CVE-2025-47950 (GCVE-0-2025-47950)
Vulnerability from cvelistv5 – Published: 2025-06-06 17:32 – Updated: 2025-06-06 21:27
VLAI
EPSS
VEX
Title
CoreDNS Vulnerable to DoQ Memory Exhaustion via Stream Amplification
Summary
CoreDNS is a DNS server that chains plugins. In versions prior to 1.12.2, a Denial of Service (DoS) vulnerability exists in the CoreDNS DNS-over-QUIC (DoQ) server implementation. The server previously created a new goroutine for every incoming QUIC stream without imposing any limits on the number of concurrent streams or goroutines. A remote, unauthenticated attacker could open a large number of streams, leading to uncontrolled memory consumption and eventually causing an Out Of Memory (OOM) crash — especially in containerized or memory-constrained environments. The patch in version 1.12.2 introduces two key mitigation mechanisms: `max_streams`, which caps the number of concurrent QUIC streams per connection with a default value of `256`; and `worker_pool_size`, which Introduces a server-wide, bounded worker pool to process incoming streams with a default value of `1024`. This eliminates the 1:1 stream-to-goroutine model and ensures that CoreDNS remains resilient under high concurrency. Some workarounds are available for those who are unable to upgrade. Disable QUIC support by removing or commenting out the `quic://` block in the Corefile, use container runtime resource limits to detect and isolate excessive memory usage, and/or monitor QUIC connection patterns and alert on anomalies.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-06-06 18:40 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/coredns/coredns/security/advis… | x_refsource_CONFIRM |
| https://github.com/coredns/coredns/commit/efaed02… | x_refsource_MISC |
| https://datatracker.ietf.org/doc/html/rfc9250 | x_refsource_MISC |
| https://github.com/quic-go/quic-go | x_refsource_MISC |
| https://www.usenix.org/conference/usenixsecurity2… | x_refsource_MISC |
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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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