Google TensorFlow up to 2.1.3/2.2.2/2.3.2/2.4.1 quantized_batch_norm_op.cc divide by zero
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.1 | $0-$5k | 0.00 |
Summary
A vulnerability was found in Google TensorFlow up to 2.1.3/2.2.2/2.3.2/2.4.1. It has been rated as problematic. This issue affects the function tf.raw_ops.QuantizedBatchNormWithGlobalNormalization of the file core/kernels/quantized_batch_norm_op.cc. The manipulation leads to divide by zero.
This vulnerability is documented as CVE-2021-29548. The attack can be initiated remotely. There is not any exploit available.
To fix this issue, it is recommended to deploy a patch.
Details
A vulnerability was found in Google TensorFlow up to 2.1.3/2.2.2/2.3.2/2.4.1 (Artificial Intelligence Software) and classified as problematic. This issue affects the function tf.raw_ops.QuantizedBatchNormWithGlobalNormalization of the file core/kernels/quantized_batch_norm_op.cc. The manipulation with an unknown input leads to a divide by zero vulnerability. Using CWE to declare the problem leads to CWE-369. The product divides a value by zero. Impacted is availability.
The weakness was released 05/15/2021. It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2021-29548. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit. The attack technique deployed by this issue is T1499 according to MITRE ATT&CK.
Upgrading to version 2.1.4, 2.2.3, 2.3.3, 2.4.2 or 2.5.0 eliminates this vulnerability. Applying a patch is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be patching the affected component.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Type
Vendor
Name
Version
License
Website
- Vendor: https://www.google.com/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 4.3VulDB Meta Temp Score: 4.1
VulDB Base Score: 4.3
VulDB Temp Score: 4.1
VulDB Vector: 🔍
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
Exploiting
Class: Divide by zeroCWE: CWE-369 / CWE-404
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: PatchStatus: 🔍
0-Day Time: 🔍
Upgrade: TensorFlow 2.1.4/2.2.3/2.3.3/2.4.2/2.5.0
Patch: github.com
Timeline
03/30/2021 🔍05/15/2021 🔍
05/15/2021 🔍
05/16/2021 🔍
Sources
Vendor: google.comAdvisory: github.com
Status: Confirmed
Confirmation: 🔍
CVE: CVE-2021-29548 (🔍)
GCVE (CVE): GCVE-0-2021-29548
GCVE (VulDB): GCVE-100-175091
Entry
Created: 05/15/2021 08:00Updated: 05/16/2021 15:02
Changes: 05/15/2021 08:00 (41), 05/16/2021 14:58 (6), 05/16/2021 15:02 (1)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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