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-2021-825 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `AllToAll` can be made to execute a division by 0. This occurs whenever the `split_count` argument is 0. 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-2021-41218', 'GHSA-9crf-c6qr-r273'} | 2021-12-09T06:35:43.909633Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273'} | null |
PyPI | GHSA-p28m-34f6-967q | High severity vulnerability that affects pyopenssl | Python Cryptographic Authority pyopenssl version prior to version 17.5.0 contains a CWE-416: Use After Free vulnerability in X509 object handling that can result in Use after free can lead to possible denial of service or remote code execution.. This attack appear to be exploitable via Depends on the calling application and if it retains a reference to the memory.. This vulnerability appears to have been fixed in 17.5.0. | {'CVE-2018-1000807'} | 2022-03-03T05:13:06.759843Z | 2018-10-10T16:10:38Z | HIGH | null | {'CWE-416'} | {'https://access.redhat.com/errata/RHSA-2019:0085', 'https://github.com/advisories/GHSA-p28m-34f6-967q', 'https://usn.ubuntu.com/3813-1/', 'https://github.com/pyca/pyopenssl/pull/723', 'https://github.com/pyca/pyopenssl', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000807', 'http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00014.html'} | null |
PyPI | GHSA-x5cp-9pcf-pp3h | Denial of Service in Tensorflow | ### Impact
The `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L241-L244
Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
### 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 is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4) | {'CVE-2020-15199'} | 2021-08-26T15:11:57Z | 2020-09-25T18:28:24Z | MODERATE | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15199', '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-x5cp-9pcf-pp3h'} | null |
PyPI | GHSA-h98h-8mxr-m8gx | Out-of-bounds read in TensorFlow possibly causing disclosure of the contents of process memory. | TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decoder in core/kernels/decode_bmp_op.cc. | {'CVE-2018-21233'} | 2022-03-03T05:13:28.032180Z | 2020-05-13T16:01:35Z | MODERATE | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/49f73c55d56edffebde4bca4a407ad69c1cae433', 'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-001.md', 'https://nvd.nist.gov/vuln/detail/CVE-2018-21233'} | null |
PyPI | PYSEC-2019-160 | null | The mirroring support (-M, --use-mirrors) in Python Pip before 1.5 uses insecure DNS querying and authenticity checks which allows attackers to perform man-in-the-middle attacks. | {'CVE-2013-5123'} | 2021-07-15T02:22:17.687153Z | 2019-11-05T22:15:00Z | null | null | null | {'https://security-tracker.debian.org/tracker/CVE-2013-5123', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2013-5123', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-April/155291.html', 'http://www.openwall.com/lists/oss-security/2013/08/21/17', 'https://bugzilla.suse.com/show_bug.cgi?id=CVE-2013-5123', 'http://www.securityfocus.com/bid/77520', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-April/155248.html', 'http://www.openwall.com/lists/oss-security/2013/08/21/18'} | null |
PyPI | PYSEC-2021-433 | null | S3Scanner before 2.0.2 allows Directory Traversal via a crafted bucket, as demonstrated by a <Key>../ substring in a ListBucketResult element. | {'CVE-2021-32061', 'GHSA-qppg-v75c-r5ff'} | 2021-11-29T21:27:52.731426Z | 2021-11-29T03:15:00Z | null | null | null | {'https://github.com/sa7mon/S3Scanner/releases/tag/2.0.2', 'https://github.com/sa7mon/S3Scanner/issues/122', 'https://github.com/advisories/GHSA-qppg-v75c-r5ff', 'https://vuln.ryotak.me/advisories/62'} | null |
PyPI | GHSA-545v-42p7-98fq | Heap out of bounds read in `MaxPoolGradWithArgmax` | ### Impact
The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:
```python
import tensorflow as tf
input = tf.constant([10.0, 10.0, 10.0], shape=[1, 1, 3, 1], dtype=tf.float32)
grad = tf.constant([10.0, 10.0, 10.0, 10.0], shape=[1, 1, 1, 4], dtype=tf.float32)
argmax = tf.constant([1], shape=[1], dtype=tf.int64)
ksize = [1, 1, 1, 1]
strides = [1, 1, 1, 1]
tf.raw_ops.MaxPoolGradWithArgmax(
input=input, grad=grad, argmax=argmax, ksize=ksize, strides=strides,
padding='SAME', include_batch_in_index=False)
```
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.
### Patches
We have patched the issue in GitHub commit [dcd7867de0fea4b72a2b34bd41eb74548dc23886](https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886).
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-2021-29570'} | 2022-03-03T05:13:39.721123Z | 2021-05-21T14:25:25Z | LOW | null | {'CWE-125'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29570', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-545v-42p7-98fq', 'https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886'} | null |
PyPI | PYSEC-2020-9 | null | A flaw was found in Ansible 2.7.17 and prior, 2.8.9 and prior, and 2.9.6 and prior when using the Extract-Zip function from the win_unzip module as the extracted file(s) are not checked if they belong to the destination folder. An attacker could take advantage of this flaw by crafting an archive anywhere in the file system, using a path traversal. This issue is fixed in 2.10. | {'CVE-2020-1737', 'GHSA-893h-35v4-mxqx'} | 2020-06-13T04:15:00Z | 2020-03-09T16:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/U3IMV3XEIUXL6S4KPLYYM4TVJQ2VNEP2/', 'https://github.com/ansible/ansible/issues/67795', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FWDK3QUVBULS3Q3PQTGEKUQYPSNOU5M3/', 'https://github.com/advisories/GHSA-893h-35v4-mxqx', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QT27K5ZRGDPCH7GT3DRI3LO4IVDVQUB7/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1737', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2014-98 | null | Cross-site scripting (XSS) vulnerability in plugins/main/content/js/ajenti.coffee in Eugene Pankov Ajenti 1.2.13 allows remote authenticated users to inject arbitrary web script or HTML via the command field in the Cron functionality. | {'CVE-2014-2260'} | 2021-12-13T06:35:03.047936Z | 2014-04-30T23:58:00Z | null | null | null | {'https://github.com/Eugeny/ajenti/issues/233', 'https://github.com/Eugeny/ajenti/commit/3270fd1d78391bb847b4c9ce37cf921f485b1310', 'http://packetstormsecurity.com/files/124804/Ajenti-1.2.13-Cross-Site-Scripting.html', 'http://www.osvdb.org/102174', 'http://www.securityfocus.com/bid/64982'} | null |
PyPI | PYSEC-2021-599 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version. | {'CVE-2021-37686', 'GHSA-mhhc-q96p-mfm9'} | 2021-12-09T06:35:06.351462Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mhhc-q96p-mfm9'} | null |
PyPI | PYSEC-2017-67 | null | PySAML2 allows remote attackers to conduct XML external entity (XXE) attacks via a crafted SAML XML request or response. | {'CVE-2016-10127'} | 2021-07-25T23:34:51.281897Z | 2017-03-03T15:59:00Z | null | null | null | {'https://github.com/rohe/pysaml2/issues/366', 'https://github.com/rohe/pysaml2/pull/379', 'http://www.securityfocus.com/bid/95376', 'https://github.com/rohe/pysaml2/commit/6e09a25d9b4b7aa7a506853210a9a14100b8bc9b', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=850716', 'http://www.openwall.com/lists/oss-security/2017/01/19/5'} | null |
PyPI | GHSA-4hrh-9vmp-2jgg | Heap buffer overflow in `StringNGrams` | ### Impact
An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`:
```python
import tensorflow as tf
separator = b'\x02\x00'
ngram_widths = [7, 6, 11]
left_pad = b'\x7f\x7f\x7f\x7f\x7f'
right_pad = b'\x7f\x7f\x25\x5d\x53\x74'
pad_width = 50
preserve_short_sequences = True
l = ['', '', '', '', '', '', '', '', '', '', '']
data = tf.constant(l, shape=[11], dtype=tf.string)
l2 = [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, 3]
data_splits = tf.constant(l2, shape=[116], dtype=tf.int64)
out = tf.raw_ops.StringNGrams(data=data,
data_splits=data_splits, separator=separator,
ngram_widths=ngram_widths, left_pad=left_pad,
right_pad=right_pad, pad_width=pad_width,
preserve_short_sequences=preserve_short_sequences)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements:
```cc
for (int ngram_index = 0; ngram_index < num_ngrams; ++ngram_index) {
int pad_width = get_pad_width(ngram_width);
int left_padding = std::max(0, pad_width - ngram_index);
int right_padding = std::max(0, pad_width - (num_ngrams - (ngram_index + 1)));
int num_tokens = ngram_width - (left_padding + right_padding);
int data_start_index = left_padding > 0 ? 0 : ngram_index - pad_width;
...
