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🛡️ CVE-2022-23570 — tensorflow

🟠 CVSS 8.0 — High ⚠️ Exploit Public CWE-476 OSV
8.0
CVSS Score
0 Low4 Medium7 High9 Critical10

Description

Null-dereference in Tensorflow

Impact

When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is [guarded by a DCHECK](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L104-L106):

```cc

const auto* attr = attrs.Find(arg->s());

DCHECK(attr != nullptr);

if (attr->value_case() == AttrValue::kList) {

// ...

}

```

However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure.

Patches

We have patched the issue in GitHub commit [8a513cec4bec15961fbfdedcaa5376522980455c](https://github.com/tensorflow/tensorflow/commit/8a513cec4bec15961fbfdedcaa5376522980455c).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.

How this vulnerability can be exploited

This issue can be reached over the network, attack complexity is low, an attacker needs low-level privileges on the target. No user interaction is required. Rated impact: confidentiality none, integrity none, availability high.

CVSS metrics in full

The score comes from this vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

  • Attack vector: Network — reachable from anywhere that can route to the service.
  • Attack complexity: Low — the attack works reliably, with no preparation.
  • Attack requirements: None — no deployment-specific condition has to hold.
  • Privileges required: Low — an ordinary user account is enough.
  • User interaction: None — nobody has to be tricked into anything.
  • Confidentiality impact: None.
  • Integrity impact: None.
  • Availability impact: High — total loss, or loss the attacker controls.

Weakness class

CVE-2022-23570 is classified as CWE-476: NULL Pointer Dereference. A pointer that can be null is used without a check, crashing the process.

Affected software

CVE-2022-23570 is recorded against 3 packages.

  • tensorflow (from 2.7.0 up to 2.7.1)
  • tensorflow-cpu (from 2.6.0 up to 2.6.3)
  • tensorflow-gpu (from 2.6.0 up to 2.6.3)

Timeline and source

Published on 9 July 2026 and last revised on 13 July 2026. A public exploit is known to exist, which raises the urgency of patching considerably. A vendor advisory or fix has been published. Record sourced from OSV.

References

github.com (Web)
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Web)
github.com (Web)
github.com (Web)
github.com (Web)
pypi.org (Package)
github.com (Advisory)

Other advisories for this package

tensorflow has other advisories on record. If you are patching this one, these are worth checking on the same host:

Same weakness in other software

These advisories are the same class of weakness (CWE-476: NULL Pointer Dereference) in other software:

Details

Severity MEDIUM
CVSS Score 8.0
CVSS Vector CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CWE CWE-476
Public Exploit ⚠️ Yes
Source OSV
Published 2026-07-09
Updated 2026-08-20
Modified 2026-07-13

Affected Packages

Software From version Fixed in
tensorflow 2.7.0 2.7.1
tensorflow-cpu 2.6.0 2.6.3
tensorflow-gpu 2.6.0 2.6.3

Similar Threats

Exploit Protection

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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.

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