CVE Vulnerabilities

CVE-2026-40175

Improper Neutralization of CRLF Sequences in HTTP Headers ('HTTP Request/Response Splitting')

Published: Apr 10, 2026 | Modified: May 20, 2026
CVSS 3.x
4.8
MEDIUM
Source:
NVD
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
CVSS 2.x
RedHat/V2
RedHat/V3
9 IMPORTANT
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Ubuntu
MEDIUM
root.io logo minimus.io logo echo.ai logo

Axios is a promise based HTTP client for the browser and Node.js. Versions prior to 1.15.0 and 0.3.1 are vulnerable to a specific gadget-style attack chain in which prototype pollution in a third-party dependency may be leveraged to inject unsanitized header values into outbound requests. This vulnerability is fixed in 1.15.0 and 0.3.1.

Weakness

The product receives data from an HTTP agent/component (e.g., web server, proxy, browser, etc.), but it does not neutralize or incorrectly neutralizes CR and LF characters before the data is included in outgoing HTTP headers.

Affected Software

NameVendorStart VersionEnd Version
AxiosAxios*0.31.0 (excluding)
AxiosAxios1.0.0 (including)1.15.0 (excluding)
Red Hat Ansible Automation Platform 2.6 for RHEL 9RedHatautomation-platform-ui-0:2.6.9-1.el9ap*
Streams for Apache Kafka 3.2.0RedHatcom.github.streamshub-console*
Multicluster engine for Kubernetes 2.10RedHatmulticluster-engine/console-mce-rhel9:1777128790*
Multicluster engine for Kubernetes 2.6RedHatmulticluster-engine/console-mce-rhel9:1778511348*
Multicluster engine for Kubernetes 2.8RedHatmulticluster-engine/console-mce-rhel9:1778383863*
Multicluster engine for Kubernetes 2.9RedHatmulticluster-engine/console-mce-rhel9:1777301444*
Network Observability (NETOBSERV) 1.11.2RedHatnetwork-observability/network-observability-console-plugin-compat-rhel9:1778508956*
Network Observability (NETOBSERV) 1.11.2RedHatnetwork-observability/network-observability-console-plugin-rhel9:1778510461*
Red Hat Advanced Cluster Management for Kubernetes 2.15RedHatrhacm2/console-rhel9:1776927126*
Red Hat Advanced Cluster Security for Kubernetes 4.9RedHatadvanced-cluster-security/rhacs-main-rhel8:1779371594*
Red Hat Developer Hub 1.8RedHatrhdh/rhdh-hub-rhel9:1776784286*
Red Hat Developer Hub 1.9RedHatrhdh/rhdh-hub-rhel9:1777903262*
Red Hat Discovery 2RedHatdiscovery/discovery-ui-rhel9:1778156756*
Red Hat Migration Toolkit 1.8RedHatrhmtc/openshift-migration-ui-rhel8:1780590717*
Red Hat OpenShift AI 3.3RedHatrhoai/odh-dashboard-rhel9:1779189627*
Red Hat OpenShift AI 3.3RedHatrhoai/odh-mod-arch-gen-ai-rhel9:1778473763*
Red Hat OpenShift AI 3.3RedHatrhoai/odh-mod-arch-maas-rhel9:1779189704*
Red Hat OpenShift AI 3.3RedHatrhoai/odh-mod-arch-model-registry-rhel9:1778666987*
Red Hat OpenShift Container Platform 4.14RedHatopenshift4/ose-console:1777997704*
Red Hat OpenShift Container Platform 4.15RedHatopenshift4/ose-console:1777994748*
Red Hat OpenShift Container Platform 4.16RedHatopenshift4/ose-console-rhel9:1776827996*
Red Hat OpenShift Container Platform 4.19RedHatopenshift4/ose-monitoring-plugin-rhel9:1779249923*
Red Hat OpenShift Container Platform 4.20RedHatopenshift4/ose-agent-installer-ui-rhel9:1778645099*
Red Hat OpenShift Container Platform 4.20RedHatopenshift4/ose-monitoring-plugin-rhel9:1778638503*
