yahoo-inc/cve-impacts huggingface dataset:
CVE-2021-37617: The Nextcloud Desktop Client is a tool to synchronize files from Nextcloud Server with a computer. The Nextcloud Desktop Client invokes its uninstaller script when being installed to make sure there are no remnants of previous installations. In versions 3.0.3 through 3.2.4, the Client searches the `Uninstall.exe` file in a folder that can be written by regular users. This could lead to a case where a malicious user creates a malicious `Uninstall.exe`, which would be executed with administrative privileges on the Nextcloud Desktop Client installation. This issue is fixed in Nextcloud Desktop Client version 3.3.0. As a workaround, do not allow untrusted users to create content in the `C:\\\\` system folder and verify that there is no malicious `C:\\\\Uninstall.exe` file on the system.
Key phrases: create content in the `C:\\\\` system
CVE-2021-37618: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to print the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when printing the image ICC profile, which is a less frequently used Exiv2 operation that requires an extra command line option (`-p C`). The bug is fixed in version v0.27.5.
Key phrases: out-of-bounds read, denial of service, out of bounds read
CVE-2021-37619: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to write metadata into a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service by crashing Exiv2, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when writing the metadata, which is a less frequently used Exiv2 operation than reading the metadata. For example, to trigger the bug in the Exiv2 command-line application, you need to add an extra command-line argument such as insert. The bug is fixed in version v0.27.5.
Key phrases: out-of-bounds read, denial of service, out of bounds read, crash
CVE-2021-3762: A directory traversal vulnerability was found in the ClairCore engine of Clair. An attacker can exploit this by supplying a crafted container image which, when scanned by Clair, allows for arbitrary file write on the filesystem, potentially allowing for remote code execution.
Key phrases: for arbitrary file write on the filesystem, for remote code execution, directory traversal
CVE-2021-37620: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to read the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. The bug is fixed in version v0.27.5.
Key phrases: out-of-bounds read, denial of service, out of bounds read
CVE-2021-37621: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An infinite loop was found in Exiv2 versions v0.27.4 and earlier. The infinite loop is triggered when Exiv2 is used to print the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when printing the image ICC profile, which is a less frequently used Exiv2 operation that requires an extra command line option (`-p C`). The bug is fixed in version v0.27.5.
Key phrases: infinite loop, denial of service
CVE-2021-37622: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An infinite loop was found in Exiv2 versions v0.27.4 and earlier. The infinite loop is triggered when Exiv2 is used to modify the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when deleting the IPTC data, which is a less frequently used Exiv2 operation that requires an extra command line option (`-d I rm`). The bug is fixed in version v0.27.5.
Key phrases: infinite loop, denial of service
CVE-2021-37623: Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An infinite loop was found in Exiv2 versions v0.27.4 and earlier. The infinite loop is triggered when Exiv2 is used to modify the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when deleting the IPTC data, which is a less frequently used Exiv2 operation that requires an extra command line option (`-d I rm`). The bug is fixed in version v0.27.5.
Key phrases: infinite loop, denial of service
CVE-2021-37624: FreeSWITCH is a Software Defined Telecom Stack enabling the digital transformation from proprietary telecom switches to a software implementation that runs on any commodity hardware. Prior to version 1.10.7, FreeSWITCH does not authenticate SIP MESSAGE requests, leading to spam and message spoofing. By default, SIP requests of the type MESSAGE (RFC 3428) are not authenticated in the affected versions of FreeSWITCH. MESSAGE requests are relayed to SIP user agents registered with the FreeSWITCH server without requiring any authentication. Although this behaviour can be changed by setting the `auth-messages` parameter to `true`, it is not the default setting. Abuse of this security issue allows attackers to send SIP MESSAGE messages to any SIP user agent that is registered with the server without requiring authentication. Additionally, since no authentication is required, chat messages can be spoofed to appear to come from trusted entities. Therefore, abuse can lead to spam and enable social engineering, phishing and similar attacks. This issue is patched in version 1.10.7. Maintainers recommend that this SIP message type is authenticated by default so that FreeSWITCH administrators do not need to be explicitly set the `auth-messages` parameter. When following such a recommendation, a new parameter can be introduced to explicitly disable authentication.
