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PatchSiren cyber security CVE debrief

CVE-2026-34902 WC Product Table CVE debrief

CVE-2026-34902 is a HIGH severity Unauthenticated Cross Site Scripting (XSS) vulnerability in WooCommerce Product Table Lite versions <= 4.6.3. The vulnerability has a CVSS score of 7.1 and was published on [cvePublishedAt](https://www.cve.org/CVERecord?id=CVE-2026-34902).

Vendor
WC Product Table
Product
WooCommerce Product Table Lite
CVSS
HIGH 7.1
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-15
Original CVE updated
2026-06-15
Advisory published
2026-06-15
Advisory updated
2026-06-15

Who should care

Administrators and users of WooCommerce Product Table Lite versions <= 4.6.3 should apply patches or mitigations to prevent exploitation.

Technical summary

The vulnerability is caused by a lack of proper input validation and sanitization in WooCommerce Product Table Lite versions <= 4.6.3, allowing unauthenticated attackers to inject malicious scripts.

Defensive priority

HIGH

Recommended defensive actions

  • Apply patches or updates to WooCommerce Product Table Lite to version > 4.6.3
  • Review and implement secure coding practices to prevent similar vulnerabilities

Evidence notes

Evidence of this vulnerability was provided by Patchstack (see [ref-4](https://patchstack.com/database/wordpress/plugin/wc-product-table-lite/vulnerability/wordpress-woocommerce-product-table-lite-plugin-4-6-3-cross-site-scripting-xss-vulnerability?_s_id=cve)).

Sources and references

Verified primary and authoritative sources

  • CVE-2026-34902 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-34902

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-34902 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-34902

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.