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19865125520dae798edef62fe30a3cb8d081e3fc33f1ceaaa8c1bdf846252d10 | NVD | CVE-2022-35984 | CVE-2022-35984: tensorflow | 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 72180be03447a10810ed... | 2022-09-16T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
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21ba867c9408798a760f2369df1df6353d16396712ea39f8df955264cabd3e20 | NVD | CVE-2021-41203 | CVE-2021-41203: tensorflow | TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation... | 2021-11-05T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | high | [
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a51ecbd517c4e09192e6c977b260992f2afef92f898834c8d4203d3a14d13ed2 | NVD | CVE-2025-4287 | CVE-2025-4287: PyTorch | A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function torch.cuda.nccl.reduce of the file torch/cuda/nccl.py. The manipulation leads to denial of service. It is possible to launch the attack on the local host. The exploit has been disclosed to the publ... | 2025-05-05T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | PyTorch | AML.T0029 | Impact | low | [
"pytorch",
"CWE-404"
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76bdf7d52b722eb87fdf7412f84e6683bee44565343a54a8068386dd7ca55763 | NVD | CVE-2020-15203 | CVE-2020-15203: tensorflow | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the `fill` argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed. This may result in segmentation fault. The issu... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | high | [
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5e844b269ff89b25f2f211f5f66c1fe5974c894ecdaad5a666b6adab3aecffd9 | NVD | CVE-2022-35983 | CVE-2022-35983: tensorflow | 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 i... | 2022-09-16T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
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341e8257f2d7c0b01fc7e2df96778f586829935833f7dd14a41016b14bfbe3db | NVD | CVE-2026-47749 | CVE-2026-47749: stable-diffusion.cpp | stable-diffusion.cpp is a pure C/C++ library for running diffusion model (Stable Diffusion, Flux, Wan, Qwen Image, Z-Image, and more) inference. Versions prior to master-584-0a7ae07 are vulnerable to heap buffer overflow in SHORT_BINUNICODE parsing for PyTorch checkpoint files. The pickle .ckpt parser in src/model.cpp ... | 2026-06-16T00:00:00 | 2026-07-03T06:02:47.161104Z | leejet | stable-diffusion.cpp | AML.T0049 | Initial Access | high | [
"pytorch",
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88f3d483f1d9bd3d9ad023df621bc0d88896cc45a14d55bc3e44ca37b288b6a0 | NVD | CVE-2021-41210 | CVE-2021-41210: tensorflow | TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5... | 2021-11-05T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | high | [
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02a32044eba8c947bdde33d7792d9b787d0f878d18f2d5e4bf28eb5e1dbe3a2b | NVD | CVE-2020-15204 | CVE-2020-15204: tensorflow | In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling `tf.raw_ops.GetSessionHandle` or `tf.raw_ops.GetSessionHandleV2` results in a null pointer dereference In linked snippet, in eager mode, `ctx->session_state()` returns `nullptr`. Since code imm... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
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9128af5db3ac2740ea2ffbf6c3fc8570e58f37986b1b06538cf85a2d8a88cb31 | NVD | CVE-2020-15209 | CVE-2020-15209: tensorflow | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
"tensorflow",
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79f4f8b8b6097dde437c2edc8e259a37c3ac4a536f4cce14a37b758b4e8cf809 | NVD | CVE-2022-35982 | CVE-2022-35982: tensorflow | TensorFlow is an open source platform for machine learning. If `SparseBincount` is given inputs for `indices`, `values`, and `dense_shape` that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0... | 2022-09-16T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
"CWE-20",
"NVD-CWE-noinfo"