tstring* ngram = &output[ngram_index];
ngram->reserve(ngram_size);
for (int n = 0; n < left_padding; ++n) {
ngram->append(left_pad_);
ngram->append(separator_);
}
for (int n = 0; n < num_tokens - 1; ++n) {
ngram->append(data[data_start_index + n]);
ngram->append(separator_);
}
ngram->append(data[data_start_index + num_tokens - 1]); // <<<
for (int n = 0; n < right_padding; ++n) {
ngram->append(separator_);
ngram->append(right_pad_);
}
...
}
```
If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`.
### Patches
We have patched the issue in GitHub commit [ba424dd8f16f7110eea526a8086f1a155f14f22b](https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b).
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 Yakun Zhang and Ying Wang of Baidu X-Team. | {'CVE-2021-29542'} | 2022-04-26T18:17:07.368107Z | 2021-05-21T14:23:15Z | LOW | null | {'CWE-787', 'CWE-131'} | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29542', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hrh-9vmp-2jgg'} | null |
PyPI | GHSA-452g-f7fp-9jf7 | Type confusion during tensor casts lead to dereferencing null pointers | ### Impact
Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences.
There are multiple ways to reproduce this, listing a few examples here:
```python
import tensorflow as tf
import numpy as np
data = tf.random.truncated_normal(shape=1,mean=np.float32(20.8739),stddev=779.973,dtype=20,seed=64)
```
```python
import tensorflow as tf
import numpy as np
data =
tf.random.stateless_truncated_normal(shape=1,seed=[63,70],mean=np.float32(20.8739),stddev=779.973,dtype=20)
```
```python
import tensorflow as tf
import numpy as np
data = tf.one_hot(indices=[62,50],depth=136,on_value=np.int32(237),off_value=158,axis=856,dtype=20)
```
```python
import tensorflow as tf
import numpy as np
data = tf.range(start=np.int32(214),limit=660,delta=129,dtype=20)
```
```python
import tensorflow as tf
import numpy as np
data = tf.raw_ops.ResourceCountUpTo(resource=np.int32(30), limit=872, T=3)
```
```python
import tensorflow as tf
import numpy as np
writer_array = np.array([1,2],dtype=np.int32)
writer_tensor = tf.convert_to_tensor(writer_array,dtype=tf.resource)
```
All these examples and similar ones have the same behavior: the [conversion from Python array to C++ array](https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion:
```cc
int pyarray_type = PyArray_TYPE(array);
PyArray_Descr* descr = PyArray_DESCR(array);
switch (pyarray_type) {
...
case NPY_VOID:
// Quantized types are currently represented as custom struct types.
// PyArray_TYPE returns NPY_VOID for structs, and we should look into
// descr to derive the actual type.
// Direct feeds of certain types of ResourceHandles are represented as a
// custom struct type.
return PyArrayDescr_to_TF_DataType(descr, out_tf_datatype);
...
}
```
For the tensor types involved in the above example, the `pyarray_type` is `NPY_VOID` but the `descr` field is such that `descr->field = NULL`. Then [`PyArrayDescr_to_TF_DataType`](https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L72-L77) will trigger a null dereference:
```cc
Status PyArrayDescr_to_TF_DataType(PyArray_Descr* descr,
TF_DataType* out_tf_datatype) {
PyObject* key;
PyObject* value;
Py_ssize_t pos = 0;
if (PyDict_Next(descr->fields, &pos, &key, &value)) {
...
}
}
```
This is because the Python's `PyDict_Next` implementation would dereference the first argument.
### Patches
We have patched the issue in GitHub commit [030af767d357d1b4088c4a25c72cb3906abac489](https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489).
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 members of the Aivul Team from Qihoo 360 as well as Ye Zhang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29513'} | 2022-03-03T05:12:35.841801Z | 2021-05-21T14:20:46Z | LOW | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-452g-f7fp-9jf7', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29513'} | null |
PyPI | PYSEC-2019-79 | null | An issue was discovered in Django 1.11 before 1.11.21, 2.1 before 2.1.9, and 2.2 before 2.2.2. The clickable Current URL value displayed by the AdminURLFieldWidget displays the provided value without validating it as a safe URL. Thus, an unvalidated value stored in the database, or a value provided as a URL query parameter payload, could result in an clickable JavaScript link. | {'GHSA-7rp2-fm2h-wchj', 'CVE-2019-12308'} | 2019-06-12T17:29:00Z | 2019-06-03T17:29:00Z | null | null | null | {'https://lists.debian.org/debian-lts-announce/2019/06/msg00001.html', 'http://www.openwall.com/lists/oss-security/2019/06/03/2', 'https://github.com/advisories/GHSA-7rp2-fm2h-wchj', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/USYRARSYB7PE3S2ZQO7PZNWMH7RPGL5G/', 'https://seclists.org/bugtraq/2019/Jul/10', 'https://www.djangoproject.com/weblog/2019/jun/03/security-releases/', 'https://usn.ubuntu.com/4043-1/', 'https://docs.djangoproject.com/en/dev/releases/2.2.2/', 'https://lists.debian.org/debian-lts-announce/2019/07/msg00001.html', 'https://security.gentoo.org/glsa/202004-17', 'https://groups.google.com/forum/#!topic/django-announce/GEbHU7YoVz8', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00006.html', 'https://docs.djangoproject.com/en/dev/releases/1.11.21/', 'https://www.debian.org/security/2019/dsa-4476', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00025.html', 'http://www.securityfocus.com/bid/108559', 'https://docs.djangoproject.com/en/dev/releases/2.1.9/', 'https://docs.djangoproject.com/en/dev/releases/security/'} | null |
PyPI | GHSA-m6xf-fq7q-8743 | mutation XSS via whitelisted math or svg and raw tag in Bleach | ### Impact
A [mutation XSS](https://cure53.de/fp170.pdf) affects users calling `bleach.clean` with all of:
* the `svg` or `math` in the allowed/whitelisted tags
* an RCDATA tag (see below) in the allowed/whitelisted tags
* the keyword argument `strip=False`
### Patches
Users are encouraged to upgrade to bleach v3.1.2 or greater.
