Cyber Resilience

CVE-2023-33976

Memory Safety in Google Tensorflow ≤ 2.13.0

Published
30 July 2024
Modified
21 November 2024
Patch / advisory
CVSS Score v3.1 7.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0043 35th percentile
Risk Priority 57 floored blend · peak EPSS

Summary

CVE-2023-33976 is a high-severity Integer Overflow or Wraparound (CWE-190) vulnerability in Google Tensorflow. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 35th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Deep Learning Frameworks.

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

Vulnerability Data

TensorFlow is an end-to-end open source platform for machine learning. `array_ops.upper_bound` causes a segfault when not given a rank 2 tensor. The fix will be included in TensorFlow 2.13 and will also cherrypick this commit on TensorFlow 2.12.

CWE(s)

AI Security AnalysisAI

AI Category
Deep Learning Frameworks
Risk Domain
N/A
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: tensorflow, machine learning, tensorflow, tensorflow

Related Threats

MITRE ATT&CK Enterprise Techniques

T1068 Exploitation for Privilege Escalation Privilege Escalation
Adversaries may exploit software vulnerabilities in an attempt to elevate privileges.
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1203 Exploitation for Client Execution Execution
Adversaries may exploit software vulnerabilities in client applications to execute code.
T1210 Exploitation of Remote Services Lateral Movement
Adversaries may exploit remote services to gain unauthorized access to internal systems once inside of a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-25667Same product: Google Tensorflow
CVE-2023-25662Same product: Google Tensorflow
CVE-2023-25661Same product: Google Tensorflow
CVE-2023-25664Same product: Google Tensorflow
CVE-2023-25668Same product: Google Tensorflow
CVE-2023-25659Same product: Google Tensorflow
CVE-2023-25658Same product: Google Tensorflow
CVE-2023-25671Same product: Google Tensorflow
CVE-2023-25801Same product: Google Tensorflow
CVE-2023-25673Same product: Google Tensorflow

Affected Assets

google
tensorflow
≤ 2.13.0

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)
  • V5.2.6

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation (static analysis, fuzzing, unit tests) directly finds integer overflow defects before deployment.

Secure engineering principles require use of safe arithmetic constructs or language features that structurally eliminate integer overflow during calculation.

Input validation enforces bounds on values before arithmetic, stopping the conditions that trigger overflow or wraparound.

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.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly require use of safe arithmetic, bounds checks, and testing that prevent integer 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.

finds

Security testing in development can detect integer overflows before release.

prevents

Secure SDLC mandates input validation and arithmetic checks that prevent integer overflows.

degrades

Application security requirements include bounds checking and safe arithmetic to avoid overflow conditions.

degrades

Secure architecture principles require defensive coding patterns that mitigate integer wraparound risks.

prevents

Secure coding standards explicitly forbid unsafe integer operations and mandate overflow-safe constructs.

References