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Http4s Ember accepts Transfer-Encoding combined with Content-Length (CL.TE request smuggling)

Critical severity GitHub Reviewed Published Jul 6, 2026 in http4s/http4s

Package

maven org.http4s:http4s-ember-core_2.12 (Maven)

Affected versions

<= 0.23.34

Patched versions

0.23.35
maven org.http4s:http4s-ember-core_2.13 (Maven)
<= 0.23.34
>= 1.0.0-M1, <= 1.0.0-M46
0.23.35
1.0.0-M47
maven org.http4s:http4s-ember-core_3 (Maven)
<= 0.23.34
>= 1.0.0-M1, <= 1.0.0-M46
0.23.35
1.0.0-M47

Description

Summary

Ember's HTTP/1.1 request parser does not reject a message that carries both a
Transfer-Encoding and a Content-Length header. RFC 9112 §6.1 requires a
server to treat such a message as a framing error and close the connection.
An intermediary that follows the RFC's CL-strip-and-forward path (or that
prioritises Content-Length) will frame the body differently from Ember,
enabling HTTP request smuggling (CL.TE).

Impact

Server

Request smuggling when ember-server is an origin behind an intermediary that
forwards both headers over a keep-alive backend connection and frames by
Content-Length while Ember frames by chunked:

  • Front-end security bypass: the smuggled request reaches paths the
    intermediary's ACL/auth layer would have blocked, with attacker-chosen
    method and headers.
  • Cross-user request hijack: a dangling smuggled prefix concatenates with the
    next victim's request on the shared backend socket, capturing its headers.
  • Cache poisoning: the smuggled response is associated with the next request
    key in a caching proxy.

Client

ember-client shares the same parser on the response path. An upstream that
sends both headers can desync a pooled client connection. This requires a
malicious or compromised upstream.

Preconditions

  • Unauthenticated remote attacker (server)
  • ember-server as origin behind a keep-alive intermediary
  • Intermediary forwards a request carrying both Transfer-Encoding and
    Content-Length (RFC says it MAY reject; many forward) and frames by
    Content-Length
  • Malicious or compromised upstream (client)

Workarounds

  • Intermediary strictly rejects requests carrying both Transfer-Encoding
    and Content-Length
  • Intermediary buffers and re-encodes request bodies
  • Disable backend keep-alive between the intermediary and Ember

References

@rossabaker rossabaker published to http4s/http4s Jul 6, 2026
Published to the GitHub Advisory Database Sep 15, 2026
Reviewed Sep 15, 2026

Severity

Critical

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 High
Integrity High
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
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:H/VI:H/VA:L/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(46th percentile)

Weaknesses

Inconsistent Interpretation of HTTP Requests ('HTTP Request/Response Smuggling')

The product acts as an intermediary HTTP agent (such as a proxy or firewall) in the data flow between two entities such as a client and server, but it does not interpret malformed HTTP requests or responses in ways that are consistent with how the messages will be processed by those entities that are at the ultimate destination. Learn more on MITRE.

CVE ID

CVE-2026-69204

GHSA ID

GHSA-8h4c-x2wg-6xp8

Source code

Credits

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