### Workarounds
* modify `bleach.clean` calls to use `strip=True`, or not whitelist `math` or `svg` tags and one or more of the following tags:
```
script
noscript
style
noframes
xmp
noembed
iframe
```
* A strong [Content-Security-Policy](https://developer.mozilla.org/en-US/docs/Web/HTTP/CSP) without `unsafe-inline` and `unsafe-eval` [`script-src`s](https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Content-Security-Policy/script-src)) will also help mitigate the risk.
### References
* https://bugzilla.mozilla.org/show_bug.cgi?id=1621692
* https://cure53.de/fp170.pdf
* https://nvd.nist.gov/vuln/detail/CVE-2020-6816
* https://www.checkmarx.com/blog/vulnerabilities-discovered-in-mozilla-bleach
### Credits
* Reported by [Yaniv Nizry](https://twitter.com/ynizry) from the CxSCA AppSec group at Checkmarx
### For more information
If you have any questions or comments about this advisory:
* Open an issue at [https://github.com/mozilla/bleach/issues](https://github.com/mozilla/bleach/issues)
* Email us at [security@mozilla.org](mailto:security@mozilla.org) | {'CVE-2020-6816'} | 2022-03-03T05:14:11.493370Z | 2020-03-24T15:06:32Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-6816', 'https://www.checkmarx.com/blog/vulnerabilities-discovered-in-mozilla-bleach', 'https://advisory.checkmarx.net/advisory/CX-2020-4277', 'https://github.com/mozilla/bleach/releases/tag/v3.1.2', 'https://github.com/mozilla/bleach/security/advisories/GHSA-m6xf-fq7q-8743', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/EDQU2SZLZMSSACCBUBJ6NOSRNNBDYFW5/'} | null |
PyPI | PYSEC-2013-24 | null | The user-password-update command in python-keystoneclient before 0.2.4 accepts the new password in the --password argument, which allows local users to obtain sensitive information by listing the process. | {'CVE-2013-2013'} | 2021-07-25T23:34:51.897352Z | 2013-10-01T20:55:00Z | null | null | null | {'https://bugs.launchpad.net/python-keystoneclient/+bug/938315', 'http://www.openwall.com/lists/oss-security/2013/05/23/4', 'https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A16937'} | null |
PyPI | PYSEC-2011-19 | null | feedparser.py in Universal Feed Parser (aka feedparser or python-feedparser) before 5.0.1 allows remote attackers to cause a denial of service (application crash) via a malformed DOCTYPE declaration. | {'GHSA-6h52-4vmh-8x4f', 'CVE-2011-1156'} | 2021-08-27T03:22:03.762667Z | 2011-04-11T18:55:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-updates/2011-04/msg00026.html', 'http://secunia.com/advisories/44074', 'http://www.mandriva.com/security/advisories?name=MDVSA-2011:082', 'https://bugzilla.novell.com/show_bug.cgi?id=680074', 'http://openwall.com/lists/oss-security/2011/03/15/11', 'http://openwall.com/lists/oss-security/2011/03/14/18', 'https://github.com/advisories/GHSA-6h52-4vmh-8x4f', 'http://secunia.com/advisories/43730', 'https://bugzilla.redhat.com/show_bug.cgi?id=684877', 'http://www.securityfocus.com/bid/46867', 'https://code.google.com/p/feedparser/issues/detail?id=91', 'http://support.novell.com/security/cve/CVE-2011-1156.html'} | null |
PyPI | GHSA-h9px-9vqg-222h | Heap OOB in `QuantizeAndDequantizeV3` | ### Impact
An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`:
```python
import tensorflow as tf
tf.raw_ops.QuantizeAndDequantizeV3(
input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30],
signed_input=False, range_given=False, narrow_range=False, axis=3)
```
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:
```cc
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
```
### Patches
We have patched the issue in GitHub commit [99085e8ff02c3763a0ec2263e44daec416f6a387](https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387).
