Total
364 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-47584 | 1 Linux | 1 Linux Kernel | 2024-11-21 | N/A | 5.5 MEDIUM |
| In the Linux kernel, the following vulnerability has been resolved: iocost: Fix divide-by-zero on donation from low hweight cgroup The donation calculation logic assumes that the donor has non-zero after-donation hweight, so the lowest active hweight a donating cgroup can have is 2 so that it can donate 1 while keeping the other 1 for itself. Earlier, we only donated from cgroups with sizable surpluses so this condition was always true. However, with the precise donation algorithm implemented, f1de2439ec43 ("blk-iocost: revamp donation amount determination") made the donation amount calculation exact enabling even low hweight cgroups to donate. This means that in rare occasions, a cgroup with active hweight of 1 can enter donation calculation triggering the following warning and then a divide-by-zero oops. WARNING: CPU: 4 PID: 0 at block/blk-iocost.c:1928 transfer_surpluses.cold+0x0/0x53 [884/94867] ... RIP: 0010:transfer_surpluses.cold+0x0/0x53 Code: 92 ff 48 c7 c7 28 d1 ab b5 65 48 8b 34 25 00 ae 01 00 48 81 c6 90 06 00 00 e8 8b 3f fe ff 48 c7 c0 ea ff ff ff e9 95 ff 92 ff <0f> 0b 48 c7 c7 30 da ab b5 e8 71 3f fe ff 4c 89 e8 4d 85 ed 74 0 4 ... Call Trace: <IRQ> ioc_timer_fn+0x1043/0x1390 call_timer_fn+0xa1/0x2c0 __run_timers.part.0+0x1ec/0x2e0 run_timer_softirq+0x35/0x70 ... iocg: invalid donation weights in /a/b: active=1 donating=1 after=0 Fix it by excluding cgroups w/ active hweight < 2 from donating. Excluding these extreme low hweight donations shouldn't affect work conservation in any meaningful way. | |||||
| CVE-2021-46915 | 1 Linux | 1 Linux Kernel | 2024-11-21 | N/A | 5.5 MEDIUM |
| In the Linux kernel, the following vulnerability has been resolved: netfilter: nft_limit: avoid possible divide error in nft_limit_init div_u64() divides u64 by u32. nft_limit_init() wants to divide u64 by u64, use the appropriate math function (div64_u64) divide error: 0000 [#1] PREEMPT SMP KASAN CPU: 1 PID: 8390 Comm: syz-executor188 Not tainted 5.12.0-rc4-syzkaller #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 01/01/2011 RIP: 0010:div_u64_rem include/linux/math64.h:28 [inline] RIP: 0010:div_u64 include/linux/math64.h:127 [inline] RIP: 0010:nft_limit_init+0x2a2/0x5e0 net/netfilter/nft_limit.c:85 Code: ef 4c 01 eb 41 0f 92 c7 48 89 de e8 38 a5 22 fa 4d 85 ff 0f 85 97 02 00 00 e8 ea 9e 22 fa 4c 0f af f3 45 89 ed 31 d2 4c 89 f0 <49> f7 f5 49 89 c6 e8 d3 9e 22 fa 48 8d 7d 48 48 b8 00 00 00 00 00 RSP: 0018:ffffc90009447198 EFLAGS: 00010246 RAX: 0000000000000000 RBX: 0000200000000000 RCX: 0000000000000000 RDX: 0000000000000000 RSI: ffffffff875152e6 RDI: 0000000000000003 RBP: ffff888020f80908 R08: 0000200000000000 R09: 0000000000000000 R10: ffffffff875152d8 R11: 0000000000000000 R12: ffffc90009447270 R13: 0000000000000000 R14: 0000000000000000 R15: 0000000000000000 FS: 000000000097a300(0000) GS:ffff8880b9d00000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00000000200001c4 CR3: 0000000026a52000 CR4: 00000000001506e0 DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 Call Trace: nf_tables_newexpr net/netfilter/nf_tables_api.c:2675 [inline] nft_expr_init+0x145/0x2d0 net/netfilter/nf_tables_api.c:2713 nft_set_elem_expr_alloc+0x27/0x280 net/netfilter/nf_tables_api.c:5160 nf_tables_newset+0x1997/0x3150 net/netfilter/nf_tables_api.c:4321 nfnetlink_rcv_batch+0x85a/0x21b0 net/netfilter/nfnetlink.c:456 nfnetlink_rcv_skb_batch net/netfilter/nfnetlink.c:580 [inline] nfnetlink_rcv+0x3af/0x420 net/netfilter/nfnetlink.c:598 netlink_unicast_kernel net/netlink/af_netlink.c:1312 [inline] netlink_unicast+0x533/0x7d0 net/netlink/af_netlink.c:1338 netlink_sendmsg+0x856/0xd90 net/netlink/af_netlink.c:1927 sock_sendmsg_nosec net/socket.c:654 [inline] sock_sendmsg+0xcf/0x120 net/socket.c:674 ____sys_sendmsg+0x6e8/0x810 net/socket.c:2350 ___sys_sendmsg+0xf3/0x170 net/socket.c:2404 __sys_sendmsg+0xe5/0x1b0 net/socket.c:2433 do_syscall_64+0x2d/0x70 arch/x86/entry/common.c:46 entry_SYSCALL_64_after_hwframe+0x44/0xae | |||||
