named in ISC BIND 9.x before 9.9.9-P4, 9.10.x before 9.10.4-P4, and 9.11.x before 9.11.0-P1 allows remote attackers to cause a denial of service (assertion failure and daemon exit) via a DNAME record in the answer section of a response to a recursive query, related to db.c and resolver.c.
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.
On vulnerable configurations, the named daemon may, in some circumstances, terminate with an assertion failure. Vulnerable configurations are those that include a reference to http within the listen-on statements in their named.conf. TLS is used by both DNS over TLS (DoT) and DNS over HTTPS (DoH), but configurations using DoT alone are unaffected. Affects BIND 9.18.0 -> 9.18.2 and version 9.19.0 of the BIND 9.19 development branch.
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.
A reachable assertion in the oai_nas_5gmm_decode function of Open5GS <= 2.6.4 allows attackers to cause a Denial of Service (DoS) via a crafted NGAP packet.
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.
Transient DOS due to reachable assertion in Modem while processing config related to cross carrier scheduling, which is not supported.
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.
An issue in UPF in Open5GS UPF versions up to v2.7.2 results an assertion failure vulnerability in PFCP session parameter validation. When processing a PFCP Session Establishment Request with PDN Type=0, the UPF fails to handle the invalid value propagated from SMF (or via direct attack), triggering a fatal assertion check and causing a daemon crash.
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_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. 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 `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. 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. 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. 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 `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 `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 `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 `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. 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. `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 `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. 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. 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. 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.
There is an Assertion 'context_p->stack_depth == context_p->context_stack_depth' failed at js-parser-statm.c:2756 in parser_parse_statements in JerryScript 2.2.0.
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. 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.
The assertion `stmt->Dbc->FirstStmt' failed in MonetDB Database Server v11.43.13.
Transient DOS due to reachable assertion in Modem because of invalid network configuration.
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.
Transient DOS in modem due to reachable assertion.
Transient DOS due to reachable assertion in Modem during OSI decode scheduling.
Transient DOS due to reachable assertion in modem during MIB reception and SIB timeout
Versions affected: BIND 9.18.0 When a vulnerable version of named receives a series of specific queries, the named process will eventually terminate due to a failed assertion check.
When the vulnerability is triggered the BIND process will exit. BIND 9.18.0
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.
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
Reachable Assertion in BPv7 parser in µD3TN v0.14.0 allows attacker to disrupt service via malformed Extension Block
lldpd before 0.8.0 allows remote attackers to cause a denial of service (assertion failure and daemon crash) via a malformed packet.
Knot Resolver before 5.3.2 is prone to an assertion failure, triggerable by a remote attacker in an edge case (NSEC3 with too many iterations used for a positive wildcard proof).
A programming error in the nxdomain-redirect feature can cause an assertion failure in query.c if the alternate namespace used by nxdomain-redirect is a descendant of a zone that is served locally. The most likely scenario where this might occur is if the server, in addition to performing NXDOMAIN redirection for recursive clients, is also serving a local copy of the root zone or using mirroring to provide the root zone, although other configurations are also possible. Versions affected: BIND 9.12.0-> 9.12.4, 9.14.0. Also affects all releases in the 9.13 development branch.
A flaw in query-handling code can cause `named` to exit prematurely with an assertion failure when: - `nxdomain-redirect <domain>;` is configured, and - the resolver receives a PTR query for an RFC 1918 address that would normally result in an authoritative NXDOMAIN response. This issue affects BIND 9 versions 9.12.0 through 9.16.45, 9.18.0 through 9.18.21, 9.19.0 through 9.19.19, 9.16.8-S1 through 9.16.45-S1, and 9.18.11-S1 through 9.18.21-S1.
A bad interaction between DNS64 and serve-stale may cause `named` to crash with an assertion failure during recursive resolution, when both of these features are enabled. This issue affects BIND 9 versions 9.16.12 through 9.16.45, 9.18.0 through 9.18.21, 9.19.0 through 9.19.19, 9.16.12-S1 through 9.16.45-S1, and 9.18.11-S1 through 9.18.21-S1.
libjxl v0.5.0 is affected by a Assertion failed issue in lib/jxl/image.cc jxl::PlaneBase::PlaneBase(). When encoding a malicous GIF file using cjxl, an attacker can trigger a denial of service.