CVE-2026-86344 (GCVE-0-2026-86344)
Vulnerability from cvelistv5 – Published: 2026-10-01 21:29 – Updated: 2026-10-01 21:29
VLAI
EPSS
VEX
Title
389-ds-base: 389-ds-base: unauthenticated worker-thread-pool exhaustion via completed-operation-then-incomplete-pdu connection requeue
Summary
A flaw was found in 389-ds-base. An unauthenticated remote attacker can send a complete LDAP operation followed by the first bytes of an incomplete LDAPMessage on the same connection, causing the server to hand that connection to a second worker thread before the first worker's result is flushed. The second worker blocks until nsslapd-ioblocktimeout while holding the connection mutex, preventing delivery of the completed operation's result. Repeating this across a small number of connections proportional to the configured worker-thread pool size exhausts the entire pool under default configuration, denying service to all clients (anonymous and authenticated, plaintext and TLS) for as long as the attacker maintains the connections.
Severity
7.5 (High)
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://access.redhat.com/security/cve/CVE-2026-86344 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2529329 | issue-trackingx_refsource_REDHAT |
Impacted products
8 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Red Hat | Red Hat Directory Server 11 |
cpe:/a:redhat:directory_server:11
|
||
| Red Hat | Red Hat Directory Server 12 |
cpe:/a:redhat:directory_server:12
|
||
| Red Hat | Red Hat Directory Server 13 |
cpe:/a:redhat:directory_server:13
|
||
| Red Hat | Red Hat Enterprise Linux 10 |
cpe:/o:redhat:enterprise_linux:10
|
||
| Red Hat | Red Hat Enterprise Linux 6 |
cpe:/o:redhat:enterprise_linux:6
|
||
| Red Hat | Red Hat Enterprise Linux 7 |
cpe:/o:redhat:enterprise_linux:7
|
||
| Red Hat | Red Hat Enterprise Linux 8 |
cpe:/o:redhat:enterprise_linux:8
|
||
| Red Hat | Red Hat Enterprise Linux 9 |
cpe:/o:redhat:enterprise_linux:9
|
Date Public
2026-10-01 00:00
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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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