Total
611 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2023-52621 | 2 Linux, Redhat | 2 Linux Kernel, Enterprise Linux | 2025-05-02 | 7.8 High |
| In the Linux kernel, the following vulnerability has been resolved: bpf: Check rcu_read_lock_trace_held() before calling bpf map helpers These three bpf_map_{lookup,update,delete}_elem() helpers are also available for sleepable bpf program, so add the corresponding lock assertion for sleepable bpf program, otherwise the following warning will be reported when a sleepable bpf program manipulates bpf map under interpreter mode (aka bpf_jit_enable=0): WARNING: CPU: 3 PID: 4985 at kernel/bpf/helpers.c:40 ...... CPU: 3 PID: 4985 Comm: test_progs Not tainted 6.6.0+ #2 Hardware name: QEMU Standard PC (i440FX + PIIX, 1996) ...... RIP: 0010:bpf_map_lookup_elem+0x54/0x60 ...... Call Trace: <TASK> ? __warn+0xa5/0x240 ? bpf_map_lookup_elem+0x54/0x60 ? report_bug+0x1ba/0x1f0 ? handle_bug+0x40/0x80 ? exc_invalid_op+0x18/0x50 ? asm_exc_invalid_op+0x1b/0x20 ? __pfx_bpf_map_lookup_elem+0x10/0x10 ? rcu_lockdep_current_cpu_online+0x65/0xb0 ? rcu_is_watching+0x23/0x50 ? bpf_map_lookup_elem+0x54/0x60 ? __pfx_bpf_map_lookup_elem+0x10/0x10 ___bpf_prog_run+0x513/0x3b70 __bpf_prog_run32+0x9d/0xd0 ? __bpf_prog_enter_sleepable_recur+0xad/0x120 ? __bpf_prog_enter_sleepable_recur+0x3e/0x120 bpf_trampoline_6442580665+0x4d/0x1000 __x64_sys_getpgid+0x5/0x30 ? do_syscall_64+0x36/0xb0 entry_SYSCALL_64_after_hwframe+0x6e/0x76 </TASK> | ||||
| CVE-2022-26446 | 1 Mediatek | 56 Lr12a, Lr13, Mt2731 and 53 more | 2025-05-01 | 7.5 High |
| In Modem 4G RRC, there is a possible system crash due to improper input validation. This could lead to remote denial of service, when concatenating improper SIB12 (CMAS message), with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00867883; Issue ID: ALPS07274118. | ||||
| CVE-2024-20094 | 1 Mediatek | 21 Mt2735, Mt6833, Mt6853 and 18 more | 2025-04-25 | 7.5 High |
| In Modem, there is a possible system crash due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00843282; Issue ID: MSV-1535. | ||||
| CVE-2022-23571 | 1 Google | 1 Tensorflow | 2025-04-23 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments, if the tensors have an invalid `dtype` and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2022-23565 | 1 Google | 1 Tensorflow | 2025-04-23 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a `SavedModel` on disk such that `AttrDef`s of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2022-23564 | 1 Google | 1 Tensorflow | 2025-04-23 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2022-24777 | 1 Linuxfoundation | 1 Grpc Swift | 2025-04-23 | 7.5 High |
| grpc-swift is the Swift language implementation of gRPC, a remote procedure call (RPC) framework. Prior to version 1.7.2, a grpc-swift server is vulnerable to a denial of service attack via a reachable assertion. This is due to incorrect logic when handling GOAWAY frames. The attack is low-effort: it takes very little resources to construct and send the required sequence of frames. The impact on availability is high as the server will crash, dropping all in flight connections and requests. This issue is fixed in version 1.7.2. There are currently no known workarounds. | ||||
| CVE-2022-29228 | 2 Envoyproxy, Redhat | 2 Envoy, Service Mesh | 2025-04-23 | 7.5 High |
| Envoy is a cloud-native high-performance proxy. In versions prior to 1.22.1 the OAuth filter would try to invoke the remaining filters in the chain after emitting a local response, which triggers an ASSERT() in newer versions and corrupts memory on earlier versions. continueDecoding() shouldn’t ever be called from filters after a local reply has been sent. Users are advised to upgrade. There are no known workarounds for this issue. | ||||
| CVE-2022-31009 | 1 Wire | 1 Wire | 2025-04-23 | 5.7 Medium |
| wire-ios is an iOS client for the Wire secure messaging application. Invalid accent colors of Wire communication partners may render the iOS Wire Client partially unusable by causing it to crash multiple times on launch. These invalid accent colors can be used by and sent between Wire users. The root cause was an unnecessary assert statement when converting an integer value into the corresponding enum value, causing an exception instead of a fallback to a default value. This issue is fixed in [wire-ios](https://github.com/wireapp/wire-ios/commit/caa0e27dbe51f9edfda8c7a9f017d93b8cfddefb) and in Wire for iOS 3.100. There is no workaround available, but users may use other Wire clients (such as the [web app](https://app.wire.com)) to continue using Wire, or upgrade their client. | ||||
| CVE-2022-31100 | 1 Pomsky-lang | 1 Pomsky | 2025-04-23 | 6.5 Medium |
| rulex is a new, portable, regular expression language. When parsing untrusted rulex expressions, rulex may crash, possibly enabling a Denial of Service attack. This happens when the expression contains a multi-byte UTF-8 code point in a string literal or after a backslash, because rulex tries to slice into the code point and panics as a result. This is a security concern for you, if your service parses untrusted rulex expressions (expressions provided by an untrusted user), and your service becomes unavailable when the thread running rulex panics. The crashes are fixed in version **0.4.3**. Affected users are advised to update to this version. The only known workaround for this issue is to assume that regular expression parsing will panic and to add logic to catch panics. | ||||
| CVE-2022-35934 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor. This issue has been patched in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35935 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by assuming `input(0)`, `input(1)`, and `input(2)` to be scalar. This issue has been patched in GitHub commit c65c67f88ad770662e8f191269a907bf2b94b1bf. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35941 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The `AvgPoolOp` function takes an argument `ksize` that must be positive but is not checked. A negative `ksize` can trigger a `CHECK` failure and crash the program. We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds to this issue. | ||||
| CVE-2022-35952 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The `UnbatchGradOp` function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program. It also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program. We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35959 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of `AvgPool3DGradOp` does not fully validate the input `orig_input_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 9178ac9d6389bdc54638ab913ea0e419234d14eb. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35960 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. In `core/kernels/list_kernels.cc's TensorListReserve`, `num_elements` is assumed to be a tensor of size 1. When a `num_elements` of more than 1 element is provided, then `tf.raw_ops.TensorListReserve` fails the `CHECK_EQ` in `CheckIsAlignedAndSingleElement`. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35963 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35968 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of `AvgPoolGrad` does not fully validate the input `orig_input_shape`. This results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35969 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||
| CVE-2022-35971 | 1 Google | 1 Tensorflow | 2025-04-23 | 5.9 Medium |
| TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. | ||||