Google Chrome before 6.0.472.59 on Linux does not properly handle cursors, which might allow attackers to cause a denial of service (assertion failure) via unspecified vectors.
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.
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.
Open5GS before 2.7.1 is vulnerable to a reachable assertion that can cause an AMF crash via NAS messages from a UE: gmm_state_authentication in amf/gmm-sm.c for != OGS_ERROR.
Transient DOS in Modem while triggering a camping on an 5G cell.
There is a vulnerability in the fizz library prior to v2023.01.30.00 where a CHECK failure can be triggered remotely. This behavior requires the client supported cipher advertisement changing between the original ClientHello and the second ClientHello, crashing the process (impact is limited to denial of service).
Assertion occurs while processing Reconfiguration message due to improper validation
Transient DOS in Modem while processing RRC reconfiguration message.
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.
An assertion can be reached in the WLAN subsystem while using the Wi-Fi Fine Timing Measurement protocol in Snapdragon Wired Infrastructure and Networking
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.
There exists an vulnerability causing an abort() to be called in gRPC. The following headers cause gRPC's C++ implementation to abort() when called via http2: te: x (x != trailers) :scheme: x (x != http, https) grpclb_client_stats: x (x == anything) On top of sending one of those headers, a later header must be sent that gets the total header size past 8KB. We recommend upgrading past git commit 2485fa94bd8a723e5c977d55a3ce10b301b437f8 or v1.53 and above.
Using a specially-crafted message, an attacker may potentially cause a BIND server to reach an inconsistent state if the attacker knows (or successfully guesses) the name of a TSIG key used by the server. Since BIND, by default, configures a local session key even on servers whose configuration does not otherwise make use of it, almost all current BIND servers are vulnerable. In releases of BIND dating from March 2018 and after, an assertion check in tsig.c detects this inconsistent state and deliberately exits. Prior to the introduction of the check the server would continue operating in an inconsistent state, with potentially harmful results.
There is a reachable assertion abort in the function calcstepsizes() in jpc/jpc_dec.c in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function jpc_dec_process_siz() in jpc/jpc_dec.c:1297 in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function jpc_floorlog2() in jpc/jpc_math.c in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function dict_add_mrset() in data/dictionary.c of the libpspp library in GNU PSPP before 1.0.1 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function jpc_dec_process_sot() in jpc/jpc_dec.c in JasPer 2.0.12 that will lead to a remote denial of service attack by triggering an unexpected jpc_ppmstabtostreams return value, a different vulnerability than CVE-2018-9154.
There is a reachable assertion abort in the function jpc_pi_nextrpcl() in jpc/jpc_t2cod.c in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function jpc_dequantize() in jpc/jpc_dec.c in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function jpc_dec_process_siz() in jpc/jpc_dec.c:1296 in JasPer 2.0.12 that will lead to a remote denial of service attack.
There is a reachable assertion abort in the function dict_rename_var() in data/dictionary.c of the libpspp library in GNU PSPP before 1.0.1 that will lead to remote denial of service.
The function "Token& Scanner::peek" in scanner.cpp in yaml-cpp 0.5.3 and earlier allows remote attackers to cause a denial of service (assertion failure and application exit) via a '!2' string.
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.
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. 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.
A vulnerability was found in Open5GS up to 2.7.5. Affected by this vulnerability is the function ngap_build_downlink_nas_transport of the component AMF. The manipulation leads to reachable assertion. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. Upgrading to version 2.7.6 is able to address this issue. The identifier of the patch is bca0a7b6e01d254f4223b83831162566d4626428. It is recommended to upgrade the affected component.
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.