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.

• CVE ID
• CVE-2022-23583

• Assigner
• security-advisories@github.com

• Vulnerability Status
• Analyzed

• Published Version
• 2022-02-04T23:15:14

• Last Modified Date
• 2022-02-10T17:15:47

• Version
• 2.0

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

• Access Vector
• NETWORK

• Access Compatibility
• LOW

• Authentication
• SINGLE

• Confidentiality Impact
• NONE

• Integrity Impact
• NONE

• Availability Impact
• PARTIAL

• Base Score
• 4

• Severity
• MEDIUM

• Exploitability Score
• 8

• Impact Score
• 2.9

• Version
• 3.1

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

• Attack Vector
• NETWORK

• Attack Compatibility
• LOW

• Privileges Required
• LOW

• User Interaction
• NONE

• Scope
• UNCHANGED

• Confidentiality Impact
• NONE

• Availability Impact
• HIGH

• Base Score
• 6.5

• Base Severity
• MEDIUM

• Exploitability Score
• 2.8

• Impact Score
• 3.6