CVE-2026-7166
Published: 22 June 2026
Summary
CVE-2026-7166 is a critical-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Incibe (inferred from references). Its CVSS base score is 9.2 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked at the 30.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-38236
- 🇪🇸 INCIBE: www.incibe.es
Vulnerability details
Vulnerability involving the exposure of sensitive data provided without adequate protection. The API exposes email and phone number data from the ‘email’ and ‘telefon’ fields. This vulnerability is also present in the local database, as it contains accessible sensitive information…
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such as data on minors and municipal users. Successful exploitation of this vulnerability could allow an unauthenticated remote attacker to gain access to sensitive information and data.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Direct exposure of email addresses and user data enables account discovery via the vulnerable API/DB.
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.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.