. Its CVSS base score is 4.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 33th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-35462
Vulnerability Data
Collabora Online is a collaborative online office suite based on LibreOffice technology. This vulnerability report describes a reflected XSS vulnerability with full CSP bypass in Nextcloud installations using the recommended bundle. The vulnerability can be exploited to perform a trivial…
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account takeover attack. The vulnerability allows attackers to inject malicious code into web pages, which can be executed in the context of the victim's browser session. This means that an attacker can steal sensitive data, such as login credentials or personal information, or perform unauthorized actions on behalf of the victim, such as modifying or deleting data. In this specific case, the vulnerability allows for a trivial account takeover attack. An attacker can exploit the vulnerability to inject code into the victim's browser session, allowing the attacker to take over the victim's account without their knowledge or consent. This can lead to unauthorized access to sensitive information and data, as well as the ability to perform actions on behalf of the victim. Furthermore, the fact that the vulnerability bypasses the Content Security Policy (CSP) makes it more dangerous, as CSP is an important security mechanism used to prevent cross-site scripting attacks. By bypassing CSP, attackers can circumvent the security measures put in place by the web application and execute their malicious code. This issue has been patched in versions 22.05.13, 21.11.9, and 6.4.27. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- 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
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.