rainbutterfly/cve_corpus huggingface dataset:
CVE-2022-29183 Reflected XSS in GoCD
GoCD is a continuous delivery server. GoCD versions 20.2.0 until 21.4.0 are vulnerable to reflected cross-site scripting via abuse of the pipeline comparison function's error handling to render arbitrary HTML into the returned page. This could allow an attacker to trick a victim into executing code which would allow the attacker to operate on, or gain control over the same resources as the victim had access to. This issue is fixed in GoCD 21.4.0. As a workaround, block access to `/go/compare/.*` prior to GoCD Server via a reverse proxy, web application firewall or equivalent, which would prevent use of the pipeline comparison function.
Problem types: cwe_id: CWE-79
description: CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Affected products: vendor: gocd
product: gocd
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 4.3
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: LOW
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
version: 3.1
Published: 2022-05-20T19:10:11.000Z
CVE-2022-29184 Command Injection/Argument Injection in GoCD
GoCD is a continuous delivery server. In GoCD versions prior to 22.1.0, it is possible for existing authenticated users who have permissions to edit or create pipeline materials or pipeline configuration repositories to get remote code execution capability on the GoCD server via configuring a malicious branch name which abuses Mercurial hooks/aliases to exploit a command injection weakness. An attacker would require access to an account with existing GoCD administration permissions to either create/edit (`hg`-based) configuration repositories; create/edit pipelines and their (`hg`-based) materials; or, where "pipelines-as-code" configuration repositories are used, to commit malicious configuration to such an external repository which will be automatically parsed into a pipeline configuration and (`hg`) material definition by the GoCD server. This issue is fixed in GoCD 22.1.0. As a workaround, users who do not use/rely upon Mercurial materials can uninstall/remove the `hg`/Mercurial binary from the underlying GoCD Server operating system or Docker image.
Problem types: cwe_id: CWE-77
description: CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection')
cwe_id: CWE-88
description: CWE-88: Improper Neutralization of Argument Delimiters in a Command ('Argument Injection')
Affected products: vendor: gocd
product: gocd
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 8.8
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
version: 3.1
Published: 2022-05-20T19:25:14.000Z
CVE-2022-29185 Observable Timing Discrepancy in totp-rs
totp-rs is a Rust library that permits the creation of 2FA authentification tokens per time-based one-time password (TOTP). Prior to version 1.1.0, token comparison was not constant time, and could theorically be used to guess value of an TOTP token, and thus reuse it in the same time window. The attacker would have to know the password beforehand nonetheless. Starting with patched version 1.1.0, the library uses constant-time comparison. There are currently no known workarounds.
Problem types: cwe_id: CWE-208
description: CWE-208: Observable Timing Discrepancy
cwe_id: CWE-203
description: CWE-203: Observable Discrepancy
Affected products: vendor: constantoine
product: totp-rs
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 4.2
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: HIGH
scope: UNCHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:U/C:H/I:N/A:N
version: 3.1
Published: 2022-05-20T19:30:12.000Z
CVE-2022-29186 Use of Hard-coded Cryptographic Key in rundeck/rundeck, rundeckpro/enterprise
Rundeck is an open source automation service with a web console, command line tools and a WebAPI. Rundeck community and rundeck-enterprise docker images contained a pre-generated SSH keypair. If the id_rsa.pub public key of the keypair was copied to authorized_keys files on remote host, those hosts would allow access to anyone with the exposed private credentials. This misconfiguration only impacts Rundeck Docker instances of PagerDuty® Process Automation On Prem (formerly Rundeck) version 4.0 and earlier, not Debian, RPM or .WAR. Additionally, the id_rsa.pub file would have to be copied from the Docker image filesystem contents without overwriting it and used to configure SSH access on a host. A patch on Rundeck's `main` branch has removed the pre-generated SSH key pair, but it does not remove exposed keys that have been configured. To patch, users must run a script on hosts in their environment to search for exposed keys and rotate them. Two workarounds are available: Do not use any pre-existing public key file from the rundeck docker images to allow SSH access by adding it to authorized_keys files and, if you have copied the public key file included in the docker image, remove it from any authorized_keys files.
Problem types: cwe_id: CWE-321
description: CWE-321: Use of Hard-coded Cryptographic Key
Affected products: vendor: rundeck
product: rundeck
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 9.1
baseSeverity: CRITICAL
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
version: 3.1
Published: 2022-05-20T20:20:11.000Z
CVE-2022-29187 Bypass of safe.directory protections in Git
Git is a distributed revision control system. Git prior to versions 2.37.1, 2.36.2, 2.35.4, 2.34.4, 2.33.4, 2.32.3, 2.31.4, and 2.30.5, is vulnerable to privilege escalation in all platforms. An unsuspecting user could still be affected by the issue reported in CVE-2022-24765, for example when navigating as root into a shared tmp directory that is owned by them, but where an attacker could create a git repository. Versions 2.37.1, 2.36.2, 2.35.4, 2.34.4, 2.33.4, 2.32.3, 2.31.4, and 2.30.5 contain a patch for this issue. The simplest way to avoid being affected by the exploit described in the example is to avoid running git as root (or an Administrator in Windows), and if needed to reduce its use to a minimum. While a generic workaround is not possible, a system could be hardened from the exploit described in the example by removing any such repository if it exists already and creating one as root to block any future attacks.
