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CVE-2021-29533

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.

Published

2021-05-14T20:15:12.120

Last Modified

2024-11-21T06:01:19.577

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 2.5 (LOW)

CVSSv2 Vector

AV:L/AC:L/Au:N/C:N/I:N/A:P

  • Access Vector: LOCAL
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

3.9

Impact Score

2.9

Weaknesses
  • Type: Primary
    CWE-754
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.1.4 Yes
Application google tensorflow < 2.2.3 Yes
Application google tensorflow < 2.3.3 Yes
Application google tensorflow < 2.4.2 Yes
References