CVE-2026-7993
Google Chrome ≤ 148.0.7778.96
Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:N/A:LSummary
CVE-2026-7993 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Google Chrome. Its CVSS base score is 4.2 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Match Legitimate Resource Name or Location (T1036.005); ranked at the 9th 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-10 (Information Input Validation) and SC-39 (Process Isolation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-28089
Vulnerability Data
Insufficient validation of untrusted input in Payments in Google Chrome on Android prior to 148.0.7778.96 allowed a remote attacker who had compromised the renderer process to spoof the contents of the Omnibox (URL bar) via a crafted HTML page. (Chromium…
more
security severity: Medium)
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Vulnerability enables UI spoofing of the Omnibox/URL bar after renderer compromise, directly facilitating masquerading as a legitimate site/resource.
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires validation of untrusted input, addressing the CWE-20 root cause that permitted Omnibox spoofing from a crafted HTML page.
Enforces process isolation between renderer and browser UI components, limiting the impact of a renderer compromise on trusted Omnibox contents.
Enables monitoring of anomalous UI or rendering behavior that could indicate successful spoofing after renderer compromise.
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 require and enforce input validation during development.
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.
Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.
Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.
Regular automated validation of system software and data content, combined with scanning of all inbound files, enforces input validation at the boundary before untrusted content is processed.