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feba318ca1fc37ac210b3f050dad99fb5b677d9145839dc50078038ccee0c994 | NVD | CVE-2021-41195 | CVE-2021-41195: tensorflow | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `tf.math.segment_*` operations results in a `CHECK`-fail related abort (and denial of service) if a segment id in `segment_ids` is large. This is similar to CVE-2021-29584 (and similar other reported vulnerabilities i... | 2021-11-05T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
"CWE-190",
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] | https://nvd.nist.gov/vuln/detail/CVE-2021-41195 | {
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c2025231ce5875b95a6e5c7bbbe10980dc902787d9b64f0a407d7cda87fe3c5f | NVD | CVE-2023-30767 | CVE-2023-30767: TensorFlow | Improper buffer restrictions in Intel(R) Optimization for TensorFlow before version 2.13.0 may allow an authenticated user to potentially enable escalation of privilege via local access. | 2024-02-14T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | TensorFlow | AML.T0010.001 | Initial Access | medium | [
"tensorflow",
"CWE-92",
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7a7ecf40f4a16911577ebe8b4eeac5dc340ac0a78cf0c9d878630fd4d74c64f2 | NVD | CVE-2018-7575 | CVE-2018-7575: n/a | Google TensorFlow 1.7.x and earlier is affected by a Buffer Overflow vulnerability. The type of exploitation is context-dependent. | 2019-04-24T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | n/a | AML.T0010.001 | Initial Access | critical | [
"tensorflow",
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0deda0e341c2263ea810e715ea918a3e9bf037220616105fc0d0feda46da6986 | NVD | CVE-2021-37677 | CVE-2021-37677: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/te... | 2021-08-12T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
"CWE-20",
"CWE-1284"
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289912e63cf75023d498e355df37d6c856ee40291817aa771baaac9ff73e8ba1 | NVD | CVE-2020-15190 | CVE-2020-15190: tensorflow | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
"tensorflow",
"CWE-20",
"CWE-476",
"CWE-476"
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4d31fa3b972f44fff537721c387a193ca31580fa11a8c61851f46896ab4e3ae9 | NVD | CVE-2025-46153 | CVE-2025-46153: n/a | PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True. | 2025-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | n/a | AML.T0010.001 | Initial Access | medium | [
"pytorch",
"CWE-1176"
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e58113fcc69057ff15a9d1b39263c4a44b95461f76ac97abc8501224855cedfb | NVD | CVE-2021-29569 | CVE-2021-29569: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147... | 2021-05-14T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | low | [
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"CWE-125"
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f9e54017628dd5d31d215b357b661340afb00455de52a030584e383bb771b77d | NVD | CVE-2021-37670 | CVE-2021-37670: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb0... | 2021-08-12T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
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0ecc6ac9281ddb509c2ec0b31684c2bbce16c6dd82ae50ea08fb5b16d499ffa5 | NVD | CVE-2021-37669 | CVE-2021-37669: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00... | 2021-08-12T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
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ed31e573cbf0f7861be0545164065169619f7e3e18606db8bc020b18279ec2d4 | NVD | CVE-2023-5245 | CVE-2023-5245 | FileUtil.extract() enumerates all zip file entries and extracts each file without validating whether file paths in the archive are outside the intended directory.
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"CWE-22"
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5a2ba70b1c2897a7b6d4da03f90bc449b79a605a7ac167f25842116e24f48cb5 | NVD | CVE-2026-31239 | CVE-2026-31239: n/a | The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file without enabling the security-restrictive weights_only=True pa... | 2026-05-12T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | n/a | AML.T0049 | Initial Access | critical | [
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"CWE-502"
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42c8fa3e74994f56844b1deb11e2aea0ab372452aa914b9ad2b59fc4713fcd62 | NVD | CVE-2026-44484 | CVE-2026-44484: pytorch-lightning | PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism. | 2026-05-14T00:00:00 | 2026-07-03T06:02:47.161104Z | Lightning-AI | pytorch-lightning | AML.T0010.001 | Initial Access | critical | [
