rainbutterfly/cve_corpus huggingface dataset:
CVE-2022-35993 `CHECK` fail in `SetSize` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:20:25.000Z
CVE-2022-35994 `CHECK` fail in `CollectiveGather` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:20:31.000Z
CVE-2022-35995 `CHECK` fail in `AudioSummaryV2` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:15:12.000Z
CVE-2022-35996 Floating point exception in `Conv2D` in TensorFlow
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.
Problem types: cwe_id: CWE-369
description: CWE-369: Divide By Zero
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:55:10.000Z
CVE-2022-35997 `CHECK` fail in `tf.sparse.cross` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:15:18.000Z
CVE-2022-35998 `CHECK` fail in `EmptyTensorList` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:15:23.000Z
CVE-2022-35999 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:15:28.000Z
CVE-2022-36000 Null dereference on MLIR on empty function attributes in TensorFlow
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.
Problem types: cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:30:25.000Z
CVE-2022-36001 `CHECK` fail in `DrawBoundingBoxes` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:10:10.000Z
CVE-2022-36002 `CHECK` fail in `Unbatch` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:10:15.000Z
CVE-2022-36003 `CHECK` fail in `RandomPoissonV2` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:10:21.000Z
CVE-2022-36004 `CHECK` fail in `tf.random.gamma` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:10:26.000Z
CVE-2022-36005 `CHECK` fail in `FakeQuantWithMinMaxVarsGradient` in TensorFlow
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.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:10:31.000Z
CVE-2022-36006 Authenticated remote code execution due to insecure deserialization (GHSL-2022-063)
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.
Problem types: cwe_id: CWE-502
description: CWE-502: Deserialization of Untrusted Data
cwe_id: CWE-94
description: CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected products: vendor: arvados
product: arvados
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 7.9
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: CHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:L
version: 3.1
Published: 2022-08-14T00:20:10.000Z
CVE-2022-36007 Partial Path Traversal in com.github.jlangch:venice
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.
Problem types: cwe_id: CWE-22
description: CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Affected products: vendor: jlangch
product: venice
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: NONE
baseScore: 6.1
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:H/A:N
version: 3.1
Published: 2022-08-14T00:25:10.000Z
CVE-2022-36008 Message length overflow in frontier
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.
Problem types: cwe_id: CWE-190
description: CWE-190: Integer Overflow or Wraparound
Affected products: vendor: paritytech
product: frontier
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 7.1
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L
version: 3.1
Published: 2022-08-19T20:25:10.000Z
CVE-2022-36009 Incorrect parsing of access level in gomatrixserverlib and dendrite
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.
Problem types: cwe_id: CWE-863
description: CWE-863: Incorrect Authorization
Affected products: vendor: matrix-org
product: gomatrixserverlib
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 5
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L
version: 3.1
Published: 2022-08-19T20:35:09.000Z
CVE-2022-36010 Arbitrary code execution via function parsing in react-editable-json-tree
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.
Problem types: cwe_id: CWE-95
description: CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')
Affected products: vendor: oxyno-zeta
product: react-editable-json-tree
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 10
baseSeverity: CRITICAL
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: NONE
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
version: 3.1
Published: 2022-08-15T18:30:14.000Z
CVE-2022-36011 Null dereference on MLIR on empty function attributes in TensorFlow
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 1cf45b831eeb0cab8655c9c7c5d06ec6f45fc41b. 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.
Problem types: cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:30:21.000Z