ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2014-10 | null | PIL/IcnsImagePlugin.py in Python Imaging Library (PIL) and Pillow before 2.3.2 and 2.5.x before 2.5.2 allows remote attackers to cause a denial of service via a crafted block size. | {'CVE-2014-3589'} | 2021-07-05T00:01:23.718339Z | 2014-08-25T14:55:00Z | null | null | null | {'http://secunia.com/advisories/59825', 'http://lists.opensuse.org/opensuse-updates/2015-04/msg00056.html', 'http://www.debian.org/security/2014/dsa-3009', 'https://pypi.python.org/pypi/Pillow/2.3.2', 'https://pypi.python.org/pypi/Pillow/2.5.2', 'https://github.com/python-pillow/Pillow/commit/205e056f8f9b06ed7b925cf8aa0874bc4aaf8a7d'} | null |
PyPI | PYSEC-2021-141 | null | In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service. | {'GHSA-pq64-v7f5-gqh8', 'CVE-2021-27291'} | 2021-08-27T03:22:17.331175Z | 2021-03-17T13:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GSJRFHALQ7E3UV4FFMFU2YQ6LUDHAI55/', 'https://gist.github.com/b-c-ds/b1a2cc0c68a35c57188575eb496de5ce', 'https://www.debian.org/security/2021/dsa-4889', 'https://lists.debian.org/debian-lts-announce/2021/03/msg00024.html', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00003.html', 'https://github.com/advisories/GHSA-pq64-v7f5-gqh8', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00006.html', 'https://www.debian.org/security/2021/dsa-4878', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WSLD67LFGXOX2K5YNESSWAS4AGZIJTUQ/', 'https://github.com/pygments/pygments/commit/2e7e8c4a7b318f4032493773732754e418279a14'} | null |
PyPI | GHSA-qfc5-mcwq-26q8 | Double Free in psutil | psutil (aka python-psutil) through 5.6.5 can have a double free. This occurs because of refcount mishandling within a while or for loop that converts system data into a Python object. | {'CVE-2019-18874'} | 2022-03-03T05:13:57.772669Z | 2020-03-12T17:02:50Z | HIGH | null | {'CWE-415'} | {'https://github.com/giampaolo/psutil/blob/master/HISTORY.rst#566', 'https://github.com/giampaolo/psutil/pull/1616', 'https://lists.debian.org/debian-lts-announce/2019/11/msg00018.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2P7QI7MOTZTFXQYU23CP3RAWXCERMOAS/', 'https://usn.ubuntu.com/4204-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OLETTJYZL2SMBUI4Q2NGBMGPDPP54SRG/', 'https://nvd.nist.gov/vuln/detail/CVE-2019-18874', 'https://github.com/giampaolo/psutil/commit/7d512c8e4442a896d56505be3e78f1156f443465'} | null |
PyPI | GHSA-926q-wxr6-3crq | Moderate severity vulnerability that affects roundup | Roundup 1.6 allows XSS via the URI because frontends/roundup.cgi and roundup/cgi/wsgi_handler.py mishandle 404 errors. | {'CVE-2019-10904'} | 2022-03-03T05:14:03.497527Z | 2019-04-09T19:47:14Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-10904', 'https://bugs.python.org/issue36391', 'https://github.com/python/bugs.python.org/issues/34', 'https://www.openwall.com/lists/oss-security/2019/04/05/1', 'http://www.openwall.com/lists/oss-security/2019/04/07/1', 'https://github.com/advisories/GHSA-926q-wxr6-3crq', 'https://lists.debian.org/debian-lts-announce/2019/04/msg00009.html'} | null |
PyPI | PYSEC-2021-61 | null | clickhouse-driver before 0.1.5 allows a malicious clickhouse server to trigger a crash or execute arbitrary code (on a database client) via a crafted server response, due to a buffer overflow. | {'GHSA-vgv5-cxvh-vfxh', 'CVE-2020-26759'} | 2021-01-08T21:19:00Z | 2021-01-06T13:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-vgv5-cxvh-vfxh', 'https://github.com/mymarilyn/clickhouse-driver/commit/3e990547e064b8fca916b23a0f7d6fe8c63c7f6b', 'https://github.com/mymarilyn/clickhouse-driver/commit/d708ed548e1d6f254ba81a21de8ba543a53b5598'} | null |
PyPI | GHSA-fm39-cw8h-3p63 | Out-of-bounds Read in OpenCV | An issue was discovered in OpenCV before 3.4.7 and 4.x before 4.1.1 (OpenCV-Python before 3.4.7.28 and 4.x before 4.1.1.26). There is an out of bounds read in the function cv::predictOrdered<cv::HaarEvaluator> in modules/objdetect/src/cascadedetect.hpp, which leads to denial of service. | {'CVE-2019-14491'} | 2022-03-03T05:13:57.686816Z | 2021-10-12T22:07:14Z | HIGH | null | {'CWE-125'} | {'https://github.com/opencv/opencv/compare/371bba8...ddbd10c', 'https://github.com/opencv/opencv/issues/15125', 'https://nvd.nist.gov/vuln/detail/CVE-2019-14491', 'https://github.com/opencv/opencv/compare/33b765d...4a7ca5a', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HPFLN6QAX6SUA4XR4NMKKXX26H3TYCVQ/', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2021-784 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37673', 'GHSA-278g-rq84-9hmg'} | 2021-12-09T06:35:38.706561Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-278g-rq84-9hmg'} | null |
PyPI | GHSA-hggm-jpg3-v476 | RSA decryption vulnerable to Bleichenbacher timing vulnerability | ### Impact
RSA decryption was vulnerable to Bleichenbacher timing vulnerabilities, which would impact people using RSA decryption in online scenarios.
### Patches
This is fixed in cryptography 3.2. https://github.com/pyca/cryptography/commit/58494b41d6ecb0f56b7c5f05d5f5e3ca0320d494 is the resolving commit. | {'CVE-2020-25659'} | 2022-04-25T21:46:57.889394Z | 2020-10-27T20:33:13Z | MODERATE | null | {'CWE-385'} | {'https://github.com/pyca/cryptography/commit/58494b41d6ecb0f56b7c5f05d5f5e3ca0320d494', 'https://pypi.org/project/cryptography/', 'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-25659', 'https://github.com/pyca/cryptography', 'https://github.com/pyca/cryptography/security/advisories/GHSA-hggm-jpg3-v476', 'https://github.com/pyca/cryptography/pull/5507/commits/ce1bef6f1ee06ac497ca0c837fbd1c7ef6c2472b'} | null |
PyPI | PYSEC-2020-291 | null | In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. This results in special casing during validation at model loading time. Unfortunately, this means that the `-1` index is a valid tensor index for any operator, including those that don't expect optional inputs and including for output tensors. Thus, this allows writing and reading from outside the bounds of heap allocated arrays, although only at a specific offset from the start of these arrays. This results in both read and write gadgets, albeit very limited in scope. The issue is patched in several commits (46d5b0852, 00302787b7, e11f5558, cd31fd0ce, 1970c21, and fff2c83), and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that only operators which accept optional inputs use the `-1` special value and only for the tensors that they expect to be optional. Since this allow-list type approach is erro-prone, we advise upgrading to the patched code. | {'GHSA-cvpc-8phh-8f45', 'CVE-2020-15211'} | 2021-12-09T06:34:43.650264Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/fff2c8326280c07733828f990548979bdc893859', 'https://github.com/tensorflow/tensorflow/commit/cd31fd0ce0449a9e0f83dcad08d6ed7f1d6bef3f', 'https://github.com/tensorflow/tensorflow/commit/00302787b788c5ff04cb6f62aed5a74d936e86c0', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvpc-8phh-8f45', 'https://github.com/tensorflow/tensorflow/commit/1970c2158b1ffa416d159d03c3370b9a462aee35', 'https://github.com/tensorflow/tensorflow/commit/e11f55585f614645b360563072ffeb5c3eeff162', 'https://github.com/tensorflow/tensorflow/commit/46d5b0852528ddfd614ded79bccc75589f801bd9', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2019-238 | null | An issue was discovered in py-lmdb 0.97. mdb_node_del does not validate a memmove in the case of an unexpected node->mn_hi, leading to an invalid write operation. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker. | {'CVE-2019-16226'} | 2021-12-14T08:17:08.339672Z | 2019-09-11T15:15:00Z | null | null | null | {'https://github.com/TeamSeri0us/pocs/tree/master/lmdb/lmdb%20memory%20corruption%20vuln', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16226', 'https://pypi.org/project/lmdb'} | null |
PyPI | GHSA-jwf9-w5xm-f437 | Heap OOB in TFLite's `Gather*` implementations | ### Impact
TFLite's [`GatherNd` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather_nd.cc#L124) does not support negative indices but there are no checks for this situation.
Hence, an attacker can read arbitrary data from the heap by carefully crafting a model with negative values in `indices`.
Similar issue exists in [`Gather` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather.cc).
```python
import tensorflow as tf
import numpy as np
tf.compat.v1.disable_v2_behavior()
params = tf.compat.v1.placeholder(name="params", dtype=tf.int64, shape=(1,))
indices = tf.compat.v1.placeholder(name="indices", dtype=tf.int64, shape=())
out = tf.gather(params, indices, name='out')
with tf.compat.v1.Session() as sess:
converter = tf.compat.v1.lite.TFLiteConverter.from_session(sess, [params, indices], [out])
tflite_model = converter.convert()
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
params_data = np.reshape(np.array([1], dtype=np.int64), newshape=(1,))
indices_data = np.reshape(np.array(-10, dtype=np.int64), newshape=())
interpreter.set_tensor(input_details[0]['index'], params_data)
interpreter.set_tensor(input_details[1]['index'], indices_data)
interpreter.invoke()
```
### Patches
We have patched the issue in GitHub commits [bb6a0383ed553c286f87ca88c207f6774d5c4a8f](https://github.com/tensorflow/tensorflow/commit/bb6a0383ed553c286f87ca88c207f6774d5c4a8f) and [eb921122119a6b6e470ee98b89e65d721663179d](https://github.com/tensorflow/tensorflow/commit/eb921122119a6b6e470ee98b89e65d721663179d).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security. | {'CVE-2021-37687'} | 2021-08-24T17:49:13Z | 2021-08-25T14:40:02Z | MODERATE | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/eb921122119a6b6e470ee98b89e65d721663179d', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37687', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jwf9-w5xm-f437', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/bb6a0383ed553c286f87ca88c207f6774d5c4a8f'} | null |
PyPI | GHSA-9rpc-5v9q-5r7f | Incomplete validation in `SparseReshape` | ### Impact
Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure.
