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GHSA-gpfh-jvf9-7wg5 BIT-tensorflow-2021-41220 CVE-2021-41220 PYSEC-2021-412 PYSEC-2021-629 PYSEC-2021-827

Use after free / memory leak in `CollectiveReduceV2`

High PyPI
Severity
7.8 / 10
High · CVSS 3.1
Exploit chance (EPSS)
0.21%
Chance of exploitation in the next 30 days. Higher than 11.33% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-416 Use After Free
Fix
Available
3 packages have a fixed version

Description

Impact

The async implementation of CollectiveReduceV2 suffers from a memory leak and a use after free:

import tensorflow as tf
  
tf.raw_ops.CollectiveReduceV2(
  input=[],
  group_size=[-10, -10, -10],
  group_key=[-10, -10],
  instance_key=[-10],
  ordering_token=[],
  merge_op='Mul',
  final_op='Div')

This occurs due to the asynchronous computation and the fact that objects that have been std::move()d from are still accessed:

auto done_with_cleanup = [col_params, done = std::move(done)]() {
  done();
  col_params->Unref();
};
OP_REQUIRES_OK_ASYNC(c,
                     FillCollectiveParams(col_params, REDUCTION_COLLECTIVE,
                                          /*group_size*/ c->input(1),
                                          /*group_key*/ c->input(2),
                                          /*instance_key*/ c->input(3)),
                     done);

Here, done is already moved from by the time OP_REQUIRES_OK_ASYNC macro needs to invoke it in case of errors. In this case, we get an undefined behavior, which can manifest via crashes, std::bad_alloc throws or just memory leaks.

Patches

We have patched the issue in GitHub commit ca38dab9d3ee66c5de06f11af9a4b1200da5ef75.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

For more information

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

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Affected versions

PyPI

PackageVulnerableFixed in
tensorflow
>= 2.6.0, < 2.6.1
2.6.1
tensorflow
>= 2.6.0, < 2.6.1
>= 2.7.0rc0, < 2.7.0
2.6.1
2.7.0
tensorflow-cpu
>= 2.6.0, < 2.6.1
2.6.1
tensorflow-cpu
>= 2.6.0, < 2.6.1
>= 2.7.0rc0, < 2.7.0
2.6.1
2.7.0
tensorflow-gpu
>= 2.6.0, < 2.6.1
2.6.1
tensorflow-gpu
>= 2.6.0, < 2.6.1
>= 2.7.0rc0, < 2.7.0
2.6.1
2.7.0

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 → 2.6.1

pip
pip install --upgrade "tensorflow>=2.6.1"
poetry
poetry add "tensorflow>=2.6.1"
uv
uv add "tensorflow>=2.6.1"

tensorflow-cpu PyPI → 2.6.1

pip
pip install --upgrade "tensorflow-cpu>=2.6.1"
poetry
poetry add "tensorflow-cpu>=2.6.1"
uv
uv add "tensorflow-cpu>=2.6.1"

tensorflow-gpu PyPI → 2.6.1

pip
pip install --upgrade "tensorflow-gpu>=2.6.1"
poetry
poetry add "tensorflow-gpu>=2.6.1"
uv
uv add "tensorflow-gpu>=2.6.1"

Severity breakdown

CVSS 3.1 7.8

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

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

Weakness

CWE-416: Use After Free

The product reuses or references memory after it has been freed. At some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. Any operations using the original pointer are no longer valid because the memory "belongs" to the code that operates on the new pointer.

How to prevent it
  • Architecture and Design: Choose a language that provides automatic memory management.
  • Implementation: When freeing pointers, be sure to set them to NULL once they are freed. However, the utilization of multiple or complex data structures may lower the usefulness of this strategy.

References

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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