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CVE-2022-36014

MEDIUM
Published 2022-09-16T22:35:11.000Z
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CVSS Score

V3.1
5.9
/10
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.003
probability
of exploitation in the wild

There is a 0.3% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.521
Higher than 52.1% of all CVEs

Attack Vector Metrics

Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
NONE
Integrity
NONE
Availability
HIGH

Description

TensorFlow is an open source platform for machine learning. When `mlir::tfg::TFOp::nameAttr` receives null type list attributes, it crashes. We have patched the issue in GitHub commits 3a754740d5414e362512ee981eefba41561a63a6 and a0f0b9a21c9270930457095092f558fbad4c03e5. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Understanding This Vulnerability

This Common Vulnerabilities and Exposures (CVE) entry provides detailed information about a security vulnerability that has been publicly disclosed. CVEs are standardized identifiers assigned by MITRE Corporation to track and catalog security vulnerabilities across software and hardware products.

The severity rating (MEDIUM) indicates the potential impact of this vulnerability based on the CVSS (Common Vulnerability Scoring System) framework. Higher severity ratings typically indicate vulnerabilities that could lead to more significant security breaches if exploited. Security teams should prioritize remediation efforts based on severity, exploit availability, and the EPSS (Exploit Prediction Scoring System) score, which predicts the likelihood of exploitation in the wild.

If this vulnerability affects products or systems in your infrastructure, we recommend reviewing the affected products section, checking for available patches or updates from vendors, and implementing recommended workarounds or solutions until a permanent fix is available. Organizations should also monitor security advisories and threat intelligence feeds for updates about active exploitation of this vulnerability.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

References

EU Vulnerability Database

Monitored by ENISA for EU cybersecurity

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed MODERATE

TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr`

GHSA-7j3m-8g3c-9qqq

Advisory Details

### Impact When [`mlir::tfg::TFOp::nameAttr`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ir/importexport/graphdef_import.cc) receives null type list attributes, it crashes. ```cpp StatusOr<unsigned> GraphDefImporter::ArgNumType(const NamedAttrList &attrs, const OpDef::ArgDef &arg_def, SmallVectorImpl<Type> &types) { // Check whether a type list attribute is specified. if (!arg_def.type_list_attr().empty()) { if (auto v = attrs.get(arg_def.type_list_attr()).dyn_cast<ArrayAttr>()) { for (Attribute attr : v) { if (auto dtype = attr.dyn_cast<TypeAttr>()) { types.push_back(UnrankedTensorType::get(dtype.getValue())); } else { return InvalidArgument("Expected '", arg_def.type_list_attr(), "' to be a list of types"); } } return v.size(); } return NotFound("Type attr not found: ", arg_def.type_list_attr()); } unsigned num = 1; // Check whether a number attribute is specified. if (!arg_def.number_attr().empty()) { if (auto v = attrs.get(arg_def.number_attr()).dyn_cast<IntegerAttr>()) { num = v.getValue().getZExtValue(); } else { return NotFound("Type attr not found: ", arg_def.number_attr()); } } // Check for a type or type attribute. Type dtype; if (arg_def.type() != DataType::DT_INVALID) { TF_RETURN_IF_ERROR(ConvertDataType(arg_def.type(), b_, &dtype)); } else if (arg_def.type_attr().empty()) { return InvalidArgument("Arg '", arg_def.name(), "' has invalid type and no type attribute"); } else { if (auto v = attrs.get(arg_def.type_attr()).dyn_cast<TypeAttr>()) { dtype = v.getValue(); } else { return NotFound("Type attr not found: ", arg_def.type_attr()); } } types.append(num, UnrankedTensorType::get(dtype)); return num; } ``` ### Patches We have patched the issue in GitHub commits [3a754740d5414e362512ee981eefba41561a63a6](https://github.com/tensorflow/tensorflow/commit/3a754740d5414e362512ee981eefba41561a63a6) and [a0f0b9a21c9270930457095092f558fbad4c03e5](https://github.com/tensorflow/tensorflow/commit/a0f0b9a21c9270930457095092f558fbad4c03e5). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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.

Affected Packages

PyPI tensorflow
ECOSYSTEM: ≥0 <2.7.2
PyPI tensorflow
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow
ECOSYSTEM: ≥2.9.0 <2.9.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥0 <2.7.2
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.9.0 <2.9.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥0 <2.7.2
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.9.0 <2.9.1

CVSS Scoring

CVSS Score

5.0

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: September 16, 2022, Modified: September 19, 2022

References

Published: 2022-09-16T22:35:11.000Z
Last Modified: 2025-04-23T16:59:17.921Z
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