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`
- 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
| Package | Vulnerable | Fixed in |
|---|---|---|
| tensorflow | >= 2.6.0, < 2.6.1 |
2.6.1 |
| tensorflow | >= 2.6.0, < 2.6.1>= 2.7.0rc0, < 2.7.0 |
2.6.12.7.0 |
| 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 |
2.6.12.7.0 |
| 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 |
2.6.12.7.0 |
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
Advisories
Packages
Other links
- github.com/tensorflow/tensorflow/security/advisories/GHSA-gpfh-jvf9-7wg5
- github.com/tensorflow/tensorflow/commit/ca38dab9d3ee66c5de06f11af9a4b1200da5ef75
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-629…
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-827…
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-412.yaml
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why 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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