```python
import tensorflow as tf
input_indices = tf.constant(41, shape=[1, 1], dtype=tf.int64)
input_shape = tf.zeros([11], dtype=tf.int64)
new_shape = tf.zeros([1], dtype=tf.int64)
tf.raw_ops.SparseReshape(input_indices=input_indices,
input_shape=input_shape,
new_shape=new_shape)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments specify a valid sparse tensor.
### Patches
We have patched the issue in GitHub commit [1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6](https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29611'} | 2022-03-03T05:14:19.417863Z | 2021-05-21T14:28:35Z | LOW | null | {'CWE-20', 'CWE-665'} | {'https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29611', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9rpc-5v9q-5r7f'} | null |
PyPI | PYSEC-2017-16 | null | Cross-site request forgery (CSRF) vulnerability in Kallithea before 0.2. | {'CVE-2015-0276'} | 2021-07-05T00:01:22.120949Z | 2017-09-21T14:29:00Z | null | null | null | {'http://www.securityfocus.com/bid/74052', 'https://kallithea-scm.org/security/cve-2015-0276.html', 'http://www.openwall.com/lists/oss-security/2015/04/10/8'} | null |
PyPI | GHSA-pqjj-6f5q-gqph | Denial of Service in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to OpenCV-Python 3.3.0.9) has a denial of service (memory consumption) issue, as demonstrated by the 10-opencv-dos-memory-exhaust test case. | {'CVE-2017-12602'} | 2022-03-03T05:13:18.851591Z | 2021-10-12T22:01:34Z | HIGH | null | null | {'https://github.com/opencv/opencv/issues/9311', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12602', 'https://security.gentoo.org/glsa/201712-02', 'https://github.com/xiaoqx/pocs/blob/master/opencv.md', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2021-291 | null | 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/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vmjw-c2vp-p33c', 'CVE-2021-37669'} | 2021-08-27T03:22:45.759545Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d'} | null |
PyPI | GHSA-9xh4-23q4-v6wr | Heap buffer overflow and undefined behavior in `FusedBatchNorm` | ### Impact
The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow:
```python
import tensorflow as tf
x = tf.zeros([10, 10, 10, 6], dtype=tf.float32)
scale = tf.constant([0.0], shape=[1], dtype=tf.float32)
offset = tf.constant([0.0], shape=[1], dtype=tf.float32)
mean = tf.constant([0.0], shape=[1], dtype=tf.float32)
variance = tf.constant([0.0], shape=[1], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False
tf.raw_ops.FusedBatchNorm(
x=x, scale=scale, offset=offset, mean=mean, variance=variance,
epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,
data_format=data_format, is_training=is_training)
```
If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers:
```python
import tensorflow as tf
import numpy as np
x = tf.zeros([10, 10, 10, 1], dtype=tf.float32)
scale = tf.constant([], shape=[0], dtype=tf.float32)
offset = tf.constant([], shape=[0], dtype=tf.float32)
mean = tf.constant([], shape=[0], dtype=tf.float32)
variance = tf.constant([], shape=[0], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False
tf.raw_ops.FusedBatchNorm(
x=x, scale=scale, offset=offset, mean=mean, variance=variance,
epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,
data_format=data_format, is_training=is_training)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary.
If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior.
### Patches
We have patched the issue in GitHub commit [6972f9dfe325636b3db4e0bc517ee22a159365c0](https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29583'} | 2022-04-26T18:17:19.393448Z | 2021-05-21T14:26:35Z | LOW | null | {'CWE-476', 'CWE-787', 'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29583', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9xh4-23q4-v6wr'} | null |
PyPI | PYSEC-2022-71 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `Range` suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-qx3f-p745-w4hr', 'CVE-2022-23562'} | 2022-03-09T00:17:32.679005Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f0147751fd5d2ff23251149ebad9af9f03010732', 'https://github.com/tensorflow/tensorflow/pull/51733', 'https://github.com/tensorflow/tensorflow/issues/52676', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qx3f-p745-w4hr'} | null |
PyPI | PYSEC-2012-4 | null | The get_image_dimensions function in the image-handling functionality in Django before 1.3.2 and 1.4.x before 1.4.1 uses a constant chunk size in all attempts to determine dimensions, which allows remote attackers to cause a denial of service (process or thread consumption) via a large TIFF image. | {'CVE-2012-3444'} | 2021-07-05T00:01:18.369979Z | 2012-07-31T17:55:00Z | null | null | null | {'http://www.debian.org/security/2012/dsa-2529', 'http://www.mandriva.com/security/advisories?name=MDVSA-2012:143', 'http://www.openwall.com/lists/oss-security/2012/07/31/1', 'http://www.ubuntu.com/usn/USN-1560-1', 'http://www.openwall.com/lists/oss-security/2012/07/31/2', 'https://www.djangoproject.com/weblog/2012/jul/30/security-releases-issued/'} | null |
PyPI | GHSA-7fcj-pq9j-wh2r | Local Privilege Escalation in PyInstaller | ### Impact
Local Privilege Escalation in all Windows software frozen by PyInstaller in "onefile" mode.
The vulnerability is present only on Windows and in this particular case: If a **software frozen by PyInstaller in "onefile" mode** is launched by a (privileged) user who has **his/her "TempPath" resolving to a world writable directory**. This is the case e.g. if the software is launched as a service or as a scheduled task using a system account (in which case TempPath will default to C:\Windows\Temp).
In order to be exploitable the software has to be (re)started after the attacker has launched the exploit program. So for a service launched at startup, a service restart is needed (e.g. after a crash or an upgrade).
While PyInstaller itself was not vulnerable, all Windows software frozen by PyInstaller in "onefile" mode is vulnerable.
CVSSv3 score 7.0 (High)
CVSSv3 vector CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
Affected
- all Windows software frozen by PyInstaller in "onefile" mode
No affected
- PyInstaller itself (except if frozen by PyInstaller in "onefile" mode on Windows)
- software frozen in "one*dir*" mode
- other platforms (GNU/Linux, OS X, BSD, etc.)
### Patches
The problem is patched in commits 42a67148b3bdf9211fda8499fdc5b63acdd7e6cc (fixed code) and be948cf0954707671aa499da17b10c86b6fa5e5c (recompiled bootloaders). Users should upgrade to PyInstaller version 3.6 and rebuild their software.
### Workarounds
There is no known workaround. Users using PyInstaller to freeze their Windows software using "onefile" mode should upgrade PyInstaller and rebuild their software.
### Credits
This vulnerability was discovered and reported by Farid AYOUJIL (@faridtsl), David HA, Florent LE NIGER and Yann GASCUEL (@lnv42) from Alter Solutions (@AlterSolutions) and fixed in collaboration with
Hartmut Goebel (@htgoebel, maintainer of PyInstaller).
### Funding Development
PyInstaller is in urgent need of funding to make future security fixes happen, see <https://github.com/pyinstaller/pyinstaller/issues/4404> for details. | {'CVE-2019-16784'} | 2022-03-03T05:13:02.928204Z | 2020-01-16T22:18:27Z | HIGH | null | {'CWE-250'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-16784', 'https://github.com/pyinstaller/pyinstaller/commit/be948cf0954707671aa499da17b10c86b6fa5e5c', 'https://github.com/pyinstaller/pyinstaller/commit/42a67148b3bdf9211fda8499fdc5b63acdd7e6cc', 'https://github.com/pyinstaller/pyinstaller/security/advisories/GHSA-7fcj-pq9j-wh2r'} | null |
PyPI | PYSEC-2018-111 | null | Ajenti version version 2 contains a Cross ite Request Forgery (CSRF) vulnerability in the command execution panel of the tool used to manage the server. that can result in Code execution on the server . This attack appear to be exploitable via Being a CSRF, victim interaction is needed, when the victim access the infected trigger of the CSRF any code that match the victim privledges on the server can be executed.. | {'CVE-2018-1000082'} | 2022-02-17T09:17:11.053772Z | 2018-03-13T15:29:00Z | null | null | null | {'https://pypi.org/project/ajenti-panel', 'https://medium.com/stolabs/security-issues-on-ajenti-d2b7526eaeee', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000082'} | null |
PyPI | PYSEC-2021-442 | null | TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected. | {'CVE-2021-29514', 'GHSA-8h46-5m9h-7553'} | 2021-12-09T06:34:45.524725Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8h46-5m9h-7553', 'https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5'} | null |
PyPI | GHSA-fr58-2xhv-qp3w | Denial of Service in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to OpenCV-Python 3.3.0.9) has a denial of service (CPU consumption) issue, as demonstrated by the 11-opencv-dos-cpu-exhaust test case. | {'CVE-2017-12600'} | 2022-03-03T05:13:02.507054Z | 2021-10-12T22:01:16Z | HIGH | null | null | {'https://github.com/opencv/opencv/issues/9311', 'https://github.com/opencv/opencv-python/releases/tag/11', 'https://security.gentoo.org/glsa/201712-02', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12600', 'https://github.com/xiaoqx/pocs/blob/master/opencv.md', 'https://github.com/opencv/opencv-python/releases/tag/9', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2021-157 | null | TensorFlow is an end-to-end open source platform for machine learning. Missing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the `input`, `filter_sizes` and `out_backprop` tensors have the same shape, as they are accessed in parallel. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29520', 'GHSA-wcv5-qrj6-9pfm'} | 2021-08-27T03:22:24.934633Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wcv5-qrj6-9pfm', 'https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197'} | null |
