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Navidrome has Multiple SQL Injections and ORM Leak

Critical severity GitHub Reviewed Published Sep 20, 2024 in navidrome/navidrome • Updated Sep 20, 2024

Package

gomod github.com/navidrome/navidrome (Go)

Affected versions

< 0.53.0

Patched versions

0.53.0

Description

Security Advisory: Multiple Vulnerabilities in Navidrome

Summary

Navidrome automatically adds parameters in the URL to SQL queries. This can be exploited to access information by adding parameters like password=... in the URL (ORM Leak).

Furthermore, the names of the parameters are not properly escaped, leading to SQL Injections.

Finally, the username is used in a LIKE statement, allowing people to log in with % instead of their username.

Details

ORM Leak

When adding parameters to the URL, they are automatically included in an SQL LIKE statement (depending on the parameter's name). This allows attackers to potentially retrieve arbitrary information.

For example, attackers can use the following request to test whether some encrypted passwords start with AAA:

GET /api/user?_end=36&_order=DESC&password=AAA%

This results in an SQL query like password LIKE 'AAA%', allowing attackers to slowly brute-force passwords. (Also, any reason for using encryption instead of hashing?)

SQL Injections

When adding parameters to the URL, they are automatically added to an SQL query. The names of the parameters are not properly escaped.

This behavior can be used to inject arbitrary SQL code (SQL Injection), for example:

GET /api/album?_end=36&_order=DESC&_sort=recently_added&_start=0&SELECT+*+FROM+USER--=123 HTTP/1.1

This is only an example, but you should see an error message in the logs.

Authentication Weakness

When retrieving the user for authentication, the following code is used:

func (r *userRepository) FindByUsername(username string) (model.User, error) {
    sel := r.newSelect().Columns("").Where(Like{"user_name": username})
    var usr model.User
    err := r.queryOne(sel, &usr)
    return &usr, err
}

This relies on a LIKE statement and allows users to log in with % instead of the legitimate username.

Proof of Concept (PoC)

See above.

Impact

These vulnerabilities can be used to leak information and dump the contents of the database.

Credit

Louis Nyffenegger from PentesterLab

References

@deluan deluan published to navidrome/navidrome Sep 20, 2024
Published to the GitHub Advisory Database Sep 20, 2024
Reviewed Sep 20, 2024
Published by the National Vulnerability Database Sep 20, 2024
Last updated Sep 20, 2024

Severity

Critical

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 None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality High
Integrity High
Availability Low

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:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:L

EPSS score

0.050%
(21st percentile)

Weaknesses

CVE ID

CVE-2024-47062

GHSA ID

GHSA-58vj-cv5w-v4v6

Source code

Credits

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