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"CWE-506",
"CWE-829"
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68912ad55880c6626502303d117a2613983a1050443dc9e4a57fd175b830dad3 | NVD | CVE-2021-37688 | CVE-2021-37688: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d9... | 2021-08-12T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | high | [
"tensorflow",
"CWE-476"
] | https://nvd.nist.gov/vuln/detail/CVE-2021-37688 | {
"cve": {
"id": "CVE-2021-37688",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 2.1,
"accessVector": "LOCAL",
"vectorStri... |
eeff04224bb35a1c10c5fa5ef4fd5b4c3c06cffbf20c77962581aba3e096523c | NVD | CVE-2022-23582 | CVE-2022-23582: tensorflow | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an... | 2022-02-04T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
"CWE-617"
] | https://nvd.nist.gov/vuln/detail/CVE-2022-23582 | {
"cve": {
"id": "CVE-2022-23582",
"cveTags": [],
"metrics": {
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-23582",
"role": "CISA Coordinator",
"options": [
{
... |
5aa940be35785d9b964d024278bc79ecb37ee4e9cff17b40f1d3fa58c3973e90 | NVD | CVE-2024-31583 | CVE-2024-31583: n/a | Pytorch before version v2.2.0 was discovered to contain a use-after-free vulnerability in torch/csrc/jit/mobile/interpreter.cpp. | 2024-04-17T00:00:00 | 2026-07-03T06:02:47.161104Z | n/a | n/a | AML.T0010.001 | Initial Access | high | [
"pytorch",
"CWE-416"
] | https://nvd.nist.gov/vuln/detail/CVE-2024-31583 | {
"cve": {
"id": "CVE-2024-31583",
"cveTags": [],
"metrics": {
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2024-31583",
"role": "CISA Coordinator",
"options": [
{
... |
b3397e1dbcc0e538061da74ebc33dfdc914bef1558a804f90a6e88432896690d | NVD | CVE-2020-15196 | CVE-2020-15196: tensorflow | In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still access... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | high | [
"tensorflow",
"CWE-119",
"CWE-122",
"CWE-125"
] | https://nvd.nist.gov/vuln/detail/CVE-2020-15196 | {
"cve": {
"id": "CVE-2020-15196",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 6.5,
"accessVector": "NETWORK",
"vectorSt... |
33908079ebc4465fcc6fd674ab4285a25fc3a3e9c41d2670b3264aeb7192f497 | NVD | CVE-2020-15266 | CVE-2020-15266: tensorflow | In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7e... | 2020-10-21T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | low | [
"tensorflow",
"CWE-119",
"CWE-119"
] | https://nvd.nist.gov/vuln/detail/CVE-2020-15266 | {
"cve": {
"id": "CVE-2020-15266",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 5,
"accessVector": "NETWORK",
"vectorStri... |
df37ae8b31f86429025a41a3bb882f297d2b62cd675ce3f701bc2ddf27094b4f | NVD | CVE-2020-15197 | CVE-2020-15197: tensorflow | In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0029 | Impact | medium | [
"tensorflow",
"CWE-20",
"CWE-617"
] | https://nvd.nist.gov/vuln/detail/CVE-2020-15197 | {
"cve": {
"id": "CVE-2020-15197",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 3.5,
"accessVector": "NETWORK",
"vectorSt... |
2457e78f58d8859f5391de28a2dd6109ac0eb18d93cb863d9cc16bccb65109b3 | NVD | CVE-2020-15198 | CVE-2020-15198: tensorflow | In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thu... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
"tensorflow",
"CWE-119",
"CWE-122",
"CWE-119"
] | https://nvd.nist.gov/vuln/detail/CVE-2020-15198 | {
"cve": {
"id": "CVE-2020-15198",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 5.8,
"accessVector": "NETWORK",
"vectorSt... |
2ab1ba239fe2ca648e4add3521c07a0d46ac10e078b5adeeabf6cb58cd16c189 | NVD | CVE-2020-15199 | CVE-2020-15199: tensorflow | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `Ba... | 2020-09-25T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | medium | [
"tensorflow",
"CWE-20",
"CWE-20"
] | https://nvd.nist.gov/vuln/detail/CVE-2020-15199 | {
"cve": {
"id": "CVE-2020-15199",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 4.3,
"accessVector": "NETWORK",
"vectorSt... |
a19c97405d56c93f4bd61b397c7d19cca6bd73f49dbe75b10f2262e7b6fbc980 | NVD | CVE-2021-29570 | CVE-2021-29570: tensorflow | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725d... | 2021-05-14T00:00:00 | 2026-07-03T06:02:47.161104Z | tensorflow | tensorflow | AML.T0010.001 | Initial Access | low | [