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 Aivul Team from Qihoo 360. | {'CVE-2021-29553'} | 2022-03-03T05:13:50.806338Z | 2021-05-21T14:23:51Z | LOW | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h', 'https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29553'} | null |
PyPI | PYSEC-2021-10 | null | A SQL Injection issue in the SQL Panel in Jazzband Django Debug Toolbar before 1.11.1, 2.x before 2.2.1, and 3.x before 3.2.1 allows attackers to execute SQL statements by changing the raw_sql input field of the SQL explain, analyze, or select form. | {'CVE-2021-30459', 'GHSA-pghf-347x-c2gj'} | 2021-04-21T15:05:00Z | 2021-04-14T18:15:00Z | null | null | null | {'https://github.com/jazzband/django-debug-toolbar/releases', 'https://www.djangoproject.com/weblog/2021/apr/14/debug-toolbar-security-releases/', 'https://github.com/jazzband/django-debug-toolbar/security/advisories/GHSA-pghf-347x-c2gj'} | null |
PyPI | PYSEC-2017-88 | null | Mercurial prior to version 4.3 is vulnerable to a missing symlink check that can malicious repositories to modify files outside the repository | {'CVE-2017-1000115'} | 2021-08-27T03:22:07.021138Z | 2017-10-05T01:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2017:2489', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_4.3_.2F_4.3.1_.282017-08-10.29', 'http://www.debian.org/security/2017/dsa-3963', 'http://www.securityfocus.com/bid/100290', 'https://security.gentoo.org/glsa/201709-18'} | null |
PyPI | PYSEC-2010-22 | null | pyftpdlib before 0.1.1 does not choose a random value for the port associated with the PASV command, which makes it easier for remote attackers to obtain potentially sensitive information about the number of in-progress data connections by reading the response to this command. | {'CVE-2007-6738'} | 2010-10-20T04:00:00Z | 2010-10-19T20:00:00Z | null | null | null | {'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY'} | null |
PyPI | PYSEC-2021-833 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseBinCount` is vulnerable to a heap OOB access. This is because of missing validation between the elements of the `values` argument and the shape of the sparse output. 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-2021-41226', 'GHSA-374m-jm66-3vj8'} | 2021-12-09T06:35:45.112404Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-374m-jm66-3vj8'} | null |
PyPI | PYSEC-2020-130 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15207', 'GHSA-q4qf-3fc6-8x34'} | 2020-10-29T16:15:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34', 'https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2018-42 | null | Ansible 2.5 prior to 2.5.5, and 2.4 prior to 2.4.5, do not honor the no_log task flag for failed tasks. When the no_log flag has been used to protect sensitive data passed to a task from being logged, and that task does not run successfully, Ansible will expose sensitive data in log files and on the terminal of the user running Ansible. | {'GHSA-jwcc-j78w-j73w', 'CVE-2018-10855'} | 2021-07-02T02:41:34.017806Z | 2018-07-03T01:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2019:0054', 'https://www.debian.org/security/2019/dsa-4396', 'https://access.redhat.com/errata/RHSA-2018:1949', 'https://access.redhat.com/errata/RHSA-2018:2585', 'https://access.redhat.com/errata/RHSA-2018:1948', 'https://access.redhat.com/errata/RHSA-2018:2184', 'https://usn.ubuntu.com/4072-1/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10855', 'https://access.redhat.com/errata/RHSA-2018:2079', 'https://access.redhat.com/errata/RHSA-2018:2022', 'https://github.com/advisories/GHSA-jwcc-j78w-j73w', 'https://access.redhat.com/errata/RHBA-2018:3788'} | null |
PyPI | PYSEC-2019-199 | null | A code injection issue was discovered in PyXDG before 0.26 via crafted Python code in a Category element of a Menu XML document in a .menu file. XDG_CONFIG_DIRS must be set up to trigger xdg.Menu.parse parsing within the directory containing this file. This is due to a lack of sanitization in xdg/Menu.py before an eval call. | {'GHSA-r6v3-hpxj-r8rv', 'SNYK-PYTHON-PYXDG-174562', 'CVE-2019-12761'} | 2021-08-27T03:22:18.878765Z | 2019-06-06T19:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-r6v3-hpxj-r8rv', 'https://gist.github.com/dhondta/b45cd41f4186110a354dc7272916feba', 'https://lists.debian.org/debian-lts-announce/2019/06/msg00006.html', 'https://snyk.io/vuln/SNYK-PYTHON-PYXDG-174562'} | null |
PyPI | PYSEC-2021-130 | null | JupyterLab is a user interface for Project Jupyter which will eventually replace the classic Jupyter Notebook. In affected versions untrusted notebook can execute code on load. In particular JupyterLab doesn’t sanitize the action attribute of html `<form>`. Using this it is possible to trigger the form validation outside of the form itself. This is a remote code execution, but requires user action to open a notebook. | {'CVE-2021-32797', 'GHSA-4952-p58q-6crx'} | 2021-08-27T03:22:05.377903Z | 2021-08-09T21:15:00Z | null | null | null | {'https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-4952-p58q-6crx', 'https://github.com/jupyterlab/jupyterlab/commit/504825938c0abfa2fb8ff8d529308830a5ae42ed'} | null |
PyPI | GHSA-vw27-fwjf-5qxm | Arbitrary command execution on Windows via qutebrowserurl: URL handler | ### Impact
Starting with qutebrowser v1.7.0, the Windows installer for qutebrowser registers it as a handler for certain URL schemes. With some applications such as Outlook Desktop, opening a specially crafted URL can lead to argument injection, allowing execution of qutebrowser commands, which in turn allows arbitrary code execution via commands such as `:spawn` or `:debug-pyeval`.
Only Windows installs where qutebrowser is registered as URL handler are affected. It does *not* have to be set as default browser for the exploit to work.
### Patches
The issue has been fixed in [qutebrowser v2.4.0](https://github.com/qutebrowser/qutebrowser/releases/tag/v2.4.0) in commit 8f46ba3f6dc7b18375f7aa63c48a1fe461190430.
The fix also adds additional hardening for potential similar issues on Linux (by adding the new `--untrusted-args` flag to the `.desktop` file), though no such vulnerabilities are known.
Backported patches for older versions are available, but no further releases are planned:
- v1.7.x: d1ceaab
- v1.8.x: ca7155d
- v1.9.x: 157d871
- v1.10.x: 94a6125
- v1.11.x: 10acfbb
- v1.12.x: 363a18f
- v1.13.x: 410f262
- v1.14.x: e4f4d93
- v2.0.x: 15a1654
- v2.1.x: 509ddf2
- v2.2.x: 03dcba5
- v2.3.x: 00a694c
(commits are referring to qutebrowser/qutebrowser on GitHub)
### Workarounds
Remove qutebrowser from the default browser settings entirely, so that it does not handle any kind of URLs. Make sure to remove *all* handlers, including an (accidental) `qutebrowserURL` handler, e.g. using [NirSoft URLProtocolView](https://www.nirsoft.net/utils/url_protocol_view.html).
### Timeline
2021-10-15: Issue reported via security@qutebrowser.org by Ping Fan (Zetta) Ke of [Valkyrie-X Security Research Group (VXRL)](https://www.vxrl.hk/)
2021-10-15: Issue confirmed by @The-Compiler (lead developer), author of installer (@bitraid) contacted for help/review
2021-10-15: CVE assigned by GitHub
2021-10-15 to 2021-10-17: Fix developed
2021-10-17: Additional core developer (@toofar) contacted for help/review
2021-10-21: v2.4.0 released containing the fix
2021-10-21: Advisory and fix published
### References
See the [commit message](https://github.com/qutebrowser/qutebrowser/commit/8f46ba3f6dc7b18375f7aa63c48a1fe461190430) for additional information and references to various similar issues in other projects.
### Acknowledgements
Thanks to Ping Fan (Zetta) Ke of [Valkyrie-X Security Research Group](https://www.vxrl.hk/) (VXRL/@vxresearch) for finding and responsibly disclosing this issue.
