HighCVE-2026-102831

    Jupyterlab: Cross-site Scripting (CVE-2026-102831)

    Published Last modified Sources: Red Hat, OSV, CVE.org, Hersteller

    What is affected, what to do

    A flaw was found in JupyterLab. This vulnerability allows Cross-Site Scripting (XSS) when pasting notebook cells from the system clipboard, as the application fails to clear trusted metadata flags from imported cell data.

    The available sources name no fixed version. Check the vendor guidance in the references below.

    Affected
    • Jupyterlab gte 4.5.0, < 4.5.11..*
    • Jupyterlab Notebook gte 7.5.0, < 7.6.3..*
    • Jupyterlab Jupyterlite-core gte 0.7.0, < 0.8.4..*

    Not sure whether and how you are affected? Ask a question about this vulnerability

    Metrics

    8.1

    Priority

    XIEM Effective CVSS: highest available CVSS rating from NVD and vendor data.

    Source: Vendor (CNA), CVSS v3

    8.1

    CVSS v3

    Severity High on the scale from 0 to 10.

    Source: Red Hat, OSV, CVE.org, Hersteller

    0.2 %

    EPSS score

    Low — model estimates < 1% exploitation likelihood.

    Source: FIRST EPSS, percentile 14.7

    Show all metrics
    Severity
    High
    Priority (0–325)

    The priority score is a consolidated metric that condenses several individual signals into a single, action-guiding ranking: technical severity (CVSS), exploitation likelihood (EPSS), known-exploited status (KEV) and the context of the affected asset. The aim is to answer the only truly important question in vulnerability management: what first?

    Read in glossary
    71.90 Methodology
    Exploit maturity

    An exploit is code or a technique that specifically uses a concrete vulnerability to force unintended behaviour — such as executing code or escalating privileges. It is the tool that turns a theoretical flaw into a practical attack.

    Read in glossary
    no public PoC known
    XIEM Effective CVSS

    XIEM® is the tiered managed-security operating model from NEOSEC and a registered trademark of NEOSEC GmbH. It extends classic SIEM — the central collection, normalisation and correlation of security-relevant events — with endpoint forensics, network visibility and deception technology, and consolidates them into three building tiers: Sentry, Orchestrate and Command.

    Read in glossary
    8.1 Methodology
    CVSS v3

    CVSS is the globally established, open standard for assessing the technical severity of a vulnerability on a scale from 0 to 10. It describes how easily a flaw can be exploited and what damage it can cause — but not how likely its actual exploitation is. CVSS and the complementary EPSS deliberately answer different questions.

    Read in glossary
    8.1
    EPSS score

    The EPSS score is the absolute model output for an individual vulnerability: the estimated probability of real-world exploitation within the next 30 days, expressed as a value between 0 and 1 (i.e. 0 % to 100 %). A score of 0.42 means „the model estimates a 42 % chance of real-world exploitation within 30 days“.

    Read in glossary
    0.2 %
    Low — model estimates < 1% exploitation likelihood.
    EPSS percentile

    The EPSS percentile is the relative position of a vulnerability within all EPSS-scored CVEs, expressed as a value between 0 and 1. A percentile of 0.90 means „this CVE has a higher EPSS score than 90 % of all other scored CVEs“. Unlike the EPSS score, it is not a probability — but a positioning within a ranking.

    Read in glossary
    14.7
    Elevated — this CVE ranks above at least 10% of all CVEs scored today.
    KEV status

    The KEV catalogue is a list maintained by the US authority CISA of vulnerabilities for which active exploitation in the wild has been confirmed. It answers not the question „how severe?“ but „is it already being attacked?“ — thereby sharply prioritising patching.

    Read in glossary
    —
    Published
    CISA assessment (SSVC)
    Exploitation: none known · not automatable · Technical impact: total
    Source: CISA Vulnrichment, as of 2 October 2026
    CWE

    CWE is a catalogue of typical weakness types in software and hardware — such as flawed input validation, unsafe memory handling or poor authentication. Where a CVE names a concrete vulnerability in a concrete product, a CWE describes the underlying class of defect.

    Read in glossary
    CWE-79, CWE-345

    Detection rules

    No NEOSEC detection rule is available for this vulnerability yet.

    Classification under NIS2 and CRA

    Rule-based classification from exploitation status and severity. It does not replace a case-by-case assessment.

    NIS2

    NIS2 is EU Directive (EU) 2022/2555 to raise the level of cybersecurity across the Union. It substantially broadens obligations compared with the first NIS directive: more sectors, mandatory risk management, staged reporting duties and personal accountability of senior management.

    Read in glossary
    High technical severity: assess and remediate the vulnerability in vulnerability handling under Art. 21(2)(e) NIS2 and document the decision.
    CRA

    The CRA is EU Regulation (EU) 2024/2847 setting horizontal cybersecurity requirements for „products with digital elements“ — from industrial controllers and software to connected consumer devices. For the first time manufacturers must ensure security across the entire product lifecycle, handle vulnerabilities and provide security updates.

    Read in glossary
    From 11.12.2027, Annex I Part II CRA requires manufacturers of affected products with digital elements to handle vulnerabilities without delay and provide security updates.
    ISO/IEC 27001

    ISO/IEC 27001 is the internationally leading standard for an information security management system (ISMS). It describes a risk-based, process-oriented framework to systematically plan, implement, review and improve information security.

    Read in glossary
    Control A.8.8, management of technical vulnerabilities: assess relevance to your systems, plan remediation and keep evidence.

