Transient DOS while processing DL NAS Transport message, as specified in 3GPP 24.501 v16.
An issue found in TCPreplay tcprewrite v.4.4.3 allows a remote attacker to cause a denial of service via the tcpedit_dlt_cleanup function at plugins/dlt_plugins.c.
An issue found in TCPprep v.4.4.3 allows a remote attacker to cause a denial of service via the cidr2cidr function at the cidr.c:178 endpoint.
An issue found in TCPrewrite v.4.4.3 allows a remote attacker to cause a denial of service via the ports2PORT function at the portmap.c:69 endpoint.
MariaDB v10.5 to v10.7 was discovered to contain an assertion failure at table->get_ref_count() == 0 in dict0dict.cc.
The Device Model in ACRN before 2019w25.5-140000p relies on assert calls in devicemodel/hw/pci/core.c and devicemodel/include/pci_core.h (instead of other mechanisms for propagating error information or diagnostic information), which might allow attackers to cause a denial of service (assertion failure) within pci core. This is fixed in 1.2. 6199e653418e is a mitigation for pre-1.1 versions, whereas 2b3dedfb9ba1 is a mitigation for 1.1.
In Modem, there is a possible system crash due to an uncaught exception. This could lead to remote denial of service, if a UE has connected to a rogue base station controlled by the attacker, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00650610; Issue ID: MSV-2933.
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.
TensorFlow is an open source platform for machine learning. When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467. 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.
TensorFlow is an open source platform for machine learning. When `DrawBoundingBoxes` receives an input `boxes` that is not of dtype `float`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit da0d65cdc1270038e72157ba35bf74b85d9bda11. 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.
TensorFlow is an open source platform for machine learning. When `tf.random.gamma` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. 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.
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.
TensorFlow is an open source platform for machine learning. When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. 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.
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.
TensorFlow is an open source platform for machine learning. If `Save` or `SaveSlices` is run over tensors of an unsupported `dtype`, 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 5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4. 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.
TensorFlow is an open source platform for machine learning. When `TensorListFromTensor` receives an `element_shape` of a rank greater than one, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 3db59a042a38f4338aa207922fa2f476e000a6ee. 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.
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.
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.
TensorFlow is an open source platform for machine learning. When `TensorListScatter` and `TensorListScatterV2` receive an `element_shape` of a rank greater than one, they give a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. 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.
TensorFlow is an open source platform for machine learning. When `AudioSummaryV2` receives an input `sample_rate` with more than one element, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf6b45244992e2ee543c258e519489659c99fb7f. 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.
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.
The assertion `stmt->Dbc->FirstStmt' failed in MonetDB Database Server v11.43.13.
Transient DOS in modem due to reachable assertion.
There is an Assertion in '(flags >> CBC_STACK_ADJUST_SHIFT) >= CBC_STACK_ADJUST_BASE || (CBC_STACK_ADJUST_BASE - (flags >> CBC_STACK_ADJUST_SHIFT)) <= context_p->stack_depth' in parser_emit_cbc_backward_branch in JerryScript 2.2.0.
A flaw was found in the networking subsystem of the Linux kernel within the handling of the RPL protocol. This issue results from the lack of proper handling of user-supplied data, which can lead to an assertion failure. This may allow an unauthenticated remote attacker to create a denial of service condition on the system.
h2o is an HTTP server with support for HTTP/1.x, HTTP/2 and HTTP/3. When h2o is configured as a reverse proxy and HTTP/3 requests are cancelled by the client, h2o might crash due to an assertion failure. The crash can be exploited by an attacker to mount a Denial-of-Service attack. By default, the h2o standalone server automatically restarts, minimizing the impact. However, HTTP requests that were served concurrently will still be disrupted. The vulnerability has been addressed in commit 1ed32b2. Users may disable the use of HTTP/3 to mitigate the issue.
Suricata is a network Intrusion Detection System, Intrusion Prevention System and Network Security Monitoring engine. Prior to version 7.0.7, rules using datasets with the non-functional / unimplemented "unset" option can trigger an assertion during traffic parsing, leading to denial of service. This issue is addressed in 7.0.7. As a workaround, use only trusted and well tested rulesets.
Suricata is a network Intrusion Detection System, Intrusion Prevention System and Network Security Monitoring engine. Prior to version 7.0.7, invalid ALPN in TLS/QUIC traffic when JA4 matching/logging is enabled can lead to Suricata aborting with a panic. This issue has been addressed in 7.0.7. One may disable ja4 as a workaround.
Possible denial of service due to improper validation of DNS response when DNS client requests with PTR, NAPTR or SRV query type in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT
An issue in FlashMQ v1.14.0 allows attackers to cause an assertion failure via sending a crafted retain message, leading to a Denial of Service (DoS).
Possible denial of service scenario due to improper handling of group management action frame in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking
Possible denial of service scenario due to improper input validation of received NAS OTA message in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile
Improper handling of received malformed FTMR request frame can lead to reachable assertion while responding with FTM1 frame in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking
Possible assertion due to improper verification while creating and deleting the peer in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking
In Jasper 4.2.2, the jpc_streamlist_remove function in src/libjasper/jpc/jpc_dec.c:2407 has an assertion failure vulnerability, allowing attackers to cause a denial of service attack through a specific image file.
An exploitable denial of service vulnerability exists in the atftpd daemon functionality of atftp 0.7.git20120829-3.1+b1. A specially crafted sequence of RRQ-Multicast requests trigger an assert() call resulting in denial-of-service. An attacker can send a sequence of malicious packets to trigger this vulnerability.
The jpc_dequantize function in jpc_dec.c in JasPer 1.900.13 allows remote attackers to cause a denial of service (assertion failure) via unspecified vectors.
TensorFlow is an open source platform for machine learning. `DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43. 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.