rainbutterfly/cve_corpus huggingface dataset:
CVE-2022-29204 Missing validation causes denial of service in TensorFlow via `Conv3DBackpropFilterV2`
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-191
description: CWE-191: Integer Underflow (Wrap or Wraparound)
cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T22:40:13.000Z
CVE-2022-29205 Segfault due to missing support for quantized types in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-908
description: CWE-908: Use of Uninitialized Resource
cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T22:25:14.000Z
CVE-2022-29206 Missing validation results in undefined behavior in `SparseTensorDenseAdd` in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorDenseAdd` does not fully validate the input arguments. In this case, a reference gets bound to a `nullptr` during kernel execution. This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T22:15:13.000Z
CVE-2022-29207 Undefined behavior when users supply invalid resource handles in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
cwe_id: CWE-475
description: CWE-475: Undefined Behavior for Input to API
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T22:10:12.000Z
CVE-2022-29208 Segfault and Out-of-bounds Write write due to incomplete validation in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.EditDistance` has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service. In multiple places throughout the code, one may compute an index for a write operation. However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for `loc`. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-787
description: CWE-787: Out-of-bounds Write
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 7.1
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
version: 3.1
Published: 2022-05-20T22:30:13.000Z
CVE-2022-29209 Type confusion leading to `CHECK`-failure based denial of service in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the macros that TensorFlow uses for writing assertions (e.g., `CHECK_LT`, `CHECK_GT`, etc.) have an incorrect logic when comparing `size_t` and `int` values. Due to type conversion rules, several of the macros would trigger incorrectly. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-843
description: CWE-843: Access of Resource Using Incompatible Type ('Type Confusion')
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T23:25:14.000Z
CVE-2022-29210 Heap buffer overflow due to incorrect hash function in TensorFlow
TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function used total estimated `AllocatedBytes()`, which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. `int32_t`). It also tried to access individual tensor bytes through `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the `.data()` buffer. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.
Problem types: cwe_id: CWE-120
description: CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
cwe_id: CWE-122
description: CWE-122: Heap-based Buffer Overflow
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T23:25:21.000Z
CVE-2022-29211 Segfault in TensorFlow if `tf.histogram_fixed_width` is called with NaN values
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T23:20:15.000Z
CVE-2022-29212 Core dump when loading TFLite models with quantization in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T23:15:15.000Z
CVE-2022-29213 Incomplete validation in signal ops leads to crashes in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-20T23:30:15.000Z
CVE-2022-29214 URL Redirection to Untrusted Site ('Open Redirect') in next-auth
NextAuth.js (next-auth) is am open source authentication solution for Next.js applications. Prior to versions 3.29.3 and 4.3.3, an open redirect vulnerability is present when the developer is implementing an OAuth 1 provider. Versions 3.29.3 and 4.3.3 contain a patch for this issue. The maintainers recommend adding a certain configuration to one's `callbacks` option as a workaround for those unable to upgrade.
Problem types: cwe_id: CWE-601
description: CWE-601: URL Redirection to Untrusted Site ('Open Redirect')
Affected products: vendor: nextauthjs
product: next-auth
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 6.1
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: NONE
scope: CHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
version: 3.1
Published: 2022-05-20T23:45:11.000Z
CVE-2022-29215 Argument Injection in RegionProtect
RegionProtect is a plugin that allows users to manage certain events in certain regions of the world. Versions prior to 1.1.0 contain a YAML injection vulnerability that can cause an instant server crash if the passed arguments are not matched. Version 1.1.0 contains a patch for this issue. As a workaround, restrict operator permissions to untrusted people and avoid entering arguments likely to cause a crash.
Problem types: cwe_id: CWE-88
description: CWE-88: Improper Neutralization of Argument Delimiters in a Command ('Argument Injection')
Affected products: vendor: kaidomc-pm-pl
product: RegionProtect
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 7.5
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-05-21T00:05:10.000Z
CVE-2022-29216 Code injection in `saved_model_cli` in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4.
Problem types: cwe_id: CWE-94
description: CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 7.8
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
version: 3.1
Published: 2022-05-20T23:35:13.000Z
CVE-2022-29217 Key confusion through non-blocklisted public key formats in PyJWT
PyJWT is a Python implementation of RFC 7519. PyJWT supports multiple different JWT signing algorithms. With JWT, an attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify `jwt.algorithms.get_default_algorithms()` to get support for all algorithms, or specify a single algorithm. The issue is not that big as `algorithms=jwt.algorithms.get_default_algorithms()` has to be used. Users should upgrade to v2.4.0 to receive a patch for this issue. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.
Problem types: cwe_id: CWE-327
description: CWE-327: Use of a Broken or Risky Cryptographic Algorithm
Affected products: vendor: jpadilla
product: pyjwt
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.4
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N
version: 3.1
Published: 2022-05-24T14:10:10.000Z
CVE-2022-29218 Unauthorized takeover for new versions of some platform-specific gems
RubyGems is a package registry used to supply software for the Ruby language ecosystem. An ordering mistake in the code that accepts gem uploads allowed some gems (with platforms ending in numbers, like `arm64-darwin-21`) to be temporarily replaced in the CDN cache by a malicious package. The bug has been patched, and is believed to have never been exploited, based on an extensive review of logs and existing gems by rubygems. The easiest way to ensure that an application has not been exploited by this vulnerability is to verify all downloaded .gems checksums match the checksum recorded in the RubyGems.org database. RubyGems.org has been patched and is no longer vulnerable to this issue.
