PatchSiren cyber security CVE debrief
CVE-2026-6230 tainacan CVE debrief
The Tainacan plugin for WordPress, specifically versions up to and including 1.0.3, is vulnerable to a time-based blind SQL Injection attack. This vulnerability exists due to insufficient escaping of the user-supplied 'geoquery' parameter and a lack of sufficient preparation on the existing SQL query. As a result, unauthenticated attackers can inject additional SQL queries, potentially leading to the disclosure of sensitive information. Users of the Tainacan plugin for WordPress should be aware of this vulnerability and take necessary actions to mitigate the risk. This vulnerability allows attackers to append additional SQL queries into existing queries, which can be used to extract sensitive information from the database.
- Vendor
- tainacan
- Product
- Unknown
- CVSS
- HIGH 7.5
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-07-08
- Original CVE updated
- 2026-07-08
- Advisory published
- 2026-07-08
- Advisory updated
- 2026-07-08
Who should care
Users of the Tainacan plugin for WordPress, particularly those with versions up to and including 1.0.3, should be aware of this vulnerability and take necessary actions to mitigate the risk. This includes updating the plugin to a version beyond 1.0.3, implementing monitoring for suspicious database queries, and restricting access to the plugin's functionality.
Technical summary
The vulnerability in the Tainacan plugin for WordPress is caused by insufficient escaping on the user-supplied 'geoquery' parameter and a lack of sufficient preparation on the existing SQL query. This allows attackers to inject additional SQL queries, potentially leading to sensitive information disclosure. The vulnerability affects all versions up to and including 1.0.3 of the plugin. Users should update the plugin to a version beyond 1.0.3 to mitigate this risk.
Defensive priority
High priority should be given to updating the Tainacan plugin to a version beyond 1.0.3. In the meantime, users can implement compensating controls such as monitoring database queries for suspicious activity and restricting access to the plugin's functionality.
Recommended defensive actions
- Update the Tainacan plugin to a version beyond 1.0.3
- Implement monitoring for suspicious database queries
- Restrict access to the plugin's functionality
- Consider using a Web Application Firewall (WAF) to detect and prevent SQL injection attacks
- Review compensating controls for exposed systems while remediation is scheduled and verified
- Check relevant monitoring, detection, and logs for exposed assets that need extra review
- Track exceptions, retest remediated assets, and close the item only after evidence is documented
Evidence notes
The CVE record was published on 2026-07-08T12:17:20.660Z and last modified on 2026-07-08T14:55:07.843Z. The NVD entry is currently Deferred. The Tainacan plugin for WordPress is vulnerable to time-based blind SQL Injection via the 'geoquery' parameter in all versions up to and including 1.0.3 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database. Evidence is limited to CVE and NVD details.
Sources and references
Verified primary and authoritative sources
-
CVE-2026-6230 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-6230
CVE Program - Official CVE Program record with source-provided CVE metadata.
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CVE-2026-6230 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-6230
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
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Source reference
Unverified legacy reference
URL: https://github.com/tainacan/tainacan/commit/579d28d7752b27ed3407f5197abb6349b3efc3c9
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.