Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/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-2025-39817 is a high-severity Out-of-bounds Read (CWE-125) vulnerability in Linux Linux Kernel. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 6th 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-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-29597
Vulnerability Data
In the Linux kernel, the following vulnerability has been resolved: efivarfs: Fix slab-out-of-bounds in efivarfs_d_compare Observed on kernel 6.6 (present on master as well): BUG: KASAN: slab-out-of-bounds in memcmp+0x98/0xd0 Call trace: kasan_check_range+0xe8/0x190 __asan_loadN+0x1c/0x28 memcmp+0x98/0xd0 efivarfs_d_compare+0x68/0xd8 __d_lookup_rcu_op_compare+0x178/0x218 __d_lookup_rcu+0x1f8/0x228 d_alloc_parallel+0x150/0x648 lookup_open.isra.0+0x5f0/0x8d0 open_last_lookups+0x264/0x828…
more
path_openat+0x130/0x3f8 do_filp_open+0x114/0x248 do_sys_openat2+0x340/0x3c0 __arm64_sys_openat+0x120/0x1a0 If dentry->d_name.len < EFI_VARIABLE_GUID_LEN , 'guid' can become negative, leadings to oob. The issue can be triggered by parallel lookups using invalid filename: T1 T2 lookup_open ->lookup simple_lookup d_add // invalid dentry is added to hash list lookup_open d_alloc_parallel __d_lookup_rcu __d_lookup_rcu_op_compare hlist_bl_for_each_entry_rcu // invalid dentry can be retrieved ->d_compare efivarfs_d_compare // oob Fix it by checking 'guid' before cmp.
- 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 directly finds out-of-bounds read flaws through static analysis, fuzzing, and dynamic bounds checks.
Secure engineering principles require bounds checking and memory-safe constructs that stop out-of-bounds reads from being introduced.
Process isolation confines the effects of an out-of-bounds read to the compromised process.
Input validation rejects malformed indices or lengths that would otherwise cause reads outside buffer bounds.
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 such as bounds checking and memory-safe languages directly prevent out-of-bounds reads.
Vulnerability scanning and recording can discover instances of out-of-bounds reads after code is deployed.
Routine patching replaces vulnerable code containing out-of-bounds read flaws.
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 includes fuzzing and static analysis that detect out-of-bounds read defects before release.
Logging can record evidence of an out-of-bounds read but does not prevent the weakness itself.
Secure development life cycle mandates input validation and bounds checking that directly prevent out-of-bounds reads.
Application security requirements include explicit bounds and memory-safety specifications that mitigate buffer over-reads.
Secure system architecture and engineering principles require memory-safe design patterns and runtime protections against out-of-bounds access.
Secure coding standards explicitly forbid unsafe pointer arithmetic and mandate bounds-checked reads, eliminating CWE-125.