PyPI | PYSEC-2021-507 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-79fv-9865-4qcv', 'CVE-2021-29579'} | 2021-12-09T06:34:55.622531Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79fv-9865-4qcv', 'https://github.com/tensorflow/tensorflow/commit/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7'} | null |
PyPI | PYSEC-2020-157 | null | Open redirect vulnerability in werkzeug before 0.11.6 via a double slash in the URL. | {'GHSA-3p3h-qghp-hvh2', 'CVE-2020-28724'} | 2020-12-01T16:05:00Z | 2020-11-18T15:15:00Z | null | null | null | {'https://github.com/pallets/werkzeug/pull/890/files', 'https://github.com/pallets/werkzeug/issues/822', 'https://github.com/advisories/GHSA-3p3h-qghp-hvh2', 'https://github.com/pallets/flask/issues/1639'} | null |
PyPI | PYSEC-2008-3 | null | Directory traversal vulnerability in the _get_file_path function in (1) lib/sessions.py in CherryPy 3.0.x up to 3.0.2, (2) filter/sessionfilter.py in CherryPy 2.1, and (3) filter/sessionfilter.py in CherryPy 2.x allows remote attackers to create or delete arbitrary files, and possibly read and write portions of arbitrary files, via a crafted session id in a cookie. | {'CVE-2008-0252'} | 2021-07-16T01:31:05.763719Z | 2008-01-12T02:46:00Z | null | null | null | {'http://www.cherrypy.org/changeset/1775', 'http://secunia.com/advisories/28354', 'http://www.vupen.com/english/advisories/2008/0039', 'http://www.securityfocus.com/bid/27181', 'http://secunia.com/advisories/28353', 'https://bugs.gentoo.org/show_bug.cgi?id=204829', 'http://www.cherrypy.org/changeset/1776', 'http://secunia.com/advisories/28611', 'http://secunia.com/advisories/28620', 'http://secunia.com/advisories/28769', 'http://security.gentoo.org/glsa/glsa-200801-11.xml', 'https://www.redhat.com/archives/fedora-package-announce/2008-January/msg00240.html', 'https://www.redhat.com/archives/fedora-package-announce/2008-January/msg00297.html', 'http://www.cherrypy.org/ticket/744', 'http://www.securityfocus.com/archive/1/487001/100/0/threaded', 'https://issues.rpath.com/browse/RPL-2127', 'http://www.debian.org/security/2008/dsa-1481', 'http://www.cherrypy.org/changeset/1774'} | null |
PyPI | PYSEC-2021-854 | null | A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. | {'CVE-2021-33430', 'GHSA-6p56-wp2h-9hxr'} | 2021-12-22T21:28:25.850575Z | 2021-12-17T19:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-6p56-wp2h-9hxr', 'https://github.com/numpy/numpy/issues/18939'} | null |
PyPI | PYSEC-2018-25 | null | In Apache Spark 1.0.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, when using PySpark or SparkR, it's possible for a different local user to connect to the Spark application and impersonate the user running the Spark application. | {'CVE-2018-1334'} | 2021-06-16T00:03:24.717902Z | 2018-07-12T13:29:00Z | null | null | null | {'https://lists.apache.org/thread.html/4d6d210e319a501b740293daaeeeadb51927111fb8261a3e4cd60060@%3Cdev.spark.apache.org%3E', 'https://spark.apache.org/security.html#CVE-2018-1334'} | null |
PyPI | PYSEC-2020-229 | null | django-nopassword before 5.0.0 stores cleartext secrets in the database. | {'GHSA-37cf-r3w2-gjfw', 'CVE-2019-10682'} | 2021-08-27T03:21:57.541967Z | 2020-03-18T15:15:00Z | null | null | null | {'https://github.com/relekang/django-nopassword/blob/8e8cfc765ee00adfed120c2c79bf71ef856e9022/nopassword/models.py#L14', 'https://github.com/relekang/django-nopassword/compare/v4.0.1...v5.0.0', 'https://github.com/relekang/django-nopassword/commit/d8b4615f5fbfe3997d96cf4cb3e342406396193c', 'https://github.com/advisories/GHSA-37cf-r3w2-gjfw'} | null |
PyPI | PYSEC-2021-229 | null | TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29592', 'GHSA-jjr8-m8g8-p6wv'} | 2021-08-27T03:22:37.768858Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jjr8-m8g8-p6wv', 'https://github.com/tensorflow/tensorflow/commit/f8378920345f4f4604202d4ab15ef64b2aceaa16'} | null |
PyPI | PYSEC-2021-679 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29553', 'GHSA-h9px-9vqg-222h'} | 2021-12-09T06:35:23.959666Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h', 'https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387'} | null |
PyPI | PYSEC-2021-383 | null | Nameko through 2.13.0 can be tricked into performing arbitrary code execution when deserializing the config file. | {'GHSA-6p52-jr3q-c94g', 'CVE-2021-41078'} | 2021-10-29T05:27:28.492888Z | 2021-10-26T13:15:00Z | null | null | null | {'https://github.com/nameko/nameko', 'https://github.com/nameko/nameko/security/advisories/GHSA-6p52-jr3q-c94g'} | null |
PyPI | PYSEC-2021-36 | null | An issue was discovered in Pillow before 8.1.1. In TiffDecode.c, there is a negative-offset memcpy with an invalid size. | {'GHSA-8xjq-8fcg-g5hw', 'CVE-2021-25290'} | 2021-03-22T14:11:00Z | 2021-03-19T04:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-8xjq-8fcg-g5hw', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html'} | null |
PyPI | PYSEC-2021-696 | null | 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/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29570', 'GHSA-545v-42p7-98fq'} | 2021-12-09T06:35:26.840571Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-545v-42p7-98fq', 'https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886'} | null |
PyPI | GHSA-65xw-pcqw-hjrh | Cross site scripting in apache airflow | It was discovered that the "Trigger DAG with config" screen was susceptible to XSS attacks via the `origin` query argument. This issue affects Apache Airflow versions 2.2.3 and below. | {'CVE-2021-45229'} | 2022-03-07T20:47:58.195568Z | 2022-02-26T00:00:45Z | MODERATE | null | {'CWE-79'} | {'https://github.com/apache/airflow', 'https://lists.apache.org/thread/phx76cgtmhwwdy780rvwhobx8qoy4bnk', 'https://nvd.nist.gov/vuln/detail/CVE-2021-45229'} | null |
PyPI | PYSEC-2017-41 | null | The XML-RPC server in supervisor before 3.0.1, 3.1.x before 3.1.4, 3.2.x before 3.2.4, and 3.3.x before 3.3.3 allows remote authenticated users to execute arbitrary commands via a crafted XML-RPC request, related to nested supervisord namespace lookups. | {'CVE-2017-11610'} | 2021-07-05T00:01:27.197995Z | 2017-08-23T14:29:00Z | null | null | null | {'https://github.com/Supervisor/supervisor/blob/3.1.4/CHANGES.txt', 'https://access.redhat.com/errata/RHSA-2017:3005', 'https://github.com/Supervisor/supervisor/blob/3.3.3/CHANGES.txt', 'http://www.debian.org/security/2017/dsa-3942', 'https://github.com/Supervisor/supervisor/blob/3.2.4/CHANGES.txt', 'https://github.com/Supervisor/supervisor/issues/964', 'https://github.com/Supervisor/supervisor/blob/3.0.1/CHANGES.txt', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4GMSCGMM477N64Z3BM34RWYBGSLK466B/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DTPDZV4ZRICDYAYZVUHSYZAYDLRMG2IM/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JXGWOJNSWWK2TTWQJZJUP66FLFIWDMBQ/', 'https://security.gentoo.org/glsa/201709-06', 'https://www.exploit-db.com/exploits/42779/'} | null |
PyPI | GHSA-mw6v-crh8-8533 | Integer Overflow or Wraparound in Google TensorFlow | Google TensorFlow 1.7.x and earlier is affected by a Buffer Overflow vulnerability. The type of exploitation is context-dependent. | {'CVE-2018-7575'} | 2022-03-23T22:30:08.476235Z | 2019-04-30T15:36:41Z | CRITICAL | null | {'CWE-190'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-004.md', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7575', 'https://github.com/tensorflow/tensorflow/commit/d107fee1e4a9a4462f01564798d345802acc2aef'} | null |
PyPI | GHSA-g4gq-j4p2-j8fr | Remote Code Execution via Script (Python) objects under Python 3 | ### Impact
Background: The optional add-on package `Products.PythonScripts` adds `Script (Python)` to the list of content items a user can add to the Zope object database. Inside these scripts users can write Python code that is executed when rendered through the web. The code environment in these script objects is limited, it relies on the `RestrictedPython` package to provide a "safe" subset of Python instructions as well as the `AccessControl` package that defines security policies for execution in the context of a Zope application.
Recently the `AccessControl` package was updated to fix a remote code execution security issue. A link to the security advisory is provided in the References section below. The bug tightens the `AccessControl` security policies for Zope by blocking access to unsafe classes inside the Python `string` module.
You are only affected if the following are true:
- You use Python 3 for your Zope deployment (Zope 4 on Python 2 is not affected)
- You run Zope 4 below version 4.6.3 or Zope 5 below version 5.3
- You have installed the optional `Products.PythonScripts` add-on package
By default, you need to have the admin-level Zope "Manager" role to add or edit Script (Python) objects through the web. Only sites that allow untrusted users to add/edit these scripts through the web - which would be a very unusual configuration to begin with - are at risk.
### Patches
The problem has been fixed in `AccessControl` versions 4.3 and 5.2. Zope releases 4.6.3 and 5.3 now require these new `AccessControl` releases.
### Workarounds
A site administrator can restrict adding/editing Script (Python) objects through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing these scripts through the web should be restricted to trusted users only. This is the default configuration in Zope.