Problem types: cwe_id: CWE-282
description: CWE-282: Improper Ownership Management
cwe_id: CWE-427
description: CWE-427: Uncontrolled Search Path Element
Affected products: vendor: git
product: git
CVSS v3.1: version: 3.1
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
attackVector: LOCAL
attackComplexity: LOW
privilegesRequired: LOW
userInteraction: NONE
scope: UNCHANGED
confidentialityImpact: HIGH
integrityImpact: HIGH
availabilityImpact: HIGH
baseScore: 7.8
baseSeverity: HIGH
Published: 2022-07-12T00:00:00.000Z
CVE-2022-29188 Smokescreen SSRF via deny list bypass (square brackets) in Smokescreen
Smokescreen is an HTTP proxy. The primary use case for Smokescreen is to prevent server-side request forgery (SSRF) attacks in which external attackers leverage the behavior of applications to connect to or scan internal infrastructure. Smokescreen also offers an option to deny access to additional (e.g., external) URLs by way of a deny list. There was an issue in Smokescreen that made it possible to bypass the deny list feature by surrounding the hostname with square brackets (e.g. `[example.com]`). This only impacted the HTTP proxy functionality of Smokescreen. HTTPS requests were not impacted. Smokescreen version 0.0.4 contains a patch for this issue.
Problem types: cwe_id: CWE-918
description: CWE-918: Server-Side Request Forgery (SSRF)
Affected products: vendor: stripe
product: smokescreen
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 5.3
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
version: 3.1
Published: 2022-05-20T23:50:10.000Z
CVE-2022-29189 Buffer for inbound DTLS fragments has no limit
Pion DTLS is a Go implementation of Datagram Transport Layer Security. Prior to version 2.1.4, a buffer that was used for inbound network traffic had no upper limit. Pion DTLS would buffer all network traffic from the remote user until the handshake completes or timed out. An attacker could exploit this to cause excessive memory usage. Version 2.1.4 contains a patch for this issue. There are currently no known workarounds available.
Problem types: cwe_id: CWE-120
description: CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
Affected products: vendor: pion
product: dtls
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 5.3
baseSeverity: MEDIUM
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:L
version: 3.1
Published: 2022-05-20T23:55:16.000Z
CVE-2022-29190 Header reconstruction method can be thrown into an infinite loop in Pion DTLS
Pion DTLS is a Go implementation of Datagram Transport Layer Security. Prior to version 2.1.4, an attacker can send packets that sends Pion DTLS into an infinite loop when processing. Version 2.1.4 contains a patch for this issue. There are currently no known workarounds available.
Problem types: cwe_id: CWE-835
description: CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop')
Affected products: vendor: pion
product: dtls
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: 2022-05-20T23:55:10.000Z
CVE-2022-29191 Missing validation causes denial of service via `GetSessionTensor` 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.GetSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. 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: 2022-05-20T20:50:11.000Z
CVE-2022-29192 Missing validation crashes `QuantizeAndDequantizeV4Grad` 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.QuantizeAndDequantizeV4Grad` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. 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: 2022-05-20T20:30:14.000Z
CVE-2022-29193 Missing validation causes `TensorSummaryV2` in TensorFlow to crash
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.TensorSummaryV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. 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: 2022-05-20T21:20:14.000Z
CVE-2022-29194 Missing validation causes denial of service via `DeleteSessionTensor` 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.DeleteSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. 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: 2022-05-20T21:10:12.000Z
CVE-2022-29195 Missing validation causes denial of service in TensorFlow via `StagePeek`
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.StagePeek` 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 `index` is a scalar but there is no validation for this before accessing its value. 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: 2022-05-20T22:00:15.000Z
CVE-2022-29196 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.Conv3DBackpropFilterV2` 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 does not validate that the `filter_sizes` argument is a vector. 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: 2022-05-20T21:55:12.000Z
CVE-2022-29197 Missing validation causes denial of service in TensorFlow via `UnsortedSegmentJoin`
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 scalar but there is no validation for this before accessing its value. 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: 2022-05-20T21:55:18.000Z
CVE-2022-29198 Missing validation causes denial of service in TensorFlow via `SparseTensorToCSRSparseMatrix`
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.SparseTensorToCSRSparseMatrix` 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 `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. 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: 2022-05-20T21:50:12.000Z
CVE-2022-29199 Missing validation causes denial of service in TensorFlow via `LoadAndRemapMatrix`
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.LoadAndRemapMatrix 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 `initializing_values` is a vector but there is no validation for this before accessing its value. 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: 2022-05-20T21:40:12.000Z
CVE-2022-29200 Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`
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.LSTMBlockCell` 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 does not validate the ranks of any of the arguments to this API call. This results in `CHECK`-failures when the elements of the tensor are accessed. 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: 2022-05-20T21:30:14.000Z
CVE-2022-29201 Missing validation in `QuantizedConv2D` results in undefined behavior 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.QuantizedConv2D` does not fully validate the input arguments. In this case, references get bound to `nullptr` for each argument that is empty. 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: 2022-05-20T23:00:15.000Z
CVE-2022-29202 Denial of service in TensorFlow due to lack of validation in `tf.ragged.constant`
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.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. 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-400
description: CWE-400: Uncontrolled Resource Consumption
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: 2022-05-20T22:55:13.000Z
CVE-2022-29203 Integer overflow in `SpaceToBatchND` 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.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in 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-190
description: CWE-190: Integer Overflow or Wraparound
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: 2022-05-20T22:50:11.000Z