### Contact
If you have any questions or comments about this advisory, please email [security@qutebrowser.org](mailto:security@qutebrowser.org). | {'CVE-2021-41146'} | 2022-03-03T05:13:43.293872Z | 2021-10-22T16:20:10Z | HIGH | null | {'CWE-77', 'CWE-641', 'CWE-88'} | {'https://github.com/qutebrowser/qutebrowser/commit/8f46ba3f6dc7b18375f7aa63c48a1fe461190430', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41146', 'https://github.com/qutebrowser/qutebrowser/security/advisories/GHSA-vw27-fwjf-5qxm', 'https://github.com/qutebrowser/qutebrowser'} | null |
PyPI | GHSA-c968-pq7h-7fxv | Division by 0 in `Conv3DBackprop*` | ### Impact
The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0:
```python
import tensorflow as tf
input_sizes = tf.constant([0, 0, 0, 0, 0], shape=[5], dtype=tf.int32)
filter_tensor = tf.constant([], shape=[0, 0, 0, 1, 0], dtype=tf.float32)
out_backprop = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
tf.raw_ops.Conv3DBackpropInputV2(input_sizes=input_sizes, filter=filter_tensor, out_backprop=out_backprop, strides=[1, 1, 1, 1, 1], padding='SAME', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
```
```python
import tensorflow as tf
input_sizes = tf.constant([1], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
filter_tensor = tf.constant([0, 0, 0, 1, 0], shape=[5], dtype=tf.int32)
out_backprop = tf.constant([], shape=[1, 1, 1, 1, 0], dtype=tf.float32)
tf.raw_ops.Conv3DBackpropFilterV2(input=input_sizes, filter_sizes=filter_tensor, out_backprop=out_backprop, strides=[1, 1, 1, 1, 1], padding='SAME', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero:
```cc
const int64 size_A = output_image_size * dims.out_depth;
const int64 size_B = filter_total_size * dims.out_depth;
const int64 size_C = output_image_size * filter_total_size;
const int64 work_unit_size = size_A + size_B + size_C;
...
const size_t shard_size =
use_parallel_contraction
? 1
: (target_working_set_size + work_unit_size - 1) / work_unit_size;
```
Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error.
### Patches
We have patched the issue in GitHub commit [311403edbc9816df80274bd1ea8b3c0c0f22c3fa](https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa).
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 Yakun Zhang and Ying Wang of Baidu X-Team. | {'CVE-2021-29522'} | 2022-03-03T05:13:17.830516Z | 2021-05-21T14:21:39Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29522'} | null |
PyPI | PYSEC-2021-560 | null | TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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-c5x2-p679-95wc', 'CVE-2021-37647'} | 2021-12-09T06:35:03.005830Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc', 'https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7'} | null |
PyPI | PYSEC-2014-61 | null | member_portrait.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allows remote authenticated users to modify or delete portraits of other users via unspecified vectors. | {'CVE-2013-4197'} | 2021-07-25T23:34:47.083456Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'https://bugzilla.redhat.com/show_bug.cgi?id=978478', 'http://seclists.org/oss-sec/2013/q3/261', 'http://plone.org/products/plone/security/advisories/20130618-announcement'} | null |
PyPI | PYSEC-2022-139 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. 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-2022-23575', 'GHSA-c94w-c95p-phf8'} | 2022-03-09T00:18:27.680857Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8', 'https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558'} | null |
PyPI | PYSEC-2021-425 | null | Matrix is an ecosystem for open federated Instant Messaging and Voice over IP. In versions 1.41.0 and prior, unauthorised users can access the membership (list of members, with their display names) of a room if they know the ID of the room. The vulnerability is limited to rooms with `shared` history visibility. Furthermore, the unauthorised user must be using an account on a vulnerable homeserver that is in the room. Server administrators should upgrade to 1.41.1 or later in order to receive the patch. One workaround is available. Administrators of servers that use a reverse proxy could, with potentially unacceptable loss of functionality, block the endpoints: `/_matrix/client/r0/rooms/{room_id}/members` with `at` query parameter, and `/_matrix/client/unstable/rooms/{room_id}/members` with `at` query parameter. | {'CVE-2021-39164', 'GHSA-3x4c-pq33-4w3q'} | 2021-11-16T03:58:44.571857Z | 2021-08-31T17:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/releases/tag/v1.41.1', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-3x4c-pq33-4w3q', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2VHDEPCZ22GJFMZCWA2XZAGPOEV72POF/', 'https://github.com/matrix-org/synapse/commit/cb35df940a', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PXT7ID7DNBRN2TVTETU3SYQHJKEG6PXN/'} | null |
PyPI | GHSA-c7pr-343r-5c46 | missing clamps for decimal args in external functions | ### Impact
The following code does not properly validate that its input is in bounds.
```python
@external
def foo(x: decimal) -> decimal:
return x
```
### Patches
0.3.0 / #2447
### Workarounds
Don't use decimal args
| {'CVE-2021-41122'} | 2022-03-03T05:11:16.304563Z | 2021-10-06T17:48:46Z | MODERATE | null | {'CWE-682'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41122', 'https://github.com/vyperlang/vyper/security/advisories/GHSA-c7pr-343r-5c46', 'https://github.com/vyperlang/vyper/pull/2447', 'https://github.com/vyperlang/vyper'} | null |
PyPI | PYSEC-2022-16 | null | Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prior to 3.2.1 are vulnerable to Server-Side Request Forgery (SSRF). Any user deploying Jupyter Server or Notebook with jupyter-proxy-server extension enabled is affected. A lack of input validation allows authenticated clients to proxy requests to other hosts, bypassing the `allowed_hosts` check. Because authentication is required, which already grants permissions to make the same requests via kernel or terminal execution, this is considered low to moderate severity. Users may upgrade to version 3.2.1 to receive a patch or, as a workaround, install the patch manually. | {'CVE-2022-21697', 'GHSA-gcv9-6737-pjqw'} | 2022-02-01T17:37:55.179786Z | 2022-01-25T14:15:00Z | null | null | null | {'https://github.com/jupyterhub/jupyter-server-proxy/compare/v3.2.0...v3.2.1.patch', 'https://github.com/jupyterhub/jupyter-server-proxy/commit/fd31930bacd12188c448c886e0783529436b99eb', 'https://github.com/jupyterhub/jupyter-server-proxy/security/advisories/GHSA-gcv9-6737-pjqw'} | null |
PyPI | PYSEC-2019-176 | null | python-docutils allows insecure usage of temporary files | {'CVE-2009-5042', 'GHSA-cg75-6938-wx58'} | 2021-08-27T03:42:08.729631Z | 2019-10-31T16:15:00Z | null | null | null | {'https://security-tracker.debian.org/tracker/CVE-2009-5042', 'https://github.com/advisories/GHSA-cg75-6938-wx58'} | null |
PyPI | GHSA-267x-w5hx-8hjr | Integer Overflow or Wraparound in OpenCV | In opencv/modules/imgcodecs/src/grfmt_pxm.cpp, function ReadNumber did not checkout the input length, which lead to integer overflow. If the image is from remote, may lead to remote code execution or denial of service. This affects OpenCV 3.3 (corresponding with OpenCV-Python version 3.3.0.9) and earlier. | {'CVE-2017-12864'} | 2022-03-03T05:13:14.232807Z | 2021-10-12T22:02:45Z | HIGH | null | {'CWE-190'} | {'https://nvd.nist.gov/vuln/detail/CVE-2017-12864', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://github.com/opencv/opencv/issues/9372', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://security.gentoo.org/glsa/201712-02', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2013-32 | null | cache.py in Suds 0.4, when tempdir is set to None, allows local users to redirect SOAP queries and possibly have other unspecified impact via a symlink attack on a cache file with a predictable name in /tmp/suds/. | {'CVE-2013-2217'} | 2021-12-05T22:42:34.622348Z | 2013-09-23T20:55:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=978696', 'http://lists.opensuse.org/opensuse-updates/2013-07/msg00062.html', 'http://www.ubuntu.com/usn/USN-2008-1', 'http://www.openwall.com/lists/oss-security/2013/06/27/8'} | null |
PyPI | GHSA-xqfj-cr6q-pc8w | Crash in `tf.transpose` with complex inputs | ### Impact
Passing a complex argument to `tf.transpose` at the same time as passing `conjugate=True` argument results in a crash:
```python
import tensorflow as tf
tf.transpose(conjugate=True, a=complex(1))
```
### Patches
We have received a patch for the issue in GitHub commit [1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88](https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88).
