CVE-2026-104872 in opentelemetry-js-contrib
Summary
by MITRE • 10/02/2026
OpenTelemetry JavaScript Contrib provides instrumentation libraries for collecting telemetry from JavaScript applications. Prior to versions 0.66.0 of @opentelemetry/instrumentation-cassandra-driver, 0.65.0 of @opentelemetry/instrumentation-knex, 0.67.0 of @opentelemetry/instrumentation-mongoose, @opentelemetry/instrumentation-mysql, and @opentelemetry/instrumentation-mysql2, 0.46.0 of @opentelemetry/instrumentation-oracledb, 0.73.0 of @opentelemetry/instrumentation-pg, and 0.40.0 of @opentelemetry/instrumentation-tedious, the packages add the database connection username to every instrumented database operation as the db.user span attribute. The attribute is emitted by default and is not controlled by enhancedDatabaseReporting or another opt-in setting. Configured observability backends therefore receive database account names that may expose service topology, role or environment information, and account naming patterns. This issue is fixed in versions 0.66.0, 0.65.0, 0.67.0, 0.46.0, 0.73.0, and 0.40.0 of the respective packages.
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Analysis
by VulDB Data Team • 10/02/2026
The OpenTelemetry JavaScript Contrib project provides a suite of instrumentation libraries designed to automatically collect telemetry data from various JavaScript applications, facilitating observability through metrics, traces, and logs. A significant information disclosure vulnerability was identified within several of these database-specific instrumentation packages prior to their respective patched versions. Specifically, the flaw affects opentelemetry/instrumentation-cassandra-driver before version 0.66.0, opentelemetry/instrumentation-knex before version 0.65.0, opentelemetry/instrumentation-mongoose and related MySQL instrumentation packages (opentelemetry/instrumentation-mysql and opentelemetry/instrumentation-mysql2) before version 0.67.0, opentelemetry/instrumentation-oracledb before version 0.46.0, opentelemetry/instrumentation-pg before version 0.73.0, and opentelemetry/instrumentation-tedious before version 0.40.0. This vulnerability stems from the default behavior of these libraries to automatically inject sensitive contextual data into telemetry spans without adequate sanitization or user control mechanisms in earlier releases.
The core technical flaw involves the automatic inclusion of the database connection username as a span attribute named db.user for every instrumented database operation executed by an application using these libraries. This attribute is emitted by default and, critically, it was not gated behind configuration flags such as enhancedDatabaseReporting or other opt-in settings that typically govern sensitive data collection in OpenTelemetry instrumentation. Consequently, any observability backend configured to receive telemetry from the affected applications would automatically ingest plaintext database account names with every query executed. This behavior persists regardless of whether the application developer intended for such detailed connection metadata to be exported, creating a passive but persistent channel for information leakage.
The operational impact of this vulnerability extends beyond simple credential exposure and touches upon broader security principles regarding service topology and identity management. The inclusion of database usernames in telemetry data can inadvertently reveal sensitive architectural details about the environment. For instance, account naming patterns often correlate with specific environments such as development, staging, or production, allowing attackers to infer the operational context of the target system. Furthermore, these names may reflect role-based access control structures, revealing which services interact with databases and potentially exposing internal service dependencies that should remain hidden from external observers. If an attacker gains access to telemetry data through a compromised observability backend or via network interception during transmission, they can leverage this information for reconnaissance purposes, mapping out the application's infrastructure and identifying high-value targets based on privileged account names.
This vulnerability aligns with CWE-200, which defines Information Exposure as the intentional or unintentional disclosure of information to an actor that is not explicitly authorized to have access to that information. It also relates to CWE-532, where log entries contain sensitive personal data, although in this case, the exposure occurs via telemetry spans rather than traditional application logs. From a threat modeling perspective using the MITRE ATT&CK framework, this behavior facilitates Reconnaissance activities under techniques such as T1087 (Account Discovery) and potentially aids in lateral movement if combined with other vulnerabilities by providing clear indicators of internal service roles and connections. The lack of an opt-in mechanism for sensitive attributes like usernames represents a design oversight where security-by-default principles were not fully applied to identity-related metadata.
To mitigate this risk, organizations must ensure that all affected OpenTelemetry instrumentation packages are upgraded to their patched versions immediately. For opentelemetry/instrumentation-cassandra-driver, the version should be updated to 0.66.0 or higher; for opentelemetry/instrumentation-knex, it is 0.65.0 or higher; for opentelemetry/instrumentation-mongoose, mysql, and mysql2 instruments, the threshold is 0.67.0 or higher; for opentelemetry/instrumentation-oracledb, version 0.46.0 or later is required; for pg instrumentation, version 0.73.0 or newer must be installed; and for tedious instrumentation, version 0.40.0 or above resolves the issue. In addition to upgrading dependencies, developers should audit their telemetry configurations to ensure that no other sensitive attributes are being inadvertently exported without proper sanitization policies. Implementing strict data filtering rules at the observability backend level can also serve as a compensating control to strip out any remaining db.user fields before they are stored or analyzed, thereby reducing the attack surface for information disclosure attacks.