WordPress LazyLoad Plugin Stored XSS via Comment Content

The LazyLoad Plugin – Lazy Load Images, Videos, and Iframes plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'comment_content (rendered inline into the page HTML)' parameter in all versions up to, and including, 2.4.0 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. WordPress core's wp_kses_data allow-list does not strip the crafted payload on save because it uses only permitted tags and attributes; the event handler is concealed inside a broken attribute region and is only promoted to a real DOM attribute by the plugin's render-time str_replace transformation. Additionally, a site administrator must approve the crafted comment before the payload is served to other visitors.

Casky was already ahead

This CVE exploits attack patterns that Casky's 323matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

The LazyLoad Plugin for WordPress contains a stored cross-site scripting (XSS) vulnerability in versions up to 2.4.0 that allows unauthenticated attackers to inject malicious scripts through comment content. Because the plugin fails to properly sanitize and escape user input before rendering it inline in page HTML, attackers can craft comments containing arbitrary JavaScript that executes in the browsers of all users who view the affected page. This vulnerability is particularly dangerous because it persists in the database and affects any visitor, not just the attacker, making it a widespread attack surface for WordPress sites using this plugin. Organizations running WordPress with LazyLoad enabled are at risk of credential theft, session hijacking, malware distribution, and defacement through compromised comment sections.

Casky's 323 matched skills leverage Claude's extended reasoning to detect the attack patterns associated with MITRE techniques TA0001 (Reconnaissance) and TA0043 (Reconnaissance) by analyzing data flows that expose stored XSS vulnerabilities. Practitioners using Casky would observe findings highlighting insufficient input validation and output encoding gaps in comment processing pipelines, coupled with detection of HTML/JavaScript patterns in stored comment data that should have been sanitized. The platform maps these observations to CWE-79 signals and correlates them with known exploitation patterns, enabling security teams to identify vulnerable plugin instances, audit existing comments for injected payloads, and prioritize remediation before attackers can weaponize this vector at scale.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

323 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-100196.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

Run

abusing-dpapi-for-credential-access

red teaming · high

Run

abusing-shadow-credentials-for-privesc

red teaming · high

Run

MITRE ATT&CK Techniques

TA0001 TA0043

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