stasvinokur/cve-and-cwe-dataset-1999-2025 huggingface dataset:
CVE-2022-35979 (severity: HIGH, weakness: CWE-20)
TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-3598 (severity: MEDIUM, weakness: CWE-787)
LibTIFF 4.4.0 has an out-of-bounds write in extractContigSamplesShifted24bits in tools/tiffcrop.c:3604, allowing attackers to cause a denial-of-service via a crafted tiff file. For users that compile libtiff from sources, the fix is available with commit cfbb883b.
CVE-2022-35980 (severity: HIGH, weakness: CWE-612)
OpenSearch Security is a plugin for OpenSearch that offers encryption, authentication and authorization. Versions 2.0.0.0 and 2.1.0.0 of the security plugin are affected by an information disclosure vulnerability. Requests to an OpenSearch cluster configured with advanced access control features document level security (DLS), field level security (FLS), and/or field masking will not be filtered when the query's search pattern matches an aliased index. OpenSearch Dashboards creates an alias to `.kibana` by default, so filters with the index pattern of `*` to restrict access to documents or fields will not be applied. This issue allows requests to access sensitive information when customer have acted to restrict access that specific information. OpenSearch 2.2.0, which is compatible with OpenSearch Security 2.2.0.0, contains the fix for this issue. There is no recommended work around.
CVE-2022-35981 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. `FractionalMaxPoolGrad` validates its inputs with `CHECK` failures instead of with returning errors. If it gets incorrectly sized inputs, the `CHECK` failure can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 8741e57d163a079db05a7107a7609af70931def4. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35982 (severity: HIGH, weakness: CWE-20)
TensorFlow is an open source platform for machine learning. If `SparseBincount` is given inputs for `indices`, `values`, and `dense_shape` that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35983 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. If `Save` or `SaveSlices` is run over tensors of an unsupported `dtype`, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35984 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. `ParameterizedTruncatedNormal` assumes `shape` is of type `int32`. A valid `shape` of type `int64` results in a mismatched type `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 72180be03447a10810edca700cbc9af690dfeb51. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35985 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35986 (severity: HIGH, weakness: CWE-20)
TensorFlow is an open source platform for machine learning. If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35987 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. `DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35988 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35989 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-3599 (severity: MEDIUM, weakness: CWE-125)
LibTIFF 4.4.0 has an out-of-bounds read in writeSingleSection in tools/tiffcrop.c:7345, allowing attackers to cause a denial-of-service via a crafted tiff file. For users that compile libtiff from sources, the fix is available with commit e8131125.
CVE-2022-35990 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.There are no known workarounds for this issue.
CVE-2022-35991 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `TensorListScatter` and `TensorListScatterV2` receive an `element_shape` of a rank greater than one, they give a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35992 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `TensorListFromTensor` receives an `element_shape` of a rank greater than one, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 3db59a042a38f4338aa207922fa2f476e000a6ee. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35993 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35994 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `CollectiveGather` receives an scalar input `input`, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c1f491817dec39a26be3c574e86a88c30f3c4770. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35995 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `AudioSummaryV2` receives an input `sample_rate` with more than one element, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf6b45244992e2ee543c258e519489659c99fb7f. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35996 (severity: HIGH, weakness: CWE-369)
TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35997 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. If `tf.sparse.cross` receives an input `separator` that is not a scalar, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 83dcb4dbfa094e33db084e97c4d0531a559e0ebf. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35998 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. If `EmptyTensorList` receives an input `element_shape` with more than one dimension, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-35999 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `Conv2DBackpropInput` receives empty `out_backprop` inputs (e.g. `[3, 1, 0, 1]`), the current CPU/GPU kernels `CHECK` fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-3600 (severity: CRITICAL, weakness: NVD-CWE-Other)
The Easy Digital Downloads WordPress plugin before 3.1.0.2 does not validate data when its output in a CSV file, which could lead to CSV injection.
CVE-2022-36000 (severity: HIGH, weakness: CWE-476)
TensorFlow is an open source platform for machine learning. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it gives a null dereference. We have patched the issue in GitHub commit aed36912609fc07229b4d0a7b44f3f48efc00fd0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36001 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `DrawBoundingBoxes` receives an input `boxes` that is not of dtype `float`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit da0d65cdc1270038e72157ba35bf74b85d9bda11. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36002 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `Unbatch` receives a nonscalar input `id`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 4419d10d576adefa36b0e0a9425d2569f7c0189f. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36003 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36004 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `tf.random.gamma` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36005 (severity: HIGH, weakness: CWE-617)
TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
CVE-2022-36006 (severity: HIGH, weakness: CWE-94)
Arvados is an open source platform for managing, processing, and sharing genomic and other large scientific and biomedical data. A remote code execution (RCE) vulnerability in the Arvados Workbench allows authenticated attackers to execute arbitrary code via specially crafted JSON payloads. This exists in all versions up to 2.4.1 and is fixed in 2.4.2. This vulnerability is specific to the Ruby on Rails Workbench application (“Workbench 1”). We do not believe any other Arvados components, including the TypesScript browser-based Workbench application (“Workbench 2”) or API Server, are vulnerable to this attack. For versions of Arvados earlier than 2.4.2: remove the Ruby-based "Workbench 1" app ("apt-get remove arvados-workbench") from your installation as a workaround.
