WooCommerce Product Feed Manager SQL Injection Flaw

The Product Feed Manager For WooCommerce WordPress plugin before 7.6.1 does not properly sanitise and escape product-feed custom filter rules before using them in a SQL query, allowing users with the Contributor role and above to perform SQL injection attacks.

Casky was already ahead

This CVE exploits attack patterns that Casky's 322matched 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 Product Feed Manager For WooCommerce plugin before version 7.6.1 contains a critical SQL injection vulnerability in its custom filter rules functionality. This vulnerability stems from improper sanitization and escaping of user-supplied input before it's incorporated into SQL queries (CWE-89). Any user with Contributor role or higher—a relatively common permission level in WordPress environments—can exploit this to execute arbitrary SQL commands against the site's database. This is particularly dangerous because contributors are often content creators or editors who may not be suspected of malicious intent, making this an insider-threat vector. Organizations running affected versions of this plugin face risks including unauthorized data access, data manipulation, authentication bypass, and potential lateral movement within their infrastructure.

Casky's 322 mapped skills leverage Claude AI with extended reasoning to detect the attack patterns associated with this vulnerability across MITRE ATT&CK's Initial Access (TA0001) and Persistence (TA0043) techniques. Practitioners using Casky would identify suspicious activity patterns including: malformed SQL syntax in application logs, unusual database query execution from low-privileged WordPress accounts, database connection attempts with unexpected parameters, and authentication anomalies in wp-admin access logs. The platform's skills would flag filter rule parameters containing SQL keywords (SELECT, UNION, DROP, etc.) and monitor for sequential requests that probe database structure—classic SQL injection reconnaissance. By correlating these behavioral indicators with known exploitation signatures, Casky helps practitioners detect both pre-attack reconnaissance and active exploitation attempts before successful compromise occurs.

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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 →

322 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-15258.

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

Investigate the attack patterns behind CVE-2026-15258

Casky has 322 skills that investigate the attack patterns behind CVE-2026-15258. Run one and get CVSS-scored findings in 3 minutes.

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