### References
* [AccessControl security advisory GHSA-qcx9-j53g-ccgf](https://github.com/zopefoundation/AccessControl/security/advisories/GHSA-qcx9-j53g-ccgf)
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [Zope issue tracker](https://github.com/zopefoundation/Zope/issues)
* Email us at [security@plone.org](mailto:security@plone.org)
| {'CVE-2021-32811'} | 2022-03-03T05:12:44.272513Z | 2021-08-05T17:00:37Z | HIGH | null | {'CWE-915'} | {'https://github.com/zopefoundation/Zope/commit/f72a18dda8e9bf2aedb46168761668464a4be988', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32811', 'https://github.com/zopefoundation/Zope', 'https://github.com/zopefoundation/Zope/security/advisories/GHSA-g4gq-j4p2-j8fr', 'https://github.com/zopefoundation/AccessControl/security/advisories/GHSA-qcx9-j53g-ccgf'} | null |
PyPI | GHSA-94jq-q5v2-76wj | Improper certificate management in AWS IoT Device SDK v2 | Connections initialized by the AWS IoT Device SDK v2 for Java (versions prior to 1.3.3), Python (versions prior to 1.5.18), C++ (versions prior to 1.12.7) and Node.js (versions prior to 1.5.1) did not verify server certificate hostname during TLS handshake when overriding Certificate Authorities (CA) in their trust stores on Windows. This issue has been addressed in aws-c-io submodule versions 0.9.13 onward. This issue affects: Amazon Web Services AWS IoT Device SDK v2 for Java versions prior to 1.3.3 on Microsoft Windows. Amazon Web Services AWS IoT Device SDK v2 for Python versions prior to 1.5.18 on Microsoft Windows. Amazon Web Services AWS IoT Device SDK v2 for C++ versions prior to 1.12.7 on Microsoft Windows. Amazon Web Services AWS IoT Device SDK v2 for Node.js versions prior to 1.5.3 on Microsoft Windows. | {'CVE-2021-40828'} | 2022-03-03T05:13:50.572827Z | 2021-11-24T21:02:24Z | MODERATE | null | {'CWE-295'} | {'https://github.com/aws/aws-iot-device-sdk-java-v2', 'https://github.com/aws/aws-iot-device-sdk-java-v2/commit/67950ad2a02f2f9355c310b69dc9226b017f32f2', 'https://github.com/aws/aws-iot-device-sdk-python-v2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-40828', 'https://github.com/aws/aws-iot-device-sdk-js-v2', 'https://github.com/aws/aws-iot-device-sdk-cpp-v2', 'https://github.com/awslabs/aws-c-io/', 'https://github.com/aws/aws-iot-device-sdk-python-v2/commit/fd4c0ba04b35eab9e20c635af5548fcc5a92d8be', 'https://github.com/aws/aws-iot-device-sdk-js-v2/commit/4be41394f1aee979e6f4b012fcb01eecabd0c08d'} | null |
PyPI | PYSEC-2021-415 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `FusedBatchNorm` kernels is vulnerable to a heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41223', 'GHSA-f54p-f6jp-4rhr'} | 2021-11-13T06:52:45.621437Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/aab9998916c2ffbd8f0592059fad352622f89cda', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f54p-f6jp-4rhr'} | null |
PyPI | GHSA-r3vr-prwv-86g9 | High severity vulnerability that affects python-gnupg | The shell_quote function in python-gnupg 0.3.5 does not properly quote strings, which allows context-dependent attackers to execute arbitrary code via shell metacharacters in unspecified vectors, as demonstrated using "$(" command-substitution sequences, a different vulnerability than CVE-2014-1928. NOTE: this vulnerability exists because of an incomplete fix for CVE-2013-7323. | {'CVE-2014-1927'} | 2021-09-17T14:15:08Z | 2018-11-06T23:14:39Z | HIGH | null | {'CWE-20'} | {'https://github.com/advisories/GHSA-r3vr-prwv-86g9', 'https://bitbucket.org/vinay.sajip/python-gnupg', 'http://secunia.com/advisories/56616', 'https://code.google.com/p/python-gnupg/issues/detail?id=98', 'https://nvd.nist.gov/vuln/detail/CVE-2014-1927', 'http://seclists.org/oss-sec/2014/q1/294', 'http://secunia.com/advisories/59031', 'http://www.debian.org/security/2014/dsa-2946', 'http://seclists.org/oss-sec/2014/q1/245', 'https://code.google.com/p/python-gnupg/'} | null |
PyPI | PYSEC-2022-109 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-vjg4-v33c-ggc4', 'CVE-2022-21730'} | 2022-03-09T00:18:23.671699Z | 2022-02-03T11:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360'} | null |
PyPI | GHSA-j8c8-67vp-6mx7 | Arbitrary memory read in `ImmutableConst` | ### Impact
The `ImmutableConst` operation in TensorFlow can be tricked into reading arbitrary memory contents:
```python
import tensorflow as tf
with open('/tmp/test','wb') as f:
f.write(b'\xe2'*128)
data = tf.raw_ops.ImmutableConst(dtype=tf.string,shape=3,memory_region_name='/tmp/test')
print(data)
```
This is because the `tstring` TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype.
### Patches
We have patched the issue in GitHub commit [3712a2d3455e6ccb924daa5724a3652a86f6b585](https://github.com/tensorflow/tensorflow/commit/3712a2d3455e6ccb924daa5724a3652a86f6b585) and GitHub commit [1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b](https://github.com/tensorflow/tensorflow/commit/1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41227'} | 2022-03-03T05:12:51.029397Z | 2021-11-10T18:34:49Z | MODERATE | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8c8-67vp-6mx7', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41227', 'https://github.com/tensorflow/tensorflow/commit/1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/3712a2d3455e6ccb924daa5724a3652a86f6b585'} | null |
PyPI | PYSEC-2022-26 | null | treq is an HTTP library inspired by requests but written on top of Twisted's Agents. Treq's request methods (`treq.get`, `treq.post`, etc.) and `treq.client.HTTPClient` constructor accept cookies as a dictionary. Such cookies are not bound to a single domain, and are therefore sent to *every* domain ("supercookies"). This can potentially cause sensitive information to leak upon an HTTP redirect to a different domain., e.g. should `https://example.com` redirect to `http://cloudstorageprovider.com` the latter will receive the cookie `session`. Treq 2021.1.0 and later bind cookies given to request methods (`treq.request`, `treq.get`, `HTTPClient.request`, `HTTPClient.get`, etc.) to the origin of the *url* parameter. Users are advised to upgrade. For users unable to upgrade Instead of passing a dictionary as the *cookies* argument, pass a `http.cookiejar.CookieJar` instance with properly domain- and scheme-scoped cookies in it. | {'CVE-2022-23607', 'GHSA-fhpf-pp6p-55qc'} | 2022-02-08T17:32:07.420457Z | 2022-02-01T11:15:00Z | null | null | null | {'https://github.com/twisted/treq/security/advisories/GHSA-fhpf-pp6p-55qc'} | null |
PyPI | GHSA-6gmv-pjp9-p8w8 | Out of bounds read in Tensorflow | ### Impact
The [implementation of shape inference for `ReverseSequence`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671) does not fully validate the value of `batch_dim` and can result in a heap OOB read:
```python
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.ReverseSequence(
input = ['aaa','bbb'],
seq_lengths = [1,1,1],
seq_dim = -10,
batch_dim = -10 )
return y
test()
```
There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values:
```cc
const int32_t input_rank = c->Rank(input);
if (batch_dim >= input_rank) {
return errors::InvalidArgument(
"batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);
}
// ...
DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);
```
Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then [the implementation of `Dim`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428) would access elements before the start of an array:
```cc
DimensionHandle Dim(ShapeHandle s, int64_t idx) {
if (!s.Handle() || s->rank_ == kUnknownRank) {
return UnknownDim();
}
return DimKnownRank(s, idx);
}
·
static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {
CHECK_NE(s->rank_, kUnknownRank);
if (idx < 0) {
return s->dims_[s->dims_.size() + idx];
}
return s->dims_[idx];
}
```
### Patches
We have patched the issue in GitHub commit [37c01fb5e25c3d80213060460196406c43d31995](https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team. | {'CVE-2022-21728'} | 2022-03-03T05:14:02.194954Z | 2022-02-09T18:29:24Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428', 'https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21728', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2016-3 | null | The cookie parsing code in Django before 1.8.15 and 1.9.x before 1.9.10, when used on a site with Google Analytics, allows remote attackers to bypass an intended CSRF protection mechanism by setting arbitrary cookies. | {'CVE-2016-7401'} | 2021-07-05T00:01:20.518242Z | 2016-10-03T18:59:00Z | null | null | null | {'http://rhn.redhat.com/errata/RHSA-2016-2041.html', 'http://rhn.redhat.com/errata/RHSA-2016-2043.html', 'http://www.securityfocus.com/bid/93182', 'http://rhn.redhat.com/errata/RHSA-2016-2042.html', 'http://rhn.redhat.com/errata/RHSA-2016-2039.html', 'http://www.debian.org/security/2016/dsa-3678', 'http://rhn.redhat.com/errata/RHSA-2016-2038.html', 'https://www.djangoproject.com/weblog/2016/sep/26/security-releases/', 'http://www.ubuntu.com/usn/USN-3089-1', 'http://rhn.redhat.com/errata/RHSA-2016-2040.html', 'http://www.securitytracker.com/id/1036899'} | null |
PyPI | PYSEC-2019-146 | null | ansible before versions 2.8.6, 2.7.14, 2.6.20 is vulnerable to a None | {'CVE-2019-14856'} | 2021-07-02T02:41:34.512855Z | 2019-11-26T14:15:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00021.html', 'https://access.redhat.com/errata/RHSA-2020:0756', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-14856', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00026.html'} | null |
PyPI | PYSEC-2018-72 | null | Accessing private content via str.format in through-the-web templates and scripts in Plone 2.5-5.1rc1. This improves an earlier hotfix. Since the format method was introduced in Python 2.6, this part of the hotfix is only relevant for Plone 4 and 5. | {'CVE-2017-1000483'} | 2021-08-25T04:30:16.983029Z | 2018-01-03T18:29:00Z | null | null | null | {'https://plone.org/security/hotfix/20171128/sandbox-escape'} | null |
PyPI | PYSEC-2021-803 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version. | {'CVE-2021-37692', 'GHSA-cmgw-8vpc-rc59'} | 2021-12-09T06:35:40.404135Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cmgw-8vpc-rc59', 'https://github.com/tensorflow/tensorflow/pull/50508'} | null |
PyPI | PYSEC-2010-12 | null | Cross-site scripting (XSS) vulnerability in Django 1.2.x before 1.2.2 allows remote attackers to inject arbitrary web script or HTML via a csrfmiddlewaretoken (aka csrf_token) cookie. | {'GHSA-fxpg-gg9g-76gj', 'CVE-2010-3082'} | 2021-07-15T02:22:08.006222Z | 2010-09-14T19:00:00Z | null | null | null | {'http://www.ubuntu.com/usn/USN-1004-1', 'http://www.djangoproject.com/weblog/2010/sep/08/security-release/', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/61729', 'https://bugzilla.redhat.com/show_bug.cgi?id=632239', 'https://github.com/advisories/GHSA-fxpg-gg9g-76gj', 'http://marc.info/?l=oss-security&m=128403961700444&w=2', 'http://www.securityfocus.com/bid/43116'} | null |
PyPI | PYSEC-2020-100 | null | It was found that python-rsa is vulnerable to Bleichenbacher timing attacks. An attacker can use this flaw via the RSA decryption API to decrypt parts of the cipher text encrypted with RSA. | {'CVE-2020-25658', 'GHSA-xrx6-fmxq-rjj2'} | 2021-11-11T23:07:45.968611Z | 2020-11-12T14:15:00Z | null | null | null | {'https://github.com/sybrenstuvel/python-rsa/issues/165', 'https://github.com/advisories/GHSA-xrx6-fmxq-rjj2', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-25658'} | null |
PyPI | GHSA-7fvx-3jfc-2cpc | Heap OOB in `ResourceScatterUpdate` | ### Impact
An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`:
```python
import tensorflow as tf
v = tf.Variable([b'vvv'])
tf.raw_ops.ResourceScatterUpdate(
resource=v.handle,
indices=[0],
updates=['1', '2', '3', '4', '5'])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship.