Red Hat OpenShift Container Platform 4.21RedHatopenshift4/ose-agent-installer-ui-rhel9:1778539338*
Red Hat OpenShift Container Platform 4.21RedHatopenshift4/ose-monitoring-plugin-rhel9:1778539219*
Red Hat OpenShift Dev Spaces 3.27RedHatdevspaces/code-rhel9:1776744110*
Red Hat OpenShift Dev Spaces 3.27RedHatdevspaces/dashboard-rhel9:1776795511*
Red Hat OpenShift Service Mesh 2.6RedHatopenshift-service-mesh/kiali-ossmc-rhel8:1776202125*
Red Hat OpenShift Service Mesh 2.6RedHatopenshift-service-mesh/kiali-rhel8:1776191302*
Red Hat OpenShift Service Mesh 3.0RedHatopenshift-service-mesh/kiali-ossmc-rhel9:1776151124*
Red Hat OpenShift Service Mesh 3.0RedHatopenshift-service-mesh/kiali-rhel9:1776151272*
Red Hat OpenShift Service Mesh 3.1RedHatopenshift-service-mesh/kiali-ossmc-rhel9:1776151106*
Red Hat OpenShift Service Mesh 3.1RedHatopenshift-service-mesh/kiali-rhel9:1776151270*
Red Hat OpenShift Service Mesh 3.2RedHatopenshift-service-mesh/kiali-ossmc-rhel9:1776155669*
Red Hat OpenShift Service Mesh 3.2RedHatopenshift-service-mesh/kiali-rhel9:1776149682*
Red Hat OpenShift Service Mesh 3.3RedHatopenshift-service-mesh/kiali-ossmc-rhel9:1776151134*
Red Hat OpenShift Service Mesh 3.3RedHatopenshift-service-mesh/kiali-rhel9:1776151277*
Red Hat Satellite 6.18RedHatsatellite/iop-advisor-frontend-rhel9:1776250950*
Red Hat Satellite 6.18RedHatsatellite/iop-host-inventory-frontend-rhel9:1776216284*
Red Hat Satellite 6.18RedHatsatellite/iop-vulnerability-frontend-rhel9:1776269713*
Red Hat Trusted Artifact Signer 1.3RedHatrhtas/rhtas-console-rhel9:1776672801*
Red Hat Trusted Artifact Signer 1.3RedHatrhtas/rhtas-console-rhel9:1776778645*
Node-axiosUbuntuupstream*

Extended Description

     HTTP agents or components may include a web server, load balancer, reverse proxy, web caching proxy, application firewall, web browser, etc. Regardless of the role, they are expected to maintain coherent, consistent HTTP communication state across all components. However, including unexpected data in an HTTP header allows an attacker to specify the entirety of the HTTP message that is rendered by the client HTTP agent (e.g., web browser) or back-end HTTP agent (e.g., web server), whether the message is part of a request or a response.

When an HTTP request contains unexpected CR and LF characters, the server may respond with an output stream that is interpreted as “splitting” the stream into two different HTTP messages instead of one. CR is carriage return, also given by %0d or \r, and LF is line feed, also given by %0a or \n. In addition to CR and LF characters, other valid/RFC compliant special characters and unique character encodings can be utilized, such as HT (horizontal tab, also given by %09 or \t) and SP (space, also given as + sign or %20). These types of unvalidated and unexpected data in HTTP message headers allow an attacker to control the second “split” message to mount attacks such as server-side request forgery, cross-site scripting, and cache poisoning attacks. HTTP response splitting weaknesses may be present when:

Potential Mitigations

  • 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. If an input does not strictly conform to specifications, reject it or transform it into something that conforms.
  • 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.

References