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9554 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2017-5048 | 4 Apple, Google, Linux and 1 more | 5 Macos, Android, Chrome and 2 more | 2021-09-08 | 6.8 MEDIUM | 8.8 HIGH |
| An integer overflow in FFmpeg in Google Chrome prior to 57.0.2987.98 for Mac, Windows, and Linux and 57.0.2987.108 for Android allowed a remote attacker to perform an out of bounds memory write via a crafted video file, related to ChunkDemuxer. | |||||
| CVE-2011-0782 | 2 Apple, Google | 2 Macos, Chrome | 2021-09-08 | 5.0 MEDIUM | N/A |
| Google Chrome before 9.0.597.84 on Mac OS X does not properly mitigate an unspecified flaw in the Mac OS X 10.5 SSL libraries, which allows remote attackers to cause a denial of service (application crash) via unknown vectors. | |||||
| CVE-2015-5237 | 1 Google | 1 Protobuf | 2021-09-02 | 6.5 MEDIUM | 8.8 HIGH |
| protobuf allows remote authenticated attackers to cause a heap-based buffer overflow. | |||||
| CVE-2021-37692 | 1 Google | 1 Tensorflow | 2021-08-31 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version. | |||||
| CVE-2020-8567 | 3 Google, Hashicorp, Microsoft | 3 Secret Manager Provider For Secret Store Csi Driver, Vault Provider For Secrets Store Csi Driver, Azure Key Vault Provider For Secrets Store Csi Driver | 2021-08-27 | 4.0 MEDIUM | 6.5 MEDIUM |
| Kubernetes Secrets Store CSI Driver Vault Plugin prior to v0.0.6, Azure Plugin prior to v0.0.10, and GCP Plugin prior to v0.2.0 allow an attacker who can create specially-crafted SecretProviderClass objects to write to arbitrary file paths on the host filesystem, including /var/lib/kubelet/pods. | |||||
| CVE-2021-29983 | 2 Google, Mozilla | 2 Android, Firefox | 2021-08-25 | 4.3 MEDIUM | 6.5 MEDIUM |
| Firefox for Android could get stuck in fullscreen mode and not exit it even after normal interactions that should cause it to exit. *Note: This issue only affected Firefox for Android. Other operating systems are unaffected.*. This vulnerability affects Firefox < 91. | |||||
| CVE-2021-0627 | 1 Google | 1 Android | 2021-08-25 | 4.6 MEDIUM | 6.7 MEDIUM |
| In OMA DRM, there is a possible memory corruption due to an integer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05722434; Issue ID: ALPS05722434. | |||||
| CVE-2021-0626 | 1 Google | 1 Android | 2021-08-25 | 4.6 MEDIUM | 6.7 MEDIUM |
| In ged, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05687510; Issue ID: ALPS05687510. | |||||
| CVE-2021-0628 | 1 Google | 1 Android | 2021-08-25 | 4.6 MEDIUM | 6.7 MEDIUM |
| In OMA DRM, there is a possible memory corruption due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05722454; Issue ID: ALPS05722454. | |||||
| CVE-2021-0646 | 1 Google | 1 Android | 2021-08-25 | 4.6 MEDIUM | 7.8 HIGH |
| In sqlite3_str_vappendf of sqlite3.c, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege if the user can also inject a printf into a privileged process's SQL with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-9 Android-10 Android-11 Android-8.1Android ID: A-153352319 | |||||
| CVE-2021-0420 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to a missing bounds check. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05381065. | |||||
| CVE-2021-0419 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336713. | |||||
| CVE-2021-0418 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336706. | |||||
| CVE-2021-0416 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336700. | |||||
| CVE-2021-0408 | 1 Google | 1 Android | 2021-08-24 | 2.1 LOW | 5.5 MEDIUM |
| In asf extractor, there is a possible out of bounds read due to an incorrect bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05489195; Issue ID: ALPS05489220. | |||||
| CVE-2021-0407 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 6.7 MEDIUM |
| In clk driver, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05479659; Issue ID: ALPS05479659. | |||||
| CVE-2021-0642 | 1 Google | 1 Android | 2021-08-24 | 4.3 MEDIUM | 5.5 MEDIUM |
| In onResume of VoicemailSettingsFragment.java, there is a possible way to retrieve a trackable identifier without permissions due to a missing permission check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-8.1 Android-9Android ID: A-185126149 | |||||
| CVE-2021-0641 | 1 Google | 1 Android | 2021-08-24 | 2.1 LOW | 5.5 MEDIUM |
| In getAvailableSubscriptionInfoList of SubscriptionController.java, there is a possible disclosure of unique identifiers due to a missing permission check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.1 Android-9 Android-10 Android-11Android ID: A-185235454 | |||||
| CVE-2021-0640 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 7.8 HIGH |
| In noteAtomLogged of StatsdStats.cpp, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-9Android ID: A-187957589 | |||||
| CVE-2021-0639 | 1 Google | 1 Android | 2021-08-24 | 2.1 LOW | 5.5 MEDIUM |
| In multiple functions of libl3oemcrypto.cpp, there is a possible weakness in the existing obfuscation mechanism due to the way sensitive data is handled. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-190724551 | |||||
| CVE-2021-0593 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 7.8 HIGH |
| In sendDevicePickedIntent of DevicePickerFragment.java, there is a possible way to invoke a privileged broadcast receiver due to a confused deputy. This could lead to local escalation of privilege with User execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-8.1 Android-9Android ID: A-179386068 | |||||
| CVE-2021-0591 | 1 Google | 1 Android | 2021-08-24 | 6.8 MEDIUM | 7.3 HIGH |
