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This project will be discontinued after December 13, 2021. [more]
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Leap
(Opensuse)| Date | Id | Summary | Products | Score | Patch | Annotated |
|---|---|---|---|---|---|---|
| 2020-09-25 | CVE-2020-15192 | 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... | Tensorflow, Leap | 4.3 | ||
| 2020-09-25 | CVE-2020-15195 | 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. | Tensorflow, Leap | 8.8 | ||
| 2020-09-25 | CVE-2020-15193 | 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`... | Tensorflow, Leap | 7.1 | ||
| 2020-09-25 | CVE-2020-15202 | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults,... | Tensorflow, Leap | 9.0 | ||
| 2020-09-25 | CVE-2020-15203 | 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. | Tensorflow, Leap | 7.5 | ||
| 2020-09-25 | CVE-2020-15205 | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit... | Tensorflow, Leap | 9.8 | ||
| 2020-09-25 | CVE-2020-15207 | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue... | Tensorflow, Leap | 9.0 | ||
| 2020-09-25 | CVE-2020-15210 | 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. | Tensorflow, Leap | 6.5 | ||
| 2020-02-20 | CVE-2020-9272 | ProFTPD 1.3.7 has an out-of-bounds (OOB) read vulnerability in mod_cap via the cap_text.c cap_to_text function. | Backports_sle, Leap, Proftpd, Simatic_net_cp_1543\-1_firmware, Simatic_net_cp_1545\-1_firmware | 7.5 | ||
| 2019-08-14 | CVE-2019-9506 | The Bluetooth BR/EDR specification up to and including version 5.1 permits sufficiently low encryption key length and does not prevent an attacker from influencing the key length negotiation. This allows practical brute-force attacks (aka "KNOB") that can decrypt traffic and inject arbitrary ciphertext without the victim noticing. | Iphone_os, Mac_os_x, Tvos, Watchos, Ubuntu_linux, Debian_linux, Android, Alp\-Al00b_firmware, Ares\-Al00b_firmware, Ares\-Al10d_firmware, Ares\-Tl00c_firmware, Asoka\-Al00ax_firmware, Atomu\-L33_firmware, Atomu\-L41_firmware, Atomu\-L42_firmware, Barca\-Al00_firmware, Berkeley\-Al20_firmware, Berkeley\-L09_firmware, Berkeley\-Tl10_firmware, Bla\-Al00b_firmware, Bla\-L29c_firmware, Bla\-Tl00b_firmware, Cairogo\-L22_firmware, Charlotte\-L29c_firmware, Columbia\-Al10b_firmware, Columbia\-Al10i_firmware, Columbia\-L29d_firmware, Columbia\-Tl00d_firmware, Cornell\-Al00a_firmware, Cornell\-Al00i_firmware, Cornell\-Al00ind_firmware, Cornell\-Al10ind_firmware, Cornell\-L29a_firmware, Cornell\-Tl10b_firmware, Dubai\-Al00a_firmware, Dura\-Al00a_firmware, Dura\-Tl00a_firmware, Emily\-L29c_firmware, Ever\-L29b_firmware, Figo\-L23_firmware, Figo\-L31_firmware, Figo\-Tl10b_firmware, Florida\-Al20b_firmware, Florida\-L21_firmware, Florida\-L22_firmware, Florida\-L23_firmware, Florida\-Tl10b_firmware, Harry\-Al00c_firmware, Harry\-Al10b_firmware, Harry\-Tl00c_firmware, Hima\-L29c_firmware, Honor_10_lite_firmware, Honor_20_firmware, Honor_20_pro_firmware, Honor_8a_firmware, Honor_8x_firmware, Honor_view_10_firmware, Honor_view_20_firmware, Imanager_neteco_6000_firmware, Imanager_neteco_firmware, Jakarta\-Al00a_firmware, Johnson\-Tl00d_firmware, Johnson\-Tl00f_firmware, Katyusha\-Al00a_firmware, Laya\-Al00ep_firmware, Leland\-L21a_firmware, Leland\-L31a_firmware, Leland\-L32a_firmware, Leland\-L32c_firmware, Leland\-L42a_firmware, Leland\-L42c_firmware, Leland\-Tl10b_firmware, Leland\-Tl10c_firmware, Lelandp\-Al00c_firmware, Lelandp\-Al10b_firmware, Lelandp\-Al10d_firmware, Lelandp\-L22a_firmware, Lelandp\-L22c_firmware, Lelandp\-L22d_firmware, London\-Al40ind_firmware, Madrid\-Al00a_firmware, Madrid\-Tl00a_firmware, Mate_20_firmware, Mate_20_pro_firmware, Mate_20_x_firmware, Neo\-Al00d_firmware, Nova_3_firmware, Nova_4_firmware, Nova_5_firmware, Nova_5i_pro_firmware, Nova_lite_3_firmware, P20_firmware, P20_pro_firmware, P30_firmware, P30_pro_firmware, P_smart_2019_firmware, P_smart_firmware, Paris\-Al00ic_firmware, Paris\-L21b_firmware, Paris\-L21meb_firmware, Paris\-L29b_firmware, Potter\-Al00c_firmware, Potter\-Al10a_firmware, Princeton\-Al10b_firmware, Princeton\-Al10d_firmware, Princeton\-Tl10c_firmware, Sydney\-Al00_firmware, Sydney\-L21_firmware, Sydney\-L21br_firmware, Sydney\-L22_firmware, Sydney\-L22br_firmware, Sydney\-Tl00_firmware, Sydneym\-Al00_firmware, Sydneym\-L01_firmware, Sydneym\-L03_firmware, Sydneym\-L21_firmware, Sydneym\-L22_firmware, Sydneym\-L23_firmware, Tony\-Al00b_firmware, Tony\-Tl00b_firmware, Y5_2018_firmware, Y5_lite_firmware, Y6_2019_firmware, Y6_prime_2018_firmware, Y6_pro_2019_firmware, Y7_2019_firmware, Y9_2019_firmware, Yale\-Al00a_firmware, Yale\-Al50a_firmware, Yale\-L21a_firmware, Yale\-L61c_firmware, Yale\-Tl00b_firmware, Yalep\-Al10b_firmware, Leap, Enterprise_linux, Enterprise_linux_aus, Enterprise_linux_eus, Enterprise_linux_for_real_time, Enterprise_linux_for_real_time_eus, Enterprise_linux_for_real_time_for_nfv, Enterprise_linux_for_real_time_for_nfv_eus, Enterprise_linux_server, Enterprise_linux_server_aus, Enterprise_linux_server_tus, Enterprise_linux_tus, Mrg_realtime, Virtualization_host_eus | 8.1 |