CVE-2026-34513 (GCVE-0-2026-34513)

Vulnerability from cvelistv5 – Published: 2026-04-01 20:06 – Updated: 2026-06-23 15:50
VLAI
Title
AIOHTTP: Denial of Service (DoS) via Unbounded DNS Cache in TCPConnector
Summary
AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to version 3.13.4, an unbounded DNS cache could result in excessive memory usage possibly resulting in a DoS situation. This issue has been patched in version 3.13.4.
Severity
2.7 (Low)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:U
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-02 15:14 UTC
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
Impacted products
Vendor Product Version CPE status
aio-libs aiohttp Affected: < 3.13.4
guessed Create a notification for this product.
Show details on NVD website
To clipboard 

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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

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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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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.