Security Resilience

CVE-2023-31031

Memory Safety in Nvidia Dgx A100 Firmware ≤ 1.25

Published
12 January 2024
Modified
09 October 2025
Patch / advisory
CVSS Score v3.1 4.2
Click a component to see what it means
Raw vectorCVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L
EPSS Score 0.0019 8th percentile
Risk Priority 33 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2023-31031 is a medium-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Nvidia Dgx A100 Firmware. Its CVSS base score is 4.2 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Data Obfuscation (T1001); ranked at the 8th 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 SI-10 (Information Input Validation) — see the control section below for these in your framework.

EU & UK References

Vulnerability Data

NVIDIA DGX Station A100 and DGX Station A800 SBIOS contains a vulnerability where a user may cause a heap-based buffer overflow by local access. A successful exploit of this vulnerability may lead to code execution, denial of service, information disclosure,…

more

and data tampering.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1001 Data Obfuscation Command And Control
Adversaries may obfuscate command and control traffic to make it more difficult to detect.
T1001.002 Steganography Command And Control
Adversaries may use steganographic techniques to hide command and control traffic to make detection efforts more difficult.
T1003.001 LSASS Memory Credential Access
Adversaries may attempt to access credential material stored in the process memory of the Local Security Authority Subsystem Service (LSASS).
T1003.002 Security Account Manager Credential Access
Adversaries may attempt to extract credential material from the Security Account Manager (SAM) database either through in-memory techniques or through the Windows Registry where the SAM database is stored.
T1003.004 LSA Secrets Credential Access
Adversaries with SYSTEM access to a host may attempt to access Local Security Authority (LSA) secrets, which can contain a variety of different credential materials, such as credentials for service accounts.
T1003.006 DCSync Credential Access
Adversaries may attempt to access credentials and other sensitive information by abusing a Windows Domain Controller's application programming interface (API)(Citation: Microsoft DRSR Dec 2017) (Citation: Microsoft GetNCCChanges) (Citati…
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-0199Same vendor: Nvidia
CVE-2023-0200Same vendor: Nvidia
CVE-2023-0201Same vendor: Nvidia
CVE-2023-25506Same vendor: Nvidia
CVE-2023-25528Same vendor: Nvidia
CVE-2023-0208Same vendor: Nvidia
CVE-2026-24272Same vendor: Nvidia
CVE-2026-24268Same vendor: Nvidia
CVE-2026-24180Same vendor: Nvidia
CVE-2023-0182Same vendor: Nvidia

Affected Assets

nvidia
dgx a100 firmware
≤ 1.25

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.4.1

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation (including fuzzing and memory-error detectors) can discover heap overflows after they have been coded.

Input validation enforces bounds checking on data written to heap buffers, directly stopping the overflow condition from being introduced.

Requiring documented secure-development standards and tools can mandate bounds-checked coding practices that avoid the weakness.

Security engineering principles require use of memory-safe constructs and bounds-checked allocation routines that avoid introducing heap overflows.

Memory-protection mechanisms limit the ability of a heap overflow to execute attacker-controlled code or corrupt adjacent 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.

ID.RA-01 partial match
blocks

Vulnerability scanning and recording can discover heap-overflow flaws but does not prevent their introduction in code.

PR.PS-02 partial match
blocks

Timely patching removes known heap-overflow instances after they exist.

PR.PS-06 partial match
blocks

Secure-development practices directly require bounds checking and safe memory handling that prevent heap overflows.

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.

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References