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GHSA-cwv3-863g-39vx BIT-tensorflow-2021-29591 CVE-2021-29591 PYSEC-2021-228 PYSEC-2021-519 PYSEC-2021-717

Stack overflow due to looping TFLite subgraph

High PyPI
Severity
0.0 / 10
High · CVSS 4.0
Exploit chance (EPSS)
0.26%
Chance of exploitation in the next 30 days. Higher than 18.08% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-674 Uncontrolled Recursion
CWE-835 Loop with Unreachable Exit Condition ('Infinite Loop')
Fix
Available
3 packages have a fixed version

Description

Impact

TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls.

For example, the While implementation could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the Eval function for the other and this quickly exhaust all stack space.

Patches

We have patched the issue in GitHub commit 9c1dc920d8ffb4893d6c9d27d1f039607b326743 (for the While operator) and in GitHub commit c6173f5fe66cdbab74f4f869311fe6aae2ba35f4 (in general).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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.

Attribution

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

Affected versions

PyPI

PackageVulnerableFixed in
tensorflow
< 2.1.4
2.1.4
tensorflow
>= 2.2.0, < 2.2.3
2.2.3
tensorflow
>= 2.3.0, < 2.3.3
2.3.3
tensorflow
>= 2.4.0, < 2.4.2
2.4.2
tensorflow
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
2.1.4
2.2.3
2.3.3
2.4.2
tensorflow-cpu
< 2.1.4
2.1.4
tensorflow-cpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-cpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-cpu
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-cpu
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
2.1.4
2.2.3
2.3.3
2.4.2
tensorflow-gpu
< 2.1.4
2.1.4
tensorflow-gpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-gpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-gpu
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-gpu
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
2.1.4
2.2.3
2.3.3
2.4.2

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 → 2.1.4

pip
pip install --upgrade "tensorflow>=2.1.4"
poetry
poetry add "tensorflow>=2.1.4"
uv
uv add "tensorflow>=2.1.4"

tensorflow-cpu PyPI → 2.1.4

pip
pip install --upgrade "tensorflow-cpu>=2.1.4"
poetry
poetry add "tensorflow-cpu>=2.1.4"
uv
uv add "tensorflow-cpu>=2.1.4"

tensorflow-gpu PyPI → 2.1.4

pip
pip install --upgrade "tensorflow-gpu>=2.1.4"
poetry
poetry add "tensorflow-gpu>=2.1.4"
uv
uv add "tensorflow-gpu>=2.1.4"

Severity breakdown

CVSS 4.0 0.0

CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:L/VA:H/SC:N/SI:N/SA:N

Attack vector
Local
Attack complexity
Low
Attack requirements
None
Privileges required
Low
User interaction
None
Confidentiality (vulnerable system)
High
Integrity (vulnerable system)
Low
Availability (vulnerable system)
High
Confidentiality (subsequent systems)
None
Integrity (subsequent systems)
None
Availability (subsequent systems)
None

CVSS 3.1 7.3

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

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

Weakness

CWE-674: Uncontrolled Recursion

The product does not properly control the amount of recursion that takes place, consuming excessive resources, such as allocated memory or the program stack.

How to prevent it
  • Implementation: Ensure that an end condition will be reached under all logic conditions. The end condition may include checking against the depth of recursion and exiting with an error if the recursion goes too deep. The complexity of the end condition contributes to the effectiveness of this action.
  • Implementation: Increase the stack size.

CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop')

The product contains an iteration or loop with an exit condition that cannot be reached, i.e., an infinite loop.

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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