Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:NSummary
CVE-2024-4455 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Yithemes Yith Woocommerce Ajax Search. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 40% of CVEs by exploit likelihood; 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.
The YITH WooCommerce Ajax Search plugin for WordPress is affected by a stored cross-site scripting vulnerability in versions up to and including 2.4.0. The flaw resides in the handling of the ‘item’ parameter and stems from insufficient input sanitization and output escaping, allowing arbitrary scripts to be stored and later executed in the browser of users who access an injected page.
Unauthenticated attackers can exploit the issue remotely with no user interaction required. Successful exploitation permits injection of malicious web scripts that run in the context of the affected site, enabling actions such as data theft or unauthorized operations within the WordPress environment due to the changed scope.
References including Wordfence threat intelligence and WordPress plugin trac changesets indicate that the issue is resolved by applying the available patch, which updates the affected statistic list table code to enforce proper escaping.
The associated EPSS score rose from a low baseline to a peak of 0.1006 before receding to the current value of 0.0664, signaling that exploitation interest emerged after public disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-44074
Vulnerability Data
The YITH WooCommerce Ajax Search plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the ‘item’ parameter in versions up to, and including, 2.4.0 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers…
more
to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page.
- 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.