CVE-2026-42534
Nlnetlabs Unbound ≤ 1.25.1
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/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:AmberSummary
CVE-2026-42534 is a medium-severity Expected Behavior Violation (CWE-440) vulnerability in Nlnetlabs Unbound. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 45th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-6 (Security and Privacy Function Verification) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-31082
Vulnerability Data
NLnet Labs Unbound up to and including version 1.25.0 has a vulnerability in the jostle logic that could defeat its purpose and degrade resolution performance. Retransmits of the same query could renew the age of slow running queries and not…
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allow the jostle logic to see them as aged and potential targets for replacement with new queries. An adversary who can query a vulnerable Unbound and who can control a domain name server that replies slowly and/or maliciously to Unbound's queries can exploit the vulnerability and degrade the resolution performance of Unbound. When Unbound's 'num-queries-per-thread' reaches its limit, the jostle logic kicks in. When a new query comes in, half of the available queries that are also slow to resolve are candidates for replacement. The vulnerability then happens because duplicate queries that need resolution would skew the aging result by using the timestamp of the latest duplicate query instead of the original one that started the resolution effort. Cache and local data response performance remains unaffected. Coordinated attacks could raise this to a denial of resolution service. Unbound 1.25.1 contains a patch with a fix to attach an initial, non-updatable start time for incoming queries that allow the jostle logic to work as intended.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation directly checks whether implemented functions match their specifications.
Security function verification confirms that functions operate according to their defined expected behavior.
Documented development standards and tools can mandate safe reference-count patterns and static checks.
Requiring a documented security architecture and design reduces the chance that implementation deviates from intended behavior.
Engineering principles can require correct resource lifetime and reference management during design and implementation.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly enforce specification compliance and catch expected-behavior violations during development.
Security testing and exercises help discover behavior deviations before deployment.
Vulnerability identification can surface spec-violating flaws, while eliminating the weakness reduces some vulnerability backlog.
Routine software maintenance and patching can remediate discovered specification violations.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development and acceptance validates that functions behave as specified.
Secure development life cycle mandates verification against specifications, directly reducing expected-behavior violations.
Application security requirements explicitly define expected behavior that must be met.
Secure system architecture principles encourage explicit resource-ownership models that mitigate reference-count misuse.
Secure coding practices enforce adherence to functional specifications during implementation.
Change management can catch specification deviations introduced by modifications.