5.5
CVE-2021-29533
- EPSS 0.02%
- Published 14.05.2021 20:15:12
- Last modified 21.11.2024 06:01:19
- Source security-advisories@github.com
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TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. 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.
Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version < 2.1.4
Google ≫ Tensorflow Version >= 2.2.0 < 2.2.3
Google ≫ Tensorflow Version >= 2.3.0 < 2.3.3
Google ≫ Tensorflow Version >= 2.4.0 < 2.4.2
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
Type | Source | Score | Percentile |
---|---|---|---|
EPSS | FIRST.org | 0.02% | 0.024 |
Source | Base Score | Exploit Score | Impact Score | Vector string |
---|---|---|---|---|
nvd@nist.gov | 5.5 | 1.8 | 3.6 |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
|
nvd@nist.gov | 2.1 | 3.9 | 2.9 |
AV:L/AC:L/Au:N/C:N/I:N/A:P
|
security-advisories@github.com | 2.5 | 1 | 1.4 |
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
|
CWE-754 Improper Check for Unusual or Exceptional Conditions
The product does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the product.