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Rack::Session::Cookie secrets: decrypt failure fallback enables secretless session forgery and Marshal deserialization

Critical severity GitHub Reviewed Published Apr 7, 2026 in rack/rack-session

Package

bundler rack-session (RubyGems)

Affected versions

>= 2.0.0, < 2.1.2

Patched versions

2.1.2

Description

Rack::Session::Cookie incorrectly handles decryption failures when configured with secrets:. If cookie decryption fails, the implementation falls back to a default decoder instead of rejecting the cookie. This allows an unauthenticated attacker to supply a crafted session cookie that is accepted as valid session data without knowledge of any configured secret.

Because this mechanism is used to load session state, an attacker can manipulate session contents and potentially gain unauthorized access.

Details

When secrets: is configured, Rack::Session::Cookie attempts to decrypt incoming session cookies using one of the configured encryptors. If all decrypt attempts fail, the implementation does not reject the cookie. Instead, it falls back to decoding the cookie using a default coder.

This fallback path processes attacker-controlled cookie data as trusted session state. The behavior is implicit and occurs even when encrypted cookies are expected.

The fallback decoder is applied automatically and does not require the application to opt into a non-encrypted session format. As a result, a client can send a specially crafted cookie value that bypasses the intended integrity protections provided by secrets:.

This issue affects both default configurations and those using alternative serializers for encrypted payloads.

Impact

Any Rack application using Rack::Session::Cookie with secrets: may be affected.

Note

Rails applications are typically not affected — Rails uses ActionDispatch::Session::CookieStore, which is a separate implementation backed by ActiveSupport::MessageEncryptor and does not share the vulnerable code path.

An unauthenticated attacker can supply a crafted session cookie that is accepted as valid session data. This can lead to authentication bypass or privilege escalation in applications that rely on session values for identity or authorization decisions.

Depending on application behavior and available runtime components, processing of untrusted session data may also expose additional risks.

Mitigation

  • Update to a patched version ofrack-session that rejects cookies when decryption fails under the secrets: configuration.
    • After updating, rotate session secrets to invalidate existing session cookies, since attacker-supplied session data may have been accepted and re-issued prior to the fix.

References

@ioquatix ioquatix published to rack/rack-session Apr 7, 2026
Published by the National Vulnerability Database Apr 7, 2026
Published to the GitHub Advisory Database Apr 8, 2026
Reviewed Apr 8, 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 None
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:N/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Improper Authentication

When an actor claims to have a given identity, the product does not prove or insufficiently proves that the claim is correct. Learn more on MITRE.

Insufficient Verification of Data Authenticity

The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data. Learn more on MITRE.

Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. Learn more on MITRE.

Reliance on Cookies without Validation and Integrity Checking

The product relies on the existence or values of cookies when performing security-critical operations, but it does not properly ensure that the setting is valid for the associated user. Learn more on MITRE.

CVE ID

CVE-2026-39324

GHSA ID

GHSA-33qg-7wpp-89cq

Source code

Credits

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