CVE-2022-31606

NVIDIA GPU Display Driver for Windows contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape, where a failure to properly validate data might allow an attacker with basic user capabilities to cause an out-of-bounds access in kernel mode, which could lead to denial of service, information disclosure, escalation of privileges, or data tampering.

Weakness

The product writes data past the end, or before the beginning, of the intended buffer.

Affected Software

Potential Mitigations

• Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

• For example, many languages that perform their own memory management, such as Java and Perl, are not subject to buffer overflows. Other languages, such as Ada and C#, typically provide overflow protection, but the protection can be disabled by the programmer.

• Be wary that a language’s interface to native code may still be subject to overflows, even if the language itself is theoretically safe.

• Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

• Examples include the Safe C String Library (SafeStr) by Messier and Viega [REF-57], and the Strsafe.h library from Microsoft [REF-56]. These libraries provide safer versions of overflow-prone string-handling functions.

• Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index checking.

• D3-SFCV (Stack Frame Canary Validation) from D3FEND [REF-1334] discusses canary-based detection in detail.

• Consider adhering to the following rules when allocating and managing an application’s memory:

• Run or compile the software using features or extensions that randomly arrange the positions of a program’s executable and libraries in memory. Because this makes the addresses unpredictable, it can prevent an attacker from reliably jumping to exploitable code.

• Examples include Address Space Layout Randomization (ASLR) [REF-58] [REF-60] and Position-Independent Executables (PIE) [REF-64]. Imported modules may be similarly realigned if their default memory addresses conflict with other modules, in a process known as “rebasing” (for Windows) and “prelinking” (for Linux) [REF-1332] using randomly generated addresses. ASLR for libraries cannot be used in conjunction with prelink since it would require relocating the libraries at run-time, defeating the whole purpose of prelinking.

• For more information on these techniques see D3-SAOR (Segment Address Offset Randomization) from D3FEND [REF-1335].

• Use a CPU and operating system that offers Data Execution Protection (using hardware NX or XD bits) or the equivalent techniques that simulate this feature in software, such as PaX [REF-60] [REF-61]. These techniques ensure that any instruction executed is exclusively at a memory address that is part of the code segment.

• For more information on these techniques see D3-PSEP (Process Segment Execution Prevention) from D3FEND [REF-1336].

References

• https://nvidia.custhelp.com/app/answers/detail/a_id/5383