CVE-2026-44182 in Enterprise Gateway
Summary
by MITRE • 07/17/2026
Jupyter Enterprise Gateway launches remote Jupyter Notebook kernels across distributed clusters like Apache Spark, Kubernetes, and Docker Swarm. In versions prior to 3.3.0, the server interpolates untrusted environment variables (e.g., KERNEL_XXX) into Kubernetes manifests without YAML-aware escaping, enabling YAML injection attacks. Attackers can inject new fields, overwrite critical fields (e.g., duplicate securityContext keys, where the last one prevails), and inject document boundaries (--- for new documents, ... for end-of-document) to generate multiple resources, potentially creating arbitrary types, such as privileged pods. The Jinja2 template for the Kubernetes manifest contains several kernel_xxx variables, such as kernel_working_dir that are used when rendering the manifest and are all vectors for YAML injection. This issue has been fixed in version 3.3.0.
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Analysis
by VulDB Data Team • 07/17/2026
The Jupyter Enterprise Gateway represents a critical component in modern data science and machine learning environments, facilitating distributed computing by launching remote Jupyter Notebook kernels across various cluster infrastructures including Apache Spark, Kubernetes, and Docker Swarm. This system serves as a bridge between interactive notebook interfaces and computational backends, enabling researchers and developers to leverage powerful distributed processing capabilities while maintaining the familiar notebook workflow. The gateway's architecture relies heavily on templating mechanisms to generate configuration manifests for target environments, particularly Kubernetes where it creates pod specifications for kernel execution. However, this templating approach introduced a fundamental security flaw in versions prior to 3.3.0 that has significant implications for cluster security and integrity.
The technical vulnerability stems from insufficient input validation and sanitization within the Jinja2 templating engine used to construct Kubernetes manifests. When processing environment variables such as KERNEL_XXX prefixed parameters, the system directly interpolates these values into the manifest without proper YAML escaping or validation mechanisms. This creates a classic YAML injection vulnerability where maliciously crafted environment variable values can alter the structure and content of generated manifests. The kernel_working_dir and other kernel_xxx variables serve as primary attack vectors since they are rendered directly into the Kubernetes pod specification without sanitization. Attackers exploiting this weakness can inject new fields, modify existing configurations, or even overwrite critical security parameters such as securityContext definitions where the last occurrence takes precedence, potentially leading to privilege escalation.
The operational impact of this vulnerability extends beyond simple code injection, creating opportunities for attackers to manipulate the entire pod lifecycle and resource allocation within Kubernetes clusters. By injecting document boundaries using triple dashes (---) and ellipses (...), adversaries can generate multiple Kubernetes resources from a single manifest, potentially creating unintended objects such as privileged pods with elevated permissions. This capability enables attackers to establish persistent access points within clusters or escalate privileges beyond what the original kernel execution should permit. The vulnerability particularly affects environments where notebook users might have access to modify environment variables or where automated deployment processes incorporate user-provided configuration data. Organizations relying on Jupyter Enterprise Gateway for distributed computing workloads face significant risk of unauthorized privilege escalation, data exfiltration, and cluster compromise.
Security practitioners addressing this vulnerability should prioritize immediate upgrade to version 3.3.0 or later where proper YAML escaping mechanisms have been implemented. The fix typically involves implementing comprehensive input validation and sanitization routines that escape special YAML characters within interpolated variables before rendering templates. Organizations should also consider implementing additional security controls such as pod security policies, restricted service accounts, and runtime monitoring for unusual Kubernetes manifest modifications. From a compliance perspective, this vulnerability aligns with CWE-134 Uncontrolled Format String and CWE-20 Improper Input Validation, while attack patterns correspond to ATT&CK techniques involving privilege escalation through container manipulation and credential access via compromised notebook environments. Regular security assessments of templating systems and environment variable handling should be implemented as part of broader infrastructure security programs to prevent similar vulnerabilities in other components that process user-provided data within configuration templates.