Key phrases: send SIP MESSAGE messages to any SIP user, security issue, social engineering, phishing, spoofing
CVE-2021-37625: Skytable is an open source NoSQL database. In versions prior to 0.6.4 an incorrect check of return value of the accept function in the run-loop for a TCP socket/TLS socket/TCP+TLS multi-socket causes an early exit from the run loop that should continue infinitely unless terminated by a local user, effectively causing the whole database server to shut down. This has severe impact and can be used to easily cause DoS attacks without the need to use much bandwidth. The attack vectors include using an incomplete TLS connection for example by not providing the certificate for the connection and using a specially crafted TCP packet that triggers the application layer backoff algorithm.
Key phrases: severe impact, dos, incomplete tls connection
CVE-2021-37626: Contao is an open source CMS that allows you to create websites and scalable web applications. In affected versions it is possible to load PHP files by entering insert tags in the Contao back end. Installations are only affected if they have untrusted back end users who have the rights to modify fields that are shown in the front end. Update to Contao 4.4.56, 4.9.18 or 4.11.7 to resolve. If you cannot update then disable the login for untrusted back end users.
Key phrases: create websites and scalable web applications, php files
CVE-2021-37627: Contao is an open source CMS that allows creation of websites and scalable web applications. In affected versions it is possible to gain privileged rights in the Contao back end. Installations are only affected if they have untrusted back end users who have access to the form generator. All users are advised to update to Contao 4.4.56, 4.9.18 or 4.11.7. As a workaround users may disable the form generator or disable the login for untrusted back end users.
Key phrases: gain privileged, gain privileged rights in the Contao back end
CVE-2021-37628: Nextcloud Richdocuments is an open source collaborative office suite. In affected versions the File Drop features ("Upload Only" public link shares in Nextcloud) can be bypassed using the Nextcloud Richdocuments app. An attacker was able to read arbitrary files in such a share. It is recommended that the Nextcloud Richdocuments is upgraded to 3.8.4 or 4.2.1. If upgrading is not possible then it is recommended to disable the Richdocuments application.
Key phrases: read arbitrary files, file drop features
CVE-2021-37629: Nextcloud Richdocuments is an open source collaborative office suite. In affected versions there is a lack of rate limiting on the Richdocuments OCS endpoint. This may have allowed an attacker to enumerate potentially valid share tokens. It is recommended that the Nextcloud Richdocuments app is upgraded to either 3.8.4 or 4.2.1 to resolve. For users unable to upgrade it is recommended that the Richdocuments application be disabled.
Key phrases: rate limiting, disabled
CVE-2021-3763: A flaw was found in the Red Hat AMQ Broker management console in version 7.8 where an existing user is able to access some limited information even when the role the user is assigned to should not be allow access to the management console. The main impact is to confidentiality as this flaw means some role bindings are incorrectly checked, some privileged meta information such as queue names and configuration details are disclosed but the impact is limited as not all information is accessible and there is no affect to integrity.
Key phrases: the management console, confidentiality, integrity
CVE-2021-37630: Nextcloud Circles is an open source social network built for the nextcloud ecosystem. In affected versions the Nextcloud Circles application allowed any user to join any "Secret Circle" without approval by the Circle owner leaking private information. It is recommended that Nextcloud Circles is upgraded to 0.19.15, 0.20.11 or 0.21.4. There are no workarounds for this issue.
CVE-2021-37631: Deck is an open source kanban style organization tool aimed at personal planning and project organization for teams integrated with Nextcloud. In affected versions the Deck application didn't properly check membership of users in a Circle. This allowed other users in the instance to gain access to boards that have been shared with a Circle, even if the user was not a member of the circle. It is recommended that Nextcloud Deck is upgraded to 1.5.1, 1.4.4 or 1.2.9. If you are unable to update it is advised to disable the Deck plugin.
Key phrases: gain access
CVE-2021-37632: SuperMartijn642's Config Lib is a library used by a number of mods for the game Minecraft. The versions of SuperMartijn642's Config Lib between 1.0.4 and 1.0.8 are affected by a vulnerability and can be exploited on both servers and clients. Using SuperMartijn642's Config Lib, servers will send a packet to clients with the server's config values. In order to read `enum` values from the packet data, `ObjectInputStream#readObject` is used. `ObjectInputStream#readObject` will instantiate a class based on the input data. Since, the packet data is not validated before `ObjectInputStream#readObject` is called, an attacker can instantiate any class by sending a malicious packet. If a suitable class is found, the vulnerability can lead to a number of exploits, including remote code execution. Although the vulnerable packet is typically only send from server to client, it can theoretically also be send from client to server. This means both clients and servers running SuperMartijn642's Config Lib between 1.0.4 and 1.0.8 are vulnerable. The vulnerability has been patched in SuperMartijn642's Config lib 1.0.9. Both, players and server owners, should update to 1.0.9 or higher.