    Description

    A flaw was found in JupyterLab. This vulnerability allows Cross-Site Scripting (XSS) when pasting notebook cells from the system clipboard, as the application fails to clear trusted metadata flags from imported cell data. A remote attacker could exploit this by enticing a user to paste malicious cell content, bypassing output sanitization. Successful exploitation enables the execution of arbitrary scripts within the user's authenticated session, potentially leading to unauthorized actions and information disclosure.

    Source: redhat_csaf, OSV (Open Source Vulnerabilities), cvelistv5, NVD (NIST), GitHub Security Advisories

    Affected products

    The following versions are affected. Older releases of the same product line are also vulnerable unless stated otherwise.

    Affected products
    Affected versionsFixed in
    jupyterlabjupyterlab
    • ≥ 4.5.0, < 4.5.11
    • —
    jupyterlabjupyterlite-core
    • ≥ 0.7.0, < 0.8.4
    • —
    jupyterlabnotebook
    • ≥ 7.5.0, < 7.6.3
    • —
    pypinotebook
    • 7.5.3
    • 7.6.0b0
    • 7.6.0a2
    • 7.5.2
    • 7.6.0
    • 7.6.0rc1
    • 7.6.0rc0
    • 7.6.2
    • 7.6.0a3
    • 7.5.0
    • 7.6.0a0
    • 7.5.5
    • 7.6.1
    • 7.5.6
    • 7.5.7
    • 7.5.4
    • 7.6.0b1
    • 7.6.0a1
    • 7.5.1
    • 7.6.0a4
    • 7.6.0a5
    • 7.5.8
    • —
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    Vendors and products

    Weakness classes (CWE)

    • CWE-79Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

      Base

      The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

      Entry at MITRE CWE-79

    • CWE-345Insufficient Verification of Data Authenticity

      Class

      The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data.

      Entry at MITRE CWE-345

    References & sources

    • github.comjupyterlab/jupyterlab/security/advisories/GHSA-6966-vjj6-99xvx_refsource_CONFIRM
    • github.comjupyterlab/jupyterlab/commit/1a10a7da5ff655849b21581c2633b46483…x_refsource_MISC
    • github.comjupyterlab/jupyterlab/commit/7f9f29e29e0c83fb17b0f11da57d06b3c6…x_refsource_MISC
    • github.comjupyterlab/jupyterlab/commit/cf6e89a8d315c4134cefa50c220bca296d…x_refsource_MISC
    • github.comjupyterlab/jupyterlab/releases/tag/v4.5.11x_refsource_MISC
    • github.comjupyterlab/jupyterlab/releases/tag/v4.6.4x_refsource_MISC
    • NVD (NIST)vuln/detail/CVE-2026-102831advisory
    • github.comjupyterlab/jupyterlabpackage
    • pypi.orgproject/jupyterlabpackage
    • GitHub Security Advisoriesadvisories/GHSA-6966-vjj6-99xvadvisory
    • pypi.orgproject/jupyterlitepackage
    • pypi.orgproject/jupyterlite-corepackage
    • pypi.orgproject/notebookpackage

    Changes to this CVE

    Who changed this CVE and when: NVD (analysis, affected products, CVSS), the CVE publisher (CNA) and additional providers such as CISA (ADP).

    1. Record modifiedCISA ADP

      CISA assessment (SSVC): exploitation: none known, automatable: no

      Show the original change
      Individual changes of this event as published by NVD
      TypeActionBeforeAfter
      SSVC assessmentadded
      —
      {"id":"CVE-2026-102831","role":"CISA Coordinator","options":[{"exploitation":"none"},{"automatable":"no"},{"technicalImpact":"total"}],"version":"2.0.3","timestamp":"2026-10-02T12:22:47.366494Z"}

      Source identifier: 134c704f-9b21-4f2e-91b3-4a467353bcc0

    2. ReceivedGitHub

      CVSS V3.1: AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N

      Weakness type: CWE-79, CWE-345

      Description added or changed

      Show 11 original changes
      Individual changes of this event as published by NVD
      TypeActionBeforeAfter
      Descriptionadded
      —
      JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 4.5.0 until 4.5.11 and 4.6.4, from Notebook 7.5.0 until 7.6.3, and from JupyterLite Core 0.7.0 until 0.8.4, the system clipboard cell-paste path accepts attacker-controlled cell JSON without clearing metadata.trusted. When useSystemClipboardForCells is active and pasteCodeCellsWithoutOutput is disabled, a pasted code cell can mark HTML output as trusted, bypass output sanitization, and execute script in the authenticated JupyterLab origin without executing the cell. Markdown and raw cells are not affected because their output is sanitized. This issue is fixed in JupyterLab 4.5.11 and 4.6.4, Notebook 7.6.3, and JupyterLite Core 0.8.4.
      CVSSadded
      —
      AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N
      Weakness type (CWE)added
      —
      CWE-79
      Weakness type (CWE)added
      —
      CWE-345
      Affected versions (publisher)added
      —
      New affected value received. <a href="https://github.com/CVEProject/cvelistV5/blob/main/cves/2026/102xxx/CVE-2026-102831.json">CVE-2026-102831</a>
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/commit/1a10a7da5ff655849b21581c2633b46483ae0be9
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/commit/7f9f29e29e0c83fb17b0f11da57d06b3c6a40d96
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/commit/cf6e89a8d315c4134cefa50c220bca296da466a7
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.11
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.4
      Referenceadded
      —
      https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-6966-vjj6-99xv

      Source identifier: security-advisories@github.com

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