Vulnerability Monitor

The vendors, products, and vulnerabilities you care about

CVE-2022-23583


Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.


Published

2022-02-04T23:15:14.820

Last Modified

2024-11-21T06:48:51.923

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 6.5 (MEDIUM)

CVSSv2 Vector

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

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

8.0

Impact Score

2.9

Weaknesses
  • Type: Secondary
    CWE-617
  • Type: Primary
    CWE-843

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow ≤ 2.5.2 Yes
Application google tensorflow ≤ 2.6.2 Yes
Application google tensorflow 2.7.0 Yes

References