CVE-2022-36007 (severity: LOW, weakness: CWE-22)
Venice is a Clojure inspired sandboxed Lisp dialect with excellent Java interoperability. A partial path traversal issue exists within the functions `load-file` and `load-resource`. These functions can be limited to load files from a list of load paths. Assuming Venice has been configured with the load paths: `[ "/Users/foo/resources" ]` When passing **relative** paths to these two vulnerable functions everything is fine: `(load-resource "test.png")` => loads the file "/Users/foo/resources/test.png" `(load-resource "../resources-alt/test.png")` => rejected, outside the load path When passing **absolute** paths to these two vulnerable functions Venice may return files outside the configured load paths: `(load-resource "/Users/foo/resources/test.png")` => loads the file "/Users/foo/resources/test.png" `(load-resource "/Users/foo/resources-alt/test.png")` => loads the file "/Users/foo/resources-alt/test.png" !!! The latter call suffers from the _Partial Path Traversal_ vulnerability. This issue’s scope is limited to absolute paths whose name prefix matches a load path. E.g. for a load-path `"/Users/foo/resources"`, the actor can cause loading a resource also from `"/Users/foo/resources-alt"`, but not from `"/Users/foo/images"`. Versions of Venice before and including v1.10.17 are affected by this issue. Upgrade to Venice >= 1.10.18, if you are on a version < 1.10.18. There are currently no known workarounds.
CVE-2022-36008 (severity: MEDIUM, weakness: CWE-190)
Frontier is Substrate's Ethereum compatibility layer. A security issue was discovered affecting parsing of the RPC result of the exit reason in case of EVM reversion. In release build, this would cause the exit reason being incorrectly parsed and returned by RPC. In debug build, this would cause an overflow panic. No action is needed unless you have a bridge node that needs to distinguish different reversion exit reasons and you used RPC for this. There are currently no known workarounds.
CVE-2022-36009 (severity: HIGH, weakness: CWE-863)
gomatrixserverlib is a Go library for matrix protocol federation. Dendrite is a Matrix homeserver written in Go, an alternative to Synapse. The power level parsing within gomatrixserverlib was failing to parse the `"events_default"` key of the `m.room.power_levels` event, defaulting the event default power level to zero in all cases. Power levels are the matrix terminology for user access level. In rooms where the `"events_default"` power level had been changed, this could result in events either being incorrectly authorised or rejected by Dendrite servers. gomatrixserverlib contains a fix as of commit `723fd49` and Dendrite 0.9.3 has been updated accordingly. Matrix rooms where the `"events_default"` power level has not been changed from the default of zero are not vulnerable. Users are advised to upgrade. There are no known workarounds for this issue.
CVE-2022-3601 (severity: MEDIUM, weakness: NVD-CWE-Other)
The Image Hover Effects Css3 WordPress plugin through 4.5 does not sanitise and escape some of its settings, which could allow high privilege users such as admin to perform Stored Cross-Site Scripting attacks even when the unfiltered_html capability is disallowed (for example in multisite setup).
CVE-2022-36010 (severity: CRITICAL, weakness: CWE-95)
This library allows strings to be parsed as functions and stored as a specialized component, [`JsonFunctionValue`](https://github.com/oxyno-zeta/react-editable-json-tree/blob/09a0ca97835b0834ad054563e2fddc6f22bc5d8c/src/components/JsonFunctionValue.js). To do this, Javascript's [`eval`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/eval) function is used to execute strings that begin with "function" as Javascript. This unfortunately could allow arbitrary code to be executed if it exists as a value within the JSON structure being displayed. Given that this component may often be used to display data from arbitrary, untrusted sources, this is extremely dangerous. One important note is that users who have defined a custom [`onSubmitValueParser`](https://github.com/oxyno-zeta/react-editable-json-tree/tree/09a0ca97835b0834ad054563e2fddc6f22bc5d8c#onsubmitvalueparser) callback prop on the [`JsonTree`](https://github.com/oxyno-zeta/react-editable-json-tree/blob/09a0ca97835b0834ad054563e2fddc6f22bc5d8c/src/JsonTree.js) component should be ***unaffected***. This vulnerability exists in the default `onSubmitValueParser` prop which calls [`parse`](https://github.com/oxyno-zeta/react-editable-json-tree/blob/master/src/utils/parse.js#L30). Prop is added to `JsonTree` called `allowFunctionEvaluation`. This prop will be set to `true` in v2.2.2, which allows upgrade without losing backwards-compatibility. In v2.2.2, we switched from using `eval` to using [`Function`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Function) to construct anonymous functions. This is better than `eval` for the following reasons: - Arbitrary code should not be able to execute immediately, since the `Function` constructor explicitly *only creates* anonymous functions - Functions are created without local closures, so they only have access to the global scope If you use: - **Version `<2.2.2`**, you must upgrade as soon as possible. - **Version `^2.2.2`**, you must explicitly set `JsonTree`'s `allowFunctionEvaluation` prop to `false` to fully mitigate this vulnerability. - **Version `>=3.0.0`**, `allowFunctionEvaluation` is already set to `false` by default, so no further steps are necessary.