TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr`
Impact
When mlir::tfg::TFOp::nameAttr receives null type list attributes, it crashes.
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 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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Affected software
Click a technology to see all vulnerabilities affecting it.
| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
| Python (PyPI) | tensorflow-cpu | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
| Python (PyPI) | tensorflow-gpu | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7j3m-8g3c-9qqq
- https://nvd.nist.gov/vuln/detail/CVE-2022-36014
- https://github.com/tensorflow/tensorflow/commit/3a754740d5414e362512ee981eefba41561a63a6
- https://github.com/tensorflow/tensorflow/commit/a0f0b9a21c9270930457095092f558fbad4c03e5
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ir/importexport/graphdef_import.cc
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
- https://pypi.org/project/tensorflow
- https://github.com/advisories/GHSA-7j3m-8g3c-9qqq
- https://pypi.org/project/tensorflow-cpu
- https://pypi.org/project/tensorflow-gpu
- CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-476- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 16.09.2022
- Updated
- 11.10.2026 14:18
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2026-3129 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3292 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-7j3m-8g3c-9qqq - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-966 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: tensorflow
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 433
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 112
- Medium 210
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr` this entry
Know which vulnerabilities affect your application
With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.