A flaw was found in knot-resolver before version 2.3.0. Malformed DNS messages may cause denial of service.

Knot Resolver before 5.5.3 allows remote attackers to cause a denial of service (CPU consumption) because of algorithmic complexity. During an attack, an authoritative server must return large NS sets or address sets.

Certain DNSSEC aspects of the DNS protocol (in RFC 4033, 4034, 4035, 6840, and related RFCs) allow remote attackers to cause a denial of service (CPU consumption) via one or more DNSSEC responses, aka the "KeyTrap" issue. One of the concerns is that, when there is a zone with many DNSKEY and RRSIG records, the protocol specification implies that an algorithm must evaluate all combinations of DNSKEY and RRSIG records.

Knot Resolver before 5.7.0 performs many TCP reconnections upon receiving certain nonsensical responses from servers.

Knot Resolver before 5.1.1 allows traffic amplification via a crafted DNS answer from an attacker-controlled server, aka an "NXNSAttack" issue. This is triggered by random subdomains in the NSDNAME in NS records.

Knot Resolver before 5.6.0 enables attackers to consume its resources, launching amplification attacks and potentially causing a denial of service. Specifically, a single client query may lead to a hundred TCP connection attempts if a DNS server closes connections without providing a response.

Knot DNS before 1.5.2 allows remote attackers to cause a denial of service (application crash) via a crafted DNS message.

knot-resolver before version 4.3.0 is vulnerable to denial of service through high CPU utilization. DNS replies with very many resource records might be processed very inefficiently, in extreme cases taking even several CPU seconds for each such uncached message. For example, a few thousand A records can be squashed into one DNS message (limit is 64kB).

BIRD Internet Routing Daemon 1.6.x through 1.6.7 and 2.x through 2.0.5 has a stack-based buffer overflow. The BGP daemon's support for RFC 8203 administrative shutdown communication messages included an incorrect logical expression when checking the validity of an input message. Sending a shutdown communication with a sufficient message length causes a four-byte overflow to occur while processing the message, where two of the overflow bytes are attacker-controlled and two are fixed.

In Wireshark 2.4.0 to 2.4.13, 2.6.0 to 2.6.7, and 3.0.0, the GSS-API dissector could crash. This was addressed in epan/dissectors/packet-gssapi.c by ensuring that a valid dissector is called.

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.

Envoy is a cloud-native, open source edge and service proxy. When an upstream TLS cluster is used with `auto_sni` enabled, a request containing a `host`/`:authority` header longer than 255 characters triggers an abnormal termination of Envoy process. Envoy does not gracefully handle an error when setting SNI for outbound TLS connection. The error can occur when Envoy attempts to use the `host`/`:authority` header value longer than 255 characters as SNI for outbound TLS connection. SNI length is limited to 255 characters per the standard. Envoy always expects this operation to succeed and abnormally aborts the process when it fails. This vulnerability is fixed in 1.30.1, 1.29.4, 1.28.3, and 1.27.5.

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.

Pexip Infinity before 39.0 has Improper Input Validation in the media implementation, allowing a remote attacker to trigger a software abort via a crafted media stream, resulting in a denial of service.

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. If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, 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.

TensorFlow is an open source platform for machine learning. When `RandomPoissonV2` 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. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, 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 bd90b3efab4ec958b228cd7cfe9125be1c0cf255. 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 `tf.sparse.cross` receives an input `separator` that is not a scalar, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 83dcb4dbfa094e33db084e97c4d0531a559e0ebf. 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.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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. `FractionalMaxPoolGrad` validates its inputs with `CHECK` failures instead of with returning errors. If it gets incorrectly sized inputs, the `CHECK` failure can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 8741e57d163a079db05a7107a7609af70931def4. 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 `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. 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 `tensorflow::full_type::SubstituteFromAttrs` receives a `FullTypeDef& t` that is not exactly three args, it triggers a `CHECK`-fail instead of returning a status. We have patched the issue in GitHub commit 6104f0d4091c260ce9352f9155f7e9b725eab012. 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. 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 `CollectiveGather` receives an scalar input `input`, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c1f491817dec39a26be3c574e86a88c30f3c4770. 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.

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.

Polipo through 1.1.1, when NDEBUG is omitted, allows denial of service via a reachable assertion during parsing of a malformed Range header. NOTE: This vulnerability only affects products that are no longer supported by the maintainer

TensorFlow is an open source platform for machine learning. `ParameterizedTruncatedNormal` assumes `shape` is of type `int32`. A valid `shape` of type `int64` results in a mismatched type `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 72180be03447a10810edca700cbc9af690dfeb51. 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 `Unbatch` receives a nonscalar input `id`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 4419d10d576adefa36b0e0a9425d2569f7c0189f. 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 `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.

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.

Active command timeout since WM status change cmd is not removed from active queue if peer sends multiple deauth frames. in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8009, APQ8017, APQ8053, APQ8096AU, MDM9206, MDM9207C, MDM9607, MDM9640, MDM9650, MSM8905, MSM8909W, MSM8917, MSM8920, MSM8937, MSM8940, MSM8953, MSM8996AU, QCA6174A, QCA6574AU, QCA9377, QCA9379, QCM2150, QCN7605, QCS605, QM215, SC8180X, SDM429, SDM429W, SDM439, SDM450, SDM630, SDM632, SDM636, SDM660, SDM845, SDX20, SDX24, SDX55, SM8150, SXR1130

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.

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 `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 `Conv2DBackpropInput` receives empty `out_backprop` inputs (e.g. `[3, 1, 0, 1]`), the current CPU/GPU kernels `CHECK` fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346. 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.

Processing of repeated responses to the same query, where both responses contain ECS pseudo-options, but where the first is broken in some way, can cause BIND to exit with an assertion failure. 'Broken' in this context is anything that would cause the resolver to reject the query response, such as a mismatch between query and answer name. This issue affects BIND 9 versions 9.11.4-S1 through 9.11.37-S1 and 9.16.8-S1 through 9.16.36-S1.

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.

A reachable assertion in the mme_ue_find_by_imsi function of Open5GS <= 2.6.4 allows attackers to cause a Denial of Service (DoS) via a crafted NAS packet.

The validateInputImageSize function in modules/imgcodecs/src/loadsave.cpp in OpenCV 3.4.1 allows remote attackers to cause a denial of service (assertion failure) because (size.height <= (1<<20)) may be false. Note: “OpenCV CV_Assert is not an assertion (C-like assert()), it is regular C++ exception which can raised in case of invalid or non-supported parameters.

A reachable assertion in the amf_ue_set_suci function of Open5GS <= 2.6.4 allows attackers to cause a Denial of Service (DoS) via a crafted NAS packet.

Transient DOS due to reachable assertion in Modem during OSI decode scheduling.

Transient DOS due to reachable assertion in Modem because of invalid network configuration.

The validateInputImageSize function in modules/imgcodecs/src/loadsave.cpp in OpenCV 3.4.1 allows remote attackers to cause a denial of service (assertion failure) because (size.width <= (1<<20)) may be false. Note: “OpenCV CV_Assert is not an assertion (C-like assert()), it is regular C++ exception which can raised in case of invalid or non-supported parameters.

Transient DOS due to reachable assertion in Modem while processing SIB1 Message.

Transient DOS due to reachable assertion in modem when network repeatedly sent invalid message container for NR to LTE handover.