CVE-2024-43971
XSS in Sunshinephotocart Sunshine Photo Cart ≤ 3.2.6
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:LSummary
CVE-2024-43971 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Sunshinephotocart Sunshine Photo Cart. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 45th 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.
CVE-2024-43971 is a cross-site scripting vulnerability arising from improper neutralization of input during web page generation, classified under CWE-79. It affects the Sunshine Photo Cart WordPress plugin, impacting all versions through 3.2.5. The flaw carries a CVSS 3.1 score of 7.1, reflecting network attack vector, low complexity, no required privileges, required user interaction, changed scope, and low impacts on confidentiality, integrity, and availability.
An unauthenticated attacker can exploit the issue by supplying crafted input that is rendered unsafely in a victim's browser session. Successful exploitation allows the attacker to execute arbitrary scripts in the context of the affected site, potentially leading to limited data exposure, interface manipulation, or other actions within the user's browser.
The vulnerability is documented in the Patchstack advisory, which identifies the affected plugin versions and links the issue to the public CVE record.
EPSS for this CVE rose from lower values to a peak of 0.0983 before receding to the current score of 0.0406, indicating a period of increased exploitation interest after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-40620
Vulnerability Data
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in sunshinephotocart Sunshine Photo Cart sunshine-photo-cart.This issue affects Sunshine Photo Cart: from n/a through <= 3.2.5.
- 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.