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🛡️ CVE-2022-23575 — tensorflow

🟠 CVSS 8.0 — High ⚠️ Exploit Public CWE-190 OSV
8.0
CVSS Score
0 Low4 Medium7 High9 Critical10

Description

Integer overflow in Tensorflow

Impact

The [implementation of OpLevelCostEstimator::CalculateTensorSize](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558) is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:

```cc

int64_t OpLevelCostEstimator::CalculateTensorSize(

const OpInfo::TensorProperties& tensor, bool* found_unknown_shapes) {

int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);

int size = DataTypeSize(BaseType(tensor.dtype()));

VLOG(2) << "Count: " << count << " DataTypeSize: " << size;

return count * size;

}

```

Here, count and size can be large enough to cause count * size to overflow.

Patches

We have patched the issue in GitHub commit [fcd18ce3101f245b083b30655c27b239dc72221e](https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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-2022-23575 is classified as CWE-190: Integer Overflow or Wraparound. Arithmetic produces a value too large for its type and wraps around, so a later size or bounds check passes when it should not.

Affected software

CVE-2022-23575 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-190: Integer Overflow or Wraparound) 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-190
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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