Tenebrae/cvss31vectors huggingface dataset:
CVE-2021-37686
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37688
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. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37689
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37663
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37665
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37668
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37684
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2020-18757
An issue in Dut Computer Control Engineering Co.'s PLC MAC1100 allows attackers to cause persistent denial of service (DOS) via a crafted packet.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37669
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37670
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
CVE-2021-37672
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
CVE-2021-37673
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37674
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37643
TensorFlow is an end-to-end open source platform for machine learning. If a user does not provide a valid padding value to `tf.raw_ops.MatrixDiagPartOp`, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L89) reads the first value from a tensor buffer without first checking that the tensor has values to read from. We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37647
TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37649
TensorFlow is an end-to-end open source platform for machine learning. The code for `tf.raw_ops.UncompressElement` can be made to trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/compression_ops.cc#L50-L53) obtains a pointer to a `CompressedElement` from a `Variant` tensor and then proceeds to dereference it for decompressing. There is no check that the `Variant` tensor contained a `CompressedElement`, so the pointer is actually `nullptr`. We have patched the issue in GitHub commit 7bdf50bb4f5c54a4997c379092888546c97c3ebd. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37352
An open redirect vulnerability exists in Nagios XI before version 5.8.5 that could lead to spoofing. To exploit the vulnerability, an attacker could send a link that has a specially crafted URL and convince the user to click the link.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-37353
Nagios XI Docker Wizard before version 1.1.3 is vulnerable to SSRF due to improper sanitation in table_population.php.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37704
PhpFastCache is a high-performance backend cache system (packagist package phpfastcache/phpfastcache). In versions before 6.1.5, 7.1.2, and 8.0.7 the `phpinfo()` can be exposed if the `/vendor` is not protected from public access. This is a rare situation today since the vendor directory is often located outside the web directory or protected via server rule (.htaccess, etc). Only the v6, v7 and v8 will be patched respectively in 8.0.7, 7.1.2, 6.1.5. Older versions such as v5, v4 are not longer supported and will **NOT** be patched. As a workaround, protect the `/vendor` directory from public access.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L
CVE-2021-33056
Belledonne Belle-sip before 4.5.20, as used in Linphone and other products, can crash via an invalid From header in a SIP message.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CVE-2021-33199
In Expression Engine before 6.0.3, addonIcon in Addons/file/mod.file.php relies on the untrusted input value of input->get('file') instead of the fixed file names of icon.png and icon.svg.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37599
The exporter/Login.aspx login form in the Exporter in Nuance Winscribe Dictation 4.1.0.99 is vulnerable to SQL injection that allows a remote, unauthenticated attacker to read the database (and execute code in some situations) via the txtPassword parameter.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CVE-2021-37635
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
CVE-2021-37641
TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
CVE-2021-37644
TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to `num_elements` list argument of `tf.raw_ops.TensorListReserve` causes the runtime to abort the process due to reallocating a `std::vector` to have a negative number of elements. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/list_kernels.cc#L312) calls `std::vector.resize()` with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37645
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37646
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37650
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-31399
On 2N Access Unit 2.0 2.31.0.40.5 devices, an attacker can pose as the web relay for a man-in-the-middle attack.
CVSS 3.1 vector: CVSS:3.1/AV:A/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:L
CVE-2021-27741
" Security vulnerability in HCL Commerce Management Center allowing XML external entity (XXE) injection"
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H
CVE-2020-18759
An information disclosure vulnerability exists in the EPA protocol of Dut Computer Control Engineering Co.'s PLC MAC1100.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
CVE-2021-37651
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N
CVE-2021-37654
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor. We have patched the issue in GitHub commit bc9c546ce7015c57c2f15c168b3d9201de679a1d. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
CVE-2021-37655
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
CVE-2021-37656
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToSparse`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order. We have patched the issue in GitHub commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
CVE-2021-34659
The Plugmatter Pricing Table Lite WordPress plugin is vulnerable to Reflected Cross-Site Scripting via the `email` parameter in the ~/license.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 1.0.32.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-34663
The jQuery Tagline Rotator WordPress plugin is vulnerable to Reflected Cross-Site Scripting due to the use of $_SERVER['PHP_SELF'] in the ~/jquery-tagline-rotator.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 0.1.5.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-34664
