CVE-2024-24766
Icewhale Casaos-Userservice 0.4.4-3 – 0.4.7
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2024-24766 is a medium-severity Observable Response Discrepancy (CWE-204) vulnerability in Icewhale Casaos-Userservice. Its CVSS base score is 6.2 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked in the top 48% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to IA-6 (Authentication Feedback) and SI-11 (Error Handling) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0898
Vulnerability Data
CasaOS-UserService provides user management functionalities to CasaOS. Starting in version 0.4.4.3 and prior to version 0.4.7, the Casa OS Login page disclosed the username enumeration vulnerability in the login page. An attacker can enumerate the CasaOS username using the application…
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response. If the username is incorrect application gives the error `**User does not exist**`. If the password is incorrect application gives the error `**Invalid password**`. Version 0.4.7 fixes this issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
V13.4.5
Mitigating Controls (NIST 800-53 r5) AI
Obscuring authentication feedback directly stops one common source of observable response discrepancies.
Error handling explicitly requires messages that avoid revealing exploitable internal information.
Information flow enforcement can block responses that would otherwise disclose internal state to unauthorized parties.
Boundary protection monitors and filters outbound responses that could leak internal state.
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 prevent introduction of inconsistent response behavior that leaks internal state.
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 observable response discrepancies before deployment.
Network security controls can enforce uniform responses and suppress observable discrepancies.
Secure SDLC practices include error-handling and response standardization to avoid information disclosure.
Application security requirements typically mandate consistent, non-revealing error messages.
Secure architecture principles discourage designs that leak internal state via differing responses.
Secure coding standards explicitly require uniform error handling to prevent information leakage.