Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-21919 is a high-severity Out-of-bounds Write (CWE-787) vulnerability in Linux Linux Kernel. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 12th 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 SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-9402
Vulnerability Data
In the Linux kernel, the following vulnerability has been resolved: sched/fair: Fix potential memory corruption in child_cfs_rq_on_list child_cfs_rq_on_list attempts to convert a 'prev' pointer to a cfs_rq. This 'prev' pointer can originate from struct rq's leaf_cfs_rq_list, making the conversion invalid…
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and potentially leading to memory corruption. Depending on the relative positions of leaf_cfs_rq_list and the task group (tg) pointer within the struct, this can cause a memory fault or access garbage data. The issue arises in list_add_leaf_cfs_rq, where both cfs_rq->leaf_cfs_rq_list and rq->leaf_cfs_rq_list are added to the same leaf list. Also, rq->tmp_alone_branch can be set to rq->leaf_cfs_rq_list. This adds a check `if (prev == &rq->leaf_cfs_rq_list)` after the main conditional in child_cfs_rq_on_list. This ensures that the container_of operation will convert a correct cfs_rq struct. This check is sufficient because only cfs_rqs on the same CPU are added to the list, so verifying the 'prev' pointer against the current rq's list head is enough. Fixes a potential memory corruption issue that due to current struct layout might not be manifesting as a crash but could lead to unpredictable behavior when the layout changes.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and bounds checks) finds out-of-bounds write flaws before deployment.
Requiring documented secure-development standards and tools can mandate bounds-checked coding practices that avoid the weakness.
Input validation can structurally reject or sanitize data that would otherwise trigger an out-of-bounds write.
Memory-protection mechanisms limit the exploitability and blast radius of a successful out-of-bounds write.
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-development practices (static analysis, bounds checking, code review) are the primary means of preventing out-of-bounds writes.
Vulnerability scanning and recording can discover out-of-bounds write flaws so they can be remediated.
Patching or replacing vulnerable software directly eliminates known instances of this coding weakness.
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 in development and acceptance can detect and prevent out-of-bounds write defects.
Secure development life cycle mandates practices that prevent out-of-bounds writes.
Application security requirements can specify bounds-checking and safe memory handling.
Secure architecture and engineering principles reduce the likelihood of buffer overflows.
Secure coding directly addresses out-of-bounds writes through language choice and coding standards.
Change management can enforce review gates that catch unsafe memory operations before deployment.