{"description":"Trending threats, MITRE ATT\u0026CK coverage, and detection metadata. Fed continuously.","feed_url":"https://feed.craftedsignal.io/products/jupyterlab-4.6.0-4.6.1/feed.json","home_page_url":"https://feed.craftedsignal.io/","items":[{"_cs_actors":[],"_cs_cpes":[],"_cs_cves":[],"_cs_exploited":false,"_cs_has_poc":false,"_cs_poc_references":[],"_cs_products":["JupyterLab (3.3.0-4.5.9)","JupyterLab (4.6.0-4.6.1)"],"_cs_severities":["high"],"_cs_tags":["xss","jupyterlab","code-execution","vulnerability","cloud"],"_cs_type":"advisory","_cs_vendors":["Project Jupyter"],"content_html":"\u003cp\u003eJupyterLab versions 3.3.0 through 4.5.9 and 4.6.0 through 4.6.1 are affected by a cross-site scripting (XSS) vulnerability related to improper validation of notebook display settings within the \u003ccode\u003eoverrides.json\u003c/code\u003e file. This flaw, tracked as a GitHub Security Advisory (GHSA-pppj-hq3g-57pj) with a pending CVE, allows an attacker to embed malicious code within a crafted \u003ccode\u003eoverrides.json\u003c/code\u003e file. When this file is either deliberately imported by a user via the Settings Editor's \u0026quot;Import\u0026quot; button or automatically applied due to write access on a multi-tenant file system, the embedded code executes within the victim's JupyterLab session. This enables an attacker to perform actions such as reading or modifying the user's notebooks and files, and running arbitrary code through the associated notebook server and kernels, thereby compromising the user's environment. The vulnerability stems from the expectation that settings files only modify display preferences, not execute code.\u003c/p\u003e\n\u003ch2 id=\"attack-chain\"\u003eAttack Chain\u003c/h2\u003e\n\u003col\u003e\n\u003cli\u003eAttacker crafts a malicious \u003ccode\u003eoverrides.json\u003c/code\u003e file containing XSS payloads designed to bypass JupyterLab's validation for certain notebook display settings.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eInitial Access Option 1 (User Interaction):\u003c/strong\u003e Attacker delivers the malicious \u003ccode\u003eoverrides.json\u003c/code\u003e to a victim, potentially via social engineering, and convinces them to import it through the JupyterLab Settings Editor's \u0026quot;Import\u0026quot; button.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eInitial Access Option 2 (Privileged Write Access):\u003c/strong\u003e Attacker with write access to a shared or multi-tenant file system places the malicious \u003ccode\u003eoverrides.json\u003c/code\u003e in a directory from which JupyterLab automatically loads user settings.\u003c/li\u003e\n\u003cli\u003eJupyterLab loads and processes the malicious \u003ccode\u003eoverrides.json\u003c/code\u003e file, either manually imported or automatically applied at startup.\u003c/li\u003e\n\u003cli\u003eDue to insufficient validation of the embedded settings, the XSS payload executes within the victim's JupyterLab session, running with the user's privileges.\u003c/li\u003e\n\u003cli\u003eThe attacker's code gains the ability to read or modify the victim's notebooks and other associated files.\u003c/li\u003e\n\u003cli\u003eThe attacker's code can execute arbitrary commands on the victim's behalf through the Jupyter notebook server, potentially interacting with connected computational kernels.\u003c/li\u003e\n\u003cli\u003eThe ultimate objective is to compromise user data, intellectual property, or gain further access to the underlying infrastructure through the hijacked session.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2 id=\"impact\"\u003eImpact\u003c/h2\u003e\n\u003cp\u003eSuccessful exploitation of this vulnerability allows an attacker to execute arbitrary code within the victim's JupyterLab session with the same privileges as the affected user. This directly translates to the ability to read, modify, and exfiltrate the user's notebooks and other files accessible through JupyterLab. Furthermore, the attacker can leverage the compromised session to run code on the user's behalf through the associated Jupyter notebook server, potentially interacting with any connected computational kernels. While no specific victim counts or targeted sectors are identified in the advisory, any organization utilizing JupyterLab, especially in shared or multi-tenant environments, is at risk of intellectual property theft, data manipulation, or unauthorized resource utilization.\u003c/p\u003e\n\u003ch2 id=\"recommendation\"\u003eRecommendation\u003c/h2\u003e\n\u003cul\u003e\n\u003cli\u003eUpgrade JupyterLab to version 4.6.2 or 4.5.10 immediately to apply the security patches addressing the XSS vulnerability.\u003c/li\u003e\n\u003cli\u003eEstablish and enforce a trusted process for distributing JupyterLab configuration files, discouraging users from importing arbitrary \u003ccode\u003eoverrides.json\u003c/code\u003e files from untrusted sources.\u003c/li\u003e\n\u003cli\u003eFor multi-tenant or shared file systems, restrict write permissions on JupyterLab application settings directories and other configuration paths to prevent unauthorized users from placing malicious \u003ccode\u003eoverrides.json\u003c/code\u003e files that could be automatically loaded.\u003c/li\u003e\n\u003c/ul\u003e\n","date_modified":"2026-07-22T23:19:08Z","date_published":"2026-07-22T23:19:08Z","id":"https://feed.craftedsignal.io/briefs/2026-07-jupyterlab-xss/","summary":"A cross-site scripting (XSS) vulnerability exists in JupyterLab versions 3.3.0 through 4.5.9 and 4.6.0 through 4.6.1, allowing arbitrary code execution because notebook display settings in the `overrides.json` file are not properly validated, enabling an attacker to craft a malicious file which, when imported by a user or automatically applied on a multi-tenant file system, can execute hidden instructions and compromise user data.","title":"JupyterLab Cross-site Scripting via Crafted Settings File","url":"https://feed.craftedsignal.io/briefs/2026-07-jupyterlab-xss/"}],"language":"en","title":"CraftedSignal Threat Feed - JupyterLab (4.6.0-4.6.1)","version":"https://jsonfeed.org/version/1.1"}