Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-39689 is a high-severity Use After Free (CWE-416) vulnerability in Linux Linux Kernel. Its CVSS base score is 7.8 (High).
Operationally, 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 SI-16 (Memory Protection) and SA-11 (Developer Testing and Evaluation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-31536
Vulnerability Data
In the Linux kernel, the following vulnerability has been resolved: ftrace: Also allocate and copy hash for reading of filter files Currently the reader of set_ftrace_filter and set_ftrace_notrace just adds the pointer to the global tracer hash to its iterator.…
more
Unlike the writer that allocates a copy of the hash, the reader keeps the pointer to the filter hashes. This is problematic because this pointer is static across function calls that release the locks that can update the global tracer hashes. This can cause UAF and similar bugs. Allocate and copy the hash for reading the filter files like it is done for the writers. This not only fixes UAF bugs, but also makes the code a bit simpler as it doesn't have to differentiate when to free the iterator's hash between writers and readers.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires memory protection mechanisms that prevent use-after-free access to shared kernel hash structures.
Requires developer testing and evaluation that can detect UAF bugs in ftrace filter hash handling before release.
Mandates secure development processes and tools that enforce proper allocation and copying of dynamic kernel data structures.
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 incorporate memory-safety tooling and reviews that prevent most use-after-free defects.
Vulnerability identification processes can discover use-after-free issues via scanning or analysis but do not prevent their introduction.
Routine patching removes known use-after-free instances after they have been introduced in released software.
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 can detect use-after-free bugs before release.
Secure SDLC mandates memory-safety practices that reduce use-after-free defects.
Application security requirements can specify memory-management rules that mitigate use-after-free.
Secure architecture principles include memory-safety design choices that limit use-after-free exposure.
Secure coding standards directly prescribe avoidance of use-after-free patterns.
Change-management processes help ensure memory-safety fixes are deployed consistently.