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| purl | pkg:pypi/tensorflow@2.2.0rc3 |
| Vulnerability | Summary | Fixed by |
|---|---|---|
|
VCID-16bv-43x5-2yev
Aliases: CVE-2020-15201 GHSA-p5f8-gfw5-33w4 PYSEC-2020-124 PYSEC-2020-281 PYSEC-2020-316 |
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
|
VCID-1sqz-62wf-nbd5
Aliases: CVE-2020-15266 GHSA-xwhf-g6j5-j5gc PYSEC-2020-139 PYSEC-2020-296 PYSEC-2020-331 |
In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. |
Affected by 198 other vulnerabilities. |
|
VCID-22fx-g11c-hyg7
Aliases: CVE-2020-15191 GHSA-q8qj-fc9q-cphr PYSEC-2020-114 PYSEC-2020-271 PYSEC-2020-306 |
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. |
Affected by 151 other vulnerabilities. Affected by 205 other vulnerabilities. |
|
VCID-26ws-81w3-q7cz
Aliases: CVE-2020-15265 GHSA-rrfp-j2mp-hq9c PYSEC-2020-138 PYSEC-2020-295 PYSEC-2020-330 |
In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. |
Affected by 198 other vulnerabilities. |
|
VCID-4p31-hqj7-kfau
Aliases: CVE-2020-15192 GHSA-8fxw-76px-3rxv PYSEC-2020-115 PYSEC-2020-272 PYSEC-2020-307 |
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. |
Affected by 151 other vulnerabilities. Affected by 205 other vulnerabilities. |
|
VCID-5781-vzmv-rkg4
Aliases: CVE-2021-41201 GHSA-j86v-p27c-73fm PYSEC-2021-394 PYSEC-2021-611 PYSEC-2021-809 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-5gv5-xuze-q7he
Aliases: CVE-2020-15200 GHSA-x7rp-74x2-mjf3 PYSEC-2020-123 PYSEC-2020-280 PYSEC-2020-315 |
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
|
VCID-5j3t-baqf-dbhs
Aliases: CVE-2021-41195 GHSA-cq76-mxrc-vchh PYSEC-2021-842 PYSEC-2021-844 PYSEC-2021-846 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. |
|
VCID-68ym-s45d-8bhk
Aliases: CVE-2021-41225 GHSA-7r94-xv9v-63jw PYSEC-2021-417 PYSEC-2021-634 PYSEC-2021-832 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-6wh3-uhcu-jqef
Aliases: CVE-2021-41196 GHSA-m539-j985-hcr8 PYSEC-2021-389 PYSEC-2021-606 PYSEC-2021-804 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-6yd6-npyx-93cx
Aliases: CVE-2021-41207 GHSA-7v94-64hj-m82h PYSEC-2021-399 PYSEC-2021-616 PYSEC-2021-814 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-79xv-tn5e-xqgr
Aliases: CVE-2020-15197 GHSA-qc53-44cj-vfvx PYSEC-2020-120 PYSEC-2020-277 PYSEC-2020-312 |
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
|
VCID-7avd-xuag-ybbv
Aliases: CVE-2021-41215 GHSA-x3v8-c8qx-3j3r PYSEC-2021-407 PYSEC-2021-624 PYSEC-2021-822 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-7gat-e8qw-e7hd
Aliases: CVE-2021-41210 GHSA-m342-ff57-4jcc PYSEC-2021-402 PYSEC-2021-619 PYSEC-2021-817 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-85jp-mtkt-6kb1
Aliases: CVE-2021-41214 GHSA-vwhq-49r4-gj9v PYSEC-2021-406 PYSEC-2021-623 PYSEC-2021-821 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-8bz4-tb8u-ckdy
Aliases: CVE-2021-41202 GHSA-xrqm-fpgr-6hhx PYSEC-2021-395 PYSEC-2021-612 PYSEC-2021-810 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-9na3-g739-u7de
Aliases: CVE-2020-15199 GHSA-x5cp-9pcf-pp3h PYSEC-2020-122 PYSEC-2020-279 PYSEC-2020-314 |
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
|
VCID-at48-mrdj-a3en
Aliases: CVE-2021-41226 GHSA-374m-jm66-3vj8 PYSEC-2021-418 PYSEC-2021-635 PYSEC-2021-833 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-au3q-9qpz-pkgy
Aliases: CVE-2021-41223 GHSA-f54p-f6jp-4rhr PYSEC-2021-415 PYSEC-2021-632 PYSEC-2021-830 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-bgt5-979r-auc5
Aliases: CVE-2021-41209 GHSA-6hpv-v2rx-c5g6 PYSEC-2021-401 PYSEC-2021-618 PYSEC-2021-816 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-bh5b-u3zt-puf9
Aliases: CVE-2021-41221 GHSA-cqv6-3phm-hcwx PYSEC-2021-413 PYSEC-2021-630 PYSEC-2021-828 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-cswq-zynn-h7ct
