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Hubuum client library (Rust): Sensitive data may be exposed through default diagnostics

Low severity GitHub Reviewed Published Jul 23, 2026 in hubuum/hubuum-client-rust • Updated Jul 24, 2026

Package

cargo hubuum_client (Rust)

Affected versions

<= 0.6.0

Patched versions

0.6.1

Description

Summary

hubuum_client diagnostics can expose sensitive request, response, import/export, task, delivery, or server-provided data when applications format or log errors and public models.

Affected behavior

Native reqwest::Error values retain the full request URL. Converting those errors into ApiError::Http, or exhausting retries and storing the error text in ApiError::RetryExhausted, preserves query parameter values. Detailed HTTP and decoding errors can retain server-provided messages, response bodies, or payload details, including through error source chains.

Several public response and model types also derived or implemented diagnostics over untrusted or secret-adjacent fields. These include raw response bodies and cursors; rendered and JSON export payloads; import schemas and object data; task summaries, links, output URLs, events, and import-result details; event-delivery claims and errors; event sink configuration; subscription routing; and remote-call failure details. High-level backup and export runners additionally copied unsuccessful server task summaries into ApiError::Api.

Applications commonly log errors and response values, so credentials, tokens, cursors, filters, echoed request content, imported object data, schema defaults, task or delivery details, and other sensitive payloads can be written to logs even though normal request logging redacts query values.

Remediation

The proposed fix redacts query values from embedded request URLs before storing native HTTP errors and applies the same sanitization to exhausted retries. Default error and model diagnostics now report safe metadata rather than server messages, payloads, cursors, links, configuration, or secret-adjacent details. JSON codec errors no longer appear in the standard source chain, and unsuccessful high-level backup/export operations use the structured TaskUnsuccessful variant without copying task summaries.

Explicit response, error, task, import, export, event, and delivery APIs continue to expose original values for applications that deliberately inspect them.

Validation

Regression coverage exercises direct HTTP conversion, async and blocking retry exhaustion, response and decoding diagnostics, import/export/raw-response containers, unsuccessful async and blocking task runners, task/event/import-result models, and secret-bearing event and remote models. The workspace format, lint, documentation, test, feature-matrix, Rust 1.88 MSRV, OpenAPI validation, release-metadata, and combined library plus consumer integration suites pass against the immutable Hubuum 0.0.3 image.

References

@terjekv terjekv published to hubuum/hubuum-client-rust Jul 23, 2026
Published to the GitHub Advisory Database Jul 24, 2026
Reviewed Jul 24, 2026
Last updated Jul 24, 2026

Severity

Low

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Insertion of Sensitive Information into Log File

The product writes sensitive information to a log file. Learn more on MITRE.

CVE ID

No known CVE

GHSA ID

GHSA-2625-rw7m-5q5x

Source code

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