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SwiftNIO: CRLF Injection in outbound HTTP request URI via NIOHTTPRequestHeadersValidator

Moderate severity GitHub Reviewed Published May 21, 2026 in apple/swift-nio • Updated Jun 12, 2026

Package

swift github.com/apple/swift-nio (Swift)

Affected versions

>= 2.0.0, <= 2.99.0

Patched versions

2.100.0

Description

Programs using swift-nio is vulnerable to HTTP request smuggling and HTTP response splitting attacks, caused by insufficient validation of outbound HTTP/1.1 request and response start line components.

This vulnerability affects all swift-nio versions from 2.0.0 to 2.99.0. It is fixed in 2.100.0 and later releases.

This vulnerability is caused by the NIOHTTPRequestHeadersValidator and NIOHTTPResponseHeadersValidator channel handlers only validating header field names and values, while leaving the request URI, request method, and response reason phrase unvalidated. An attacker who can influence the content of these fields — for example by controlling a URL path or a custom HTTP method in a proxy application — can inject CR/LF sequences or other control characters into the HTTP start line. This allows construction of arbitrary additional HTTP requests or responses on the wire, a classic HTTP request smuggling or HTTP response splitting attack.

Exploiting this vulnerability requires the attacker to influence the content of outbound HTTP start line fields. In proxy applications that forward attacker-controlled URIs or methods, this is straightforward. For clients, a malicious server that triggers a redirect to a crafted URL could exploit the URI validation gap. For servers, any client that can cause the server to emit a crafted response reason phrase could exploit the response splitting gap.

In vulnerable applications, where attacker controlled data is supplied to these fields, the attack is low-effort: injecting a CRLF sequence into a URI or reason phrase requires only a single crafted request. Successful exploitation can allow an attacker to smuggle additional HTTP requests past intermediaries or split HTTP responses, potentially bypassing WAFs or poisoning web caches. However, most applications are not vulnerable at all.

The risk can be mitigated by ensuring that all user-controlled input is sanitized before being used in HTTP start line components. However, this mitigation places the burden on application developers and is error-prone.

The issue is fixed by extending NIOHTTPRequestHeadersValidator to validate request URIs against the character set defined in RFC 9112 Section 3.2 and RFC 3986 Section 3, and to validate custom HTTP methods against the token grammar defined in RFC 9110. NIOHTTPResponseHeadersValidator is extended to validate custom response reason phrases against RFC 9112 Section 4. Applications that use these validator channel handlers — which are installed by default when using addHTTPClientHandlers() or addHTTPServerHandlers() — will reject invalid outbound messages with an HTTPParserError.invalidHeaderToken error rather than emitting them to the network.

SwiftNIO is grateful to @kuranikaran and @YLChen-007 for their reporting and assistance with the project's process.

References

@Lukasa Lukasa published to apple/swift-nio May 21, 2026
Published to the GitHub Advisory Database Jun 12, 2026
Reviewed Jun 12, 2026
Last updated Jun 12, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity High
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:H/SA:N/E:U

EPSS score

Weaknesses

Improper Neutralization of CRLF Sequences ('CRLF Injection')

The product uses CRLF (carriage return line feeds) as a special element, e.g. to separate lines or records, but it does not neutralize or incorrectly neutralizes CRLF sequences from inputs. Learn more on MITRE.

CVE ID

CVE-2026-28970

GHSA ID

GHSA-cq87-8r7h-962v

Source code

Credits

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