Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:LSummary
CVE-2024-22411 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Avohq Avo. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 50% of CVEs by exploit likelihood; 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.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-22411 is a cross-site scripting flaw in the Avo framework for building admin panels in Ruby on Rails applications. It occurs in Avo 3 pre12 and earlier releases when HTML supplied to the error or succeed methods of an Avo::BaseAction subclass is rendered directly into toast or notification elements without sanitization, corresponding to CWE-79.
An authenticated user with low privileges can supply crafted HTML through an action response, causing script execution in the browser of any user who views the resulting notification. The attack requires user interaction to trigger display of the notification and yields limited impacts on confidentiality, integrity, and availability under the reported CVSS 6.5 vector.
The GitHub security advisory GHSA-g8vp-2v5p-9qfh and associated release notes direct users to upgrade to Avo 3.3.0 or 2.47.0; the fixing commits sanitize the supplied text before rendering.
The EPSS score has remained flat at 0.0577 with no material rise after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0353
Vulnerability Data
Avo is a framework to create admin panels for Ruby on Rails apps. In Avo 3 pre12, any HTML inside text that is passed to `error` or `succeed` in an `Avo::BaseAction` subclass will be rendered directly without sanitization in the…
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toast/notification that appears in the UI on Action completion. A malicious user could exploit this vulnerability to trigger a cross site scripting attack on an unsuspecting user. This issue has been addressed in the 3.3.0 and 2.47.0 releases of Avo. Users are advised to upgrade.
- 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.