CVE-2021-29534
Summary
| CVE | CVE-2021-29534 |
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| State | PUBLIC |
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| Assigner | [email protected] |
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| Source Priority | CVE Program / NVD first with legacy fallback |
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| Published | 2021-05-14 20:15:00 UTC |
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| Updated | 2021-07-27 17:30:00 UTC |
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| Description | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. |
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NVD Known Affected Configurations (CPE 2.3)
References
| Reference | Source | Link | Tags |
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| `CHECK`-fail in `SparseConcat` · Advisory · tensorflow/tensorflow · GitHub |
CONFIRM |
github.com |
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| Fix overflow CHECK issue with `tf.raw_ops.AddManySparseToTensorsMap`. · tensorflow/tensorflow@69c68ec · GitHub |
MISC |
github.com |
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| CVE Program record |
CVE.ORG |
www.cve.org |
canonical |
| NVD vulnerability detail |
NVD |
nvd.nist.gov |
canonical, analysis |
No vendor comments have been submitted for this CVE.
Legacy QID Mappings
- 982514 Python (pip) Security Update for tensorflow-gpu (GHSA-6j9c-grc6-5m6g)
