CVE-2023-6459 in Mattermost
Summary
by MITRE • 12/06/2023
Mattermost is grouping calls in the /metrics endpoint by id and reports that id in the response. Since this id is the channelID, the public /metrics endpoint is revealing channelIDs.
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Analysis
by VulDB Data Team • 12/30/2023
The vulnerability described in CVE-2023-6459 affects the Mattermost collaboration platform, specifically exposing sensitive channel identifiers through its metrics endpoint. This issue represents a significant information disclosure concern that undermines the platform's security posture by inadvertently revealing internal system identifiers to unauthorized parties. The vulnerability stems from the design of the metrics endpoint which aggregates and reports data grouping calls by channel identifiers, thereby making channel IDs accessible through what should be a public monitoring interface. This exposure occurs because the metrics endpoint does not properly sanitize or obfuscate the channel identifiers that are used as grouping keys in its reporting mechanism.
The technical flaw manifests in the way the /metrics endpoint processes and presents data aggregation results. When the system groups calls by channel ID for reporting purposes, it fails to implement proper access controls or data masking techniques that would prevent sensitive identifiers from being exposed to public consumers of the metrics endpoint. This design oversight creates a situation where any user with access to the public metrics endpoint can extract channel identifiers, potentially enabling further reconnaissance activities. The vulnerability aligns with CWE-200, which addresses improper exposure of sensitive information, and represents a clear violation of the principle of least privilege by making internal system identifiers accessible without proper authorization. The channel IDs exposed through this mechanism can be used by attackers to gain insights into the platform's internal structure, potentially enabling targeted attacks against specific channels or users within those channels.
The operational impact of this vulnerability extends beyond simple information disclosure, as channel IDs can serve as valuable intelligence for attackers conducting reconnaissance activities. Once an attacker obtains channel IDs, they can potentially use this information to craft more targeted social engineering attacks, identify high-value channels for compromise, or map the platform's organizational structure. The exposure of channel identifiers also creates opportunities for enumeration attacks where adversaries systematically discover and target specific channels within the Mattermost environment. This vulnerability particularly affects organizations that rely on Mattermost for sensitive communications, as it undermines the confidentiality of internal channel structures and could lead to unauthorized access to private conversations. The attack surface is further expanded when considering that channel IDs may be used in conjunction with other vulnerabilities or attack vectors to compromise the overall security posture of the platform.
Organizations should implement immediate mitigations to address this vulnerability by ensuring that the metrics endpoint properly sanitizes or removes channel identifiers from public responses. The recommended approach involves modifying the endpoint's data processing logic to either obfuscate or completely remove channel identifiers from the metrics output, preventing their exposure to unauthorized users. Additionally, access controls should be implemented to restrict access to the metrics endpoint to authorized personnel only, ensuring that sensitive information is not inadvertently exposed through public interfaces. This remediation aligns with ATT&CK technique T1592, which focuses on reconnaissance through information gathering, and emphasizes the importance of proper data sanitization and access control implementation. Organizations should also conduct regular security assessments of their monitoring and metrics endpoints to identify similar vulnerabilities that may expose internal system identifiers or sensitive information to unauthorized parties. The implementation of proper logging and monitoring for access to the metrics endpoint can help detect potential abuse of this vulnerability and provide early warning of reconnaissance activities targeting the platform's internal structures.