Vulnerability in Jupyter Notebook (CVE-2018-19351)

Summary

Vulnerability in Jupyter Notebook (CVE-2018-19351). Risk of unauthorized operations or information disclosure.

Original description

The description as published by the source.

Jupyter Notebook before 5.7.1 allows XSS via an untrusted notebook because nbconvert responses are considered to have the same origin as the notebook server. In other words, nbconvert endpoints can execute JavaScript with access to the server API. In notebook/nbconvert/handlers.py, NbconvertFileHandler and NbconvertPostHandler do not set a Content Security Policy to prevent this.

Source: OSV.dev (Open Source Vulnerabilities) NVD GitHub Advisory OSV

Auto-generated summary

Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.

A vulnerability tracked as CVE-2018-19351 has been found in Jupyter Notebook.
Risk of unauthorized operations or information disclosure.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "Jupyter Notebook CVE-2018-19351" on the vendor's site.

CVE-2018-19351 (Jupyter Notebook)
Attack vector: remote (network-reachable) / unauthenticated
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.

❓ What is the problem

A vulnerability (unclassified) exists in Jupyter Notebook.

📍 Affected scope

Check the vendor advisory for the affected versions of Jupyter Notebook.

🔥 Severity

Severity: ?. Risk of unauthorized operations or information disclosure.

🔧 How to fix

Update to the patched release per vendor advisory.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Audit SBOM/dependencies to find affected services.

Response actions

Concrete steps and command examples for SOC/SRE teams to execute in order

1
Identify exposure identify
```
Audit SBOM/dependencies for affected components.
```
資産台帳・SBOM・依存マニフェストで Jupyter Notebook を使っているサービスとバージョンを洗い出す。
2
Post-deployment verification verify
```
Confirm patched version is live in production
```
パッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。

Summary

Original description

Auto-generated summary

Response actions

References