eprosima Fast DDS is a C++ implementation of the Data Distribution Service standard of the Object Management Group. Prior to versions 2.10.0, 2.9.2, and 2.6.5, a malformed GAP submessage can trigger assertion failure, crashing FastDDS. Version 2.10.0, 2.9.2, and 2.6.5 contain a patch for this issue.
Open62541 v1.4.6 is has an assertion failure in fuzz_binary_decode, which leads to a crash.
Transient DOS while processing a random-access response (RAR) with an invalid PDU length on LTE network.
Magma versions <= 1.8.0 (fixed in v1.9 commit 08472ba98b8321f802e95f5622fa90fec2dea486) are susceptible to an assertion-based crash when an oversized NAS packet is received. An attacker may leverage this behavior to repeatedly crash the MME via either a compromised base station or via an unauthenticated cellphone within range of a base station managed by the MME, causing a denial of service.
StringEqual in TiXmlDeclaration::Parse in tinyxmlparser.cpp in TinyXML through 2.6.2 has a reachable assertion (and application exit) via a crafted XML document with a '\0' located after whitespace.
In 5G Modem, there is a possible system crash due to improper error handling. This could lead to remote denial of service when receiving malformed RRC messages, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY01130256; Issue ID: MOLY01130256 (MSV-848).
In 5G Modem, there is a possible system crash due to improper error handling. This could lead to remote denial of service when receiving malformed RRC messages, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY01128524; Issue ID: MOLY01128524 (MSV-846).
Transient DOS while processing multiple payload container type with incorrect container length received in DL NAS transport OTA in NR.
In 5G Modem, there is a possible system crash due to improper error handling. This could lead to remote denial of service when receiving malformed RRC messages, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY01128524; Issue ID: MOLY01130183 (MSV-850).
A denial of service flaw was found in the way BIND handled DNSSEC validation. A remote attacker could use this flaw to make named exit unexpectedly with an assertion failure via a specially crafted DNS response.
Unbound before 1.9.5 allows an assertion failure and denial of service in dname_pkt_copy via an invalid packet. NOTE: The vendor disputes that this is a vulnerability. Although the code may be vulnerable, a running Unbound installation cannot be remotely or locally exploited
A flaw was found in the vLLM library. A completions API request with an empty prompt will crash the vLLM API server, resulting in a denial of service.
In MPD before 0.23.8, as used on Automotive Grade Linux and other platforms, the PipeWire output plugin mishandles a Drain call in certain situations involving truncated files. Eventually there is an assertion failure in libmpdclient because libqtappfw passes in a NULL pointer.
An issue was discovered in the libsofia-sip fork in drachtio-server before 0.8.20. It allows remote attackers to cause a denial of service (daemon crash) via a crafted UDP message that leads to a failure of the libsofia-sip-ua/tport/tport.c self assertion.
Unbound before 1.9.5 allows an assertion failure via a compressed name in dname_pkt_copy. NOTE: The vendor disputes that this is a vulnerability. Although the code may be vulnerable, a running Unbound installation cannot be remotely or locally exploited
Unbound before 1.9.5 allows an assertion failure and denial of service in synth_cname. NOTE: The vendor disputes that this is a vulnerability. Although the code may be vulnerable, a running Unbound installation cannot be remotely or locally exploited
rPGP is a pure Rust implementation of OpenPGP. Prior to 0.14.1, rPGP allows an attacker to trigger rpgp crashes by providing crafted data. This vulnerability is fixed in 0.14.1.
Quicly is an IETF QUIC protocol implementation. Quicly up to commtit d720707 is susceptible to a denial-of-service attack. A remote attacker can exploit these bugs to trigger an assertion failure that crashes process using quicly. The vulnerability is addressed with commit 2a95896104901589c495bc41460262e64ffcad5c.
FlashMQ v1.14.0 was discovered to contain an assertion failure in the function PublishCopyFactory::getNewPublish, which occurs when the QoS value of the publish object is greater than 0.
TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListResize` is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 888e34b49009a4e734c27ab0c43b0b5102682c56. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. An input `sparse_matrix` that is not a matrix with a shape with rank 0 will trigger a `CHECK` fail in `tf.raw_ops.SparseMatrixNNZ`. We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in `SdcaOptimizer`. We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Client queries that trigger serving stale data and that also require lookups in local authoritative zone data may result in an assertion failure. This issue affects BIND 9 versions 9.16.13 through 9.16.50, 9.18.0 through 9.18.27, 9.19.0 through 9.19.24, 9.11.33-S1 through 9.11.37-S1, 9.16.13-S1 through 9.16.50-S1, and 9.18.11-S1 through 9.18.27-S1.
This issue can affect BIND 9 resolvers with `stale-answer-enable yes;` that also make use of the option `stale-answer-client-timeout`, configured with a value greater than zero. If the resolver receives many queries that require recursion, there will be a corresponding increase in the number of clients that are waiting for recursion to complete. If there are sufficient clients already waiting when a new client query is received so that it is necessary to SERVFAIL the longest waiting client (see BIND 9 ARM `recursive-clients` limit and soft quota), then it is possible for a race to occur between providing a stale answer to this older client and sending an early timeout SERVFAIL, which may cause an assertion failure. This issue affects BIND 9 versions 9.16.12 through 9.16.36, 9.18.0 through 9.18.10, 9.19.0 through 9.19.8, and 9.16.12-S1 through 9.16.36-S1.
Transient DOS due to reachable assertion in Modem while processing config related to cross carrier scheduling, which is not supported.
Transient DOS due to reachable assertion in modem while processing sib with incorrect values from network.
Transient DOS due to reachable assertion in WLAN while processing PEER ID populated by TQM.
Transient DOS due to reachable assertion in Modem when UE received Downlink Data Indication message from the network.
Reachable Assertion in BPv7 parser in µD3TN v0.14.0 allows attacker to disrupt service via malformed Extension Block
Transient DOS in Modem while triggering a camping on an 5G cell.
A reachable assertion was found in Frrouting frr-bgpd 8.3.0 in the peek_for_as4_capability function. Attackers can maliciously construct BGP open packets and send them to BGP peers running frr-bgpd, resulting in DoS.
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. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, 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 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. 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. 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.
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.
TensorFlow is an open source platform for machine learning. If `RaggedTensorToVariant` is given a `rt_nested_splits` list that contains tensors of ranks 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 88f93dfe691563baa4ae1e80ccde2d5c7a143821. 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 `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. 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. `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 `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. `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. 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 `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 `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 `QuantizeAndDequantizeV3` is given a nonscalar `num_bits` input tensor, 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 f3f9cb38ecfe5a8a703f2c4a8fead434ef291713. 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_per_channel_gradient` receives input `min` or `max` of rank other than 1, 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. If `EmptyTensorList` receives an input `element_shape` with more than one dimension, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. 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. 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.