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GHSA-cvx7-x8pj-x2gw CVE-2025-47950 GO-2025-3743

CoreDNS Vulnerable to DoQ Memory Exhaustion via Stream Amplification

High Go
Severity
7.5 / 10
High · CVSS 3.1
Exploit chance (EPSS)
1.19%
Chance of exploitation in the next 30 days. Higher than 67.90% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-770 Allocation of Resources Without Limits or Throttling
Fix
1.12.2
Upgrade github.com/coredns/coredns to this version or later

Description

Summary

A Denial of Service (DoS) vulnerability was discovered 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.

Impact

  • Component: server_quic.go
  • Attack Vector: Remote, network-based
  • Attack Complexity: Low
  • Privileges Required: None
  • User Interaction: None
  • Impact: High availability loss (OOM kill or unresponsiveness)

This issue affects deployments with quic:// enabled in the Corefile. A single attacker can cause the CoreDNS instance to become unresponsive using minimal bandwidth and CPU.

Patches

The patch introduces two key mitigation mechanisms:

  • max_streams: Caps the number of concurrent QUIC streams per connection. Default: 256.
  • worker_pool_size: Introduces a server-wide, bounded worker pool to process incoming streams. Default: 1024.

This eliminates the 1:1 stream-to-goroutine model and ensures that CoreDNS remains resilient under high concurrency. The new configuration options are exposed through the quic Corefile block:

quic {
    max_streams 256
    worker_pool_size 1024
}

These defaults are generous and aligned with typical DNS-over-QUIC client behavior.

Workarounds

If you're unable to upgrade immediately, you can:

  • Disable QUIC support by removing or commenting out the quic:// block in your Corefile
  • Use container runtime resource limits to detect and isolate excessive memory usage
  • Monitor QUIC connection patterns and alert on anomalies

References

Credit

Thanks to @thevilledev for disclovering this vulnerability and contributing a high-quality fix.

For more information

Please consult our security guide for more information regarding our security process.

Affected versions

Go

PackageVulnerableFixed in
github.com/coredns/coredns
< 1.12.2
1.12.2

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

github.com/coredns/coredns Go → 1.12.2

go
go get github.com/coredns/coredns@v1.12.2 && go mod tidy

Severity breakdown

CVSS 3.1 7.5

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-770: Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.

How to prevent it
  • Requirements: Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
  • Architecture and Design: Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
  • Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Architecture and Design, Implementation: If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery. Ensure that all failures in resource allocation place the system into a safe posture.
  • Operation, Architecture and Design: Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems. When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users. Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).

References

Advisories

Packages

Other links

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-9gm5-9rfh-m6vx
CoreDNS DoH/DoQ/gRPC bypass UPDATE rejection enforced on UDP/TCP
High Also affects github.com/coredns/coredns
GHSA-mrg3-qvqr-jw29
CoreDNS: Unauthenticated memory exhaustion in custom transports
High Also affects github.com/coredns/coredns
GHSA-74w3-63xv-x9mv
CoreDNS `k8s_external` headless AXFR can emit an empty transfer batch that panics the `transfer` plugin
Low Also affects github.com/coredns/coredns
GHSA-vp29-5652-4fw9
CoreDNS has TSIG authentication bypass on gRPC and QUIC transports
Critical Also affects github.com/coredns/coredns
GHSA-qhmp-q7xh-99rh
CoreDNS has TSIG authentication bypass on DoT, DoH, DoH3, DoQ, and gRPC
High Also affects github.com/coredns/coredns
GHSA-h8mm-c463-wjq3
CoreDNS' transfer stanza selection uses lexicographic compare (subzone ACL bypass)
High Also affects github.com/coredns/coredns
GHSA-63cw-r7xf-jmwr
CoreDNS DoH GET oversized dns= query parameter causes pre-validation CPU and memory amplification
High Also affects github.com/coredns/coredns
GHSA-2wpx-qpw2-g5h5
CoreDNS' DoQ worker pool does not bound stream backlog
High Also affects github.com/coredns/coredns
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