What is the CVSS score of CVE-2024-27103?

CVE-2024-27103 has a CVSS 3.1 base score of 6.1 (Medium). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N. EPSS exploitation probability: 0.4%.

Is there a patch available for CVE-2024-27103?

Yes, a patch is available for CVE-2024-27103. Update the affected software to the latest version immediately.

Querybook CVE-2024-27103

MEDIUM

Cross-site Scripting (XSS) (CWE-79)

2024-02-28 security-advisories@github.com

XSS Querybook

6.1

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

6.1 MEDIUM

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

Required

Scope

Changed

Confidentiality

Low

Integrity

Low

Availability

None

Lifecycle Timeline

CVE Published

Feb 28, 2024 - 18:15 nvd

MEDIUM 6.1

DescriptionNVD

Querybook is a Big Data Querying UI. When a user searches for their queries, datadocs, tables and lists, the search result is marked and highlighted, and this feature uses dangerouslySetInnerHTML which means that if the highlighted result has an XSS payload it will trigger. While the input to dangerouslySetInnerHTML is not sanitized for the data inside of queries which leads to an XSS vulnerability. During the "query auto-suggestion" the name of the suggested tables are set with innerHTML which leads to the XSS vulnerability. A patch to rectify this issue has been introduced in Querybook version 3.31.2.

AnalysisAI

Querybook is a Big Data Querying UI. Rated medium severity (CVSS 6.1), this vulnerability is remotely exploitable, no authentication required, low attack complexity. This Cross-Site Scripting (XSS) vulnerability could allow attackers to inject malicious scripts into web pages viewed by other users.

Technical ContextAI

This vulnerability is classified as Cross-Site Scripting (XSS) (CWE-79), which allows attackers to inject malicious scripts into web pages viewed by other users. Querybook is a Big Data Querying UI. When a user searches for their queries, datadocs, tables and lists, the search result is marked and highlighted, and this feature uses dangerouslySetInnerHTML which means that if the highlighted result has an XSS payload it will trigger. While the input to dangerouslySetInnerHTML is not sanitized for the data inside of queries which leads to an XSS vulnerability. During the "query auto-suggestion" the name of the suggested tables are set with innerHTML which leads to the XSS vulnerability. A patch to rectify this issue has been introduced in Querybook version 3.31.2. Affected products include: Pinterest Querybook. Version information: version 3.31.2..

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Sanitize all user input, use Content-Security-Policy headers, encode output contextually (HTML, JS, URL). Use frameworks with built-in XSS protection.