CVE-2026-67223 (GCVE-0-2026-67223)
Vulnerability from cvelistv5 – Published: 2026-09-25 16:15 – Updated: 2026-09-25 17:51
VLAI
EPSS
VEX
Title
RabbitMQ: LDAP DN injection via unescaped substitution
Summary
RabbitMQ is a messaging and streaming broker. The advisory establishes affected 3.13, 4.0, 4.1, 4.2, and 4.3 maintenance lines but contains conflicting first-fixed versions for the 3.13, 4.0, and 4.1 lines. fill/2 substitutes ${username} into user_dn_pattern without RFC 4514 DN escaping, allowing a crafted username to alter the LDAP bind DN and potentially select a different directory entry. Exploitation requires rabbitmq_auth_backend_ldap with a user_dn_pattern containing ${username}, a directory layout in which the injected suffix resolves usefully, and a password valid for the resulting DN. The advisory body identifies 3.13.15, 4.0.20, 4.1.11, 4.2.9, and 4.3.3 as fixed, while structured metadata identifies 3.13.18, 4.0.23, 4.1.14, 4.2.9, and 4.3.3. No fixed-version assertion is certifiable until a curator resolves this conflict.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-25 17:50 UTC
CWE
- CWE-90 - Improper Neutralization of Special Elements used in an LDAP Query ('LDAP Injection')
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/rabbitmq/rabbitmq-server/secur… | x_refsource_CONFIRM |
| https://github.com/rabbitmq/rabbitmq-server/commi… | x_refsource_MISC |
| https://github.com/rabbitmq/rabbitmq-server/commi… | x_refsource_MISC |
| https://github.com/rabbitmq/rabbitmq-server/relea… | x_refsource_MISC |
| https://github.com/rabbitmq/rabbitmq-server/relea… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| rabbitmq | rabbitmq-server |
Affected:
>= 3.13.0, < 3.13.18
Affected: >= 4.0.0, < 4.0.23 Affected: >= 4.1.0, < 4.1.14 Affected: >= 4.2.0, < 4.2.9 Affected: >= 4.3.0, < 4.3.3 |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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