Aliases: CVE-2021-41217 GHSA-5crj-c72x-m7gq PYSEC-2021-409 PYSEC-2021-626 PYSEC-2021-824 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-dcp4-adwb-efd7
Aliases: CVE-2021-41198 GHSA-2p25-55c9-h58q PYSEC-2021-391 PYSEC-2021-608 PYSEC-2021-806 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-ffnh-y8v7-9yg7
Aliases: CVE-2021-41227 GHSA-j8c8-67vp-6mx7 PYSEC-2021-419 PYSEC-2021-636 PYSEC-2021-834 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-h638-b3zk-wqfa
Aliases: CVE-2021-41228 GHSA-3rcw-9p9x-582v PYSEC-2021-420 PYSEC-2021-637 PYSEC-2021-835 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-k9e7-kmzx-wqbn
Aliases: CVE-2021-41206 GHSA-pgcq-h79j-2f69 PYSEC-2021-843 PYSEC-2021-845 PYSEC-2021-847 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. |
|
VCID-kq2a-p2fu-n7gc
Aliases: CVE-2021-41222 GHSA-cpf4-wx82-gxp6 PYSEC-2021-414 PYSEC-2021-631 PYSEC-2021-829 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-ngd2-qzsa-ubdv
Aliases: CVE-2021-41197 GHSA-prcg-wp5q-rv7p PYSEC-2021-390 PYSEC-2021-607 PYSEC-2021-805 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-p2z3-j6kf-p3dd
Aliases: CVE-2021-41218 GHSA-9crf-c6qr-r273 PYSEC-2021-410 PYSEC-2021-627 PYSEC-2021-825 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-qe3m-tepe-sqbq
Aliases: CVE-2021-41213 GHSA-h67m-xg8f-fxcf PYSEC-2021-405 PYSEC-2021-622 PYSEC-2021-820 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-r184-6v15-tqgm
Aliases: CVE-2021-41200 GHSA-gh8h-7j2j-qv4f PYSEC-2021-393 PYSEC-2021-610 PYSEC-2021-808 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-sdzd-ajns-dkh1
Aliases: CVE-2020-15193 GHSA-rjjg-hgv6-h69v PYSEC-2020-116 PYSEC-2020-273 PYSEC-2020-308 |
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. |
Affected by 151 other vulnerabilities. Affected by 205 other vulnerabilities. |
|
VCID-tdvx-q3rc-wqd4
Aliases: CVE-2020-15196 GHSA-pg59-2f92-5cph PYSEC-2020-119 PYSEC-2020-276 PYSEC-2020-311 |
In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
|
VCID-tf8j-fa4n-2qcy
Aliases: CVE-2021-41224 GHSA-rg3m-hqc5-344v PYSEC-2021-416 PYSEC-2021-633 PYSEC-2021-831 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-ty1g-525f-jkan
Aliases: CVE-2021-41216 GHSA-3ff2-r28g-w7h9 PYSEC-2021-408 PYSEC-2021-625 PYSEC-2021-823 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-uqae-1yv2-fuc2
Aliases: CVE-2021-41219 GHSA-4f99-p9c2-3j8x PYSEC-2021-411 PYSEC-2021-628 PYSEC-2021-826 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-v7xq-gfna-5kfw
Aliases: CVE-2021-41204 GHSA-786j-5qwq-r36x PYSEC-2021-397 PYSEC-2021-614 PYSEC-2021-812 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-vsxn-sk73-dbg5
Aliases: CVE-2021-41205 GHSA-49rx-x2rw-pc6f PYSEC-2021-398 PYSEC-2021-615 PYSEC-2021-813 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-wdpc-4xjf-pqgh
Aliases: CVE-2021-41203 GHSA-7pxj-m4jf-r6h2 PYSEC-2021-396 PYSEC-2021-613 PYSEC-2021-811 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-wskj-uyt9-akab
Aliases: CVE-2021-41199 GHSA-5hx2-qx8j-qjqm PYSEC-2021-392 PYSEC-2021-609 PYSEC-2021-807 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-xdz6-2ckp-a3dw
Aliases: CVE-2021-41212 GHSA-fr77-rrx3-cp7g PYSEC-2021-404 PYSEC-2021-621 PYSEC-2021-819 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-y5ak-4gg9-sqaj
Aliases: CVE-2021-41208 GHSA-57wx-m983-2f88 PYSEC-2021-400 PYSEC-2021-617 PYSEC-2021-815 |
multiple issues |
Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 0 other vulnerabilities. Affected by 56 other vulnerabilities. |
|
VCID-y634-q7n4-jbhu
Aliases: CVE-2020-15198 GHSA-jc87-6vpp-7ff3 PYSEC-2020-121 PYSEC-2020-278 PYSEC-2020-313 |
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Affected by 205 other vulnerabilities. |
| Vulnerability | Summary | Aliases |
|---|---|---|
| This package is not known to fix vulnerabilities. | ||