Out of bounds read in Tensorflow
CVE-2022-21728

8.1HIGH

Key Information:

Vendor
Google
Vendor
CVE Published:
3 February 2022

Badges

πŸ‘Ύ Exploit Exists🟑 Public PoC

Summary

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ReverseSequence does not fully validate the value of batch_dim and can result in a heap OOB read. There is a check to make sure the value of batch_dim does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of Dim would access elements before the start of an array. 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.

Exploit Proof of Concept (PoC)

PoC code is written by security researchers to demonstrate the vulnerability can be exploited. PoC code is also a key component for weaponization which could lead to ransomware.

References

CVSS V3.1

Score:
8.1
Severity:
HIGH
Confidentiality:
High
Integrity:
None
Availability:
High
Attack Vector:
Network
Attack Complexity:
Low
Privileges Required:
Low
User Interaction:
None
Scope:
Unchanged

Timeline

  • 🟑

    Public PoC available

  • πŸ‘Ύ

    Exploit known to exist

  • Vulnerability published

  • Vulnerability Reserved

Collectors

NVD DatabaseMitre Database1 Proof of Concept(s)
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