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Improper Removal of Sensitive Information Before Storage or Transfer in irrd

High severity GitHub Reviewed Published Mar 31, 2022 in irrdnet/irrd • Updated Sep 24, 2024

Package

pip irrd (pip)

Affected versions

>= 4.2.0, < 4.2.3

Patched versions

4.2.3

Description

IRRd did not always filter password hashes in query responses relating to mntner objects and database exports. This may have allowed adversaries to retrieve some of these hashes, perform a brute-force search for the clear-text passphrase, and use these to make unauthorised changes to affected IRR objects. This issue only affected instances that process password hashes, which means it is limited to IRRd instances that serve authoritative databases. IRRd instances operating solely as mirrors of other IRR databases are not affected.

The issue occurred:

  • For mntner objects where all password hash names (MD5-PW and CRYPT-PW) were in lower or mixed case in the auth attribute. For these objects, hashes remained in the output of all queries of any method and all database exports made with the export_destination setting. Fortunately, objects in the common public IRR database virtually all use uppercase hash names which means very few of those objects were affected.
  • For any GraphQL queries that queried the auth field on mntner objects.
  • For any GraphQL queries that queried the objectText field on the journal field on mntner objects, if the nrtm_access_list setting permitted journal access.

The two GraphQL cases are visible in logs, allowing users to determine whether any existing objects had their hashes exposed.
This has been fixed in IRRd 4.2.3 and the main branch. Versions in the 4.1.x series never were affected. Users of the 4.2.x series are strongly recommended to upgrade. All users running a more recent version from the main branch should update to the latest version. Alternatively, but not recommended, apply the patch manually [for 4.2.x]

References

@mxsasha mxsasha published to irrdnet/irrd Mar 31, 2022
Published by the National Vulnerability Database Mar 31, 2022
Published to the GitHub Advisory Database Apr 1, 2022
Reviewed Apr 1, 2022
Last updated Sep 24, 2024

Severity

High

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

EPSS score

0.150%
(52nd percentile)

Weaknesses

CVE ID

CVE-2022-24798

GHSA ID

GHSA-cqxx-66wh-8pjw

Source code

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