Key phrases: remote code execution
CVE-2021-37633: Discourse is an open source discussion platform. In versions prior to 2.7.8 rendering of d-popover tooltips can be susceptible to XSS attacks. This vulnerability only affects sites which have modified or disabled Discourse's default Content Security Policy. This issue is patched in the latest `stable` 2.7.8 version of Discourse. As a workaround users may ensure that the Content Security Policy is enabled, and has not been modified in a way which would make it more vulnerable to XSS attacks.
Key phrases: xss
CVE-2021-37634: Leafkit is a templating language with Swift-inspired syntax. Versions prior to 1.3.0 are susceptible to Cross-site Scripting (XSS) attacks. This affects anyone passing unsanitised data to Leaf's variable tags. Before this fix, Leaf would not escape any strings passed to tags as variables. If an attacker managed to find a variable that was rendered with their unsanitised data, they could inject scripts into a generated Leaf page, which could enable XSS attacks if other mitigations such as a Content Security Policy were not enabled. This has been patched in 1.3.0. As a workaround sanitize any untrusted input before passing it to Leaf and enable a CSP to block inline script and CSS data.
Key phrases: cross-site scripting (xss)
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.
CVE-2021-37636: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit d9204be9f49520cdaaeb2541d1dc5187b23f31d9. 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.
Key phrases: division by 0 error
CVE-2021-37637: TensorFlow is an end-to-end open source platform for machine learning. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. 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.
Key phrases: null pointer dereference
CVE-2021-37638: TensorFlow is an end-to-end open source platform for machine learning. Sending invalid argument for `row_partition_types` of `tf.raw_ops.RaggedTensorToTensor` API results in a null pointer dereference and undefined behavior. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L328) accesses the first element of a user supplied list of values without validating that the provided list is not empty. We have patched the issue in GitHub commit 301ae88b331d37a2a16159b65b255f4f9eb39314. 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.
Key phrases: null pointer dereference, undefined behavior
CVE-2021-37639: TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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.
Key phrases: heap oob read, null pointer
CVE-2021-3764: A memory leak flaw was found in the Linux kernel's ccp_run_aes_gcm_cmd() function that allows an attacker to cause a denial of service. The vulnerability is similar to the older CVE-2019-18808. The highest threat from this vulnerability is to system availability.
Key phrases: cause a denial of service, memory leak flaw, system availability
CVE-2021-37640: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements. The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. We have patched the issue in GitHub commit 4923de56ec94fff7770df259ab7f2288a74feb41. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1 as this is the other affected version.
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.
CVE-2021-37642: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_variable_ops.cc#L865) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit 4aacb30888638da75023e6601149415b39763d76. 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.
Key phrases: division by 0 error
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.
Key phrases: null pointer dereference
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.
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.
Key phrases: integer overflow
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.
Key phrases: integer overflow
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.
Key phrases: null pointer, null pointer dereference
CVE-2021-37648: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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.
Key phrases: null pointer dereference
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.
Key phrases: null pointer dereference
CVE-2021-3765: validator.js is vulnerable to Inefficient Regular Expression Complexity
Key phrases: inefficient regular expression complexity
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.
Key phrases: heap buffer overflow, segmentation fault
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.
CVE-2021-37652: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. 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.
Key phrases: use after free error, double free
CVE-2021-37653: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. 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.
Key phrases: crash
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.
Key phrases: crash
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.
Key phrases: read from outside of bounds
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.
Key phrases: undefined behavior, null pointer
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.
Key phrases: undefined behavior, null pointer
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.
Key phrases: undefined behavior, null pointer
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.
Key phrases: undefined behavior, null pointer, heap oob reads
CVE-2021-3766: objection.js is vulnerable to Improperly Controlled Modification of Object Prototype Attributes ('Prototype Pollution')
Key phrases: improperly controlled modification of object prototype attributes, prototype pollution
CVE-2021-37660: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. 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-2021-37661: 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.
Key phrases: denial of service, crash
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.
Key phrases: undefined behavior
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.
Key phrases: undefined behavior, null pointer
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.
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.
Key phrases: undefined behavior, null pointer
CVE-2021-37666: 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.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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.
Key phrases: undefined behavior, null pointer
CVE-2021-37667: 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.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. 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.
Key phrases: undefined behavior, null pointer
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.
Key phrases: denial of service