Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:NSummary
CVE-2025-64351 is a medium-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 11th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-15 (Information Output Filtering) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-37341
Vulnerability Data
Insertion of Sensitive Information Into Sent Data vulnerability in Rank Math SEO Rank Math SEO seo-by-rank-math allows Retrieve Embedded Sensitive Data.This issue affects Rank Math SEO: from n/a through <= 1.0.252.1.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Insufficient information to map techniques.CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly filters sensitive information from being included in outputs or responses sent by the Rank Math SEO plugin.
Enforces information flow policies to block unauthorized sensitive data from leaving the system in plugin-generated responses.
Requires confidentiality protection on transmitted data, mitigating exposure when sensitive information is inadvertently inserted by the plugin.
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 prevent insertion of sensitive data into application outputs and messages.
Monitoring runtime data flows and outputs can detect sensitive data being transmitted.
Protecting data-in-transit can include filtering or encrypting to avoid exposing sensitive content.
Protecting data-in-use includes removing confidential values before they are processed or sent.
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.
Data-masking techniques can prevent sensitive values from appearing in transmitted payloads.
Classification identifies sensitive data so it is not inadvertently transmitted.
Labelling makes sensitive data visible to developers and prevents accidental inclusion in outbound messages.
Information-transfer rules directly govern what data may be sent to external parties.
PII-protection requirements reduce the chance of sending personal data to unauthorized recipients.
DLP controls inspect and block outbound flows that contain sensitive information.