| In sendReplyIntentToReceiver of BluetoothPermissionActivity.java, there is a possible way to invoke privileged broadcast receivers due to a confused deputy. This could lead to local escalation of privilege with User execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-9 Android-10 Android-11 Android-8.1Android ID: A-179386960 | |||||
| CVE-2021-0584 | 1 Google | 1 Android | 2021-08-24 | 2.1 LOW | 5.5 MEDIUM |
| In verifyBufferObject of Parcel.cpp, there is a possible out of bounds read due to an improper input validation. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-8.1 Android-9 Android-10Android ID: A-179289794 | |||||
| CVE-2021-0582 | 1 Google | 1 Android | 2021-08-24 | 3.3 LOW | 6.5 MEDIUM |
| In wifi driver, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure to a proximal attacker with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187149601 | |||||
| CVE-2021-0580 | 1 Google | 1 Android | 2021-08-24 | 3.3 LOW | 6.5 MEDIUM |
| In wifi driver, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure to a proximal attacker with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187231637 | |||||
| CVE-2021-0581 | 1 Google | 1 Android | 2021-08-24 | 3.3 LOW | 6.5 MEDIUM |
| In wifi driver, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure to a proximal attacker with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187231638 | |||||
| CVE-2021-0579 | 1 Google | 1 Android | 2021-08-24 | 3.3 LOW | 6.5 MEDIUM |
| In wifi driver, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure to a proximal attacker with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187231636 | |||||
| CVE-2021-0578 | 1 Google | 1 Android | 2021-08-24 | 3.3 LOW | 6.5 MEDIUM |
| In wifi driver, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure to a proximal attacker with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187161772 | |||||
| CVE-2021-0576 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 7.8 HIGH |
| In flv extractor, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187236084 | |||||
| CVE-2021-0574 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 7.8 HIGH |
| In asf extractor, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187234876 | |||||
| CVE-2021-0573 | 1 Google | 1 Android | 2021-08-24 | 4.6 MEDIUM | 7.8 HIGH |
| In asf extractor, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android SoCAndroid ID: A-187231635 | |||||
| CVE-2021-0519 | 1 Google | 1 Android | 2021-08-24 | 7.2 HIGH | 7.8 HIGH |
| In BITSTREAM_FLUSH of ih264e_bitstream.h, there is a possible out of bounds write due to a heap buffer overflow. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-8.1 Android-9Android ID: A-176533109 | |||||
| CVE-2021-38591 | 1 Google | 1 Android | 2021-08-20 | 2.1 LOW | 3.3 LOW |
| An issue was discovered on LG mobile devices with Android OS P and Q software for mt6762/mt6765/mt6883. Attackers can change some of the NvRAM content by leveraging the misconfiguration of a debug command. The LG ID is LVE-SMP-210005 (August 2021). | |||||
| CVE-2021-37690 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 6.6 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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. | |||||
| CVE-2021-37668 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. 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. | |||||
| CVE-2021-37665 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. 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. | |||||
| CVE-2021-37663 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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. | |||||
| CVE-2021-37670 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. 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. | |||||
| CVE-2021-37672 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. 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. | |||||
| CVE-2021-37669 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. 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. | |||||
| CVE-2021-37677 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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. | |||||
| CVE-2021-37673 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. 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. | |||||
| CVE-2021-37674 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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. | |||||
| CVE-2021-37679 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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. | |||||
| CVE-2021-37678 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 8.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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. | |||||
| CVE-2021-37682 | 1 Google | 1 Tensorflow | 2021-08-19 | 3.6 LOW | 7.1 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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. | |||||
| CVE-2021-37685 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. 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. | |||||
| CVE-2021-37684 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). 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. | |||||
| CVE-2021-37683 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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. | |||||
| CVE-2021-37691 | 1 Google | 1 Tensorflow | 2021-08-18 | 2.1 LOW | 5.5 MEDIUM |
| 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 division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||