{"url":"http://public2.vulnerablecode.io/api/packages/500402?format=json","purl":"pkg:pypi/tflite@1.15.0.post1","type":"pypi","namespace":"","name":"tflite","version":"1.15.0.post1","qualifiers":{},"subpath":"","is_vulnerable":true,"next_non_vulnerable_version":null,"latest_non_vulnerable_version":null,"affected_by_vulnerabilities":[{"url":"http://public2.vulnerablecode.io/api/vulnerabilities/7481?format=json","vulnerability_id":"VCID-b8d3-rvxx-xfhf","summary":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","references":[{"reference_url":"https://api.first.org/data/v1/epss?cve=CVE-2021-37689","reference_id":"","reference_type":"","scores":[{"value":"0.00013","scoring_system":"epss","scoring_elements":"0.02011","published_at":"2026-05-29T12:55:00Z"}],"url":"https://api.first.org/data/v1/epss?cve=CVE-2021-37689"},{"reference_url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-602.yaml","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-602.yaml"},{"reference_url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-800.yaml","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-800.yaml"},{"reference_url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-311.yaml","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-311.yaml"},{"reference_url":"https://github.com/tensorflow/tensorflow","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/tensorflow/tensorflow"},{"reference_url":"https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70"},{"reference_url":"https://github.com/tensorflow/tensorflow/commit/d6b57f461b39fd1aa8c1b870f1b974aac3554955","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/tensorflow/tensorflow/commit/d6b57f461b39fd1aa8c1b870f1b974aac3554955"},{"reference_url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wf5p-c75w-w3wh","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wf5p-c75w-w3wh"},{"reference_url":"https://nvd.nist.gov/vuln/detail/CVE-2021-37689","reference_id":"","reference_type":"","scores":[{"value":"7.8","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},{"value":"8.5","scoring_system":"cvssv4","scoring_elements":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://nvd.nist.gov/vuln/detail/CVE-2021-37689"},{"reference_url":"https://security.archlinux.org/AVG-2292","reference_id":"AVG-2292","reference_type":"","scores":[{"value":"Critical","scoring_system":"archlinux","scoring_elements":""}],"url":"https://security.archlinux.org/AVG-2292"},{"reference_url":"https://github.com/advisories/GHSA-wf5p-c75w-w3wh","reference_id":"GHSA-wf5p-c75w-w3wh","reference_type":"","scores":[],"url":"https://github.com/advisories/GHSA-wf5p-c75w-w3wh"}],"fixed_packages":[{"url":"http://public2.vulnerablecode.io/api/packages/370793?format=json","purl":"pkg:pypi/tflite@2.3.4","is_vulnerable":false,"affected_by_vulnerabilities":[],"resource_url":"http://public2.vulnerablecode.io/packages/pkg:pypi/tflite@2.3.4"},{"url":"http://public2.vulnerablecode.io/api/packages/370794?format=json","purl":"pkg:pypi/tflite@2.4.3","is_vulnerable":false,"affected_by_vulnerabilities":[],"resource_url":"http://public2.vulnerablecode.io/packages/pkg:pypi/tflite@2.4.3"},{"url":"http://public2.vulnerablecode.io/api/packages/370795?format=json","purl":"pkg:pypi/tflite@2.5.1","is_vulnerable":false,"affected_by_vulnerabilities":[],"resource_url":"http://public2.vulnerablecode.io/packages/pkg:pypi/tflite@2.5.1"}],"aliases":["BIT-tensorflow-2021-37689","CVE-2021-37689","GHSA-wf5p-c75w-w3wh","PYSEC-2021-311","PYSEC-2021-602","PYSEC-2021-800"],"risk_score":null,"exploitability":null,"weighted_severity":null,"resource_url":"http://public2.vulnerablecode.io/vulnerabilities/VCID-b8d3-rvxx-xfhf"},{"url":"http://public2.vulnerablecode.io/api/vulnerabilities/52179?format=json","vulnerability_id":"VCID-dyn3-98s1-53fu","summary":"Buffer overflow in `CONV_3D_TRANSPOSE` on TFLite\n### Impact\nThe reference kernel of the [`CONV_3D_TRANSPOSE`](https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121) TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result.\n\nInstead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels.\n\nAn attacker can craft a model with a specific number of input channels in a way similar to the attached example script. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter (i.e. `experimental_op_resolver_type=tf.lite.experimental.OpResolverType.BUILTIN_REF` is used).\n```python\nimport tensorflow as tf\nmodel = tf.keras.Sequential(\n    [\n        tf.keras.layers.InputLayer(input_shape=(2, 2, 2, 1024), batch_size=1),\n        tf.keras.layers.Conv3DTranspose(\n            filters=8,\n            kernel_size=(2, 2, 2),\n            padding=\"same\",\n            data_format=\"channels_last\",\n        ),\n    ]\n)\n\nconverter = tf.lite.TFLiteConverter.from_keras_model(model)\ntflite_model = converter.convert()\n\ninterpreter = tf.lite.Interpreter(\n    model_content=tflite_model,\n    experimental_op_resolver_type=tf.lite.experimental.OpResolverType.BUILTIN_REF,\n)\n\ninterpreter.allocate_tensors()\ninterpreter.set_tensor(\n    interpreter.get_input_details()[0][\"index\"], tf.zeros(shape=[1, 2, 2, 2, 1024])\n)\ninterpreter.invoke()\n```\n\n### Patches\nWe have patched the issue in GitHub commit [72c0bdcb25305b0b36842d746cc61d72658d2941](https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Thibaut Goetghebuer-Planchon, Arm Ltd.","references":[{"reference_url":"https://api.first.org/data/v1/epss?cve=CVE-2022-41894","reference_id":"","reference_type":"","scores":[{"value":"0.00225","scoring_system":"epss","scoring_elements":"0.45247","published_at":"2026-05-29T12:55:00Z"}],"url":"https://api.first.org/data/v1/epss?cve=CVE-2022-41894"},{"reference_url":"https://github.com/tensorflow/tensorflow","reference_id":"","reference_type":"","scores":[{"value":"7.1","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://github.com/tensorflow/tensorflow"},{"reference_url":"https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121","reference_id":"","reference_type":"","scores":[{"value":"7.1","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""},{"value":"Track*","scoring_system":"ssvc","scoring_elements":"SSVCv2/E:P/A:N/T:T/P:M/B:A/M:M/D:R/2025-04-22T15:40:39Z/"}],"url":"https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121"},{"reference_url":"https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941","reference_id":"","reference_type":"","scores":[{"value":"7.1","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""},{"value":"Track*","scoring_system":"ssvc","scoring_elements":"SSVCv2/E:P/A:N/T:T/P:M/B:A/M:M/D:R/2025-04-22T15:40:39Z/"}],"url":"https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941"},{"reference_url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6q3-vv32-2cq5","reference_id":"","reference_type":"","scores":[{"value":"7.1","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H"},{"value":"HIGH","scoring_system":"cvssv3.1_qr","scoring_elements":""},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""},{"value":"Track*","scoring_system":"ssvc","scoring_elements":"SSVCv2/E:P/A:N/T:T/P:M/B:A/M:M/D:R/2025-04-22T15:40:39Z/"}],"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6q3-vv32-2cq5"},{"reference_url":"https://nvd.nist.gov/vuln/detail/CVE-2022-41894","reference_id":"","reference_type":"","scores":[{"value":"7.1","scoring_system":"cvssv3.1","scoring_elements":"CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H"},{"value":"HIGH","scoring_system":"generic_textual","scoring_elements":""}],"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-41894"},{"reference_url":"https://github.com/advisories/GHSA-h6q3-vv32-2cq5","reference_id":"GHSA-h6q3-vv32-2cq5","reference_type":"","scores":[{"value":"HIGH","scoring_system":"cvssv3.1_qr","scoring_elements":""}],"url":"https://github.com/advisories/GHSA-h6q3-vv32-2cq5"}],"fixed_packages":[],"aliases":["CVE-2022-41894","GHSA-h6q3-vv32-2cq5"],"risk_score":null,"exploitability":null,"weighted_severity":null,"resource_url":"http://public2.vulnerablecode.io/vulnerabilities/VCID-dyn3-98s1-53fu"}],"fixing_vulnerabilities":[],"risk_score":null,"resource_url":"http://public2.vulnerablecode.io/packages/pkg:pypi/tflite@1.15.0.post1"}