CVE-2026-72923 (GCVE-0-2026-72923)
Vulnerability from cvelistv5 – Published: 2026-09-08 17:12 – Updated: 2026-09-08 17:53
VLAI
EPSS
VEX
Title
Microsoft.OpenApi.YamlReader/Readers vulnerable to denial of service via YAML alias expansion
Summary
In Microsoft.OpenApi.YamlReader from 2.0.0-preview.11 until 2.12.0 and from 3.0.0 until 3.10.0, and in Microsoft.OpenApi.Readers prior to 1.6.30, a small YAML OpenAPI document containing nested anchors and aliases can cause uncontrolled resource consumption when parsed through the public YAML reader APIs. YAML is parsed through SharpYaml, which represents aliases as shared nodes in a directed acyclic graph, so the parsed YAML graph stays small, but converting that graph to System.Text.Json.Nodes.JsonNode requires every alias to be materialized as an independent node because a JsonNode cannot be attached to multiple parents. Without a bound on that conversion work, a document with N nested anchors each referenced k times can require k^N materialized JSON nodes, leading to excessive memory allocation and process termination through out-of-memory conditions, a billion laughs style denial of service. The patched versions bound the YAML-to-JSON conversion by node count and nesting depth and report an OpenApiDiagnostic error instead of expanding without limit. This vulnerability is fixed in Microsoft.OpenApi.YamlReader 2.12.0 and 3.10.0, and Microsoft.OpenApi.Readers 1.6.30.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-08 17:36 UTC
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
1 reference
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Microsoft | OpenApi.YamlReader |
Affected:
2.0.0-preview.11 , < 2.12.0
(semver)
Affected: 3.0.0 , < 3.10.0 (semver) |
guessed | |
| Microsoft | OpenApi.Readers |
Affected:
0 , < 1.6.30
(semver)
|
guessed |
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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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