Cyber Resilience

CVE-2026-10992

Google Chrome ≤ 149.0.7827.53

Published
04 June 2026
Modified
20 July 2026
CVSS Score v3.1 6.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N
EPSS Score 0.0031 23th percentile
Risk Priority 35 floored blend · peak EPSS

Summary

CVE-2026-10992 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Google Chrome. Its CVSS base score is 6.5 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Drive-by Compromise (T1189); ranked at the 23th 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 AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

Insufficient data validation in Animation in Google Chrome prior to 149.0.7827.53 allowed a remote attacker to obtain potentially sensitive information from process memory via a crafted HTML page. (Chromium security severity: Medium)

CWE(s)

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1189 Drive-by Compromise Initial Access
Adversaries may gain access to a system through a user visiting a website over the normal course of browsing.
Why these techniques?

Direct info leak via crafted HTML enables drive-by compromise for memory data access in browser.

Confidence: MEDIUM · MITRE ATT&CK Enterprise v19.0

CVEs Like This One

CVE-2026-13893Same product: Google Chrome
CVE-2026-16415Same product: Google Chrome
CVE-2026-13921Same product: Google Chrome
CVE-2026-13959Same product: Google Chrome
CVE-2026-14009Same product: Google Chrome
CVE-2026-14083Same product: Google Chrome
CVE-2026-16421Same product: Google Chrome
CVE-2026-10974Same product: Google Chrome
CVE-2026-11066Same product: Google Chrome
CVE-2026-14411Same product: Google Chrome

Affected Assets

google
chrome
≤ 149.0.7827.53

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)
  • SI-10 Information Input Validation
  • AC-4 Information Flow Enforcement
  • SI-16 Memory Protection
Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)
  • 6 hardening rules · 3 OS baselines
Validate
Prove the fix (OWASP ASVS)

Mitigating Controls (NIST 800-53 r5) AI

prevent

Directly enforces validation of untrusted inputs (crafted HTML/animation data) to block the CWE-20 flaw that leaks process memory.

prevent

Enforces information-flow policies that can stop unauthorized exfiltration of sensitive data from browser process memory.

prevent

Applies memory-protection mechanisms that reduce the ability to read sensitive contents from a compromised Chrome process.

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.

PR.PS-06 mostly match
prevents

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.

detects

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.

prevents

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.

prevents

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.

prevents

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.

prevents

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.

none

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.

References