Vulnerabilities (CVE)

Filtered by vendor Opensuse Subscribe
Filtered by product Leap
Total 1255 CVE
CVE Vendors Products Updated CVSS v2 CVSS v3
CVE-2019-15166 6 Apple, Debian, Fedoraproject and 3 more 6 Mac Os X, Debian Linux, Fedora and 3 more 2021-09-23 5.0 MEDIUM 7.5 HIGH
lmp_print_data_link_subobjs() in print-lmp.c in tcpdump before 4.9.3 lacks certain bounds checks.
CVE-2020-10663 6 Apple, Debian, Fedoraproject and 3 more 6 Macos, Debian Linux, Fedora and 3 more 2021-09-22 5.0 MEDIUM 7.5 HIGH
The JSON gem through 2.2.0 for Ruby, as used in Ruby 2.4 through 2.4.9, 2.5 through 2.5.7, and 2.6 through 2.6.5, has an Unsafe Object Creation Vulnerability. This is quite similar to CVE-2013-0269, but does not rely on poor garbage-collection behavior within Ruby. Specifically, use of JSON parsing methods can lead to creation of a malicious object within the interpreter, with adverse effects that are application-dependent.
CVE-2018-16845 4 Canonical, Debian, Nginx and 1 more 4 Ubuntu Linux, Debian Linux, Nginx and 1 more 2021-09-22 5.8 MEDIUM 6.1 MEDIUM
nginx before versions 1.15.6, 1.14.1 has a vulnerability in the ngx_http_mp4_module, which might allow an attacker to cause infinite loop in a worker process, cause a worker process crash, or might result in worker process memory disclosure by using a specially crafted mp4 file. The issue only affects nginx if it is built with the ngx_http_mp4_module (the module is not built by default) and the .mp4. directive is used in the configuration file. Further, the attack is only possible if an attacker is able to trigger processing of a specially crafted mp4 file with the ngx_http_mp4_module.
CVE-2018-16843 4 Canonical, Debian, Nginx and 1 more 4 Ubuntu Linux, Debian Linux, Nginx and 1 more 2021-09-22 7.8 HIGH 7.5 HIGH
nginx before versions 1.15.6 and 1.14.1 has a vulnerability in the implementation of HTTP/2 that can allow for excessive memory consumption. This issue affects nginx compiled with the ngx_http_v2_module (not compiled by default) if the 'http2' option of the 'listen' directive is used in a configuration file.
CVE-2016-0742 4 Canonical, Debian, Nginx and 1 more 4 Ubuntu Linux, Debian Linux, Nginx and 1 more 2021-09-22 5.0 MEDIUM 7.5 HIGH
The resolver in nginx before 1.8.1 and 1.9.x before 1.9.10 allows remote attackers to cause a denial of service (invalid pointer dereference and worker process crash) via a crafted UDP DNS response.
CVE-2016-0746 4 Canonical, Debian, Nginx and 1 more 4 Ubuntu Linux, Debian Linux, Nginx and 1 more 2021-09-22 7.5 HIGH 9.8 CRITICAL
Use-after-free vulnerability in the resolver in nginx 0.6.18 through 1.8.0 and 1.9.x before 1.9.10 allows remote attackers to cause a denial of service (worker process crash) or possibly have unspecified other impact via a crafted DNS response related to CNAME response processing.
CVE-2016-0747 4 Canonical, Debian, Nginx and 1 more 4 Ubuntu Linux, Debian Linux, Nginx and 1 more 2021-09-22 5.0 MEDIUM 5.3 MEDIUM
The resolver in nginx before 1.8.1 and 1.9.x before 1.9.10 does not properly limit CNAME resolution, which allows remote attackers to cause a denial of service (worker process resource consumption) via vectors related to arbitrary name resolution.
CVE-2020-15193 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-21 5.5 MEDIUM 7.1 HIGH
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
CVE-2020-15190 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-21 5.0 MEDIUM 5.3 MEDIUM
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15191 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-21 5.0 MEDIUM 5.3 MEDIUM
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
CVE-2020-15192 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-21 4.0 MEDIUM 4.3 MEDIUM
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
CVE-2020-15705 7 Canonical, Debian, Gnu and 4 more 14 Ubuntu Linux, Debian Linux, Grub2 and 11 more 2021-09-21 4.4 MEDIUM 6.4 MEDIUM
GRUB2 fails to validate kernel signature when booted directly without shim, allowing secure boot to be bypassed. This only affects systems where the kernel signing certificate has been imported directly into the secure boot database and the GRUB image is booted directly without the use of shim. This issue affects GRUB2 version 2.04 and prior versions.
CVE-2020-10683 5 Canonical, Dom4j Project, Netapp and 2 more 34 Ubuntu Linux, Dom4j, Oncommand Api Services and 31 more 2021-09-17 7.5 HIGH 9.8 CRITICAL
dom4j before 2.0.3 and 2.1.x before 2.1.3 allows external DTDs and External Entities by default, which might enable XXE attacks. However, there is popular external documentation from OWASP showing how to enable the safe, non-default behavior in any application that uses dom4j.
CVE-2020-8492 5 Canonical, Debian, Fedoraproject and 2 more 5 Ubuntu Linux, Debian Linux, Fedora and 2 more 2021-09-16 7.1 HIGH 6.5 MEDIUM
Python 2.7 through 2.7.17, 3.5 through 3.5.9, 3.6 through 3.6.10, 3.7 through 3.7.6, and 3.8 through 3.8.1 allows an HTTP server to conduct Regular Expression Denial of Service (ReDoS) attacks against a client because of urllib.request.AbstractBasicAuthHandler catastrophic backtracking.
CVE-2020-15195 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 6.5 MEDIUM 8.8 HIGH
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15203 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 5.0 MEDIUM 7.5 HIGH
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the `fill` argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed. This may result in segmentation fault. The issue is patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15211 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 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-2020-15204 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 5.0 MEDIUM 5.3 MEDIUM
In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling `tf.raw_ops.GetSessionHandle` or `tf.raw_ops.GetSessionHandleV2` results in a null pointer dereference In linked snippet, in eager mode, `ctx->session_state()` returns `nullptr`. Since code immediately dereferences this, we get a segmentation fault. The issue is patched in commit 9a133d73ae4b4664d22bd1aa6d654fec13c52ee1, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15210 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 5.8 MEDIUM 6.5 MEDIUM
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15208 2 Google, Opensuse 2 Tensorflow, Leap 2021-09-16 7.5 HIGH 9.8 CRITICAL
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.