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 in [#42105](https://github.com/tensorflow/issues/42105) and fixed in [#46973](https://github.com/tensorflow/issues/46973). | {'CVE-2021-29618'} | 2022-03-03T05:12:38.691679Z | 2021-05-21T14:28:58Z | LOW | null | {'CWE-755'} | {'https://github.com/tensorflow/issues/46973', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29618', 'https://github.com/tensorflow/issues/42105', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-cr6q-pc8w', 'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88'} | null |
PyPI | PYSEC-2017-71 | null | win_useradd, salt-cloud and the Linode driver in salt 2015.5.x before 2015.5.6, and 2015.8.x before 2015.8.1 leak password information in debug logs. | {'CVE-2015-6941'} | 2021-07-25T23:34:53.862989Z | 2017-08-09T16:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=1273066', 'https://github.com/twangboy/salt/commit/c0689e32154c41f59840ae10ffc5fbfa30618710', 'https://docs.saltstack.com/en/latest/topics/releases/2015.5.6.html', 'https://docs.saltstack.com/en/latest/topics/releases/2015.8.1.html'} | null |
PyPI | GHSA-cpqf-3c3r-c9g2 | Cobbler before 3.3.0 allows log poisoning | Cobbler before 3.3.0 allows log poisoning, and resultant Remote Code Execution, via an XMLRPC method that logs to the logfile for template injection. | {'CVE-2021-40323'} | 2022-03-03T05:14:04.246526Z | 2021-10-05T17:53:20Z | HIGH | null | {'CWE-94'} | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://nvd.nist.gov/vuln/detail/CVE-2021-40323', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0', 'https://github.com/cobbler/cobbler'} | null |
PyPI | PYSEC-2020-219 | null | In wagtail-2fa before 1.4.1, any user with access to the CMS can view and delete other users 2FA devices by going to the correct path. The user does not require special permissions in order to do so. By deleting the other users device they can disable the target users 2FA devices and potentially compromise the account if they figure out their password. The problem has been patched in version 1.4.1. | {'GHSA-9gjv-6qq6-v7qm', 'CVE-2020-5240'} | 2021-08-25T04:30:36.375287Z | 2020-03-13T22:15:00Z | null | null | null | {'https://github.com/labd/wagtail-2fa/security/advisories/GHSA-9gjv-6qq6-v7qm', 'https://github.com/labd/wagtail-2fa/commit/ac23550d33b7436e90e3beea904647907eba5b74'} | null |
PyPI | PYSEC-2021-649 | 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.AddManySparseToTensorsMap`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/kernels/sparse_tensors_map_ops.cc#L257) takes the values specified in `sparse_shape` 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. | {'GHSA-2cpx-427x-q2c6', 'CVE-2021-29523'} | 2021-12-09T06:35:18.759879Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2cpx-427x-q2c6'} | null |
PyPI | PYSEC-2021-219 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same 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. | {'GHSA-c45w-2wxr-pp53', 'CVE-2021-29582'} | 2021-08-27T03:22:35.924594Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53'} | null |
PyPI | GHSA-gv26-jpj9-c8gq | Incomplete validation in `SparseSparseMinimum` | ### Impact
Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:
```python
import tensorflow as tf
a_indices = tf.ones([45, 92], dtype=tf.int64)
a_values = tf.ones([45], dtype=tf.int64)
a_shape = tf.ones([1], dtype=tf.int64)
b_indices = tf.ones([1, 1], dtype=tf.int64)
b_values = tf.ones([1], dtype=tf.int64)
b_shape = tf.ones([1], dtype=tf.int64)
tf.raw_ops.SparseSparseMinimum(a_indices=a_indices,
a_values=a_values,
a_shape=a_shape,
b_indices=b_indices,
b_values=b_values,
b_shape=b_shape)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.
### Patches
We have patched the issue in GitHub commit [ba6822bd7b7324ba201a28b2f278c29a98edbef2](https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2) followed by GitHub commit [f6fde895ef9c77d848061c0517f19d0ec2682f3a](https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a).
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-2021-29607'} | 2022-03-18T18:03:17.505392Z | 2022-03-18T17:52:25Z | MODERATE | null | {'CWE-754'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29607', 'https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq', 'https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2'} | null |
PyPI | PYSEC-2014-36 | null | Cross-site scripting (XSS) vulnerability in python_scripts.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to inject arbitrary web script or HTML via unspecified vectors, related to "{u,}translate." | {'CVE-2012-5494'} | 2021-09-01T08:44:29.835907Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone-hotfix/releases/20121106', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone/security/advisories/20121106/10'} | null |
PyPI | PYSEC-2021-537 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. 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-cjc7-49v2-jp64', 'CVE-2021-29609'} | 2021-12-09T06:35:00.330206Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc', 'https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64'} | null |
PyPI | PYSEC-2021-167 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. 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-xcwj-wfcm-m23c', 'CVE-2021-29530'} | 2021-08-27T03:22:26.683297Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xcwj-wfcm-m23c', 'https://github.com/tensorflow/tensorflow/commit/e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd'} | null |
PyPI | PYSEC-2020-93 | null | A heap overflow in Sqreen PyMiniRacer (aka Python Mini Racer) before 0.3.0 allows remote attackers to potentially exploit heap corruption. | {'CVE-2020-25489', 'GHSA-vwcg-7xqw-qcxw'} | 2020-09-24T13:39:00Z | 2020-09-17T18:15:00Z | null | null | null | {'https://blog.sqreen.com/vulnerability-disclosure-finding-a-vulnerability-in-sqreens-php-agent-and-how-we-fixed-it/', 'https://github.com/sqreen/PyMiniRacer/compare/v0.2.0...v0.3.0', 'https://github.com/advisories/GHSA-vwcg-7xqw-qcxw'} | null |
PyPI | PYSEC-2018-15 | null | An issue was discovered in Mayan EDMS before 3.0.3. The Tags app has XSS because tag label values are mishandled. | {'GHSA-5h6m-9mvx-m6c5', 'CVE-2018-16407'} | 2021-06-10T06:51:46.544830Z | 2018-09-03T19:29:00Z | null | null | null | {'https://gitlab.com/mayan-edms/mayan-edms/commit/076468a9225e4630a463c0bbceb8e5b805fe380c', 'https://github.com/advisories/GHSA-5h6m-9mvx-m6c5', 'https://gitlab.com/mayan-edms/mayan-edms/blob/master/HISTORY.rst', 'https://gitlab.com/mayan-edms/mayan-edms/issues/496'} | null |
