CVE-2026-94653 in Thrift
Summary
by MITRE • 10/02/2026
Inefficient Algorithmic Complexity vulnerability in Apache Thrift PHP bindings.
This issue affects Apache Thrift: before 0.25.0.
Users are recommended to upgrade to version 0.25.0, which fixes the issue.
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Analysis
by VulDB Data Team • 10/02/2026
The identified vulnerability resides within the Apache Thrift PHP bindings and is classified as an inefficient algorithmic complexity flaw. This type of security weakness typically arises when a software component processes input in a manner that scales poorly with respect to size or complexity, often exhibiting quadratic or exponential time complexity rather than linear growth. In the context of networked services like those built on Apache Thrift, such inefficiencies are particularly dangerous because they can be triggered by remote attackers sending specially crafted requests. The root cause lies in how the PHP serialization and deserialization logic handles specific data structures or protocol messages, potentially leading to excessive CPU consumption during parsing operations.
From a technical perspective, this vulnerability allows for potential denial-of-service attacks against services relying on Apache Thrift for inter-process communication. An attacker could exploit this inefficiency by submitting deeply nested or excessively large serialized objects that force the PHP interpreter into prolonged computational loops. This behavior consumes significant server resources, potentially rendering the service unavailable to legitimate users without necessarily crashing the application entirely. The lack of proper bounds checking or optimized parsing algorithms means that a relatively small amount of malicious input can result in disproportionate resource exhaustion, creating an asymmetric attack vector where minimal effort yields high impact on system stability.
The operational impact of this flaw extends beyond simple performance degradation. In production environments handling high volumes of traffic, even minor inefficiencies can amplify under load, leading to cascading failures across dependent services. If the Thrift server is part of a larger microservices architecture, the resource starvation caused by these inefficient computations could affect other critical components sharing the same host resources. Furthermore, this vulnerability may serve as an initial foothold for more sophisticated attacks if combined with other weaknesses, although its primary manifestation remains focused on availability disruption through computational exhaustion rather than data integrity or confidentiality breaches.
Industry standards categorize such flaws under CWE-400, which describes uncontrolled resource consumption due to inefficient algorithmic complexity. This classification highlights the importance of designing algorithms that maintain predictable performance characteristics regardless of input size. Additionally, from a tactical standpoint related to MITRE ATT&CK frameworks, this vulnerability aligns with techniques involving denial-of-service via application layer exhaustion, specifically targeting service availability through computational overload rather than network bandwidth saturation. Understanding these mappings helps security teams prioritize remediation efforts based on established risk models and threat intelligence.
To mitigate the risks associated with this vulnerability, organizations using Apache Thrift in their infrastructure must upgrade to version 0.25.0 or later as soon as possible. This release incorporates fixes that address the underlying algorithmic inefficiencies within the PHP bindings, ensuring more robust handling of serialized data structures. Until an upgrade can be performed, administrators should implement strict input validation and size limits on incoming Thrift messages at the network perimeter using firewalls or API gateways to prevent excessively large payloads from reaching the vulnerable application layer. Monitoring CPU usage patterns for anomalies may also help in detecting active exploitation attempts early enough to trigger automated scaling responses or incident response procedures.