Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:LSummary
CVE-2026-23493 is a high-severity Insertion of Sensitive Information into Log File (CWE-532) vulnerability in Pimcore Pimcore. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Unsecured Credentials (T1552); ranked at the 32th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-23493 affects Pimcore, an open-source data and experience management platform, in versions prior to 12.3.1 and 11.5.14. The vulnerability arises because the http_error_log file logs sensitive data from the $_COOKIE and $_SERVER superglobals, including database passwords, session cookies, and other potentially confidential details. This information exposure through log files (CWE-532) has a CVSS v3.1 base score of 8.6 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L), indicating high severity due to significant confidentiality impact.
Unauthenticated attackers with network access can exploit this vulnerability by accessing the http_error_log file through the Pimcore backend, without requiring privileges or user interaction. Successful exploitation allows recovery of sensitive credentials and session data, potentially enabling further compromise such as unauthorized database access, session hijacking, or lateral movement within the environment, alongside limited integrity and availability disruption.
Mitigation is available through patches released for the affected branches: upgrade to Pimcore 12.3.1 or 11.5.14. The fixes are detailed in GitHub commit 002ec7d5f84973819236796e5b314703b58e8601, pull request #18918, and the corresponding release tags, with additional guidance in the GHSA-q433-j342-rp9h security advisory.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-2729
Vulnerability Data
Pimcore is an Open Source Data & Experience Management Platform. Prior to 12.3.1 and 11.5.14, the http_error_log file stores the $_COOKIE and $_SERVER variables, which means sensitive information such as database passwords, cookie session data, and other details can be…
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accessed or recovered through the Pimcore backend. This vulnerability is fixed in 12.3.1 and 11.5.14.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Procedures mandate excluding sensitive data from logs to prevent unauthorized exposure via audit records.
Identifies insertion of sensitive data into logs, allowing detection of unauthorized disclosure.
Cross-organizational coordination enables agreement on what data to include in audit logs, directly reducing insertion of sensitive information.
Identifying logging as a data action allows prevention of sensitive information being inserted into log files.
The process of identifying and eradicating spilled information applies directly to sensitive data inserted into log files.
Specific processing rules for sensitive PII categories commonly include restrictions on logging, making insertion of such data into log files less likely.
PIAs detect planned or existing logging of PII and require removal or protection, preventing insertion of sensitive information into logs.
Limits insertion of sensitive operational details into logs by treating such data as key information requiring protection.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prohibit writing sensitive data to logs; eliminating the weakness satisfies only one narrow slice of the control.
Log generation configuration can and should exclude sensitive data, but the control statement focuses on availability rather than content filtering.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Requiring de-identification and privacy controls before logs leave the organization reduces the chance that sensitive data inadvertently captured in logs becomes exposed to external parties.
By defining what records must be kept, where, and for how long, the control discourages the inadvertent inclusion of sensitive information in logs or other externally accessible files that fall outside the formal record system.
Mandating deletion of temporary files and logs that may contain sensitive information prevents those artifacts from remaining accessible after the data is no longer needed.
When log entries are produced from masked data sets, the control prevents the inadvertent insertion of sensitive values into externally accessible log files.
DLP inspection of logs and file transfers can detect and block the inadvertent placement of sensitive tokens or credentials into externally accessible log files before they are written or transmitted.
Requiring restrictions on free-text fields and proper error-message handling stops developers from embedding or leaking sensitive data into logs or diagnostic output.