The Moova for WooCommerce WordPress plugin is vulnerable to Reflected Cross-Site Scripting via the lat parameter in the ~/Checkout/Checkout.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 3.5.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-34665
The WP SEO Tags WordPress plugin is vulnerable to Reflected Cross-Site Scripting via the saq_txt_the_filter parameter in the ~/wp-seo-tags.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 2.2.7.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-34666
The Add Sidebar WordPress plugin is vulnerable to Reflected Cross-Site Scripting via the add parameter in the ~/wp_sidebarMenu.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 2.0.0.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-34667
The Calendar_plugin WordPress plugin is vulnerable to Reflected Cross-Site Scripting due to the use of `$_SERVER['PHP_SELF']` in the ~/calendar.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 1.0.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-37707
Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a vulnerability that allows manipulation of product reviews via API. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N
CVE-2021-38315
The SP Project & Document Manager WordPress plugin is vulnerable to attribute-based Reflected Cross-Site Scripting via the from and to parameters in the ~/functions.php file which allows attackers to inject arbitrary web scripts, in versions up to and including 4.25.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CVE-2021-21859
An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. The stri_box_read function is used when processing atoms using the 'stri' FOURCC code. An attacker can convince a user to open a video to trigger this vulnerability.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CVE-2021-21860
An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. A specially crafted MPEG-4 input can cause an improper memory allocation resulting in a heap-based buffer overflow that causes memory corruption. The FOURCC code, 'trik', is parsed by the function within the library. An attacker can convince a user to open a video to trigger this vulnerability.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CVE-2021-21861
An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. When processing the 'hdlr' FOURCC code, a specially crafted MPEG-4 input can cause an improper memory allocation resulting in a heap-based buffer overflow that causes memory corruption. An attacker can convince a user to open a video to trigger this vulnerability.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CVE-2021-37708
Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a command injection vulnerability in mail agent settings. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-38608
Incorrect Access Control in Tranquil WAPT Enterprise - before 1.8.2.7373 and before 2.0.0.9450 allows guest OS users to escalate privileges via WAPT Agent.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-32826
Proxyee-Down is open source proxy software. An attacker being able to provide an extension script (eg: through a MiTM attack or by hosting a malicious extension) may be able to run arbitrary commands on the system running Proxyee-Down. For more details including a PoC see the referenced GHSL-2021-053. As of the writing of this CVE there is currently no patched version.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:H/A:N
CVE-2021-32827
MockServer is open source software which enables easy mocking of any system you integrate with via HTTP or HTTPS. An attacker that can trick a victim into visiting a malicious site while running MockServer locally, will be able to run arbitrary code on the MockServer machine. With an overly broad default CORS configuration MockServer allows any site to send cross-site requests. Additionally, MockServer allows you to create dynamic expectations using Javascript or Velocity templates. Both engines may allow an attacker to execute arbitrary code on-behalf of MockServer. By combining these two issues (Overly broad CORS configuration + Script injection), an attacker could serve a malicious page so that if a developer running MockServer visits it, they will get compromised. For more details including a PoC see the referenced GHSL-2021-059.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:N/I:H/A:N
CVE-2021-21568
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.x contain an insufficient logging vulnerability. An authenticated user with ISI_PRIV_LOGIN_PAPI could make un-audited and un-trackable configuration changes to settings that their roles have privileges to change.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
CVE-2021-21592
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.x improperly handle an exceptional condition. A remote low privileged user could potentially exploit this vulnerability, leading to unauthorized information disclosure.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:N
CVE-2021-21594
Dell PowerScale OneFS versions 8.2.2 - 9.1.0.x contain a use of get request method with sensitive query strings vulnerability. It can lead to potential disclosure of sensitive data. Dell recommends upgrading at your earliest opportunity.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H
CVE-2021-21595
Dell EMC PowerScale OneFS versions 8.2.x - 9.1.1.x contain an improper neutralization of special elements used in an OS command. This vulnerability could allow the compadmin user to elevate privileges. This only impacts Smartlock WORM compliance mode clusters as a critical vulnerability and Dell recommends to update/upgrade at the earliest opportunity.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:H/A:H
CVE-2021-21599
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.1.x contain an OS command injection vulnerability. This may allow a user with ISI_PRIV_LOGIN_SSH or ISI_PRIV_LOGIN_CONSOLE to escalate privileges and escape the compliance guarantees. This only impacts Smartlock WORM compliance mode clusters as a critical vulnerability and Dell recommends to update/upgrade at the earliest opportunity.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:H/A:H
CVE-2021-36278
Dell EMC PowerScale OneFS versions 8.2.x, 9.1.0.x, and 9.1.1.1 contain a sensitive information exposure vulnerability in log files. A local malicious user with ISI_PRIV_LOGIN_SSH, ISI_PRIV_LOGIN_CONSOLE, or ISI_PRIV_SYS_SUPPORT privileges may exploit this vulnerability to access sensitive information. If any third-party consumes those logs, the same sensitive information is available to those systems as well.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
