WordPress Gravity Forms Stored XSS via Consent Field Validation

The Gravity Forms plugin for WordPress is vulnerable to Stored Cross-Site Scripting via Consent field hidden inputs in versions up to and including 2.10.0. This is due to a flawed state validation mechanism that fails open when input is sanitized by wp_kses(), combined with insufficient output escaping. The state validation logic creates two hashes (raw input and wp_kses-sanitized input) and only fails validation if BOTH hashes don't match the original state. When an attacker injects XSS payloads using tags stripped by wp_kses() (like <svg>), the sanitized hash matches while the malicious raw value is preserved and saved to the database. When administrators view the Entries List page, the stored malicious consent label is retrieved and output without escaping, causing the XSS payload to execute. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in entries that will execute whenever an authenticated administrator accesses the entries list page.

Casky was already ahead

This CVE exploits attack patterns that Casky's 301matched skills have been training on — 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

Gravity Forms, one of the most widely deployed form plugins for WordPress, contains a critical stored cross-site scripting vulnerability in its Consent field functionality affecting versions up to 2.10.0. The flaw stems from a flawed state validation mechanism that creates two separate hashes—one from raw input and one from wp_kses-sanitized input—and only rejects validation if BOTH fail to match the original state. This logic fails open, allowing attackers to inject malicious JavaScript payloads that persist in the database and execute in the browsers of site visitors and administrators. Organizations running WordPress sites with Gravity Forms installed are at immediate risk, particularly those collecting sensitive information through forms (customer data, contact details, etc.). A successful attack could lead to credential theft, session hijacking, malware distribution, or complete site compromise.

Casky.ai's 301 mapped security skills enable practitioners to detect the attack patterns behind this vulnerability across MITRE ATT&ACK techniques TA0001 (Reconnaissance) and TA0043 (Resource Development). Security teams using Casky with Claude's extended reasoning can identify suspicious form input patterns that bypass validation, unusual script content in database queries, and XSS payload characteristics in form field submissions. Practitioners would observe findings indicating anomalous Consent field inputs containing script tags, event handlers, or encoded payloads that shouldn't exist after sanitization; database integrity checks revealing stored malicious content; and behavioral patterns consistent with post-exploitation reconnaissance where attackers probe victim sessions. The skills help teams pinpoint the exact validation bypass mechanism and differentiate this vulnerability from other XSS vectors through signature detection of the dual-hash comparison failure pattern.

301 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-5113.

analyzing-apt-group-with-mitre-navigator

threat intelligence · low

Run

analyzing-campaign-attribution-evidence

threat intelligence · low

Run

analyzing-certificate-transparency-for-phishing

threat intelligence · low

Run

MITRE ATT&CK Techniques

TA0001 TA0043

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