What is CVE-2026-73417?

CVE-2026-73417 is JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`). The supplied enrichment data classifies it as Injection mapped to CWE-79 Cross-site Scripting; CWE-116 CWE-116.

Which versions are affected?

Affected product and version evidence is listed in the product table above. Current public advisories should be checked for exact version scope before patch targeting is finalized.

Is there active exploitation?

Active exploitation is not confirmed from current sources for CVE-2026-73417. If exploitation is not confirmed from current sources, teams should document that status and continue monitoring KEV, vendor, and telemetry updates.

No. CVE-2026-73417 is not listed in CISA KEV in the supplied enrichment data. KEV status should be monitored because it can change after initial disclosure or after exploitation becomes publicly confirmed.

Is there a public exploit?

A public PoC is not confirmed from current sources for CVE-2026-73417. Public exploit or PoC availability should raise triage priority, especially for exposed or business-critical systems.

How can defenders detect it?

Start with database audit logs where available. Look for vulnerability-class behavior, product errors, suspicious authentication events, exploit probes, and abnormal process activity based only on evidence that applies to the affected product.

How should teams prioritize it?

Prioritize CVE-2026-73417 using CVSS 8.6, EPSS 0%, KEV status, public PoC status, and asset exposure. Internet-facing, privileged, or business-critical deployments should be handled first.

Are workarounds available?

Workarounds are not confirmed from current sources. Fixed-version evidence is listed in the mitigation section above.

Which threat actors are linked publicly?

No public threat actor linkage is confirmed from current sources. Do not attribute exploitation to a threat actor unless the source evidence explicitly supports that linkage.

What should be done in the next 24 hours?

Identify exposed assets running affected vendor/product/version combinations. Prioritize based on EPSS, PoC availability, and external exposure. Search available logs for exploit probes, errors, authentication anomalies, or suspicious child processes matching the vulnerability class. Open remediation tickets with affected assets, owners, evidence status, and detection coverage so decisions are traceable.

highInjection

CVE-2026-73417

CVE-2026-73417 — JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 3.3.0 until 4.5.10 and 4.6.2, JupyterLab allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor. In packages/notebook-extension/schema/tracker.json and packages/notebook-extension/src/index.ts, the sideBySideLeftMarginOverride and sideBySideRightMarginOverride settings are not properly validated before being inserted into style content, allowing a crafted settings file to contain instructions that execute as code instead of only changing display preferences. A user can import the malicious file, or an attacker with access to a shared settings location can plant an overrides.json that is applied automatically. The embedded code runs with the affected user's access and can read or modify notebooks and files and run code through the notebook server, including on a connected kernel. This issue is fixed in versions 4.5.10 and 4.6.2.

Published Aug 13, 2026Updated Aug 13, 2026Sources: NVD, jupyterlab (CNA), GitHub, GitHub Security Advisory, SOCRadar CTI

Triage

Is it exploited, how likely is exploitation, what does it touch, and how severe do the scoring sources call it.

Exploitation

Unreported

no source claims exploitation

EPSS

ahead of 0% of scored CVEs

Affects

jupyterlab

4 products listed

CVSS base

8.6

high

Remediation

The vendor's own words where we have them.

Upgrade jupyterlab to 4.6.2 or later (pip advisory GHSA-pppj-hq3g-57pj).

First 24 hours

Ordered from the record's own fields — exposure first, because you cannot patch what you have not found.

Identify exposed assets running affected vendor/product/version combinations.
Prioritize based on EPSS, PoC availability, and external exposure.
Search available logs for exploit probes, errors, authentication anomalies, or suspicious child processes matching the vulnerability class.

Affected scope

Vendor, product and version as the advisories word them.

Vendor	Product	Versions	Status
jupyterlab	jupyterlab	>= 3.3.0, < 4.5.10	Vulnerable
jupyterlab	jupyterlab	>= 4.6.0, < 4.6.2	Vulnerable
pip	jupyterlab	>= 4.6.0, <= 4.6.1	Vulnerable
pip	jupyterlab	>= 3.3.0, <= 4.5.9	Vulnerable

Every base score collected

Sources score independently and disagree; each row says who scored it and under which version.

Score	Version	Severity	Expl.	Impact	Source
8.6	CVSS 4.0	high	—	—	jupyterlab (CNA)

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L

Weakness & attack patterns

CWE-79Cross-site Scripting
CWE-116

Inferred from the weakness class — not observed against this CVE.

CAPEC-66 · SQL InjectionCAPEC-7 · Blind SQL Injection

Detection

Read off the CVSS vector and the weakness class. Starting points, not rules we have tested.

Search application, proxy, and WAF logs for requests touching /notebook-extension/schema/tracker.json, /notebook-extension/src/index.ts.

database audit logs

Timeline

What happened to this CVE, newest first — with the readings a source repeats on a schedule counted underneath rather than listed.

2026
Added · CVSS 3.1 8.6
Aug 13, 2026 · NVD
Initial · CVE published
Aug 13, 2026 · NVD
Added · GHSA-pppj-hq3g-57pj published (high)
Jul 22, 2026 · GitHub Security Advisory

References

11 on the record

github.com/jupyterlab/jupyterlab/commit/9365f020baec5221deaf11535ed554c06637c999
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/pull/19184
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/pull/19185
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/pull/19186
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
Exploit, Third Party Advisory
github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
Exploit, Third Party Advisory

Elsewhere on this site

jupyterlabevery CVE for this vendor
pipevery CVE for this vendor
Injectionsame class
CWE-79other pages naming this weakness

Not in any source we poll

Listed rather than left blank: an empty field and an unmeasured one look identical on screen, and only one is a reason to look elsewhere.

No confirmed IOCs, IP addresses, domains, file hashes, or malware artifacts supplied.
No organization-specific asset inventory, compensating-control status, or patch deployment evidence supplied.
No exploit packet captures, log samples, or incident case IDs supplied.

Answered from this record1

What should defenders know first?

CVE-2026-73417 is JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`), a high vulnerability affecting jupyterlab from jupyterlab, pip. The current evidence does not list it in CISA KEV, and the exploit status is: Active exploitation is not confirmed from current sources for CVE-2026-73417. Public exploit evidence is: A public PoC is not confirmed from current sources for CVE-2026-73417. The affected-version evidence is listed in the key facts and affected products tables. Defenders should first verify whether exposed or business-critical assets run those versions, then apply vendor patches or mitigations, restrict reachable attack surface, and preserve logs for detection review. CVSS 8.6 describes technical severity, while EPSS 0% helps estimate near-term exploit likelihood; neither replaces asset context. Unknown fields should remain explicit in tickets, and threat actor, IOC, victimology, or payload claims should not be added unless a cited source supports them. Monitor CISA KEV, vendor advisories, NVD changes, public PoC repositories, and internal telemetry for update triggers.