Cyber Resilience

CVE-2023-28599

XSS in Zoom ≤ 5.13.10

XSS
Published
13 June 2023
Modified
21 November 2024
Patch / advisory
View advisory
CVSS Score v3.1 4.3
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
EPSS Score 0.0073 51th percentile
Risk Priority 38 floored blend · peak EPSS

Summary

CVE-2023-28599 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Zoom Zoom. Its CVSS base score is 4.3 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Zoom clients prior to 5.13.10 contain an HTML injection vulnerability. A malicious user could inject HTML into their display name potentially leading a victim to a malicious website during meeting creation.

CWE(s)
CWE-79CWE-74

Related Threats

MITRE ATT&CK Enterprise Techniques

T1185 Browser Session Hijacking Collection
Adversaries may take advantage of security vulnerabilities and inherent functionality in browser software to change content, modify user-behaviors, and intercept information as part of various browser session hijacking techniques.
attack.mitre.org →
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
T1221 Template Injection Stealth
Adversaries may create or modify references in user document templates to conceal malicious code or force authentication attempts.
attack.mitre.org →
T1539 Steal Web Session Cookie Credential Access
An adversary may steal web application or service session cookies and use them to gain access to web applications or Internet services as an authenticated user without needing credentials.
attack.mitre.org →
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
attack.mitre.org →
T1674 Input Injection Execution
Adversaries may simulate keystrokes on a victim’s computer by various means to perform any type of action on behalf of the user, such as launching the command interpreter using keyboard shortcuts, typing an inline script to be executed,…
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-28598Same product: Zoom Zoom
CVE-2023-39208Same product: Zoom Zoom
CVE-2023-34121Same product: Zoom Zoom
CVE-2023-6164Shared CWE-74, CWE-79
CVE-2023-47119Shared CWE-74, CWE-79
CVE-2023-36471Shared CWE-74, CWE-79
CVE-2023-4843Shared CWE-74, CWE-79
CVE-2023-4393Shared CWE-74, CWE-79
CVE-2019-3929Shared CWE-79
CVE-2023-22288Shared CWE-79

Affected Assets

zoom
zoom
≤ 5.13.10 · ≤ 5.13.10 · ≤ 5.13.10

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.2.1
  • V1.2.3
  • V1.2.5
  • V1.2.8

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

CA-8 Penetration Testing
addresses: CWE-79

Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.

SA-11 Developer Testing and Evaluation
addresses: CWE-74

Developer assessments and testing (including injection-focused techniques) identify improper neutralization of special elements, and the verifiable flaw remediation corrects them pre-deployment.

SI-10 Information Input Validation
addresses: CWE-79

Validates web inputs to reject script-related content that could produce XSS.

SI-15 Information Output Filtering
addresses: CWE-79

Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.

SI-4 System Monitoring
addresses: CWE-74

Identifies indicators of injection attacks (command, SQL, LDAP, etc.) via anomaly and attack monitoring.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).

PR.PS-02 partial match
prevents

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.8.29 Security testing in development and acceptance mostly match
finds

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

A.5.6 Contact with special interest groups partial match
prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

A.5.7 Threat intelligence partial match
prevents

Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.

A.8.15 Logging partial match
finds

Logging supports detection of injection attempts but does not prevent the weakness.

A.8.16 Monitoring activities partial match
finds

Monitoring activities can identify active injection attacks after they occur.

A.8.25 Secure development life cycle partial match
prevents

Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.

References