| CVE-2021-46312 | 1 Djvulibre Project | 1 Djvulibre | 2024-11-21 | N/A | 6.5 MEDIUM |
| An issue was discovered IW44EncodeCodec.cpp in djvulibre 3.5.28 in allows attackers to cause a denial of service via divide by zero. | |||||
| CVE-2021-46310 | 1 Djvulibre Project | 1 Djvulibre | 2024-11-21 | N/A | 6.5 MEDIUM |
| An issue was discovered IW44Image.cpp in djvulibre 3.5.28 in allows attackers to cause a denial of service via divide by zero. | |||||
| CVE-2021-46244 | 1 Hdfgroup | 1 Hdf5 | 2024-11-21 | 4.3 MEDIUM | 6.5 MEDIUM |
| A Divide By Zero vulnerability exists in HDF5 v1.13.1-1 vis the function H5T__complete_copy () at /hdf5/src/H5T.c. This vulnerability causes an aritmetic exception, leading to a Denial of Service (DoS). | |||||
| CVE-2021-44917 | 1 Gnuplot | 1 Gnuplot | 2024-11-21 | 4.3 MEDIUM | 5.5 MEDIUM |
| A Divide by Zero vulnerability exists in gnuplot 5.4 in the boundary3d function in graph3d.c, which could cause a Arithmetic exception and application crash. | |||||
| CVE-2021-44500 | 1 Fisglobal | 1 Gt.m | 2024-11-21 | 5.0 MEDIUM | 7.5 HIGH |
| An issue was discovered in FIS GT.M through V7.0-000 (related to the YottaDB code base). A lack of input validation in calls to eb_div in sr_port/eb_muldiv.c allows attackers to crash the application by performing a divide by zero. | |||||
| CVE-2021-41218 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `AllToAll` can be made to execute a division by 0. This occurs whenever the `split_count` argument is 0. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | |||||
| CVE-2021-41209 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an open source platform for machine learning. In affected versions the implementations for convolution operators trigger a division by 0 if passed empty filter tensor arguments. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | |||||
| CVE-2021-41207 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an open source platform for machine learning. In affected versions the implementation of `ParallelConcat` misses some input validation and can produce a division by 0. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | |||||
| CVE-2021-40211 | 1 Imagemagick | 1 Imagemagick | 2024-11-21 | N/A | 7.5 HIGH |
| An issue was discovered with ImageMagick 7.1.0-4 via Division by zero in function ReadEnhMetaFile of coders/emf.c. | |||||
| CVE-2021-3941 | 4 Debian, Fedoraproject, Openexr and 1 more | 4 Debian Linux, Fedora, Openexr and 1 more | 2024-11-21 | 2.1 LOW | 6.5 MEDIUM |
| In ImfChromaticities.cpp routine RGBtoXYZ(), there are some division operations such as `float Z = (1 - chroma.white.x - chroma.white.y) * Y / chroma.white.y;` and `chroma.green.y * (X + Z))) / d;` but the divisor is not checked for a 0 value. A specially crafted file could trigger a divide-by-zero condition which could affect the availability of programs linked with OpenEXR. | |||||
| CVE-2021-3432 | 1 Zephyrproject | 1 Zephyr | 2024-11-21 | 5.0 MEDIUM | 4.3 MEDIUM |
| Invalid interval in CONNECT_IND leads to Division by Zero. Zephyr versions >= v1.14.0 Divide By Zero (CWE-369). For more information, see https://github.com/zephyrproject-rtos/zephyr/security/advisories/GHSA-7364-p4wc-8mj4 | |||||
| CVE-2021-37691 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37684 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37683 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37680 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37675 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37668 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37660 | 1 Google | 1 Tensorflow | 2024-11-21 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||