"tensorflow",
"CWE-125"
] | https://nvd.nist.gov/vuln/detail/CVE-2021-29570 | {
"cve": {
"id": "CVE-2021-29570",
"cveTags": [],
"metrics": {
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 3.6,
"accessVector": "LOCAL",
"vectorStri... |
2971584deaa36daa42f24333738f364ca68d4921e9b5d4f06de9375826974589 | NVD | CVE-2025-10772 | CVE-2025-10772: LeRobot | A vulnerability was identified in huggingface LeRobot up to 0.3.3. Affected by this vulnerability is an unknown functionality of the file lerobot/common/robot_devices/robots/lekiwi_remote.py of the component ZeroMQ Socket Handler. The manipulation leads to missing authentication. The attack can only be initiated within... | 2025-09-22T00:00:00 | 2026-07-03T06:02:47.161104Z | huggingface | LeRobot | AML.T0010.001 | Initial Access | medium | [
"huggingface",
"CWE-287",
"CWE-306"
] | https://nvd.nist.gov/vuln/detail/CVE-2025-10772 | {
"cve": {
"id": "CVE-2025-10772",
"cveTags": [],
"metrics": {
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-10772",
"role": "CISA Coordinator",
"options": [
{
... |
3275e867857f7ef47ba84297949d0f93a5344911cd5e0c6e7a781f86bdd861f3 | NVD | CVE-2025-5120 | CVE-2025-5120: huggingface/smolagents | A sandbox escape vulnerability was identified in huggingface/smolagents version 1.14.0, allowing attackers to bypass the restricted execution environment and achieve remote code execution (RCE). The vulnerability stems from the local_python_executor.py module, which inadequately restricts Python code execution despite ... | 2025-07-27T00:00:00 | 2026-07-03T06:02:47.161104Z | huggingface | huggingface/smolagents | AML.T0057 | Exfiltration | critical | [
"huggingface",
"CWE-94"
] | https://nvd.nist.gov/vuln/detail/CVE-2025-5120 | {
"cve": {
"id": "CVE-2025-5120",
"cveTags": [],
"metrics": {
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-5120",
"role": "CISA Coordinator",
"options": [
{
... |
End of preview. Expand in Data Studio
ai-sentinel-feed
Unified, normalized AI incident records from public sources, mapped where possible to the MITRE ATLAS adversarial ML taxonomy.
Live API: see the project README on GitHub (tk-tobi/ai-sentinel-feed).
Dataset splits
| Split | Description |
|---|---|
incidents |
All normalized records |
incidents_atlas_mapped |
Records with a mapped ATLAS technique (not unmapped) |
jailbreaks |
Records tagged heuristically for jailbreak / prompt-injection themes |
Record counts at last sync (2026-07-03T06:03:37Z):
{
"incidents": 4396,
"incidents_atlas_mapped": 2701,
"jailbreaks": 15
}
Total incidents in incidents: 4396.
Schema
Each row is a JSON object with:
| Field | Type | Description |
|---|---|---|
id |
string | Stable SHA-256 id (source + source_id) |
source |
string | NVD, AIID, or AIAAIC |
source_id |
string | Upstream identifier (CVE id, AIID id, AIAAIC id) |
title |
string | Short headline |
description |
string | Normalized description (PII masked) |
incident_date |
date | null | When the incident occurred |
ingested_at |
datetime | When this pipeline ingested the record |
vendor |
string | null | Alleged deployer / vendor |
system |
string | null | Product or system name |
atlas_technique |
string | MITRE ATLAS technique id or unmapped |
atlas_tactic |
string | null | ATLAS tactic name |
severity |
string | critical, high, medium, low, informational |
tags |
list[string] | Source-specific tags |
url |
string | null | Canonical reference URL |
raw |
object | Untouched upstream payload subset |
Sources
- NVD: AI/ML library CVEs (
pytorch,tensorflow,langchain,huggingface) - AIID: AI Incident Database
- AIAAIC: AIAAIC Repository
Usage
from datasets import load_dataset
ds = load_dataset("tk-tobi/ai-sentinel-feed")
print(ds["incidents"][0])
# Or load a single JSONL file directly:
ds = load_dataset("json", data_files="hf://datasets/tk-tobi/ai-sentinel-feed/incidents.jsonl")
Citation
If you use this dataset, cite the upstream sources (NVD, AIID, AIAAIC) and link to the ai-sentinel-feed repository.
License
Dataset compilation and normalization code is MIT-licensed. Upstream content remains subject to each source's terms.
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