Total
7102 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2020-16048 | 1 Google | 1 Angle | 2024-11-21 | 4.3 MEDIUM | 6.5 MEDIUM |
| Out of bounds read in ANGLE allowed a remote attacker to obtain sensitive data via a crafted HTML page. | |||||
| CVE-2020-16041 | 1 Google | 1 Chrome | 2024-11-21 | 5.8 MEDIUM | 8.1 HIGH |
| Out of bounds read in networking in Google Chrome prior to 87.0.4280.88 allowed a remote attacker who had compromised the renderer process to obtain potentially sensitive information from process memory via a crafted HTML page. | |||||
| CVE-2020-15981 | 4 Debian, Fedoraproject, Google and 1 more | 4 Debian Linux, Fedora, Chrome and 1 more | 2024-11-21 | 4.3 MEDIUM | 6.5 MEDIUM |
| Out of bounds read in audio in Google Chrome prior to 86.0.4240.75 allowed a remote attacker to obtain potentially sensitive information from process memory via a crafted HTML page. | |||||
| CVE-2020-15890 | 3 Canonical, Debian, Luajit | 3 Ubuntu Linux, Debian Linux, Luajit | 2024-11-21 | 5.0 MEDIUM | 7.5 HIGH |
| LuaJit through 2.1.0-beta3 has an out-of-bounds read because __gc handler frame traversal is mishandled. | |||||
| CVE-2020-15889 | 1 Lua | 1 Lua | 2024-11-21 | 7.5 HIGH | 9.8 CRITICAL |
| Lua 5.4.0 has a getobjname heap-based buffer over-read because youngcollection in lgc.c uses markold for an insufficient number of list members. | |||||
| CVE-2020-15888 | 1 Lua | 1 Lua | 2024-11-21 | 6.8 MEDIUM | 8.8 HIGH |
| Lua through 5.4.0 mishandles the interaction between stack resizes and garbage collection, leading to a heap-based buffer overflow, heap-based buffer over-read, or use-after-free. | |||||
| CVE-2020-15630 | 2 Foxitsoftware, Microsoft | 2 Foxit Studio Photo, Windows | 2024-11-21 | 6.8 MEDIUM | 7.8 HIGH |
| This vulnerability allows remote attackers to disclose sensitive information on affected installations of Foxit Studio Photo 3.6.6.922. 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 handling of PNG 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 structure. An attacker can leverage this in conjunction with other vulnerabilities to execute code in the context of the current process. Was ZDI-CAN-10977. | |||||
| CVE-2020-15603 | 2 Microsoft, Trendmicro | 5 Windows, Antivirus\+ 2020, Internet Security 2020 and 2 more | 2024-11-21 | 7.8 HIGH | 7.5 HIGH |
| An invalid memory read vulnerability in a Trend Micro Secuity 2020 (v16.0.0.1302 and below) consumer family of products' driver could allow an attacker to manipulate the specific driver to do a system call operation with an invalid address, resulting in a potential system crash. | |||||
| CVE-2020-15572 | 1 Torproject | 1 Tor | 2024-11-21 | 4.3 MEDIUM | 7.5 HIGH |
| Tor before 0.4.3.6 has an out-of-bounds memory access that allows a remote denial-of-service (crash) attack against Tor instances built to use Mozilla Network Security Services (NSS), aka TROVE-2020-001. | |||||
| CVE-2020-15476 | 3 Debian, Linux, Ntop | 3 Debian Linux, Linux Kernel, Ndpi | 2024-11-21 | 5.0 MEDIUM | 7.5 HIGH |
| In nDPI through 3.2, the Oracle protocol dissector has a heap-based buffer over-read in ndpi_search_oracle in lib/protocols/oracle.c. | |||||
| CVE-2020-15473 | 1 Ntop | 1 Ndpi | 2024-11-21 | 6.4 MEDIUM | 9.1 CRITICAL |
| In nDPI through 3.2, the OpenVPN dissector is vulnerable to a heap-based buffer over-read in ndpi_search_openvpn in lib/protocols/openvpn.c. | |||||
| CVE-2020-15472 | 2 Debian, Ntop | 2 Debian Linux, Ndpi | 2024-11-21 | 6.4 MEDIUM | 9.1 CRITICAL |
| In nDPI through 3.2, the H.323 dissector is vulnerable to a heap-based buffer over-read in ndpi_search_h323 in lib/protocols/h323.c, as demonstrated by a payload packet length that is too short. | |||||
| CVE-2020-15471 | 1 Ntop | 1 Ndpi | 2024-11-21 | 6.4 MEDIUM | 9.1 CRITICAL |
| In nDPI through 3.2, the packet parsing code is vulnerable to a heap-based buffer over-read in ndpi_parse_packet_line_info in lib/ndpi_main.c. | |||||
| CVE-2020-15395 | 2 Fedoraproject, Mediaarea | 2 Fedora, Mediainfo | 2024-11-21 | 6.8 MEDIUM | 7.8 HIGH |
| In MediaInfoLib in MediaArea MediaInfo 20.03, there is a stack-based buffer over-read in Streams_Fill_PerStream in Multiple/File_MpegPs.cpp (aka an off-by-one during MpegPs parsing). | |||||
| CVE-2020-15265 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.0 MEDIUM | 5.9 MEDIUM |
| In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. | |||||
| CVE-2020-15211 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 5.8 MEDIUM | 4.8 MEDIUM |
| In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. This results in special casing during validation at model loading time. Unfortunately, this means that the `-1` index is a valid tensor index for any operator, including those that don't expect optional inputs and including for output tensors. Thus, this allows writing and reading from outside the bounds of heap allocated arrays, although only at a specific offset from the start of these arrays. This results in both read and write gadgets, albeit very limited in scope. The issue is patched in several commits (46d5b0852, 00302787b7, e11f5558, cd31fd0ce, 1970c21, and fff2c83), and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that only operators which accept optional inputs use the `-1` special value and only for the tensors that they expect to be optional. Since this allow-list type approach is erro-prone, we advise upgrading to the patched code. | |||||
| CVE-2020-15208 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 7.5 HIGH | 7.4 HIGH |
| In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | |||||
| CVE-2020-15196 | 1 Google | 1 Tensorflow | 2024-11-21 | 6.5 MEDIUM | 8.5 HIGH |
| In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | |||||
| CVE-2020-14937 | 1 Contiki-ng | 1 Contiki-ng | 2024-11-21 | 6.4 MEDIUM | 9.1 CRITICAL |
| Memory access out of buffer boundaries issues was discovered in Contiki-NG 4.4 through 4.5, in the SNMP BER encoder/decoder. The length of provided input/output buffers is insufficiently verified during the encoding and decoding of data. This may lead to out-of-bounds buffer read or write access in BER decoding and encoding functions. | |||||
| CVE-2020-14700 | 2 Opensuse, Oracle | 2 Leap, Vm Virtualbox | 2024-11-21 | 4.7 MEDIUM | 5.3 MEDIUM |
| Vulnerability in the Oracle VM VirtualBox product of Oracle Virtualization (component: Core). Supported versions that are affected are Prior to 5.2.44, prior to 6.0.24 and prior to 6.1.12. Difficult to exploit vulnerability allows high privileged attacker with logon to the infrastructure where Oracle VM VirtualBox executes to compromise Oracle VM VirtualBox. While the vulnerability is in Oracle VM VirtualBox, attacks may significantly impact additional products. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle VM VirtualBox accessible data. CVSS 3.1 Base Score 5.3 (Confidentiality impacts). CVSS Vector: (CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:C/C:H/I:N/A:N). | |||||