PyPI | PYSEC-2021-864 | null | The AWS IoT Device SDK v2 for Java, Python, C++ and Node.js appends a user supplied Certificate Authority (CA) to the root CAs instead of overriding it on macOS systems. Additionally, SNI validation is also not enabled when the CA has been “overridden”. TLS handshakes will thus succeed if the peer can be verified either from the user-supplied CA or the system’s default trust-store. Attackers with access to a host’s trust stores or are able to compromise a certificate authority already in the host's trust store (note: the attacker must also be able to spoof DNS in this case) may be able to use this issue to bypass CA pinning. An attacker could then spoof the MQTT broker, and either drop traffic and/or respond with the attacker's data, but they would not be able to forward this data on to the MQTT broker because the attacker would still need the user's private keys to authenticate against the MQTT broker. The 'aws_tls_ctx_options_override_default_trust_store_*' function within the aws-c-io submodule has been updated to address this behavior. This issue affects: Amazon Web Services AWS IoT Device SDK v2 for Java versions prior to 1.5.0 on macOS. Amazon Web Services AWS IoT Device SDK v2 for Python versions prior to 1.7.0 on macOS. Amazon Web Services AWS IoT Device SDK v2 for C++ versions prior to 1.14.0 on macOS. Amazon Web Services AWS IoT Device SDK v2 for Node.js versions prior to 1.6.0 on macOS. Amazon Web Services AWS-C-IO 0.10.7 on macOS. | {'CVE-2021-40831', 'GHSA-j3f7-7rmc-6wqj'} | 2022-01-05T02:16:12.554921Z | 2021-11-23T00:15:00Z | null | null | null | {'https://github.com/aws/aws-iot-device-sdk-java-v2', 'https://github.com/advisories/GHSA-j3f7-7rmc-6wqj', 'https://github.com/aws/aws-iot-device-sdk-python-v2', '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/'} | null |
PyPI | PYSEC-2019-121 | null | slixmpp version before commit 7cd73b594e8122dddf847953fcfc85ab4d316416 contains an incorrect Access Control vulnerability in XEP-0223 plugin (Persistent Storage of Private Data via PubSub) options profile, used for the configuration of default access model that can result in all of the contacts of the victim can see private data having been published to a PEP node. This attack appears to be exploitable if the user of this library publishes any private data on PEP, the node isn't configured to be private. This vulnerability appears to have been fixed in commit 7cd73b594e8122dddf847953fcfc85ab4d316416 which is included in slixmpp 1.4.2. | {'CVE-2019-1000021'} | 2020-08-24T17:37:00Z | 2019-02-04T21:29:00Z | null | null | null | {'https://xmpp.org/extensions/xep-0223.html#howitworks', 'https://lab.louiz.org/poezio/slixmpp/commit/7cd73b594e8122dddf847953fcfc85ab4d316416', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WIBP4LD2V4TBJSLZXDUAGQMD6CUI2TZR/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GKBXN7EAAR7ENEZUBKV6C6MP6QBXYTWT/'} | null |
PyPI | GHSA-wq6x-g685-w5f2 | Improper Restriction of XML External Entity Reference in Plone | Plone before 5.2.3 allows XXE attacks via a feature that is explicitly only available to the Manager role. | {'CVE-2020-28734'} | 2022-03-03T05:13:56.089720Z | 2021-04-07T21:13:00Z | HIGH | null | {'CWE-611'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-28734', 'https://github.com/plone/Products.CMFPlone/issues/3209', 'https://dist.plone.org/release/5.2.3/RELEASE-NOTES.txt', 'https://www.misakikata.com/codes/plone/python-en.html'} | null |
PyPI | PYSEC-2022-41 | null | OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. In affected versions The path parameter of the requested URL is not sanitized before being passed to the QT frontend. This path is used in all components for displaying the server access history. This leads to a rendered HTML4 Subset (QT RichText editor) in the Onionshare frontend. | {'CVE-2022-21690', 'GHSA-ch22-x2v3-v6vq'} | 2022-03-09T00:16:43.171379Z | 2022-01-18T23:15:00Z | null | null | null | {'https://github.com/onionshare/onionshare/security/advisories/GHSA-ch22-x2v3-v6vq', 'https://github.com/onionshare/onionshare/releases/tag/v2.5'} | null |
PyPI | PYSEC-2021-472 | 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.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version. | {'CVE-2021-29544', 'GHSA-6g85-3hm8-83f9'} | 2021-12-09T06:34:50.195889Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6g85-3hm8-83f9', 'https://github.com/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b'} | null |
PyPI | PYSEC-2021-188 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixTriangularSolve`(https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails. 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-2021-29551', 'GHSA-vqw6-72r7-fgw7'} | 2021-08-27T03:22:30.499582Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7'} | null |
PyPI | GHSA-f85h-23mf-2fwh | Argument Injection in Ansible | A flaw was found in Ansible Engine when the module package or service is used and the parameter 'use' is not specified. If a previous task is executed with a malicious user, the module sent can be selected by the attacker using the ansible facts file. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1738'} | 2022-03-03T05:13:23.343313Z | 2022-02-09T22:00:04Z | MODERATE | null | {'CWE-88'} | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1738', 'https://github.com/ansible/ansible', 'https://github.com/ansible/ansible/issues/67796', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1738', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | GHSA-p43w-g3c5-g5mq | Out of bounds read in Pillow | An issue was discovered in Pillow before 8.1.1. There is an out-of-bounds read in SGIRleDecode.c. | {'CVE-2021-25293'} | 2022-03-03T05:13:17.214711Z | 2021-03-29T16:35:27Z | HIGH | null | {'CWE-125'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow', 'https://github.com/python-pillow/Pillow/commit/4853e522bddbec66022c0915b9a56255d0188bf9', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25293'} | null |
PyPI | PYSEC-2019-208 | null | Google TensorFlow 1.7 and below is affected by: Buffer Overflow. The impact is: execute arbitrary code (local). | {'CVE-2018-8825', 'GHSA-frxx-2m33-6wcr'} | 2021-08-27T03:22:22.407658Z | 2019-04-23T21:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-frxx-2m33-6wcr', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-003.md'} | null |
PyPI | PYSEC-2017-26 | null | Python package pysaml2 version 4.4.0 and earlier reuses the initialization vector across encryptions in the IDP server, resulting in weak encryption of data. | {'CVE-2017-1000246', 'GHSA-cq94-qf6q-mf2h'} | 2021-07-05T00:01:25.184392Z | 2017-11-17T04:29:00Z | null | null | null | {'https://github.com/rohe/pysaml2/issues/417', 'https://github.com/advisories/GHSA-cq94-qf6q-mf2h'} | null |
PyPI | GHSA-v988-828w-xvf2 | Authentication Bypass Using an Alternate Path or Channel and Authentication Bypass by Primary Weakness in rucio-webui | ### Impact
`rucio-webui` installations of the `1.26` release line potentially leak the contents of cookies to other sessions within a wsgi container. Impact is that Rucio authentication tokens are leaked to other users accessing the `webui` within a close timeframe, thus allowing users to access the `webui` with the leaked authentication token. Privileges are therefore also escalated.