CVE-2021-36279
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.x contain an incorrect permission assignment for critical resource vulnerability. This could allow a user with ISI_PRIV_LOGIN_SSH or ISI_PRIV_LOGIN_CONSOLE to access privileged information about the cluster.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H
CVE-2021-36280
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.x contain an incorrect permission assignment for critical resource vulnerability. This could allow a user with ISI_PRIV_LOGIN_SSH or ISI_PRIV_LOGIN_CONSOLE to access privileged information about the cluster.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H
CVE-2021-36281
Dell EMC PowerScale OneFS versions 8.2.x - 9.2.x contain an incorrect permission assignment vulnerability. A low privileged authenticated user can potentially exploit this vulnerability to escalate privileges.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2021-36282
Dell EMC PowerScale OneFS versions 8.2.x - 9.1.0.x contain a use of uninitialized resource vulnerability. This can potentially allow an authenticated user with ISI_PRIV_LOGIN_CONSOLE or ISI_PRIV_LOGIN_SSH privileges to gain access up to 24 bytes of data within the /ifs kernel stack under certain conditions.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:N
CVE-2021-37709
Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a vulnerability involving an insecure direct object reference of log files of the Import/Export feature. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
CVE-2021-37710
Shopware is an open source eCommerce platform. Versions prior to 6.4.3.1 contain a Cross-Site Scripting vulnerability via SVG media files. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:H
CVE-2021-37711
Versions prior to 6.4.3.1 contain an authenticated server-side request forgery vulnerability in file upload via URL. Version 6.4.3.1 contains a patch. As workarounds for older versions of 6.1, 6.2, and 6.3, corresponding security measures are also available via a plugin.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2020-4706
IBM API Connect 5.0.0.0 through 5.0.8.10 is vulnerable to HTTP header injection, caused by improper validation of input by the HOST headers. By sending a specially crafted HTTP request, a remote attacker could exploit this vulnerability to inject HTTP HOST header, which will allow the attacker to conduct various attacks against the vulnerable system, including cross-site scripting, cache poisoning or session hijacking. IBM X-Force ID: 187194.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N
CVE-2020-4992
IBM DataPower Gateway 2018.4.1.0 through 2018.4.1.16 is vulnerable to cross-site request forgery which could allow an attacker to execute malicious and unauthorized actions transmitted from a user that the website trusts. IBM X-Force ID: 192737.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N
CVE-2021-25956
In “Dolibarr” application, v3.3.beta1_20121221 to v13.0.2 have “Modify” access for admin level users to change other user’s details but fails to validate already existing “Login” name, while renaming the user “Login”. This leads to complete account takeover of the victim user. This happens since the password gets overwritten for the victim user having a similar login name.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L
CVE-2021-41346
Console Window Host Security Feature Bypass Vulnerability
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
CVE-2021-25957
In “Dolibarr” application, v2.8.1 to v13.0.2 are vulnerable to account takeover via password reset functionality. A low privileged attacker can reset the password of any user in the application using the password reset link the user received through email when requested for a forgotten password.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVE-2020-28846
Cross Site Request Forgery (CSRF) vulnerability exists in SeaCMS 10.7 in admin_manager.php, which could let a malicious user add an admin account.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N
CVE-2021-32829
ZStack is open source IaaS(infrastructure as a service) software aiming to automate datacenters, managing resources of compute, storage, and networking all by APIs. Affected versions of ZStack REST API are vulnerable to post-authentication Remote Code Execution (RCE) via bypass of the Groovy shell sandbox. The REST API exposes the GET zstack/v1/batch-queries?script endpoint which is backed up by the BatchQueryAction class. Messages are represented by the APIBatchQueryMsg, dispatched to the QueryFacadeImpl facade and handled by the BatchQuery class. The HTTP request parameter script is mapped to the APIBatchQueryMsg.script property and evaluated as a Groovy script in BatchQuery.query the evaluation of the user-controlled Groovy script is sandboxed by SandboxTransformer which will apply the restrictions defined in the registered (sandbox.register()) GroovyInterceptor. Even though the sandbox heavily restricts the receiver types to a small set of allowed types, the sandbox is non effective at controlling any code placed in Java annotations and therefore vulnerable to meta-programming escapes. This issue leads to post-authenticated remote code execution. For more details see the referenced GHSL-2021-065. This issue is patched in versions 3.8.21, 3.10.8, and 4.1.0.
CVSS 3.1 vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:N
CVE-2021-3458
The Motorola MM1000 device configuration portal can be accessed without authentication, which could allow adapter settings to be modified.
CVSS 3.1 vector: CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37657
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37658
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37659
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
CVE-2021-37682
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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
CVE-2021-37661
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2021-37662
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
CVE-2021-37664
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 `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. 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.
CVSS 3.1 vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H