{"id":"PYSEC-2026-965","summary":" TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions","details":"### Impact\nWhen converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process.\n```python\nimport tensorflow as tf\n\nclass QuantConv2DTransposed(tf.keras.layers.Layer):\n    def build(self, input_shape):\n        self.kernel = self.add_weight(\"kernel\", [3, 3, input_shape[-1], 24])\n\n    def call(self, inputs):\n        filters = tf.quantization.fake_quant_with_min_max_vars_per_channel(\n            self.kernel, -3.0 * tf.ones([24]), 3.0 * tf.ones([24]), narrow_range=True\n        )\n        filters = tf.transpose(filters, (0, 1, 3, 2))\n        return tf.nn.conv2d_transpose(inputs, filters, [*inputs.shape[:-1], 24], 1)\n\ninp = tf.keras.Input(shape=(6, 8, 48), batch_size=1)\nx = tf.quantization.fake_quant_with_min_max_vars(inp, -3.0, 3.0, narrow_range=True)\nx = QuantConv2DTransposed()(x)\nx = tf.quantization.fake_quant_with_min_max_vars(x, -3.0, 3.0, narrow_range=True)\n\nmodel = tf.keras.Model(inp, x)\n\nmodel.save(\"/tmp/testing\")\nconverter = tf.lite.TFLiteConverter.from_saved_model(\"/tmp/testing\")\nconverter.optimizations = [tf.lite.Optimize.DEFAULT]\n\n# terminated by signal SIGSEGV (Address boundary error)\ntflite_model = converter.convert()\n```\n\n### Patches\nWe have patched the issue in GitHub commit [aa0b852a4588cea4d36b74feb05d93055540b450](https://github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450).\n\nThe 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.\n\n\n### For more information\nPlease 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.\n\n\n### Attribution\nThis vulnerability has been reported by Lukas Geiger via [Github issue](https://github.com/tensorflow/tensorflow/issues/53767).\n","aliases":["BIT-tensorflow-2022-36027","CVE-2022-36027","GHSA-79h2-q768-fpxr"],"modified":"2026-07-07T11:56:22.474556691Z","published":"2026-07-07T10:17:18.657225Z","references":[{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxr"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2022-36027"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/issues/53767"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450"},{"type":"PACKAGE","url":"https://github.com/tensorflow/tensorflow"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0"},{"type":"PACKAGE","url":"https://pypi.org/project/tensorflow-gpu"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-79h2-q768-fpxr"}],"affected":[{"package":{"name":"tensorflow-gpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-gpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"},{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3","2.6.4","2.6.5","2.7.0","2.7.0rc0","2.7.0rc1","2.7.1","2.8.0","2.9.0"],"database_specific":{"source":"https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow-gpu/PYSEC-2026-965.yaml"}}],"schema_version":"1.7.5","severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H"}]}