What is the CVSS score of CVE-2020-24897?

CVE-2020-24897 has a CVSS 3.1 base score of 8.9 (High). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:L. EPSS exploitation probability: 0.9%.

Table Filter And Charts For Confluence Server CVE-2020-24897

HIGH

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

2020-08-29 cve@mitre.org

XSS Atlassian Table Filter And Charts For Confluence Server

8.9

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

8.9 HIGH

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

Low

Privileges Required

Low

User Interaction

Required

Scope

Changed

Confidentiality

High

Integrity

High

Availability

Low

Lifecycle Timeline

CVE Published

Aug 29, 2020 - 20:15 nvd

HIGH 8.9

DescriptionNVD

The Table Filter and Charts for Confluence Server app before 5.3.25 (for Atlassian Confluence) allow remote attackers to inject arbitrary HTML or JavaScript via cross site scripting (XSS) through the provided Markdown markup to the "Table from CSV" macro.

AnalysisAI

The Table Filter and Charts for Confluence Server app before 5.3.25 (for Atlassian Confluence) allow remote attackers to inject arbitrary HTML or JavaScript via cross site scripting (XSS) through the. Rated high severity (CVSS 8.9), this vulnerability is remotely exploitable, low attack complexity. No vendor patch available.

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. The Table Filter and Charts for Confluence Server app before 5.3.25 (for Atlassian Confluence) allow remote attackers to inject arbitrary HTML or JavaScript via cross site scripting (XSS) through the provided Markdown markup to the "Table from CSV" macro. Affected products include: Stiltsoft Table Filter And Charts For Confluence Server. Version information: before 5.3.25.

RemediationAI

No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Sanitize all user input, use Content-Security-Policy headers, encode output contextually (HTML, JS, URL). Use frameworks with built-in XSS protection.