VulnerabilityPublished 13 Aug 2026Updated 29 Oct 2026

CVE-2026-44899: Jupyterlab · Mistune Image Directive CSS Injection Vulnerability

Affects jupyterlabSource GCVE Database

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Authoritative record:CVE-2026-44899· Medium 4.7

Not known to be exploited · CVSS 4.7 Medium : upgrade to 4.5.7_1 when convenient.

Data as of 30 Oct 2026, 09:14 UTC

CVSS 3.1 base score

4.7Medium

How severe the flaw is on the 0–10 CVSS scale.

Patch: Available – fixed in 4.5.7_1

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:N/A:N

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: Required
Scope: Changed
Confidentiality: Low
Integrity: None
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: Required: Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited.
Scope: Changed: An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 26 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade jupyterlab to 4.5.7_1.

Affected software

Product	Affected	Fixed in
Homebrewjupyterlab`pkg:brew/jupyterlab`Other threats	Affected >=1.2.0 <4.5.7_1	Fixed in 4.5.7_1

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

A patch is available in JupyterLab version 4.5.7_1 that corrects the validation logic to prevent CSS injection. Users should upgrade to this fixed version to remediate the vulnerability. No additional mitigation steps are required if the patch is applied.

Description

JupyterLab's Mistune Image directive plugin improperly validates the width and height options using a regex that only anchors at the start of the string. This allows an attacker to inject arbitrary CSS properties into the style attribute of an image element by providing a crafted width value that begins with digits but includes additional CSS declarations. This vulnerability can be exploited to create full-page overlays that visually cover the browser viewport, enabling phishing and UI redressing attacks.

Impact

An attacker can inject arbitrary CSS into the style attribute of images rendered by the Mistune Image directive, enabling UI redressing attacks such as full-page phishing overlays that can obscure legitimate page content. This can lead to user deception and potential credential theft or other social engineering attacks. The vulnerability does not impact confidentiality or availability directly but compromises user interface integrity and trust.

Summary

The vulnerability in JupyterLab's Mistune Image directive stems from a regex validation that only checks if the width and height options start with digits, allowing additional CSS to be appended unchecked. When a non-integer width is provided, the value is inserted directly into the style attribute without escaping, enabling injection of arbitrary CSS properties such as position:fixed and z-index to create overlays. The flaw affects versions from 1.2.0 up to but not including 4.5.7_1. A fix is available in version 4.5.7_1.

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What to do

Affected software

Description

AI analysisMachine-generated, updated 30 Oct 2026, 09:14 UTC

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