Cyber Resilience

CVE-2024-35225

XSS in Jupyter Server Proxy 3.0.0 – 3.2.4

XSS
Published
11 June 2024
Modified
10 April 2025
Patch / advisory
View advisory
CVSS Score v3.1 9.6
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
EPSS Score 0.0045 37th percentile
Risk Priority 70 floored blend · peak EPSS

Summary

CVE-2024-35225 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Jupyter Jupyter Server Proxy. Its CVSS base score is 9.6 (Critical).

Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 37th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Jupyter Server Proxy allows users to run arbitrary external processes alongside their notebook server and provide authenticated web access to them. Versions of 3.x prior to 3.2.4 and 4.x prior to 4.2.0 have a reflected cross-site scripting (XSS) issue. The…

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`/proxy` endpoint accepts a `host` path segment in the format `/proxy/<host>`. When this endpoint is called with an invalid `host` value, `jupyter-server-proxy` replies with a response that includes the value of `host`, without sanitization [2]. A third-party actor can leverage this by sending a phishing link with an invalid `host` value containing custom JavaScript to a user. When the user clicks this phishing link, the browser renders the response of `GET /proxy/<host>`, which runs the custom JavaScript contained in `host` set by the actor. As any arbitrary JavaScript can be run after the user clicks on a phishing link, this issue permits extensive access to the user's JupyterLab instance for an actor. Patches are included in versions 4.2.0 and 3.2.4. As a workaround, server operators who are unable to upgrade can disable the `jupyter-server-proxy` extension.

CWE(s)
CWE-79CWE-116

Related Threats

MITRE ATT&CK Enterprise Techniques

T1185 Browser Session Hijacking Collection
Adversaries may take advantage of security vulnerabilities and inherent functionality in browser software to change content, modify user-behaviors, and intercept information as part of various browser session hijacking techniques.
attack.mitre.org →
T1539 Steal Web Session Cookie Credential Access
An adversary may steal web application or service session cookies and use them to gain access to web applications or Internet services as an authenticated user without needing credentials.
attack.mitre.org →
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
attack.mitre.org →
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
T1059 Command and Scripting Interpreter Execution
Adversaries may abuse command and script interpreters to execute commands, scripts, or binaries.
attack.mitre.org →
T1189 Drive-by Compromise Initial Access
Adversaries may gain access to a system through a user visiting a website over the normal course of browsing.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-32071Shared CWE-116, CWE-79
CVE-2023-39527Shared CWE-116, CWE-79
CVE-2023-37875Shared CWE-116, CWE-79
CVE-2023-2200Shared CWE-116, CWE-79
CVE-2023-40170Same vendor: Jupyter
CVE-2023-3481Shared CWE-116, CWE-79
CVE-2023-28733Shared CWE-116, CWE-79
CVE-2023-25837Shared CWE-79
CVE-2023-22438Shared CWE-79
CVE-2023-27614Shared CWE-79

Affected Assets

jupyter
jupyter server proxy
3.0.0 — 3.2.4 · 4.1.2 — 4.2.0

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.2.1
  • V1.2.3
  • V1.3.2

Mitigating Controls (NIST 800-53 r5) AI

SA-11 Developer Testing and Evaluation good match

Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.

SI-10 Information Input Validation good match

Input validation directly enforces neutralization of untrusted data before it reaches web output generation.

SI-15 Information Output Filtering good match

Output filtering can catch or sanitize unneutralized script content before it is served to users.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).

PR.PS-02 partial match
prevents

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.8.28 Secure coding mostly match
prevents

Secure coding standards explicitly require correct output encoding and escaping to preserve message structure.

A.8.29 Security testing in development and acceptance mostly match
finds

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

A.5.6 Contact with special interest groups partial match
prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

A.5.7 Threat intelligence partial match
prevents

Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.

A.8.25 Secure development life cycle partial match
prevents

Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.

A.8.26 Application security requirements partial match
prevents

Application security requirements include explicit rules for safe output handling and encoding.

References