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GHSA-gjqc-q9g6-q2j3 BIT-tensorflow-2022-23583 CVE-2022-23583 PYSEC-2022-147 PYSEC-2022-92 PYSEC-2026-3191

`CHECK`-failures in binary ops in Tensorflow

Medium PyPI
Severity
6.5 / 10
Medium · CVSS 3.1
Exploit chance (EPSS)
0.88%
Chance of exploitation in the next 30 days. Higher than 59.08% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-617 Reachable Assertion
CWE-843 Access of Resource Using Incompatible Type ('Type Confusion')
Fix
Available
3 packages have a fixed version

Description

Impact

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:

functor::BinaryFunctor<Device, Functor, 1>()(
    eigen_device, out->template flat<Tout>(),
    input_0.template flat<Tin>(), input_1.template flat<Tin>(),
    error_ptr);

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.

Patches

We have patched the issue in GitHub commit a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9. 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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Affected versions

PyPI

PackageVulnerableFixed in
tensorflow
< 2.5.3
2.5.3
tensorflow
>= 2.6.0, < 2.6.3
2.6.3
tensorflow
>= 2.7.0, < 2.7.1
2.7.1
tensorflow
< 2.5.3
>= 2.6.0, < 2.6.3
>= 2.7.0, < 2.7.1
2.5.3
2.6.3
2.7.1
tensorflow-cpu
< 2.5.3
2.5.3
tensorflow-cpu
>= 2.6.0, < 2.6.3
2.6.3
tensorflow-cpu
>= 2.7.0, < 2.7.1
2.7.1
tensorflow-cpu
< 2.5.3
>= 2.6.0, < 2.6.3
2.5.3
2.6.3
tensorflow-gpu
< 2.5.3
2.5.3
tensorflow-gpu
>= 2.6.0, < 2.6.3
2.6.3
tensorflow-gpu
>= 2.7.0, < 2.7.1
2.7.1
tensorflow-gpu
< 2.5.3
>= 2.6.0, < 2.6.3
2.5.3
2.6.3

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

tensorflow PyPI → 2.5.3

pip
pip install --upgrade "tensorflow>=2.5.3"
poetry
poetry add "tensorflow>=2.5.3"
uv
uv add "tensorflow>=2.5.3"

tensorflow-cpu PyPI → 2.5.3

pip
pip install --upgrade "tensorflow-cpu>=2.5.3"
poetry
poetry add "tensorflow-cpu>=2.5.3"
uv
uv add "tensorflow-cpu>=2.5.3"

tensorflow-gpu PyPI → 2.5.3

pip
pip install --upgrade "tensorflow-gpu>=2.5.3"
poetry
poetry add "tensorflow-gpu>=2.5.3"
uv
uv add "tensorflow-gpu>=2.5.3"

Severity breakdown

CVSS 3.1 6.5

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

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-617: Reachable Assertion

The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.

How to prevent it
  • Implementation: Make sensitive open/close operation non reachable by directly user-controlled data (e.g. open/close resources)
  • Implementation: Perform input validation on user data.

CWE-843: Access of Resource Using Incompatible Type ('Type Confusion')

The product allocates or initializes a resource such as a pointer, object, or variable using one type, but it later accesses that resource using a type that is incompatible with the original type.

References

Advisories

Packages

Other links

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-gjh7-xx4r-x345
TensorFlow has segfault in array_ops.upper_bound
High Also affects tensorflow
GHSA-fxgc-95xx-grvq
TensorFlow Denial of Service vulnerability
Medium Also affects tensorflow
GHSA-93vr-9q9m-pj8p
TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
High Also affects tensorflow
GHSA-qjqc-vqcf-5qvj
TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
High Also affects tensorflow
GHSA-7jvm-xxmr-v5cw
TensorFlow vulnerable to integer overflow in EditDistance
High Also affects tensorflow
GHSA-64jg-wjww-7c5w
TensorFlow has Null Pointer Error in TensorArrayConcatV2
High Also affects tensorflow
GHSA-6hg6-5c2q-7rcr
TensorFlow has Heap-buffer-overflow in AvgPoolGrad
High Also affects tensorflow
GHSA-558h-mq8x-7q9g
TensorFlow has Null Pointer Error in SparseSparseMaximum
High Also affects tensorflow
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