Problem types: cwe_id: CWE-269
description: CWE-269: Improper Privilege Management
cwe_id: CWE-290
description: CWE-290: Authentication Bypass by Spoofing
Affected products: vendor: rubygems
product: rubygems.org
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.7
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: LOW
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:H/A:N
version: 3.1
Published: 2022-05-12T23:55:08.000Z
CVE-2022-29219 Integer Overflow in Lodestar
Lodestar is a TypeScript implementation of the Ethereum Consensus specification. Prior to version 0.36.0, there is a possible consensus split given maliciously-crafted `AttesterSlashing` or `ProposerSlashing` being included on-chain. Because the developers represent `uint64` values as native javascript `number`s, there is an issue when those variables with large (greater than 2^53) `uint64` values are included on chain. In those cases, Lodestar may view valid_`AttesterSlashing` or `ProposerSlashing` as invalid, due to rounding errors in large `number` values. This causes a consensus split, where Lodestar nodes are forked away from the main network. Similarly, Lodestar may consider invalid `ProposerSlashing` as valid, thus including in proposed blocks that will be considered invalid by the network. Version 0.36.0 contains a fix for this issue. As a workaround, use `BigInt` to represent `Slot` and `Epoch` values in `AttesterSlashing` and `ProposerSlashing` objects. `BigInt` is too slow to be used in all `Slot` and `Epoch` cases, so one may carefully use `BigInt` just where necessary for consensus.
Problem types: cwe_id: CWE-190
description: CWE-190: Integer Overflow or Wraparound
Affected products: vendor: ChainSafe
product: lodestar
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.5
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N
version: 3.1
Published: 2022-05-24T14:15:14.000Z
CVE-2022-29220 No verification of commits origin in github-action-merge-dependabot
github-action-merge-dependabot is an action that automatically approves and merges dependabot pull requests (PRs). Prior to version 3.2.0, github-action-merge-dependabot does not check if a commit created by dependabot is verified with the proper GPG key. There is just a check if the actor is set to `dependabot[bot]` to determine if the PR is a legit PR. Theoretically, an owner of a seemingly valid and legit action in the pipeline can check if the PR is created by dependabot and if their own action has enough permissions to modify the PR in the pipeline. If so, they can modify the PR by adding a second seemingly valid and legit commit to the PR, as they can set arbitrarily the username and email in for commits in git. Because the bot only checks if the actor is valid, it would pass the malicious changes through and merge the PR automatically, without getting noticed by project maintainers. It would probably not be possible to determine where the malicious commit came from, as it would only say `dependabot[bot]` and the corresponding email-address. Version 3.2.0 contains a patch for this issue.
Problem types: cwe_id: CWE-283
description: CWE-283: Unverified Ownership
Affected products: vendor: fastify
product: github-action-merge-dependabot
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 6.5
baseSeverity: MEDIUM
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:N
version: 3.1
Published: 2022-05-31T16:10:10.000Z
CVE-2022-29221 PHP Code Injection by malicious block or filename in Smarty
Smarty is a template engine for PHP, facilitating the separation of presentation (HTML/CSS) from application logic. Prior to versions 3.1.45 and 4.1.1, template authors could inject php code by choosing a malicious {block} name or {include} file name. Sites that cannot fully trust template authors should upgrade to versions 3.1.45 or 4.1.1 to receive a patch for this issue. There are currently no known workarounds.
Problem types: cwe_id: CWE-94
description: CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected products: vendor: smarty-php
product: smarty
CVSS v3.1: version: 3.1
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
attackVector: NETWORK
attackComplexity: LOW
privilegesRequired: LOW
userInteraction: NONE
scope: UNCHANGED
confidentialityImpact: HIGH
integrityImpact: HIGH
availabilityImpact: HIGH
baseScore: 8.8
baseSeverity: HIGH
Published: 2022-05-24T00:00:00.000Z
CVE-2022-29222 Improper Certificate Validation in Pion DTLS
Pion DTLS is a Go implementation of Datagram Transport Layer Security. Prior to version 2.1.5, a DTLS Client could provide a Certificate that it doesn't posses the private key for and Pion DTLS wouldn't reject it. This issue affects users that are using Client certificates only. The connection itself is still secure. The Certificate provided by clients can't be trusted when using a Pion DTLS server prior to version 2.1.5. Users should upgrade to version 2.1.5 to receive a patch. There are currently no known workarounds.
Problem types: cwe_id: CWE-295
description: CWE-295: Improper Certificate Validation
Affected products: vendor: pion
product: dtls
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:H/A:N
version: 3.1
Published: 2022-05-21T00:00:15.000Z
CVE-2022-29223 Buffer overflow on HUB descriptor in Azure RTOS USBX
Azure RTOS USBX is a USB host, device, and on-the-go (OTG) embedded stack. In versions prior to 6.1.10, an attacker can cause a buffer overflow by providing the Azure RTOS USBX host stack a HUB descriptor with `bNbPorts` set to a value greater than `UX_MAX_TT` which defaults to 8. For a `bNbPorts` value of 255, the implementation of `ux_host_class_hub_descriptor_get` function will modify the contents of `hub` -> `ux_host_class_hub_device` -> `ux_device_hub_tt` array violating the end boundary by 255 - `UX_MAX_TT` items. The USB host stack needs to validate the number of ports reported by the hub, and if the value is larger than UX_MAX_TT, USB stack needs to reject the request. This fix has been included in USBX release 6.1.10.
Problem types: cwe_id: CWE-120
description: CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
Affected products: vendor: azure-rtos
product: usbx
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.5
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: HIGH
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N
version: 3.1
Published: 2022-05-24T14:25:10.000Z