Raw vector
CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2024-42210 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Hcltech Unica. Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-42210 is a stored cross-site scripting (XSS) vulnerability, also known as persistent or second-order XSS, affecting HCL Unica Marketing Operations versions 12.1.8 and lower. The issue arises when the application receives data from an untrusted source and includes that data within later HTTP responses in an unsafe manner. It carries a CVSS v3.1 base score of 7.6, with the vector AV:N/AC:H/PR:H/UI:R/S:C/C:H/I:H/A:H, and is classified under CWE-79.
Exploitation requires network access (AV:N), high attack complexity (AC:H), high privileges (PR:H), and user interaction (UI:R). A successful attack can achieve high impacts on confidentiality, integrity, and availability (C:H/I:H/A:H), with a changed scope (S:C) that elevates the consequences beyond the vulnerable component.
Mitigation details are available in the HCL support knowledge base article at https://support.hcl-software.com/csm?id=kb_article&sysparm_article=KB0123760 and the vulnerability research repository on GitHub at https://github.com/MarioTesoro/vulnerability-research/blob/main/CVE-2024-42210/README.md. The CVE was published on 2026-03-19T08:16:18.700.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-55477
Vulnerability Data
A Stored cross-site scripting (XSS) vulnerability affects HCL Unica Marketing Operations v12.1.8 and lower. Stored cross-site scripting (also known as second-order or persistent XSS) arises when an application receives data from an untrusted source and includes that data within its…
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later HTTP responses in an unsafe way.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
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.
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).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
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.
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.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.