PYSEC-2026-134
Vulnerability from pysec - Published: 2026-04-07 16:16 - Updated: 2026-05-20 09:19
VLAI
Details
Strawberry GraphQL is a library for creating GraphQL APIs. Prior to 0.312.3, Strawberry GraphQL's WebSocket subscription handlers for both the graphql-transport-ws and legacy graphql-ws protocols allocate an asyncio.Task and associated Operation object for every incoming subscribe message without enforcing any limit on the number of active subscriptions per connection. An unauthenticated attacker can open a single WebSocket connection, send connection_init, and then flood subscribe messages with unique IDs. Each message unconditionally spawns a new asyncio.Task and async generator, causing linear memory growth and event loop saturation. This leads to server degradation or an OOM crash. This vulnerability is fixed in 0.312.3.
Severity
7.5 (High)
Impacted products
| Name | purl | strawberry-graphql | pkg:pypi/strawberry-graphql |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "strawberry-graphql",
"purl": "pkg:pypi/strawberry-graphql"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.312.3"
}
],
"type": "ECOSYSTEM"
}
],
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]
}
],
"aliases": [
"CVE-2026-35526",
"GHSA-hv3w-m4g2-5x77"
],
"details": "Strawberry GraphQL is a library for creating GraphQL APIs. Prior to 0.312.3, Strawberry GraphQL\u0027s WebSocket subscription handlers for both the graphql-transport-ws and legacy graphql-ws protocols allocate an asyncio.Task and associated Operation object for every incoming subscribe message without enforcing any limit on the number of active subscriptions per connection. An unauthenticated attacker can open a single WebSocket connection, send connection_init, and then flood subscribe messages with unique IDs. Each message unconditionally spawns a new asyncio.Task and async generator, causing linear memory growth and event loop saturation. This leads to server degradation or an OOM crash. This vulnerability is fixed in 0.312.3.",
"id": "PYSEC-2026-134",
"modified": "2026-05-20T09:19:17.728561Z",
"published": "2026-04-07T16:16:28.843Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/strawberry-graphql/strawberry/security/advisories/GHSA-hv3w-m4g2-5x77"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
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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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