Skip to content

Hickory DNS's DNSSEC validation may accept broken authentication chains

Moderate severity GitHub Reviewed Published Feb 8, 2025 in hickory-dns/hickory-dns • Updated Feb 10, 2025

Package

cargo hickory-proto (Rust)

Affected versions

>= 0.8.0, < 0.24.3

Patched versions

0.24.3

Description

Summary

The DNSSEC validation routines treat entire RRsets of DNSKEY records as trusted once they have established trust in only one of the DNSKEYs. As a result, if a zone includes a DNSKEY with a public key that matches a configured trust anchor, all keys in that zone will be trusted to authenticate other records in the zone. There is a second variant of this vulnerability involving DS records, where an authenticated DS record covering one DNSKEY leads to trust in signatures made by an unrelated DNSKEY in the same zone.

Details

verify_dnskey_rrset() will return Ok(true) if any record's public key matches a trust anchor. This results in verify_rrset() returning a Secure proof. This ultimately results in successfully verifying a response containing DNSKEY records. verify_default_rrset() looks up DNSKEY records by calling handle.lookup(), which takes the above code path. There's a comment following this that says "DNSKEYs were already validated by the inner query in the above lookup", but this is not the case. To fully verify the whole RRset of DNSKEYs, it would be necessary to check self-signatures by the trusted key over the other keys. Later in verify_default_rrset(), verify_rrset_with_dnskey() is called multiple times with different keys and signatures, and if any call succeeds, then its Proof is returned.

Similarly, verify_dnskey_rrset() returns Ok(false) if any DNSKEY record is covered by a DS record. A comment says "If all the keys are valid, then we are secure", but this is only checking that one key is authenticated by a DS in the parent zone's delegation point. This time, after control flow returns to verify_rrset(), it will call verify_default_rrset(). The special handling for DNSKEYs in verify_default_rrset() will then call verify_rrset_with_dnskey() using each KSK DNSKEY record, and if one call succeeds, return its Proof. If there are multiple KSK DNSKEYs in the RRset, then this leads to another authentication break. We need to either pass the authenticated DNSKEYs from the DS covering check to the RRSIG validation, or we need to perform this RRSIG validation of the DNSKEY RRset inside verify_dnskey_rrset() and cut verify_default_rrset() out of DNSKEY RRset validation entirely.

PoC

The proof of concepts have been integrated into the conformance test suite, as resolver::dnssec::scenarios::bogus::bogus_zone_plus_trust_anchor_dnskey and resolver::dnssec::scenarios::bogus::bogus_zone_plus_ds_covered_dnskey.

Impact

This impacts Hickory DNS users relying on DNSSEC verification in the client library, stub resolver, or recursive resolver.

References

@bluejekyll bluejekyll published to hickory-dns/hickory-dns Feb 8, 2025
Published to the GitHub Advisory Database Feb 10, 2025
Reviewed Feb 10, 2025
Published by the National Vulnerability Database Feb 10, 2025
Last updated Feb 10, 2025

Severity

Moderate

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 None
Integrity High
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:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(11th percentile)

Weaknesses

CVE ID

CVE-2025-25188

GHSA ID

GHSA-37wc-h8xc-5hc4

Source code

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.