CVE-2024-41924
Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-41924 is a high-severity Acceptance of Extraneous Untrusted Data With Trusted Data (CWE-349) vulnerability in Jvn (inferred from references). Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Subvert Trust Controls (T1553); ranked at the 19th 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 AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-39276
Vulnerability Data
Acceptance of extraneous untrusted data with trusted data vulnerability exists in EC-CUBE 4 series. If this vulnerability is exploited, an attacker who obtained the administrative privilege may install an arbitrary PHP package. If the obsolete versions of PHP packages are…
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installed, the product may be affected by some known vulnerabilities.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 5 hardening rules · 2 OS baselines
V1.2.2V10.4.7V3.7.3V5.3.1
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can block untrusted data from being accepted or processed as if it were trusted.
Input validation directly stops acceptance of untrusted data mixed into trusted inputs.
Associating security attributes with data allows the system to distinguish and reject extraneous untrusted portions.
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 address proper trust-boundary enforcement and input validation, preventing this class of weakness during development.
Cryptographic integrity checks on data-at-rest can detect tampering or substitution of untrusted content mixed with trusted data.
Cryptographic integrity mechanisms on data-in-transit can prevent acceptance of extraneous untrusted data by validating origin and detecting modification.
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 the weakness but does not itself implement preventive controls.
Secure development lifecycle mandates input validation and trust-boundary enforcement that directly prevents acceptance of untrusted data alongside trusted data.
Application security requirements explicitly call for strict separation and validation of trusted versus untrusted data sources.
Secure architecture principles require explicit trust boundaries and data-origin checks that mitigate mixing of trusted and untrusted inputs.
Secure coding standards mandate input sanitization and provenance checks that prevent acceptance of extraneous untrusted data.
Information access restriction limits who can supply data but does not address validation of data origin or trust level.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (1 rule)
- V-248574 YUM must be configured to prevent the installation of patches, service packs, device drivers, or OL 8 system components that have not been digitally signed using a certificate that is recognized and approved by the organization. prevents CWE-349