CVE-2026-94656 in Thrift
Summary
by MITRE • 10/02/2026
Allocation of resources without limits or throttling vulnerability in Apache Thrift ruby bindings.
This issue affects Apache Thrift: before 0.25.0.
Users are recommended to upgrade to version 0.25.0, which fixes the issue.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 10/02/2026
The identified vulnerability represents a classic resource exhaustion flaw within the Ruby language bindings of the Apache Thrift framework, specifically affecting versions prior to release 0.25.0. This security defect is categorized under CWE-770: Allocation of Resources Without Limits or Throttling, which describes scenarios where an application fails to restrict the amount of system resources that a single user or process can consume. In the context of Apache Thrift, a high-performance communication engine used for building scalable cross-language services, this flaw manifests when the Ruby client library processes incoming requests without implementing adequate constraints on memory allocation or connection handling. The underlying technical mechanism involves the failure to enforce limits on the size of data structures allocated during serialization and deserialization processes, as well as potential unbounded growth in concurrent connection pools if not properly managed by the application layer.
From a technical perspective, when an attacker sends specially crafted requests with excessively large payloads or initiates a high volume of simultaneous connections, the Ruby bindings may attempt to allocate memory proportional to these inputs without checking against predefined thresholds. Because Ruby is a dynamically typed language that manages memory automatically via garbage collection, excessive allocation can lead to significant pressure on the heap space. If the application does not implement its own safeguards, this uncontrolled resource consumption can quickly deplete available system memory. This behavior aligns with the MITRE ATT&CK technique T1496: Resource Hijacking, where an adversary uses computing resources in a way that negatively impacts other processes or users on the same host, effectively creating a denial of service condition through legitimate but abusive API usage rather than exploiting a crash bug directly.
The operational impact of this vulnerability is primarily centered around availability and system stability. A successful exploitation could result in the target application becoming unresponsive due to out-of-memory errors or severe performance degradation as the operating system struggles to manage memory pressure. In cloud-native environments, such resource exhaustion can trigger auto-scaling events that lead to increased costs or cause cascading failures across dependent services if load balancers continue routing traffic to compromised instances. Furthermore, because Apache Thrift is often used in microservices architectures where inter-service communication is frequent and automated, the vulnerability could be triggered remotely by any service configured with an older version of the Ruby client library, making it a significant risk for distributed systems relying on this framework for RPC calls.
To mitigate this risk, organizations must upgrade their Apache Thrift dependencies to version 0.25.0 or later, where the developers have implemented necessary checks and limits to prevent unbounded resource allocation. In addition to upgrading, application architects should implement defense-in-depth strategies by configuring timeouts on client connections and setting explicit size limits for request payloads at the application layer before they reach the Thrift serialization logic. Monitoring tools should be deployed to track memory usage patterns of Ruby processes associated with Thrift clients, allowing for early detection of anomalous spikes that might indicate an ongoing exploitation attempt. Regular security audits of third-party dependencies are essential to ensure that such foundational libraries remain patched against known resource management flaws.