CVE-2026-16652 (GCVE-0-2026-16652)
Vulnerability from cvelistv5 – Published: 2026-09-21 11:23 – Updated: 2026-09-21 15:33
VLAI
EPSS
VEX
Title
Temporal Server Schedule exclusion search can cause excessive CPU consumption
Summary
Temporal Server did not bound the work performed while searching for a Schedule's next action time. An authenticated caller with namespace write permission could create or update a Schedule that combines a fine-grained cadence with an exclusion calendar that rejects every candidate time, causing the server to evaluate excluded candidates without a per-search work budget. This can consume excessive CPU in Frontend and Schedule worker components. A persisted specification can also cause its backing Schedule Workflow to repeatedly fail and retry, allowing CPU consumption to continue without additional requests until the Schedule is deleted or its backing Workflow is terminated. Repeated or parallel exploitation can deny service. The issue affects availability only; it does not expose or modify Workflow data.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-21 15:32 UTC
CWE
- CWE-606 - Unchecked Input for Loop Condition
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/temporalio/temporal/pull/11014 | patch |
| https://github.com/temporalio/temporal/commit/c10… | patch |
| https://github.com/temporalio/temporal/releases/t… | release-notes |
| https://github.com/temporalio/temporal/releases/t… | release-notes |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Temporal Technologies, Inc. | Temporal Server |
Affected:
1.17.0 , ≤ 1.29.7
(semver)
Affected: 1.30.0 , < 1.30.7 (semver) Affected: 1.31.0 , < 1.31.3 (semver) cpe:2.3:a:temporal:temporal:*:*:*:*:*:*:*:* |
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},
"cveMetadata": {
"assignerOrgId": "61241ed8-fa44-4f23-92db-b8c443751968",
"assignerShortName": "Temporal",
"cveId": "CVE-2026-16652",
"datePublished": "2026-09-21T11:23:47.298Z",
"dateReserved": "2026-07-22T18:08:55.806Z",
"dateUpdated": "2026-09-21T15:33:15.387Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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