Customers of over 40,000 websites
A critical unauthenticated vulnerability is being actively exploited in the Funnel Builder plugin for WordPress, impacting more than 40,000 e-commerce websites. The flaw allows attackers to inject malicious JavaScript into the checkout pages of sites using the WooCommerce platform. This injected code functions as a payment skimmer, capturing and exfiltrating sensitive customer data, including credit card numbers, CVVs, and billing information, during the checkout process. The plugin's developer, FunnelKit, has addressed the vulnerability in version 3.15.0.3 and strongly advises all users to update immediately and inspect their sites for signs of compromise.
The vulnerability represents a significant threat to small and medium-sized businesses that rely on WordPress and WooCommerce for their e-commerce operations. The attack is particularly dangerous for several reasons:
This type of attack, often associated with groups like Magecart, involves compromising e-commerce sites to steal payment card data, a practice known as digital skimming or e-skimming.
The root cause of the vulnerability is an insecure public-facing checkout endpoint within the Funnel Builder plugin. This endpoint fails to perform proper permission checks, allowing any unauthenticated user to interact with it.
This attack leverages the T1190 - Exploit Public-Facing Application technique for initial access and T1059.007 - JavaScript for the skimming payload.
For the over 40,000 websites using a vulnerable version of the Funnel Builder plugin, the impact is severe:
Security teams and website administrators should hunt for the following indicators:
file_pathwp-content/plugins/funnel-builder/url_patterng-tag-manager.com, google-tm.comstring_patterncheckout, cardnumber, cvvlog_sourceWeb Server Access LogsImmediately update the Funnel Builder plugin to the patched version (3.15.0.3 or later) to remediate the vulnerability.
Mapped D3FEND Techniques:
Regularly audit WordPress plugins, themes, and configurations for unauthorized changes or suspicious scripts.
Mapped D3FEND Techniques:
Use a Web Application Firewall (WAF) to filter incoming traffic and block requests that match known attack patterns.
Mapped D3FEND Techniques:
The most critical and immediate action for any organization using the Funnel Builder plugin is to perform a Software Update. The vulnerability is a direct result of a code-level flaw that has been fixed by the developer, FunnelKit, in version 3.15.0.3. Delaying this update leaves the e-commerce store completely exposed to unauthenticated attackers. Administrators should navigate to their WordPress dashboard, go to the 'Plugins' section, and initiate the update for 'Funnel Builder by FunnelKit'. It is also advisable to enable automatic updates for critical plugins like this to ensure future vulnerabilities are patched promptly. Before updating a live site, best practice is to take a full backup of the site files and database. After the update is complete, verify that the checkout process and other plugin features are still functioning correctly. This single action closes the entry vector used by the attackers.
For organizations that may have been compromised before patching, System File Analysis is a crucial step in the incident response process. Since the attack involves injecting a malicious script into the plugin's settings, the malicious code is stored within the WordPress database, not just as a file on the server. Security teams or site administrators must inspect the wp_options table in their WordPress database. Look for rows related to FunnelKit or Funnel Builder settings, specifically any that store 'External Scripts'. Carefully examine the content of these fields for any JavaScript that was not added by an administrator. Look for obfuscated code or scripts loaded from suspicious, non-Google domains that mimic Google Tag Manager. A file integrity monitoring tool can also be used to check for unauthorized changes to plugin files themselves, as attackers may leave behind backdoors after the initial compromise. Removing the malicious database entry is key to eradicating the skimmer.
As a proactive and layered defense, implementing Inbound Traffic Filtering via a Web Application Firewall (WAF) can help protect against this and future similar vulnerabilities. A WAF can be configured with rules to inspect incoming HTTP requests to the WordPress site. For this specific Funnel Builder vulnerability, a custom WAF rule could be created to block unauthenticated POST requests to the plugin's vulnerable checkout endpoint. More generically, WAFs can be configured with rulesets that detect and block common web attack patterns, such as SQL injection and Cross-Site Scripting (XSS). While the attackers in this case injected their script through a settings-write vulnerability, a WAF might have detected the script payload within the request and blocked it. This provides an essential layer of protection, especially for zero-day vulnerabilities where a patch is not yet available, or for organizations that are slow to apply updates.

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.
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Every tactic, technique, and sub-technique used in this threat has been identified and mapped to the MITRE ATT&CK framework for consistent, actionable threat language.
Observables and indicators of compromise (IOCs) have been extracted and cataloged. Risk has been assessed and correlated with known threat actors and historical campaigns.
Detection rules, incident response steps, and D3FEND-aligned mitigation strategies are included so your team can act on this intelligence immediately.
Structured threat data is packaged as a STIX 2.1 bundle and can be visualized as an interactive graph β relationships between actors, malware, techniques, and indicators.
Sigma detection rules are derived from the threat techniques in this article and can be converted for deployment across any major SIEM or EDR platform.