### Patches
We have patched the issue in GitHub commit [01cff3f986259d661103412a20745928c727326f](https://github.com/tensorflow/tensorflow/commit/01cff3f986259d661103412a20745928c727326f).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-37655'} | 2022-03-03T05:14:03.632801Z | 2021-08-25T14:42:58Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7fvx-3jfc-2cpc', 'https://github.com/tensorflow/tensorflow/commit/01cff3f986259d661103412a20745928c727326f', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37655'} | null |
PyPI | PYSEC-2021-550 | null | TensorFlow is an end-to-end open source platform for machine learning. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37637', 'GHSA-c9qf-r67m-p7cg'} | 2021-12-09T06:35:02.145086Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5dc7f6981fdaf74c8c5be41f393df705841fb7c5', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9qf-r67m-p7cg'} | null |
PyPI | PYSEC-2014-51 | null | Zope before 2.13.19, as used in Plone before 4.2.3 and 4.3 before beta 1, does not reseed the pseudo-random number generator (PRNG), which makes it easier for remote attackers to guess the value via unspecified vectors. NOTE: this issue was SPLIT from CVE-2012-5508 due to different vulnerability types (ADT2). | {'GHSA-48vv-2pmq-9fvv', 'CVE-2012-6661'} | 2021-09-01T08:44:31.427296Z | 2014-11-03T22:55:00Z | null | null | null | {'https://bugs.launchpad.net/zope2/+bug/1071067', 'https://plone.org/products/plone/security/advisories/20121106/24', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://github.com/advisories/GHSA-48vv-2pmq-9fvv', 'https://plone.org/products/plone-hotfix/releases/20121124'} | null |
PyPI | PYSEC-2021-100 | null | FastAPI is a web framework for building APIs with Python 3.6+ based on standard Python type hints. FastAPI versions lower than 0.65.2 that used cookies for authentication in path operations that received JSON payloads sent by browsers were vulnerable to a Cross-Site Request Forgery (CSRF) attack. In versions lower than 0.65.2, FastAPI would try to read the request payload as JSON even if the content-type header sent was not set to application/json or a compatible JSON media type (e.g. application/geo+json). A request with a content type of text/plain containing JSON data would be accepted and the JSON data would be extracted. Requests with content type text/plain are exempt from CORS preflights, for being considered Simple requests. The browser will execute them right away including cookies, and the text content could be a JSON string that would be parsed and accepted by the FastAPI application. This is fixed in FastAPI 0.65.2. The request data is now parsed as JSON only if the content-type header is application/json or another JSON compatible media type like application/geo+json. It's best to upgrade to the latest FastAPI, but if updating is not possible then a middleware or a dependency that checks the content-type header and aborts the request if it is not application/json or another JSON compatible content type can act as a mitigating workaround. | {'GHSA-8h2j-cgx8-6xv7', 'CVE-2021-32677'} | 2021-06-22T04:54:55.863034Z | 2021-06-09T18:15:00Z | null | null | null | {'https://github.com/tiangolo/fastapi/security/advisories/GHSA-8h2j-cgx8-6xv7', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MATAWX25TYKNEKLDMKWNLYDB34UWTROA/', 'https://github.com/tiangolo/fastapi/commit/fa7e3c996edf2d5482fff8f9d890ac2390dede4d'} | null |
PyPI | GHSA-xp7p-3gx7-j6wx | calibre-web is vulnerable to Business Logic Errors | calibre-web is vulnerable to Business Logic Errors | {'CVE-2021-4171'} | 2022-03-21T19:17:04.585200Z | 2022-01-21T23:44:15Z | CRITICAL | null | null | {'https://nvd.nist.gov/vuln/detail/CVE-2021-4171', 'https://github.com/janeczku/calibre-web/commit/3e0d8763c377d2146462811e3e4ccf13f0d312ce', 'https://github.com/janeczku/calibre-web', 'https://huntr.dev/bounties/1117f439-133c-4563-afb2-6cd80607bd5c'} | null |
PyPI | GHSA-836c-xg97-8p4h | Server-Side Request Forgery in libtaxii | "TAXII libtaxii through 1.1.117, as used in EclecticIQ OpenTAXII through 0.2.0 and other products, allows SSRF via an initial http:// substring to the parse method, even when the no_network setting is used for the XML parser. NOTE: the vendor points out that the parse method "wraps the lxml library" and that this may be an issue to "raise ... to the lxml group."" | {'CVE-2020-27197'} | 2022-03-22T19:01:51.538994Z | 2021-04-30T17:34:48Z | CRITICAL | null | {'CWE-918'} | {'http://packetstormsecurity.com/files/159662/Libtaxii-1.1.117-OpenTaxi-0.2.0-Server-Side-Request-Forgery.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-27197', 'https://github.com/TAXIIProject/libtaxii', 'https://github.com/TAXIIProject/libtaxii/issues/246', 'https://github.com/TAXIIProject/libtaxii/pull/247', 'https://github.com/eclecticiq/OpenTAXII/issues/176'} | null |
PyPI | PYSEC-2021-177 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-xgc3-m89p-vr3x', 'CVE-2021-29540'} | 2021-08-27T03:22:28.584780Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xgc3-m89p-vr3x', 'https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96'} | null |
PyPI | PYSEC-2014-26 | null | OpenStack keystonemiddleware (formerly python-keystoneclient) 0.x before 0.11.0 and 1.x before 1.2.0 disables certification verification when the "insecure" option is set in a paste configuration (paste.ini) file regardless of the value, which allows remote attackers to conduct man-in-the-middle attacks via a crafted certificate. | {'CVE-2014-7144'} | 2021-07-25T23:34:38.976180Z | 2014-10-02T14:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2014/09/25/51', 'http://rhn.redhat.com/errata/RHSA-2014-1783.html', 'http://www.securityfocus.com/bid/69864', 'http://secunia.com/advisories/62709', 'http://rhn.redhat.com/errata/RHSA-2014-1784.html', 'https://bugs.launchpad.net/python-keystoneclient/+bug/1353315', 'http://www.ubuntu.com/usn/USN-2705-1', 'http://rhn.redhat.com/errata/RHSA-2015-0020.html'} | null |
PyPI | PYSEC-2021-527 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `Split` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e2752089ef7ce9bcf3db0ec618ebd23ea119d0c7/tensorflow/lite/kernels/split.cc#L63-L65). An attacker can craft a model such that `num_splits` would be 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29599', 'GHSA-97wf-p777-86jq'} | 2021-12-09T06:34:58.781489Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-97wf-p777-86jq', 'https://github.com/tensorflow/tensorflow/commit/b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d'} | null |
PyPI | PYSEC-2020-177 | null | In SaltStack Salt through 2019.2.0, the salt-api NET API with the ssh client enabled is vulnerable to command injection. This allows an unauthenticated attacker with network access to the API endpoint to execute arbitrary code on the salt-api host. | {'CVE-2019-17361'} | 2020-08-24T17:37:00Z | 2020-01-17T02:15:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2020-03/msg00026.html', 'https://docs.saltstack.com/en/latest/topics/releases/2019.2.3.html#security-fix', 'https://github.com/saltstack/salt/commits/master', 'https://usn.ubuntu.com/4459-1/', 'https://www.debian.org/security/2020/dsa-4676'} | null |
PyPI | GHSA-hmv2-79q8-fv6g | Uncontrolled Resource Consumption in urllib3 | The _encode_invalid_chars function in util/url.py in the urllib3 library 1.25.2 through 1.25.7 for Python allows a denial of service (CPU consumption) because of an inefficient algorithm. The percent_encodings array contains all matches of percent encodings. It is not deduplicated. For a URL of length N, the size of percent_encodings may be up to O(N). The next step (normalize existing percent-encoded bytes) also takes up to O(N) for each step, so the total time is O(N^2). If percent_encodings were deduplicated, the time to compute _encode_invalid_chars would be O(kN), where k is at most 484 ((10+6*2)^2). | {'CVE-2020-7212'} | 2022-03-03T05:14:01.349412Z | 2021-04-30T17:31:43Z | HIGH | null | {'CWE-400'} | {'https://pypi.org/project/urllib3/1.25.8/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-7212', 'https://github.com/urllib3/urllib3/blob/master/CHANGES.rst', 'https://github.com/urllib3/urllib3/commit/a74c9cfbaed9f811e7563cfc3dce894928e0221a'} | null |
PyPI | PYSEC-2020-83 | null | libImaging/PcxDecode.c in Pillow before 6.2.2 has a PCX P mode buffer overflow. | {'GHSA-p49h-hjvm-jg3h', 'CVE-2020-5312'} | 2020-07-10T17:09:00Z | 2020-01-03T01:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2MMU3WT2X64GS5WHDPKKC2WZA7UIIQ3A/', 'https://access.redhat.com/errata/RHSA-2020:0681', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://access.redhat.com/errata/RHSA-2020:0683', 'https://github.com/advisories/GHSA-p49h-hjvm-jg3h', 'https://github.com/python-pillow/Pillow/commit/93b22b846e0269ee9594ff71a72bec02d2bea8fd', 'https://access.redhat.com/errata/RHSA-2020:0578', 'https://access.redhat.com/errata/RHSA-2020:0580', 'https://access.redhat.com/errata/RHSA-2020:0694', 'https://access.redhat.com/errata/RHSA-2020:0566', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631'} | null |
PyPI | PYSEC-2019-131 | null | typed_ast 1.3.0 and 1.3.1 has an ast_for_arguments out-of-bounds read. An attacker with the ability to cause a Python interpreter to parse Python source (but not necessarily execute it) may be able to crash the interpreter process. This could be a concern, for example, in a web-based service that parses (but does not execute) Python code. (This issue also affected certain Python 3.8.0-alpha prereleases.) | {'GHSA-7xxv-wpxj-mx5v', 'CVE-2019-19275'} | 2020-03-14T02:15:00Z | 2019-11-26T15:15:00Z | null | null | null | {'https://github.com/python/typed_ast/commit/156afcb26c198e162504a57caddfe0acd9ed7dce', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LG5H4Q6LFVRX7SFXLBEJMNQFI4T5SCEA/', 'https://bugs.python.org/issue36495', 'https://github.com/python/typed_ast/commit/dc317ac9cff859aa84eeabe03fb5004982545b3b', 'https://github.com/advisories/GHSA-7xxv-wpxj-mx5v', 'https://github.com/python/cpython/commit/dcfcd146f8e6fc5c2fc16a4c192a0c5f5ca8c53c', 'https://github.com/python/cpython/commit/a4d78362397fc3bced6ea80fbc7b5f4827aec55e'} | null |
PyPI | PYSEC-2022-51 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-21727', 'GHSA-c6fh-56w7-fvjw'} | 2022-03-09T00:17:30.181517Z | 2022-02-03T11:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c6fh-56w7-fvjw', 'https://github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034'} | null |
PyPI | GHSA-8gv3-57p6-g35r | Heap buffer overflow in `RaggedTensorToTensor` | ### Impact
An attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`:
```python
import tensorflow as tf
shape = tf.constant([10, 10], shape=[2], dtype=tf.int64)
values = tf.constant(0, shape=[1], dtype=tf.int64)
default_value = tf.constant(0, dtype=tf.int64)
l = [849, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
row = tf.constant(l, shape=[5, 43], dtype=tf.int64)
rows = [row]
types = ['ROW_SPLITS']
tf.raw_ops.RaggedTensorToTensor(
shape=shape, values=values, default_value=default_value,
row_partition_tensors=rows, row_partition_types=types)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel:
```cc
for (INDEX_TYPE i = 0; i < row_split_size - 1; ++i) {
INDEX_TYPE row_length = row_split(i + 1) - row_split(i);
INDEX_TYPE real_length = std::min(output_size, row_length);
INDEX_TYPE parent_output_index_current = parent_output_index[i];
...
