VulnerabilityPublished 13 Aug 2026Updated 29 Oct 2026

CVE-2026-49476: Jupyterlab · Soup Sieve has Memory Exhaustion via Large Comma-Separated Selector Lists

Affects jupyterlabSource GCVE Database

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Not known to be exploited · CVSS 7.5 High : upgrade to 4.5.8 soon.

Data as of 30 Oct 2026, 08:59 UTC

CVSS 3.1 base score

7.5High

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

Patch: Available – fixed in 4.5.8

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

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

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: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 13 Aug 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 4.5.8.

Affected software

Product	Affected	Fixed in
Homebrewjupyterlab`pkg:brew/jupyterlab`Other threats	Affected >=3.3.2 <4.5.8	Fixed in 4.5.8

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AI-suggested

A patch is available and fixed in JupyterLab version 4.5.8. Users and administrators should upgrade to version 4.5.8 or later to remediate this vulnerability. Until patched, applications should avoid processing untrusted or user-supplied CSS selectors with soupsieve.compile() or Beautiful Soup's .select()/.select_one() to prevent memory exhaustion. No other mitigations are documented by the vendor.

Description

A memory exhaustion vulnerability exists in soupsieve's CSS selector parser used by Beautiful Soup 4 and JupyterLab. The parser allocates unbounded memory when compiling large comma-separated selector lists, allowing an attacker to cause denial of service by supplying a crafted CSS selector string. This can lead to out-of-memory conditions, process termination, or degraded system performance. The issue affects JupyterLab versions from 3.3.2 up to but not including 4.5.8 and is fixed in version 4.5.8.

Impact

An attacker can cause denial of service by exhausting memory on server-side Python applications using soupsieve to parse user-supplied CSS selectors. This can trigger out-of-memory kills in containerized environments, swap thrashing on physical servers, or Python MemoryError exceptions, disrupting service availability. The attack requires no authentication or user interaction and scales linearly with the size of the selector list, allowing precise tuning to exhaust system memory. Multiple concurrent attacks can amplify the impact. The vulnerability affects any application using vulnerable versions of soupsieve via Beautiful Soup 4, including JupyterLab versions >=3.3.2 <4.5.8.

Summary

The soupsieve CSS selector parser in Beautiful Soup 4 and JupyterLab does not enforce limits on the number of selectors in comma-separated lists. When a large selector string (e.g., 250,000 comma-separated 'a' selectors) is compiled, the parser creates a complex object for each selector, consuming approximately 976 bytes each. This results in a high memory amplification ratio (~488x), causing the application to allocate hundreds of megabytes of heap memory from a relatively small input. This vulnerability can be exploited by an unauthenticated attacker supplying crafted CSS selectors to soupsieve.compile() or Beautiful Soup's .select()/.select_one(), leading to memory exhaustion and denial of service.

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Affected software

Description

AI analysisMachine-generated, updated 30 Oct 2026, 08:59 UTC

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