Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:NSummary
CVE-2025-1513 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Contest-Gallery Contest Gallery. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 19th 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-2025-1513 is a stored cross-site scripting (XSS) vulnerability, classified under CWE-79, in the Photos, Files, YouTube, Twitter, Instagram, TikTok, Ecommerce Contest Gallery – Upload, Vote, Sell via PayPal or Stripe, Social Share Buttons plugin for WordPress. It affects all versions up to and including 26.0.0.1 due to insufficient input sanitization and output escaping in the Name and Comment fields when users comment on photo gallery entries. This flaw enables the injection of arbitrary web scripts into pages, with a CVSS v3.1 base score of 7.2 (AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N), indicating high severity due to its network accessibility, low complexity, lack of privileges or user interaction required, and changed scope.
Unauthenticated attackers can exploit the vulnerability by submitting malicious scripts via the Name or Comment fields during photo gallery comments. The injected scripts are then stored persistently and execute in the browser context of any user who views the affected page, potentially compromising confidentiality and integrity through actions like stealing cookies, session tokens, or sensitive data displayed on the page.
Advisories reference a patch in the WordPress plugin trac repository at changeset 3245199 for the contest-gallery repository, indicating remediation through an updated plugin version. Wordfence threat intelligence provides further details on the vulnerability at their dedicated page.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-5476
Vulnerability Data
The Photos, Files, YouTube, Twitter, Instagram, TikTok, Ecommerce Contest Gallery – Upload, Vote, Sell via PayPal or Stripe, Social Share Buttons plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the Name and Comment field when commenting on photo…
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gallery entries in all versions up to, and including, 26.0.0.1 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers 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.