CVE-2020-8276 in Brave
Summary
by MITRE • 11/09/2020
The implementation of Brave Desktop's privacy-preserving analytics system (P3A) between 1.1 and 1.18.35 logged the timestamp of when the user last opened an incognito window, including Tor windows. The intended behavior was to log the timestamp for incognito windows excluding Tor windows. Note that if a user has P3A enabled, the timestamp is not sent to Brave's server, but rather a value from:Used in last 24hUsed in last week but not 24hUsed in last 28 days but not weekEver used but not in last 28 daysNever usedThe privacy risk is low because a local attacker with disk access cannot tell if the timestamp corresponds to a Tor window or a non-Tor incognito window.
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Analysis
by VulDB Data Team • 12/04/2020
The vulnerability identified as CVE-2020-8276 resides within Brave Desktop's privacy-preserving analytics system known as P3A, affecting versions between 1.1 and 1.18.35. This flaw represents a deviation from the intended privacy protections designed to safeguard user anonymity while browsing incognito mode. The system was engineered to distinguish between regular incognito windows and Tor windows, with the latter requiring special handling due to their enhanced privacy requirements. However, the implementation contained a logical error that caused timestamps for all incognito window usage to be recorded regardless of the underlying browsing context, including those utilizing the Tor network for anonymous browsing.
The technical flaw manifests in the improper categorization of timestamp data within the P3A framework, where the system failed to correctly filter out Tor window activity from regular incognito window logging. This misclassification creates a potential privacy leak even though the actual timestamp data remains local to the user's device and is not transmitted to Brave's servers. The system employs a sophisticated anonymization technique that transforms raw timestamp data into categorical values such as "Used in last 24h", "Used in last week but not 24h", "Used in last 28 days but not week", "Ever used but not in last 28 days", and "Never used". These categorical representations are designed to prevent direct correlation with specific user activities while maintaining statistical utility for analytics purposes.
The operational impact of this vulnerability extends beyond simple data logging errors, as it introduces a subtle but significant privacy concern for users who employ Tor windows within Brave's incognito mode. While the risk assessment indicates that local attackers with disk access cannot definitively determine whether a timestamp corresponds to Tor or non-Tor incognito usage, the mere existence of this information collection creates potential for indirect correlation attacks. The vulnerability aligns with CWE-200, which addresses "Information Exposure," and represents a deviation from the principle of least privilege in privacy data collection. Attackers could potentially leverage this information alongside other behavioral patterns or metadata to infer user activities that should remain private, particularly in environments where Tor usage indicates sensitive or potentially targeted browsing behavior.
The security implications of this vulnerability are particularly concerning given the nature of Tor window usage, which often indicates activities requiring heightened privacy protection such as accessing sensitive information, conducting research, or engaging in activities that may be monitored or restricted in certain jurisdictions. This flaw demonstrates the complexity of implementing privacy-preserving systems and the potential for subtle implementation errors to undermine security assumptions. The vulnerability also reflects challenges in the ATT&CK framework's T1566 technique related to credential access through local system reconnaissance, as it creates additional data points that could be exploited by adversaries with local access to determine user behavior patterns and potentially identify Tor usage. Organizations and individuals relying on Brave's privacy protections should consider the potential for this information to be combined with other data sources to create more comprehensive behavioral profiles than intended by the system's design. The incident underscores the importance of rigorous testing and peer review of privacy-preserving mechanisms, particularly those involving complex data categorization and anonymization techniques that must maintain strict separation between different user contexts and privacy requirements.