}
```
Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`.
### Patches
We have patched the issue in GitHub commit [a84358aa12f0b1518e606095ab9cfddbf597c121](https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29560'} | 2022-04-26T18:17:10.547761Z | 2021-05-21T14:24:57Z | LOW | null | {'CWE-787', 'CWE-125'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29560', 'https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8gv3-57p6-g35r'} | null |
PyPI | PYSEC-2020-198 | null | Ansible prior to 1.5.4 mishandles the evaluation of some strings. | {'CVE-2014-2686'} | 2021-07-02T02:41:33.018970Z | 2020-01-09T13:15:00Z | null | null | null | {'https://groups.google.com/forum/#!searchin/ansible-project/1.5.4/ansible-project/MUQxiKwSQDc/id6aVaawVboJ'} | null |
PyPI | GHSA-j2x6-9323-fp7h | Integer bounds error in Vyper | ### Impact
in the following code, the return of `<iface>.returns_int128()` is not validated to fall within the bounds of `int128`. as of v0.3.0, `<iface>.returns_int128()` is validated in simple expressions, but not complex expressions.
```vyper
interface iface:
def returns_int128() -> int128: view
def returns_Bytes33() -> Bytes[33]: view
x: iface
@external
def call_out():
x: int128 = self.x.returns_int128() # affected, <0.3.0
y: uint256 = convert(self.x.returns_int128(), uint256) # affected, <0.3.2
z: Bytes[33] = concat(self.x.returns_Bytes33(), b"") # affected >= 0.3.0, <0.3.2
```
### Patches
0.3.2 (as of https://github.com/vyperlang/vyper/commit/049dbdc647b2ce838fae7c188e6bb09cf16e470b)
### Workarounds
Break up operations involving external calls into multiple statements. For instance, instead of the example above, use
```
x: int128 = self.x.returns_int128()
y: uint256 = convert(x, uint256)
``` | {'CVE-2022-24845'} | 2022-04-22T20:30:22.083907Z | 2022-04-22T20:24:13Z | HIGH | null | {'CWE-190'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-24845', 'https://github.com/vyperlang/vyper/security/advisories/GHSA-j2x6-9323-fp7h', 'https://github.com/vyperlang/vyper/commit/049dbdc647b2ce838fae7c188e6bb09cf16e470b', 'https://github.com/vyperlang/vyper'} | null |
PyPI | PYSEC-2021-462 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29534', 'GHSA-6j9c-grc6-5m6g'} | 2021-12-09T06:34:48.648836Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6j9c-grc6-5m6g'} | null |
PyPI | PYSEC-2021-198 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29561', 'GHSA-gvm4-h8j3-rjrq'} | 2021-08-27T03:22:32.310582Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq', 'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} | null |
PyPI | GHSA-7g47-xxff-9p85 | Remote unauthenticated attackers able to upload files in Onionshare | OnionShare 2.3 before 2.4 allows remote unauthenticated attackers to upload files on a non-public node when using the --receive functionality. | {'CVE-2021-41868'} | 2022-03-03T05:12:44.104897Z | 2021-11-19T20:39:44Z | CRITICAL | null | null | {'https://github.com/onionshare/onionshare/compare/v2.3.3...v2.4', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41868', 'https://www.ihteam.net/advisory/onionshare/', 'https://github.com/onionshare/onionshare'} | null |
PyPI | GHSA-hj2j-77xm-mc5v | High severity vulnerability that affects Jinja2 | In Pallets Jinja before 2.8.1, str.format allows a sandbox escape. | {'CVE-2016-10745'} | 2022-03-03T05:14:16.206594Z | 2019-04-10T14:30:13Z | HIGH | null | {'CWE-134'} | {'https://usn.ubuntu.com/4011-1/', 'https://access.redhat.com/errata/RHSA-2019:3964', 'https://access.redhat.com/errata/RHSA-2019:1022', 'https://usn.ubuntu.com/4011-2/', 'https://github.com/advisories/GHSA-hj2j-77xm-mc5v', 'https://github.com/pallets/jinja', 'https://access.redhat.com/errata/RHSA-2019:1260', 'https://github.com/pallets/jinja/commit/9b53045c34e61013dc8f09b7e52a555fa16bed16', 'https://access.redhat.com/errata/RHSA-2019:1237', 'https://palletsprojects.com/blog/jinja-281-released/', 'http://lists.opensuse.org/opensuse-security-announce/2019-05/msg00030.html', 'https://access.redhat.com/errata/RHSA-2019:4062', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00064.html', 'https://nvd.nist.gov/vuln/detail/CVE-2016-10745'} | null |
PyPI | PYSEC-2019-218 | null | libnmap < v0.6.3 is affected by: XML Injection. The impact is: Denial of service (DoS) by consuming resources. The component is: XML Parsing. The attack vector is: Specially crafted XML payload. | {'CVE-2019-1010017', 'GHSA-9ccv-p7fg-m73x'} | 2021-11-16T03:58:45.118185Z | 2019-07-15T03:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-9ccv-p7fg-m73x', 'https://github.com/savon-noir/python-libnmap/issues/87'} | null |
PyPI | GHSA-hf6p-4rv2-9qrp | Path Traversal in bikshed | This affects the package bikeshed before 3.0.0. This can occur when an untrusted source file containing include, include-code or include-raw block is processed. The contents of arbitrary files could be disclosed in the HTML output. | {'CVE-2021-23423'} | 2022-03-03T05:13:55.271297Z | 2021-08-30T16:25:42Z | MODERATE | null | {'CWE-22'} | {'https://snyk.io/vuln/SNYK-PYTHON-BIKESHED-1537647', 'https://github.com/tabatkins/bikeshed/commit/b2f668fca204260b1cad28d5078e93471cb6b2dd', 'https://github.com/tabatkins/bikeshed', 'https://nvd.nist.gov/vuln/detail/CVE-2021-23423'} | null |
PyPI | PYSEC-2017-36 | null | Directory traversal vulnerability in minion id validation in SaltStack Salt before 2016.3.8, 2016.11.x before 2016.11.8, and 2017.7.x before 2017.7.2 allows remote minions with incorrect credentials to authenticate to a master via a crafted minion ID. NOTE: this vulnerability exists because of an incomplete fix for CVE-2017-12791. | {'CVE-2017-14695'} | 2021-07-05T00:01:26.552235Z | 2017-10-24T17:29:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-updates/2017-10/msg00073.html', 'https://github.com/saltstack/salt/commit/80d90307b07b3703428ecbb7c8bb468e28a9ae6d', 'https://bugzilla.redhat.com/show_bug.cgi?id=1500748', 'https://docs.saltstack.com/en/latest/topics/releases/2016.3.8.html', 'https://docs.saltstack.com/en/latest/topics/releases/2017.7.2.html', 'http://lists.opensuse.org/opensuse-updates/2017-10/msg00075.html', 'https://docs.saltstack.com/en/latest/topics/releases/2016.11.8.html'} | null |
PyPI | GHSA-h6hq-c896-w882 | Low severity vulnerability that affects Plone | Cross-site scripting (XSS) vulnerability in the safe_html filter in Products.PortalTransforms in Plone 2.1 through 4.1 allows remote authenticated users to inject arbitrary web script or HTML via unspecified vectors, a different vulnerability than CVE-2010-2422. | {'CVE-2011-1949'} | 2022-03-03T05:13:02.870589Z | 2018-07-23T21:01:10Z | LOW | null | {'CWE-79'} | {'http://osvdb.org/72728', 'https://nvd.nist.gov/vuln/detail/CVE-2011-1949', 'https://github.com/plone/Plone', 'http://secunia.com/advisories/44775', 'http://www.securityfocus.com/archive/1/518155/100/0/threaded', 'http://securityreason.com/securityalert/8269', 'http://www.securityfocus.com/bid/48005', 'https://github.com/advisories/GHSA-h6hq-c896-w882', 'http://secunia.com/advisories/44776', 'http://plone.org/products/plone/security/advisories/CVE-2011-1949', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/67694'} | null |
PyPI | PYSEC-2019-28 | null | A flaw was found in IPA, all 4.6.x versions before 4.6.7, all 4.7.x versions before 4.7.4 and all 4.8.x versions before 4.8.3, in the way the internal function ber_scanf() was used in some components of the IPA server, which parsed kerberos key data. An unauthenticated attacker who could trigger parsing of the krb principal key could cause the IPA server to crash or in some conditions, cause arbitrary code to be executed on the server hosting the IPA server. | {'GHSA-7hpj-hfcr-5qwm', 'CVE-2019-14867'} | 2020-02-05T00:15:00Z | 2019-11-27T09:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WLFL5XDCJ3WT6JCLCQVKHZBLHGW7PW4T/', 'https://github.com/advisories/GHSA-7hpj-hfcr-5qwm', 'https://www.freeipa.org/page/Releases/4.8.3', 'https://access.redhat.com/errata/RHBA-2019:4268', 'https://www.freeipa.org/page/Releases/4.6.7', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-14867', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/67SEUWJAJ5RMH5K4Q6TS2I7HIMXUGNKF/', 'https://www.freeipa.org/page/Releases/4.7.4', 'https://access.redhat.com/errata/RHSA-2020:0378'} | null |
PyPI | PYSEC-2021-41 | null | Pillow before 8.1.1 allows attackers to cause a denial of service (memory consumption) because the reported size of a contained image is not properly checked for an ICNS container, and thus an attempted memory allocation can be very large. | {'GHSA-3wvg-mj6g-m9cv', 'CVE-2021-27922'} | 2021-03-23T19:49:00Z | 2021-03-03T09:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZTSY25UJU7NJUFHH3HWT575LT4TDFWBZ/', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/S7G44Z33J4BNI2DPDROHWGVG2U7ZH5JU/', 'https://github.com/advisories/GHSA-3wvg-mj6g-m9cv', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TQQY6472RX4J2SUJENWDZAWKTJJGP2ML/'} | null |
PyPI | GHSA-923p-fr2c-g5m2 | Exposure of Sensitive Information to an Unauthorized Actor in Ansible | A flaw was found in Ansible 2.7.16 and prior, 2.8.8 and prior, and 2.9.5 and prior when a password is set with the argument "password" of svn module, it is used on svn command line, disclosing to other users within the same node. An attacker could take advantage by reading the cmdline file from that particular PID on the procfs. | {'CVE-2020-1739'} | 2022-04-04T21:32:00.652152Z | 2021-04-07T20:30:44Z | LOW | null | {'CWE-200'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/U3IMV3XEIUXL6S4KPLYYM4TVJQ2VNEP2/', 'https://lists.debian.org/debian-lts-announce/2020/05/msg00005.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1739', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FWDK3QUVBULS3Q3PQTGEKUQYPSNOU5M3/', 'https://github.com/ansible/ansible', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1739', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QT27K5ZRGDPCH7GT3DRI3LO4IVDVQUB7/', 'https://github.com/ansible/ansible/issues/67797', 'https://www.debian.org/security/2021/dsa-4950'} | null |
PyPI | GHSA-cvgx-3v3q-m36c | Heap OOB in shape inference for `QuantizeV2` | ### Impact
The [shape inference code for `QuantizeV2`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/framework/common_shape_fns.cc#L2509-L2530) can trigger a read outside of bounds of heap allocated array:
```python
import tensorflow as tf
@tf.function
def test():
data=tf.raw_ops.QuantizeV2(
input=[1.0,1.0],
min_range=[1.0,10.0],
max_range=[1.0,10.0],
T=tf.qint32,
mode='MIN_COMBINED',
round_mode='HALF_TO_EVEN',
narrow_range=False,
axis=-100,
ensure_minimum_range=10)
return data
test()
```
This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer:
```cc
int axis = -1;
Status s = c->GetAttr("axis", &axis);
if (!s.ok() && s.code() != error::NOT_FOUND) {
return s;
}
...
