CVE-2021-29547 - CVE House
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Status published Low CVE-2021-29547

Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`

Vulnerability Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Impact Analysis

Refer to official advisory for detailed impact metrics.

Remediation

Ensure systems are updated to the latest vendor-supplied patch levels.

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Credits & Attribution

No credits recorded in the NVD database.

References

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Affected Vendor

Affected Software

tensorflow
Vulnerable Versions:
< 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2

Timeline

Official Publish: May 14th, 2021
Last Modified: August 3rd, 2024
Added to House: July 21st, 2026

CVSS Vectors

V3: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Weaknesses (CWE)

CWE-125

MITRE ATT&CK TTPs

T1190 Exploit Public-Facing Application
Initial Access
T1213 Data from Information Repositories
Collection
T1003 OS Credential Dumping
Credential Access
T1552 Unsecured Credentials
Credential Access