CVE-2026-17730 in Chrome
Summary
by MITRE • 07/30/2026
Side-channel information leakage in Autofill in Google Chrome prior to 151.0.7922.72 allowed a remote attacker who convinced a user to engage in specific UI gestures to leak cross-origin data via a crafted HTML page. (Chromium security severity: Medium)
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 07/30/2026
This vulnerability represents a sophisticated side-channel attack targeting Google Chrome's autofill functionality, specifically exploiting information leakage mechanisms that occur during user interaction with web forms. The flaw emerged from the way Chrome's autofill system handled cross-origin data exposure when users performed specific UI gestures on maliciously crafted HTML pages. The vulnerability was classified as medium severity by Chromium security team but carries significant implications for user privacy and data protection. Attackers could leverage this weakness to extract sensitive information from different origins by carefully orchestrating user interactions with specially designed web content.
The technical implementation of this vulnerability stems from insufficient isolation mechanisms between cross-origin contexts within Chrome's autofill subsystem. When users interacted with specific UI elements on compromised pages, the browser's autofill system would inadvertently expose data through timing variations or other observable side channels that could be measured by malicious actors. This type of information leakage typically occurs when the underlying system behavior differs predictably based on internal state information, creating observable patterns that can be reverse-engineered to extract meaningful data. The vulnerability specifically impacted the interaction between Chrome's user interface gesture handling and its autofill data processing components, creating a pathway for cross-origin data exfiltration.
The operational impact of this vulnerability extends beyond simple data leakage to represent a serious threat to user privacy and application security. Attackers could potentially access sensitive information such as form field contents, user preferences, or other autofill-related data from different origins without requiring direct network access or traditional exploitation methods. The attack vector required social engineering to convince users to perform specific UI gestures, making it particularly dangerous in targeted phishing campaigns or malicious website scenarios where user interaction was already expected. This vulnerability directly impacts the principle of least privilege and cross-origin isolation that modern browsers implement to protect user data, creating a scenario where legitimate browser functionality could be weaponized for information extraction.
Mitigation strategies for this vulnerability involve both immediate patching and architectural improvements to prevent similar side-channel attacks in the future. Chrome users should immediately update to version 151.0.7922.72 or later to receive the security fixes that address the underlying information leakage mechanisms. Browser vendors should implement additional safeguards around cross-origin interactions, particularly in components that handle user input and data processing. The fix likely involved strengthening isolation between different origin contexts during autofill operations and eliminating observable timing variations that could be exploited for information extraction. This vulnerability highlights the importance of considering side-channel attack vectors in browser security design and aligns with common attack patterns documented in the attack framework, particularly those involving information leakage through system behavior variations. Organizations should monitor for similar vulnerabilities in other browser components and implement comprehensive testing for side-channel risks in their security assessment processes.
This type of vulnerability falls under the category of information leakage attacks that are commonly categorized as CWE-203 Information Exposure Through Discrepancy, where differences in system behavior between different states create observable patterns that can be exploited. The attack methodology also relates to techniques described in MITRE ATT&CK framework under T1566 credential access and data exfiltration tactics, demonstrating how seemingly benign browser features can become attack vectors when proper isolation mechanisms are lacking. The security implications extend beyond individual user privacy concerns to potentially affect enterprise environments where users may be exposed to malicious content through various attack vectors including phishing emails, compromised websites, or social engineering campaigns that leverage these types of browser vulnerabilities.