Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-23575 is a medium-severity Generation of Error Message Containing Sensitive Information (CWE-209) vulnerability in Hcl Software (inferred from references). Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique System Information Discovery (T1082); ranked at the 25th 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 SI-11 (Error Handling) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-55665
Vulnerability Data
HCL Aftermarket EPC is vulnerable to attack since the application returns detailed error messages that leak information about the processing on the server. An attacker may use the contents of error messages to help launch another ,more focused attack.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V16.5.1
Mitigating Controls (NIST 800-53 r5) AI
si-11 directly requires error messages to avoid revealing exploitable information about the system or its data.
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 require sanitized error handling to prevent sensitive data disclosure.
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.
Security testing can detect error messages that leak sensitive information.
Secure coding standards explicitly forbid exposing sensitive data in errors.