🛡️ CVE-2021-37639 — tensorflow

🟠 CVSS 8.0 — High ✅ No Known Exploit CWE-125 OSV
8.0
CVSS Score
0 Low4 Medium7 High9 Critical10

Description

Null pointer dereference and heap OOB read in operations restoring tensors

Impact

When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer:

```python

import tensorflow as tf

tf.raw_ops.Restore(

file_pattern=['/tmp'],

tensor_name=[],

default_value=21,

dt=tf.int,

preferred_shard=1)

```

The same undefined behavior can be triggered by tf.raw_ops.RestoreSlice:

```python

import tensorflow as tf

tf.raw_ops.RestoreSlice(

file_pattern=['/tmp'],

tensor_name=[],

shape_and_slice='2',

dt=inp.array([tf.int]),

preferred_shard=1)

```

Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration:

```python

import tensorflow as tf

tf.raw_ops.Restore(

file_pattern=['/tmp'],

tensor_name=['x'],

default_value=21,

dt=tf.int,

preferred_shard=42)

```

The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the tensor_name user controlled input and immediately retrieves the tensor at the restoration index (controlled via preferred_shard argument). This occurs without validating that the provided list has enough values.

If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read.

Patches

We have patched the issue in GitHub commit [9e82dce6e6bd1f36a57e08fa85af213e2b2f2622](https://github.com/tensorflow/tensorflow/commit/9e82dce6e6bd1f36a57e08fa85af213e2b2f2622).

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

For more information

Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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.

How this vulnerability can be exploited

This issue can be reached with local access to the system, attack complexity is low, an attacker needs no privileges on the target. No user interaction is required. Rated impact: confidentiality high, integrity high, availability high.

Weakness class

CVE-2021-37639 is classified as CWE-125: Out-of-bounds Read. The code reads past the limits of a buffer, exposing adjacent memory contents or crashing the process.

Affected software

CVE-2021-37639 is recorded against 3 packages.

  • tensorflow
  • tensorflow-cpu (from 2.5.0 up to 2.5.1)
  • tensorflow-gpu (from 2.5.0 up to 2.5.1)

Timeline and source

Published on 6 March 2024 and last revised on 8 July 2026. No public exploit is currently recorded for this entry. A vendor advisory or fix has been published. Record sourced from OSV.

References

github.com (Web)
github.com (Web)
nvd.nist.gov (Web)

Details

Severity HIGH
CVSS Score 8.0
CVSS Vector CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
CWE CWE-125
Public Exploit ✅ No
Source OSV
Published 2024-03-06
Updated 2026-08-12
Modified 2026-07-08

Affected Packages

Software From version Fixed in
tensorflow
tensorflow-cpu 2.5.0 2.5.1
tensorflow-gpu 2.5.0 2.5.1

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