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Silent Data Truncation and State Corruption via Shortstr Integer Overflow

Critical
suchitd published GHSA-j497-x9hr-x34x Jul 22, 2026

Package

gomod github.com/rabbitmq/amqp091-go (Go)

Affected versions

<1.13.0

Patched versions

1.13.0

Description

Summary

A data integrity and protocol corruption vulnerability exists in the AMQP client's property serialization logic. When encoding AMQP short string (shortstr) fields—such as identifiers, routing strings, and content metadata—the length of the string is explicitly cast to a fixed-size 8-bit unsigned integer (uint8).

If an application provides a property string exceeding 255 bytes, the length counter silently wraps around (e.g., a length of 300 wraps to 44). As a result, the parser writes only a truncated portion of the string into the outgoing connection buffer without returning an error. This leads to silent data corruption, broken RPC routing, and unpredictable broker-side state behavior.

Vulnerability Details

Mechanism

The vulnerability resides in the wire-level serialization logic for application publishing properties:

// write.go:246
length := uint8(len(b))  // wraps silently when len(b) > 255 (e.g., 300 -> 44)

Because Go allows silent integer truncation during explicit type casting, lengths larger than $2^8 - 1$ lose their most significant bits. The underlying stream writer reads length to determine how many bytes to pull from the buffer. Because no error or boundary check accompanies this truncation, the application believes the full payload was transmitted successfully.

Affected Properties

This truncation behavior affects every standard AMQP field serialized as a shortstr:

  • CorrelationId
  • ReplyTo
  • MessageId
  • Expiration
  • UserId
  • AppId
  • ContentType
  • ContentEncoding
  • Type

Impact

The critical consequence is silent protocol desynchronization at the application layer. The underlying TCP stream remains framed properly (because the shortened length matches the bytes written), but the business logic is corrupted. Distributed transactions, request-reply correlations, and tracing headers are truncated, causing downstream systems to drop messages or route them to incorrect consumers.

Attack Vector

An attacker who can influence metadata fields processed by an upstream application (such as a user-supplied tracking ID or an long content-type header) can exploit this to break system components:

  1. Targeting RPC Routing: A user passes a malicious or overly long CorrelationId of 300 bytes through an application endpoint.
  2. Silent Truncation: The library wraps the length value to 44, transmitting only the first 44 bytes to the rabbitMQ broker.
  3. Broken Correlation: When the service processes the request and responds, the replying consumer attempts to route the message using the full 300-byte identifier. Because the broker only recognizes the truncated 44-byte ID, the reply loop breaks silently, leading to hanging processes or data leaks across transaction boundaries.

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 Low
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality Low
Integrity High
Availability Low

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:L/VI:H/VA:H/SC:L/SI:H/SA:L

CVE ID

CVE-2026-77408

Weaknesses

No CWEs

Credits