TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize (CVE-2023-25670) | HOL Guard CVE

High · CVSS 7.5CVE-2023-25670GHSA-49RQ-HWC3-X77W

TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize

Answer in brief

CVE-2023-25670 records a High severity (CVSS 7.5) vulnerability in TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize. The current sources do not mark it as known exploited. The current feed maps tensorflow (pypi), tensorflow-cpu (pypi), tensorflow-gpu (pypi). Check affected ranges and fixed versions before updating.

Analysis pending evidence review

HOL Guard separates source facts from reviewed analysis. See the methodology.

Published Mar 24, 2023Updated Sep 10, 2026Source checked Sep 10, 2026First seen by HOL Sep 10, 2026Material review Sep 10, 2026

Upstream Advisory

Key facts

Risk: High · CVSS 7.5
Exploitation: Not marked as known exploited
Affected software: 3 mapped packages or products
Fix availability: Available

Why this deserves its current priority

CVSS is 7.5. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.

Analysis status

Analysis pending evidence review

Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.

Affected scope and exposure questions

The current feed maps tensorflow (pypi), tensorflow-cpu (pypi), tensorflow-gpu (pypi). Check affected ranges and fixed versions before updating.

Mapped affected packages and fixed versions
Package	Affected range	Fixed version
tensorflowpypi	>=0 <2.11.1	2.11.1
tensorflow-cpupypi	>=0 <2.11.1	2.11.1
tensorflow-gpupypi	>=0 <2.11.1	2.11.1

Recommended response

Check inventory. Check lockfiles and deployed manifests for tensorflow, tensorflow-cpu, tensorflow-gpu.
Review the reported fix. Update tensorflow to 2.11.1; tensorflow-cpu to 2.11.1; tensorflow-gpu to 2.11.1 if you use the affected versions. Test the change in a non-production environment first.

Evidence timeline and material changes

Published upstream
Mar 24, 2023
Evidence: source:osv:source_dates:source-dates:record
Source modified
Sep 10, 2026
Evidence: source:osv:source_dates:source-dates:record
First seen by HOL
Sep 10, 2026

Sources and claim methodology

Upstream source description

### Impact NPE in QuantizedMatMulWithBiasAndDequantize with MKL enable ```python import tensorflow as tf func = tf.raw_ops.QuantizedMatMulWithBiasAndDequantize para={'a': tf.constant(138, dtype=tf.quint8), 'b': tf.constant(4, dtype=tf.qint8), 'bias': [[31.81644630432129, 47.21876525878906], [109.95201110839844, 152.07968139648438]], 'min_a': 141.5337138686371, 'max_a': [73.84139251708984, 173.15280151367188], 'min_b': [], 'max_b': [[16.128345489501953, 193.26820373535156]], 'min_freezed_output': [], 'max_freezed_output': [115.50032806396484, 156.974853515625], 'Toutput': 1.0, 'transpose_a': True, 'transpose_b': False, 'input_quant_mode': 'MIN_FIRST'} func(**para) ``` ### Patches We have patched the issue in GitHub commit [8a47a39d9697969206d23a523c977238717e8727](https://github.com/tensorflow/tensorflow/commit/8a47a39d9697969206d23a523c977238717e8727). The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1 ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by r3pwnx

Quoted source text, attributed separately from HOL analysis.