CVE-2026-15971 in SGLang
Summary
by MITRE • 07/30/2026
SGLang contains an RCE vulnerability when the optional dumper subsystem is enabled, allowing for a sandbox escape when DUMPER_SERVER_PORT is set, enabling code execution on inference requests.
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Analysis
by VulDB Data Team • 07/30/2026
The SGLang framework presents a critical remote code execution vulnerability that emerges when the optional dumper subsystem is activated and the DUMPER_SERVER_PORT environment variable is configured. This vulnerability represents a significant security flaw that undermines the sandbox isolation typically maintained by the system architecture, creating an avenue for malicious actors to execute arbitrary code within the inference processing environment. The flaw specifically manifests when the dumper functionality is enabled through configuration parameters rather than being a default feature, making it potentially exploitable in environments where this subsystem is intentionally activated for debugging or monitoring purposes.
The technical mechanism underlying this vulnerability involves a sandbox escape condition that occurs when the DUMPER_SERVER_PORT variable is set, allowing external connections to establish communication with the dumper component. This configuration creates an unintended attack surface where malicious inputs can be processed through the inference request pipeline and subsequently executed within the context of the dumper subsystem. The vulnerability stems from insufficient input validation and access control mechanisms that fail to properly isolate the dumper functionality from the main inference processing components, enabling code execution that bypasses normal security boundaries.
The operational impact of this vulnerability is severe as it allows attackers to execute arbitrary commands on systems running SGLang with the dumper subsystem enabled. This capability can be leveraged to escalate privileges, access sensitive data, install malware, or compromise the entire inference infrastructure. The vulnerability affects any deployment where the dumper functionality is enabled, particularly in production environments where debugging features might be active for troubleshooting purposes. Attackers can exploit this weakness through carefully crafted inference requests that trigger the dumper subsystem, potentially leading to complete system compromise and unauthorized access to machine learning models and associated data.
Security mitigations for this vulnerability should focus on disabling the dumper subsystem when not actively needed for debugging purposes, implementing strict environment variable validation, and ensuring proper access controls are enforced around the DUMPER_SERVER_PORT configuration. Organizations should also consider implementing network segmentation to restrict access to the dumper port, applying principle of least privilege configurations, and regularly auditing system configurations to identify potentially exposed dumper subsystems. The vulnerability aligns with CWE-78 and CWE-20 categories related to command injection and input validation failures, while also mapping to ATT&CK techniques involving privilege escalation and execution through system services. Regular security updates and proper configuration management practices are essential to prevent exploitation of this sandbox escape vulnerability in production environments.