if (axis != -1) {
...
TF_RETURN_IF_ERROR(
c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth));
}
```
The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read.
### Patches
We have patched the issue in GitHub commit [a0d64445116c43cf46a5666bd4eee28e7a82f244](https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41211'} | 2021-11-08T22:32:45Z | 2021-11-10T19:01:03Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41211', 'https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244'} | null |
PyPI | PYSEC-2018-52 | null | A flaw was found in python-cryptography versions between >=1.9.0 and <2.3. The finalize_with_tag API did not enforce a minimum tag length. If a user did not validate the input length prior to passing it to finalize_with_tag an attacker could craft an invalid payload with a shortened tag (e.g. 1 byte) such that they would have a 1 in 256 chance of passing the MAC check. GCM tag forgeries can cause key leakage. | {'CVE-2018-10903', 'GHSA-fcf9-3qw3-gxmj'} | 2021-07-15T02:22:07.445715Z | 2018-07-30T16:29:00Z | null | null | null | {'https://usn.ubuntu.com/3720-1/', 'https://github.com/advisories/GHSA-fcf9-3qw3-gxmj', 'https://github.com/pyca/cryptography/pull/4342/commits/688e0f673bfbf43fa898994326c6877f00ab19ef', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10903', 'https://access.redhat.com/errata/RHSA-2018:3600'} | null |
PyPI | PYSEC-2019-189 | null | An issue was discovered in OpenStack Neutron 11.x before 11.0.7, 12.x before 12.0.6, and 13.x before 13.0.3. By creating two security groups with separate/overlapping port ranges, an authenticated user may prevent Neutron from being able to configure networks on any compute nodes where those security groups are present, because of an Open vSwitch (OVS) firewall KeyError. All Neutron deployments utilizing neutron-openvswitch-agent are affected. | {'CVE-2019-10876'} | 2021-08-27T03:22:08.705789Z | 2019-04-05T05:29:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2019/04/09/2', 'https://review.openstack.org/#/q/topic:bug/1813007', 'https://bugs.launchpad.net/ossa/+bug/1813007', 'https://security.openstack.org/ossa/OSSA-2019-002.html', 'https://access.redhat.com/errata/RHSA-2019:0879', 'https://access.redhat.com/errata/RHSA-2019:0935'} | null |
PyPI | GHSA-cq27-v7xp-c356 | Moderate severity vulnerability that affects pycrypto | Heap-based buffer overflow in the ALGnew function in block_templace.c in Python Cryptography Toolkit (aka pycrypto) allows remote attackers to execute arbitrary code as demonstrated by a crafted iv parameter to cryptmsg.py. | {'CVE-2013-7459'} | 2022-03-03T05:12:41.100141Z | 2018-12-14T18:51:38Z | CRITICAL | null | {'CWE-119'} | {'https://github.com/dlitz/pycrypto/issues/176', 'https://github.com/dlitz/pycrypto/commit/8dbe0dc3eea5c689d4f76b37b93fe216cf1f00d4', 'https://nvd.nist.gov/vuln/detail/CVE-2013-7459', 'http://www.securityfocus.com/bid/95122', 'https://github.com/dlitz/pycrypto', 'https://bugzilla.redhat.com/show_bug.cgi?id=1409754', 'https://pony7.fr/ctf:public:32c3:cryptmsg', 'https://security.gentoo.org/glsa/201702-14', 'https://github.com/advisories/GHSA-cq27-v7xp-c356', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/C6BWNADPLKDBBQBUT3P75W7HAJCE7M3B/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/RJ37R2YLX56YZABFNAOWV4VTHTGYREAE/', 'http://www.openwall.com/lists/oss-security/2016/12/27/8'} | null |
PyPI | PYSEC-2021-823 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41216', 'GHSA-3ff2-r28g-w7h9'} | 2021-12-09T06:35:43.595346Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3ff2-r28g-w7h9', 'https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14'} | null |
PyPI | PYSEC-2020-120 | null | 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 matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15197', 'GHSA-qc53-44cj-vfvx'} | 2021-09-01T08:19:33.096342Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx'} | null |
PyPI | PYSEC-2021-570 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37657', 'GHSA-5xwc-mrhx-5g3m'} | 2021-12-09T06:35:03.842863Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m', 'https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09'} | null |
PyPI | PYSEC-2014-71 | null | OpenStack keystonemiddleware (formerly python-keystoneclient) 0.x before 0.11.0 and 1.x before 1.2.0 disables certification verification when the "insecure" option is set in a paste configuration (paste.ini) file regardless of the value, which allows remote attackers to conduct man-in-the-middle attacks via a crafted certificate. | {'CVE-2014-7144'} | 2021-07-25T23:34:52.128374Z | 2014-10-02T14:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2014/09/25/51', 'http://rhn.redhat.com/errata/RHSA-2014-1783.html', 'http://www.securityfocus.com/bid/69864', 'http://secunia.com/advisories/62709', 'http://rhn.redhat.com/errata/RHSA-2014-1784.html', 'https://bugs.launchpad.net/python-keystoneclient/+bug/1353315', 'http://www.ubuntu.com/usn/USN-2705-1', 'http://rhn.redhat.com/errata/RHSA-2015-0020.html'} | null |
PyPI | PYSEC-2021-120 | null | Webrecorder pywb before 2.6.0 allows XSS because it does not ensure that Jinja2 templates are autoescaped. | {'GHSA-947x-pv47-pp3q', 'CVE-2021-39286'} | 2021-08-18T20:29:26.806388Z | 2021-08-18T18:15:00Z | null | null | null | {'https://github.com/webrecorder/pywb/compare/v-2.5.0...v-2.6.0', 'https://github.com/advisories/GHSA-947x-pv47-pp3q', 'https://github.com/webrecorder/pywb/commit/f7bd84cdacdd665ff73ae8d09a202f60be2ebae9'} | null |
PyPI | GHSA-c6jq-h4jp-72pr | NULL Pointer Dereference in aubio | aubio v0.4.0 to v0.4.8 has a new_aubio_onset NULL pointer dereference. | {'CVE-2018-19802'} | 2022-03-03T05:13:23.679223Z | 2019-07-26T16:10:25Z | HIGH | null | {'CWE-476'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-19802', 'https://github.com/aubio/aubio/blob/0.4.9/ChangeLog'} | null |
PyPI | PYSEC-2021-435 | null | Improper output neutralization for Logs. A specific Apache Superset HTTP endpoint allowed for an authenticated user to forge log entries or inject malicious content into logs. | {'CVE-2021-42250'} | 2021-11-29T23:10:59.097625Z | 2021-11-17T15:15:00Z | null | null | null | {'https://lists.apache.org/thread/53lkszw6d3tybp5t99nvgcj538b9trw9', 'http://www.openwall.com/lists/oss-security/2021/11/17/2'} | null |
PyPI | GHSA-8wr4-2wm6-w3pr | B2 Command Line Tool TOCTOU application key disclosure | ### Impact
Linux and Mac releases of the B2 command-line tool version 3.2.0 and below contain a key disclosure vulnerability that, in certain conditions, can be exploited by local attackers through a time-of-check-time-of-use (TOCTOU) race condition.
The command line tool saves API keys (and bucket name-to-id mapping) in a local database file (`$XDG_CONFIG_HOME/b2/account_info`, `~/.b2_account_info` or a user-defined path) when `b2 authorize-account` is first run. This happens regardless of whether a valid key is provided or not. When first created, the file is world readable and is (typically a few milliseconds) later altered to be private to the user. If the directory is readable by a local attacker and the user did not yet run `b2 authorize-account` then during the brief period between file creation and permission modification, a local attacker can race to open the file and maintain a handle to it. This allows the local attacker to read the contents after the file after the sensitive information has been saved to it.
### Remediation
Users that have not yet run `b2 authorize-account` should upgrade to B2 Command-Line Tool v3.2.1 before running it.
Users that have run `b2 authorize-account` are safe if at the time of the file creation no other local users had read access to the local configuration file.
Users that have run `b2 authorize-account` where the designated path could be opened by another local user should upgrade to B2 Command-Line Tool v3.2.1 and remove the database and regenerate all application keys. Note that `b2 clear-account` does not remove the database file and it should not be used to ensure that all open handles to the file are invalidated.
