Incorrect JSON input stringification in Google's Tensorflow serving versions up to 2.18.0 allows for potentially unbounded recursion leading to server crash.

Out of bounds memory access in V8 in Google Chrome prior to 132.0.6834.110 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)

Calling of non-existent provider in MobileWips application prior to SMR Feb-2021 Release 1 allows unauthorized actions including denial of service attack by hijacking the provider.

Any project that parses untrusted Protocol Buffers data containing an arbitrary number of nested groups / series of SGROUP tags can corrupted by exceeding the stack limit i.e. StackOverflow. Parsing nested groups as unknown fields with DiscardUnknownFieldsParser or Java Protobuf Lite parser, or against Protobuf map fields, creates unbounded recursions that can be abused by an attacker.

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.

mediaserver in Android 5.x before 5.1.1 LMY48T and 6.0 before 2015-10-01 allows attackers to cause a denial of service (process crash) via unspecified vectors, aka internal bug 22278703, a different vulnerability than CVE-2015-6605.

Unspecified vulnerability in the pop-up blocking functionality in Google Chrome before 6.0.472.59 allows remote attackers to cause a denial of service (application crash) via unknown vectors.

Google Chrome before 5.0.375.99 does not properly implement modal dialogs, which allows attackers to cause a denial of service (application crash) via unspecified vectors.

The ParamTraits<SkBitmap>::Read function in common/common_param_traits.cc in Google Chrome before 4.0.249.78 does not use the correct variables in calculations designed to prevent integer overflows, which allows attackers to leverage renderer access to cause a denial of service or possibly have unspecified other impact via bitmap data, related to deserialization.

In cd_SsParseMsg of cd_SsCodec.c, there is a possible crash due to a missing null check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-244448906References: N/A

Google Chrome 1.0.154.65, 1.0.154.48, and earlier allows remote attackers to (1) cause a denial of service (application hang) via vectors involving a chromehtml: URI value for the document.location property or (2) cause a denial of service (application hang and CPU consumption) via vectors involving a series of function calls that set a chromehtml: URI value for the document.location property.

there is a possible Null Pointer Dereference (modem crash) due to improper input validation. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

Google Chrome 2.x through 2.0.172 allows remote attackers to cause a denial of service (application crash) via a long Unicode string argument to the write method, a related issue to CVE-2009-2479.

In parseUriInternal of Intent.java, there is a possible infinite loop due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

In sdpu_extract_attr_seq of sdp_utils.cc, there is a possible out of bounds read due to an incorrect bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

In SMF_ParseMetaEvent of eas_smf.c, there is a possible integer overflow. This could lead to remote denial of service due to resource exhaustion with no additional execution privileges needed. User interaction is needed for exploitation.

effects/SkDashPathEffect.cpp in Skia, as used in Google Chrome before 39.0.2171.65, computes a hash key using uninitialized integer values, which might allow remote attackers to cause a denial of service by rendering crafted data.

Remote prevention of access to cellular service with no user interaction (for example, crashing the cellular radio service with a malformed packet)

In DeregAcceptProcINT of cn_NrmmStateDeregInit.cpp, there is a possible denial of service due to a logic error in the code. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

The MPEG4Extractor::parse3GPPMetaData function in MPEG4Extractor.cpp in libstagefright in Android before 5.1.1 LMY48I does not enforce a minimum size for UTF-16 strings containing a Byte Order Mark (BOM), which allows remote attackers to cause a denial of service (integer underflow, buffer over-read, and mediaserver process crash) via crafted 3GPP metadata, aka internal bug 20923261, a related issue to CVE-2015-3828.

Multiple integer overflows in the addVorbisCodecInfo function in matroska/MatroskaExtractor.cpp in libstagefright in mediaserver in Android before 5.1.1 LMY48M allow remote attackers to cause a denial of service (device inoperability) via crafted Matroska data, aka internal bug 21296336.

mediaserver in Android before 5.1.1 LMY48T allows attackers to cause a denial of service (process crash) via unspecified vectors, aka internal bug 22954006.

PDFium, as used in Google Chrome before 41.0.2272.76, allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

Integer overflow in soundtrigger/ISoundTriggerHwService.cpp in Android allows attacks to cause a denial of service via unspecified vectors.

The Google Email application 4.2.2.0200 for Android allows remote attackers to cause a denial of service (persistent application crash) via a "Content-Disposition: ;" header in an e-mail message.

In ss_SendCallBarringPwdRequiredIndMsg of ss_CallBarring.c, there is a possible null pointer deref due to a missing null check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

OpenJPEG before r2944, as used in PDFium in Google Chrome before 40.0.2214.91, allows remote attackers to cause a denial of service (out-of-bounds read) via a crafted PDF document, related to j2k.c, jp2.c, pi.c, t1.c, t2.c, and tcd.c.

OpenJPEG before r2908, as used in PDFium in Google Chrome before 40.0.2214.91, allows remote attackers to cause a denial of service (out-of-bounds read) via a crafted PDF document, related to j2k.c, jp2.c, and t2.c.

Use-after-free vulnerability in the IndexedDB implementation in Google Chrome before 40.0.2214.91 allows remote attackers to cause a denial of service or possibly have unspecified other impact by triggering duplicate BLOB references, related to content/browser/indexed_db/indexed_db_callbacks.cc and content/browser/indexed_db/indexed_db_dispatcher_host.cc.

Skia, as used in Google Chrome before 40.0.2214.91, allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

The PDF functionality in Google Chrome before 20.0.1132.43 allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

In Telephony, there is a possible out of bounds read 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: ALPS09289881; Issue ID: MSV-2024.

In Telephony, there is a possible out of bounds read 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: ALPS09289881; Issue ID: MSV-2025.

In Telephony, there is a possible out of bounds read 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: ALPS09289881; Issue ID: MSV-2023.

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. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault 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. 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. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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 `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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 `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. 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 `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. 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.

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.

A parsing issue similar to CVE-2022-3171, but with Message-Type Extensions in protobuf-java core and lite versions prior to 3.21.7, 3.20.3, 3.19.6 and 3.16.3 can lead to a denial of service attack. Inputs containing multiple instances of non-repeated embedded messages with repeated or unknown fields causes objects to be converted back-n-forth between mutable and immutable forms, resulting in potentially long garbage collection pauses. We recommend updating to the versions mentioned above.

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. 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.