Total
7205 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2022-43616 | 1 Corel | 1 Coreldraw | 2024-11-21 | N/A | 7.8 HIGH |
| This vulnerability allows remote attackers to execute arbitrary code on affected installations of Corel CorelDRAW Graphics Suite 23.5.0.506. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of EMF images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-16371. | |||||
| CVE-2022-43615 | 1 Corel | 1 Coreldraw | 2024-11-21 | N/A | 5.5 MEDIUM |
| This vulnerability allows remote attackers to disclose sensitive information on affected installations of Corel CorelDRAW Graphics Suite 23.5.0.506. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of PDF files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-16370. | |||||
| CVE-2022-43612 | 1 Corel | 1 Coreldraw | 2024-11-21 | N/A | 5.5 MEDIUM |
| This vulnerability allows remote attackers to disclose sensitive information on affected installations of Corel CorelDRAW Graphics Suite 23.5.0.506. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of JP2 images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-16355. | |||||
| CVE-2022-43611 | 1 Corel | 1 Coreldraw | 2024-11-21 | N/A | 5.5 MEDIUM |
| This vulnerability allows remote attackers to disclose sensitive information on affected installations of Corel CorelDRAW Graphics Suite 23.5.0.506. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of BMP images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-16351. | |||||
| CVE-2022-43610 | 1 Corel | 1 Coreldraw | 2024-11-21 | N/A | 5.5 MEDIUM |
| This vulnerability allows remote attackers to disclose sensitive information on affected installations of Corel CorelDRAW Graphics Suite 23.5.0.506. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of GIF images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-16350. | |||||
| CVE-2022-43596 | 2 Debian, Openimageio | 2 Debian Linux, Openimageio | 2024-11-21 | N/A | 5.9 MEDIUM |
| An information disclosure vulnerability exists in the IFFOutput channel interleaving functionality of OpenImageIO Project OpenImageIO v2.4.4.2. A specially crafted ImageOutput Object can lead to leaked heap data. An attacker can provide malicious input to trigger this vulnerability. | |||||
| CVE-2022-43592 | 2 Debian, Openimageio | 2 Debian Linux, Openimageio | 2024-11-21 | N/A | 5.9 MEDIUM |
| An information disclosure vulnerability exists in the DPXOutput::close() functionality of OpenImageIO Project OpenImageIO v2.4.4.2. A specially crafted ImageOutput Object can lead to leaked heap data. An attacker can provide malicious input to trigger this vulnerability. | |||||
| CVE-2022-42833 | 1 Apple | 1 Macos | 2024-11-21 | N/A | 7.8 HIGH |
| An out-of-bounds read was addressed with improved input validation. This issue is fixed in macOS Ventura 13. An app may be able to execute arbitrary code with kernel privileges. | |||||
| CVE-2022-42342 | 3 Adobe, Apple, Microsoft | 6 Acrobat, Acrobat Dc, Acrobat Reader and 3 more | 2024-11-21 | N/A | 5.5 MEDIUM |
| Adobe Acrobat Reader versions 22.002.20212 (and earlier) and 20.005.30381 (and earlier) are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file. | |||||
| CVE-2022-42267 | 2 Microsoft, Nvidia | 2 Windows, Virtual Gpu | 2024-11-21 | N/A | 7.0 HIGH |
| NVIDIA GPU Display Driver for Windows contains a vulnerability where a regular user can cause an out-of-bounds read, which may lead to code execution, denial of service, escalation of privileges, information disclosure, or data tampering. | |||||
| CVE-2022-41988 | 2 Debian, Openimageio | 2 Debian Linux, Openimageio | 2024-11-21 | N/A | 7.5 HIGH |
| An information disclosure vulnerability exists in the OpenImageIO::decode_iptc_iim() functionality of OpenImageIO Project OpenImageIO v2.3.19.0. A specially-crafted TIFF file can lead to a disclosure of sensitive information. An attacker can provide a malicious file to trigger this vulnerability. | |||||
| CVE-2022-41977 | 1 Openimageio | 1 Openimageio | 2024-11-21 | N/A | 3.3 LOW |
| An out of bounds read vulnerability exists in the way OpenImageIO version v2.3.19.0 processes string fields in TIFF image files. A specially-crafted TIFF file can lead to information disclosure. An attacker can provide a malicious file to trigger this vulnerability. | |||||
| CVE-2022-41910 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 4.8 MEDIUM |
| TensorFlow is an open source platform for machine learning. The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. We have patched the issue in GitHub commit a65411a1d69edfb16b25907ffb8f73556ce36bb7. The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.8.4, 2.9.3, and 2.10.1. | |||||
| CVE-2022-41902 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 7.1 HIGH |
| TensorFlow is an open source platform for machine learning. The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. We have patched the issue in GitHub commit a65411a1d69edfb16b25907ffb8f73556ce36bb7. The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.8.4, 2.9.3, and 2.10.1. | |||||
| CVE-2022-41900 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 7.1 HIGH |
| TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1. | |||||
| CVE-2022-41897 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 4.8 MEDIUM |
| TensorFlow is an open source platform for machine learning. If `FractionMaxPoolGrad` is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash. We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. | |||||
| CVE-2022-41895 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 4.8 MEDIUM |
| TensorFlow is an open source platform for machine learning. If `MirrorPadGrad` is given outsize input `paddings`, TensorFlow will give a heap OOB error. We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. | |||||
| CVE-2022-41883 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 6.8 MEDIUM |
| TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. | |||||
| CVE-2022-41880 | 1 Google | 1 Tensorflow | 2024-11-21 | N/A | 6.8 MEDIUM |
| TensorFlow is an open source platform for machine learning. When the `BaseCandidateSamplerOp` function receives a value in `true_classes` larger than `range_max`, a heap oob read occurs. We have patched the issue in GitHub commit b389f5c944cadfdfe599b3f1e4026e036f30d2d4. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. | |||||
| CVE-2022-41873 | 1 Contiki-ng | 1 Contiki-ng | 2024-11-21 | N/A | 4.2 MEDIUM |
| Contiki-NG is an open-source, cross-platform operating system for Next-Generation IoT devices. Versions prior to 4.9 are vulnerable to an Out-of-bounds read. While processing the L2CAP protocol, the Bluetooth Low Energy stack of Contiki-NG needs to map an incoming channel ID to its metadata structure. While looking up the corresponding channel structure in get_channel_for_cid (in os/net/mac/ble/ble-l2cap.c), a bounds check is performed on the incoming channel ID, which is meant to ensure that the channel ID does not exceed the maximum number of supported channels.However, an integer truncation issue leads to only the lowest byte of the channel ID to be checked, which leads to an incomplete out-of-bounds check. A crafted channel ID leads to out-of-bounds memory to be read and written with attacker-controlled data. The vulnerability has been patched in the "develop" branch of Contiki-NG, and will be included in release 4.9. As a workaround, Users can apply the patch in Contiki-NG pull request 2081 on GitHub. | |||||