### Workarounds
If B2 Command-Line Tool cannot be upgraded to v3.2.1 due to a dependency conflict, a binary release can be used instead. Alternatively a new version could be installed within a virtualenv, or the permissions can be changed to prevent local users from opening the database file.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [B2 Command-Line Tool](https://github.com/Backblaze/B2_Command_Line_Tool) mentioning the CVE id in the issue title
* Email us at [security@backblaze.com](mailto:security@backblaze.com)
| {'CVE-2022-23653'} | 2022-03-08T18:31:48.597637Z | 2022-02-24T13:11:51Z | MODERATE | null | {'CWE-367'} | {'https://github.com/Backblaze/B2_Command_Line_Tool/', 'https://github.com/Backblaze/B2_Command_Line_Tool/commit/c74029f9f75065e8f7e3c3ec8e0a23fb8204feeb', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23653', 'https://github.com/Backblaze/B2_Command_Line_Tool/security/advisories/GHSA-8wr4-2wm6-w3pr'} | null |
PyPI | GHSA-m3rf-7m4w-r66q | Improper Authentication in Flask-AppBuilder | ### Impact
Improper authentication on the REST API. Allows for a malicious actor with a carefully crafted request to successfully authenticate and gain access to existing protected REST API endpoints. Only affects non database authentication types, and new REST API endpoints.
### Patches
Upgrade to Flask-AppBuilder 3.3.4
### For more information
If you have any questions or comments about this advisory:
* Open an issue in https://github.com/dpgaspar/Flask-AppBuilder
| {'CVE-2021-41265'} | 2022-03-03T05:13:53.493713Z | 2021-12-09T19:09:07Z | HIGH | null | {'CWE-287'} | {'https://github.com/dpgaspar/Flask-AppBuilder/commit/eba517aab121afa3f3f2edb011ec6bc4efd61fbc', 'https://github.com/dpgaspar/Flask-AppBuilder/releases/tag/v3.3.4', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41265', 'https://github.com/dpgaspar/Flask-AppBuilder/security/advisories/GHSA-m3rf-7m4w-r66q', 'https://github.com/dpgaspar/Flask-AppBuilder'} | null |
PyPI | GHSA-5946-mpw5-pqxx | Incorrect Default Permissions in Cobbler | An issue was discovered in Cobbler before 3.3.1. Files in /etc/cobbler are world readable. Two of those files contain some sensitive information that can be exposed to a local user who has non-privileged access to the server. The users.digest file contains the sha2-512 digest of users in a Cobbler local installation. In the case of an easy-to-guess password, it's trivial to obtain the plaintext string. The settings.yaml file contains secrets such as the hashed default password. | {'CVE-2021-45083'} | 2022-03-29T22:31:55.391600Z | 2022-02-21T00:00:20Z | HIGH | null | {'CWE-276'} | {'https://github.com/cobbler/cobbler', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.1', 'https://www.openwall.com/lists/oss-security/2022/02/18/3', 'https://github.com/cobbler/cobbler/releases', 'https://bugzilla.suse.com/show_bug.cgi?id=1193671', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/Z5CSXQE7Q4TVDQJKFYBO4XDH3BZ7BLAR/', 'https://github.com/cobbler/cobbler/pull/2945', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZCXMOUW4DH4DYWIJN44SMSU6R3CZDZBE/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-45083', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TEJN7CPW6YCHBFQPFZKGA6AVA6T5NPIW/'} | null |
PyPI | PYSEC-2022-129 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a `SavedModel` on disk such that `AttrDef`s of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23565', 'GHSA-4v5p-v5h9-6xjx'} | 2022-03-09T00:18:26.310749Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4v5p-v5h9-6xjx', 'https://github.com/tensorflow/tensorflow/commit/c2b31ff2d3151acb230edc3f5b1832d2c713a9e0'} | null |
PyPI | PYSEC-2019-166 | null | The Serialize.deserialize() method in CoAPthon3 1.0 and 1.0.1 mishandles certain exceptions, leading to a denial of service in applications that use this library (e.g., the standard CoAP server, CoAP client, example collect CoAP server and client) when they receive crafted CoAP messages. | {'GHSA-c6fm-rgw4-8q73', 'CVE-2018-12679'} | 2021-08-25T04:57:20.904496Z | 2019-04-02T19:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-c6fm-rgw4-8q73', 'https://github.com/Tanganelli/CoAPthon3/issues/16'} | null |
PyPI | GHSA-v7m9-9497-p9gr | Possible pod name collisions in jupyterhub-kubespawner | ### Impact
_What kind of vulnerability is it? Who is impacted?_
JupyterHub deployments using:
- KubeSpawner <= 0.11.1 (e.g. zero-to-jupyterhub 0.9.0) and
- enabled named_servers (not default), and
- an Authenticator that allows:
- usernames with hyphens or other characters that require escape (e.g. `user-hyphen` or `user@email`), and
- usernames which may match other usernames up to but not including the escaped character (e.g. `user` in the above cases)
In this circumstance, certain usernames will be able to craft particular server names which will grant them access to the default server of other users who have matching usernames.
### Patches
_Has the problem been patched? What versions should users upgrade to?_
Patch will be released in kubespawner 0.12 and zero-to-jupyterhub 0.9.1
### Workarounds
_Is there a way for users to fix or remediate the vulnerability without upgrading?_
#### KubeSpawner
Specify configuration:
for KubeSpawner
```python
from traitlets import default
from kubespawner import KubeSpawner
class PatchedKubeSpawner(KubeSpawner):
@default("pod_name_template")
def _default_pod_name_template(self):
if self.name:
return "jupyter-{username}-{servername}"
else:
return "jupyter-{username}"
@default("pvc_name_template")
def _default_pvc_name_template(self):
if self.name:
return "claim-{username}-{servername}"
else:
return "claim-{username}"
c.JupyterHub.spawner_class = PatchedKubeSpawner
```
**Note for KubeSpawner:** this configuration will behave differently before and after the upgrade, so will need to be removed when upgrading. Only apply this configuration while still using KubeSpawner ≤ 0.11.1 and remove it after upgrade to ensure consistent pod and pvc naming.
Changing the name template means pvcs for named servers will have different names. This will result in orphaned PVCs for named servers across Hub upgrade! This may appear as data loss for users, depending on configuration, but the orphaned PVCs will still be around and data can be migrated manually (or new PVCs created manually to reference existing PVs) before deleting the old PVCs and/or PVs.
### References
_Are there any links users can visit to find out more?_
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [kubespawner](https://github.com/jupyterhub/kubespawner)
* Email us at [security@ipython.org](mailto:security@ipython.org)
Credit: Jining Huang | {'CVE-2020-15110'} | 2022-03-03T05:14:03.632392Z | 2020-07-22T23:07:16Z | MODERATE | null | {'CWE-863'} | {'https://github.com/jupyterhub/kubespawner', 'https://github.com/jupyterhub/kubespawner/commit/3dfe870a7f5e98e2e398b01996ca6b8eff4bb1d0', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15110', 'https://github.com/jupyterhub/kubespawner/security/advisories/GHSA-v7m9-9497-p9gr'} | null |
PyPI | PYSEC-2013-22 | null | easy_install in setuptools before 0.7 uses HTTP to retrieve packages from the PyPI repository, and does not perform integrity checks on package contents, which allows man-in-the-middle attackers to execute arbitrary code via a crafted response to the default use of the product. | {'CVE-2013-1633'} | 2021-07-15T02:22:20.324113Z | 2013-08-06T02:52:00Z | null | null | null | {'http://www.reddit.com/r/Python/comments/17rfh7/warning_dont_use_pip_in_an_untrusted_network_a/', 'https://pypi.python.org/pypi/setuptools/0.9.8#changes'} | null |
PyPI | GHSA-8843-m7mw-mxqm | Buffer overflow in Pillow | In Pillow before 6.2.3 and 7.x before 7.0.1, there are two Buffer Overflows in libImaging/TiffDecode.c. | {'CVE-2020-10379'} | 2022-03-03T05:14:16.304336Z | 2020-07-27T21:52:41Z | HIGH | null | {'CWE-120'} | {'https://github.com/python-pillow/Pillow/commits/master/src/libImaging', 'https://snyk.io/vuln/SNYK-PYTHON-PILLOW-574577', 'https://github.com/python-pillow/Pillow/pull/4538', 'https://github.com/python-pillow/Pillow/commit/46f4a349b88915787fea3fb91348bb1665831bbb#diff-9478f2787e3ae9668a15123b165c23ac', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10379', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOKHNWV2VS5GESY7IBD237E7C6T3I427/', 'https://github.com/python-pillow/Pillow', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.3.html', 'https://usn.ubuntu.com/4430-2/', 'https://pillow.readthedocs.io/en/stable/releasenotes/7.1.0.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BEBCPE4F2VHTIT6EZA2YZQZLPVDEBJGD/'} | null |
PyPI | PYSEC-2017-61 | null | Cross-site scripting (XSS) vulnerability in the URL checking infrastructure in Plone CMS 5.x through 5.0.6, 4.x through 4.3.11, and 3.3.x through 3.3.6 allows remote attackers to inject arbitrary web script or HTML via a crafted URL. | {'CVE-2016-7138'} | 2021-07-25T23:34:49.134095Z | 2017-03-07T16:59:00Z | null | null | null | {'http://seclists.org/fulldisclosure/2016/Oct/80', 'http://www.securityfocus.com/archive/1/539572/100/0/threaded', 'http://www.securityfocus.com/bid/92752', 'http://www.openwall.com/lists/oss-security/2016/09/05/5', 'http://www.openwall.com/lists/oss-security/2016/09/05/4', 'http://packetstormsecurity.com/files/139110/Plone-CMS-4.3.11-5.0.6-XSS-Traversal-Open-Redirection.html', 'https://plone.org/security/hotfix/20160830/non-persistent-xss-in-plone-1'} | null |
PyPI | PYSEC-2020-209 | null | A flaw was found in the Ansible Engine, in ansible-engine 2.8.x before 2.8.15 and ansible-engine 2.9.x before 2.9.13, when installing packages using the dnf module. GPG signatures are ignored during installation even when disable_gpg_check is set to False, which is the default behavior. This flaw leads to malicious packages being installed on the system and arbitrary code executed via package installation scripts. The highest threat from this vulnerability is to integrity and system availability. | {'GHSA-m429-fhmv-c6q2', 'CVE-2020-14365'} | 2021-07-02T02:41:35.012028Z | 2020-09-23T13:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-m429-fhmv-c6q2', 'https://bugzilla.redhat.com/show_bug.cgi?id=1869154'} | null |
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