Vulnerabilities in pkg:pypi/distributed

PACKAGE
Advisory Identifier: GHSA-c336-7962-wfj2
Advisory Summary

CVE-2026-23528 is a MODERATE remote code execution vulnerability (CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')) affecting Distributed libraries in the PyPI ecosystem. The issue involves dask distributed is vulnerable to remote code execution via jupyter proxy and dashboard. Remediation is available by upgrading affected packages to version 2026.1.0.

2 Known Advisory Record(s)
Package Vulnerability Intelligence

pkg:pypi/distributed

2 Known Advisory Record(s)

Vulnerability advisories affecting package pkg:pypi/distributed. Select an advisory below to view technical details or fixes.

Advisory ID CVE / NVD Severity Summary
GHSA-c336-7962-wfj2 CVE-2026-23528 MODERATE Dask Distributed is Vulnerable to Remote Code Execution via Jupyter Proxy and Dashboard
GHSA-hwqr-f3v9-hwxr CVE-2021-42343 CRITICAL Workers for local Dask clusters mistakenly listened on public interfaces

CVE-2026-23528 at a Glance

CVE Identifier CVE-2026-23528
GHSA Identifier GHSA-c336-7962-wfj2
Severity MODERATE
CVSS v3.1 Base Score N/A
CWE Classification CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Affected Product Distributed
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix CVE-2026-23528

To remediate this vulnerability, upgrade all affected Distributed dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

distributed fixed: 2026.1.0
pip install distributed>=2026.1.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show distributed

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-23528, inspect your installed packages using pip:

pip show distributed

Analyze the terminal output to locate any version of Distributed in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2026.1.0), your application is affected.

Note: The pip show distributed command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting'), where 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. In Distributed, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact When [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/), [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) and [Dask distributed](https://github.com/dask/distributed) are all run together it is possible to craft a URL which will result in code being executed by Jupyter due to a cross-side-scripting (XSS) bug in the Dask dashboard. It is possible for attackers to craft a phishing URL that assumes Jupyter Lab and Dask may be running on localhost and using default ports. If a user clicks on the malicious link it will open an error page in the Dask Dashboard via the Jupyter Lab proxy which will cause code to be executed by the default Jupyter Python kernel. In order for a user to be impacted they must be running Jupyter Lab locally on the default port (with the [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy)) and a Dask distributed cluster on the default port. Then they would need to click the link which would execute the malicious code. ### Patches This has been fixed in the `2026.1.0` release. All users should upgrade to this version. ### Mitigations There are no known workarounds for this bug. The only complete solution is to upgrade to a newer release of Dask. However, there are a few things you could do to reduce your risk. It is possible to avoid code execution via Jupyter by uninstalling the [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) and accessing the Dask dashboard directly at it's URL. However, it is still possible for an attacker to craft a URL that executes JavaScript in the user's browser in the Dask dashboard. Which is still a moderate vulnerability. Therefore we recommend all users upgrade to the latest Dask release. Another potential mitigation is to ensure both Jupyter and the Dask dashboard are running on non-standard ports. While this doesn't resolve the problem it reduces the chance of this being exploited. If an attacker knew which ports you were using they could still craft a malicious URL, but it would require a more targeted attack.

CVE-2026-23528 Affected Distributed Versions

1 component(s)
Fixed Versions:
2026.1.0
Product / Package Ecosystem Affected Versions Fixed Version
distributed
PyPI
< 2026.1.0
2026.1.0

References

Frequently Asked Questions

What is CVE-2026-23528?
CVE-2026-23528 is a security vulnerability in Distributed involving Dask Distributed is Vulnerable to Remote Code Execution via Jupyter Proxy and Dashboard under CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting').
Which Distributed versions are affected?
Affected versions include releases prior to 2026.1.0 across affected packages: distributed.
What version fixes CVE-2026-23528?
Upgrading to 2026.1.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is distributed affected?
Yes, distributed is affected in releases prior to 2026.1.0. Upgrade your dependency to 2026.1.0 or later.
What CWE is associated with CVE-2026-23528?
CVE-2026-23528 is classified under CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') (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.).
How can I check PyPI dependencies for CVE-2026-23528?
Run the dependency tree command: 'pip show distributed'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-c336-7962-wfj2",
  "modified" : "2026-06-09T10:34:51Z",
  "published" : "2026-01-16T16:58:16Z",
  "aliases" : [ "CVE-2026-23528" ],
  "summary" : "Dask Distributed is Vulnerable to Remote Code Execution via Jupyter Proxy and Dashboard",
  "details" : "### Impact\nWhen [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/), [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) and [Dask distributed](https://github.com/dask/distributed) are all run together it is possible to craft a URL which will result in code being executed by Jupyter due to a cross-side-scripting (XSS) bug in the Dask dashboard.\n\nIt is possible for attackers to craft a phishing URL that assumes Jupyter Lab and Dask may be running on localhost and using default ports. If a user clicks on the malicious link it will open an error page in the Dask Dashboard via the Jupyter Lab proxy which will cause code to be executed by the default Jupyter Python kernel.\n\nIn order for a user to be impacted they must be running Jupyter Lab locally on the default port (with the [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy)) and a Dask distributed cluster on the default port. Then they would need to click the link which would execute the malicious code.\n\n### Patches\nThis has been fixed in the `2026.1.0` release. All users should upgrade to this version.\n\n### Mitigations\nThere are no known workarounds for this bug. The only complete solution is to upgrade to a newer release of Dask. However, there are a few things you could do to reduce your risk.\n\nIt is possible to avoid code execution via Jupyter by uninstalling the [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) and accessing the Dask dashboard directly at it's URL. However, it is still possible for an attacker to craft a URL that executes JavaScript in the user's browser in the Dask dashboard. Which is still a moderate vulnerability. Therefore we recommend all users upgrade to the latest Dask release.\n\nAnother potential mitigation is to ensure both Jupyter and the Dask dashboard are running on non-standard ports. While this doesn't resolve the problem it reduces the chance of this being exploited. If an attacker knew which ports you were using they could still craft a malicious URL, but it would require a more targeted attack.",
  "severity" : [ {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "distributed"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2026.1.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/dask/distributed/security/advisories/GHSA-c336-7962-wfj2"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-23528"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/dask/distributed/commit/ab72092a8a938923c2bb51a2cd14ca26614827fa"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/dask/distributed"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/distributed/PYSEC-2026-169.yaml"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-250", "CWE-79" ],
    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-01-16T16:58:16Z",
    "nvd_published_at" : "2026-01-16T17:15:54Z"
  }
}