Rucio server / daemons are not affected by this issue, it is isolated to the webui.
### Patches
This issue is fixed in the `1.26.7` release of the `rucio-webui`.
### Workarounds
Installation of the `1.25.7` `webui` release. The `1.25` and previous webui release lines are not affected by this issue.
### References
https://github.com/rucio/rucio/issues/4928 | null | 2022-03-03T05:14:09.638497Z | 2021-10-22T16:21:07Z | HIGH | null | {'CWE-305', 'CWE-288'} | {'https://github.com/rucio/rucio/releases/tag/1.26.7', 'https://github.com/rucio/rucio', 'https://github.com/rucio/rucio/issues/4810', 'https://github.com/rucio/rucio/issues/4928', 'https://github.com/rucio/rucio/security/advisories/GHSA-v988-828w-xvf2'} | null |
PyPI | GHSA-cmc7-mfmr-xqrx | Logic error in authentication in proxy.py | before_upstream_connection in AuthPlugin in http/proxy/auth.py in proxy.py before 2.3.1 accepts incorrect Proxy-Authorization header data because of a boolean confusion (and versus or). | {'CVE-2021-3116'} | 2022-03-03T05:14:17.833004Z | 2021-04-07T21:01:25Z | HIGH | null | {'CWE-480', 'CWE-287'} | {'https://cardaci.xyz/advisories/2021/01/10/proxy.py-2.3.0-broken-basic-authentication/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-3116', 'https://github.com/abhinavsingh/proxy.py/pull/482/commits/9b00093288237f5073c403f2c4f62acfdfa8ed46', 'https://pypi.org/project/proxy.py/2.3.1/#history'} | null |
PyPI | OSV-2021-955 | Stack-buffer-overflow in Buffer_AppendIndentUnchecked | OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=36009
```
Crash type: Stack-buffer-overflow WRITE 1
Crash state:
Buffer_AppendIndentUnchecked
encode
encode
```
| null | 2022-04-13T03:26:07.069166Z | 2021-07-11T00:01:05.153778Z | HIGH | null | null | {'https://github.com/ultrajson/ultrajson/commit/5525f8c9ef8bb879dadd0eb942d524827d1b0362', 'https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=36009'} | {'https://github.com/ultrajson/ultrajson/commit/a920bfa9d85bcd78836b866d1be80c1e3dcca1da'} |
PyPI | GHSA-q8qj-fc9q-cphr | Undefined behavior in Tensorflow | ### Impact
If a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition.
However, this `status` argument is not properly checked:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L265-L267
Hence, code following these methods will bind references to null pointers:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L279-L285
This is undefined behavior and reported as an error if compiling with `-fsanitize=null`.
### Patches
We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.
### 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 discovered during variant analysis of [GHSA-rjjg-hgv6-h69v](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v). | {'CVE-2020-15191'} | 2021-08-26T15:10:50Z | 2020-09-25T18:28:25Z | MODERATE | null | {'CWE-20', 'CWE-252', 'CWE-476'} | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15191', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-gcx2-gvj7-pxv3 | Insufficient Protection against HTTP Request Smuggling in mitmproxy | ### Impact
In mitmproxy 7.0.4 and below, a malicious client or server is able to perform [HTTP request smuggling](https://en.wikipedia.org/wiki/HTTP_request_smuggling) attacks through mitmproxy. This means that a malicious client/server could smuggle a request/response through mitmproxy as part of another request/response's HTTP message body. While mitmproxy would only see one request, the target server would see multiple requests. A smuggled request is still captured as part of another request's body, but it does not appear in the request list and does not go through the usual mitmproxy event hooks, where users may have implemented custom access control checks or input sanitization.
Unless you use mitmproxy to protect an HTTP/1 service, no action is required.
### Patches
The vulnerability has been fixed in mitmproxy 8.0.0 and above.
### Acknowledgements
We thank Zeyu Zhang (@zeyu2001) for responsibly disclosing this vulnerability to the mitmproxy team.
### Timeline
- **2022-03-15**: Received initial report.
- **2022-03-15**: Verified report and confirmed receipt.
- **2022-03-16**: Shared patch with researcher.
- **2022-03-16**: Received confirmation that patch is working.
- **2022-03-19**: Published patched release and advisory. | {'CVE-2022-24766'} | 2022-03-22T19:31:57.202873Z | 2022-03-22T19:22:59Z | CRITICAL | null | {'CWE-444'} | {'https://github.com/mitmproxy/mitmproxy', 'https://mitmproxy.org/posts/releases/mitmproxy8/', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24766', 'https://github.com/mitmproxy/mitmproxy/security/advisories/GHSA-gcx2-gvj7-pxv3', 'https://github.com/mitmproxy/mitmproxy/commit/b06fb6d157087d526bd02e7aadbe37c56865c71b'} | null |
PyPI | GHSA-3gqj-cmxr-p4x2 | Forced Browsing in Twisted | Twisted before 16.3.1 does not attempt to address RFC 3875 section 4.1.18 namespace conflicts and therefore does not protect CGI applications from the presence of untrusted client data in the HTTP_PROXY environment variable, which might allow remote attackers to redirect a CGI application's outbound HTTP traffic to an arbitrary proxy server via a crafted Proxy header in an HTTP request, aka an "httpoxy" issue. | {'CVE-2016-1000111'} | 2022-03-03T05:12:09.887491Z | 2021-04-30T17:32:28Z | MODERATE | null | {'CWE-425'} | {'https://twistedmatrix.com/trac/ticket/8623', 'http://www.oracle.com/technetwork/topics/security/linuxbulletinoct2016-3090545.html', 'https://twistedmatrix.com/pipermail/twisted-web/2016-August/005268.html', 'https://nvd.nist.gov/vuln/detail/CVE-2016-1000111', 'https://www.openwall.com/lists/oss-security/2016/07/18/6'} | null |
PyPI | PYSEC-2021-51 | null | An issue was discovered in through SaltStack Salt before 3002.5. The salt.wheel.pillar_roots.write method is vulnerable to directory traversal. | {'CVE-2021-25282'} | 2021-04-01T17:15:00Z | 2021-02-27T05:15:00Z | null | null | null | {'https://github.com/saltstack/salt/releases', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YOGNT2XWPOYV7YT75DN7PS4GIYWFKOK5/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FUGLOJ6NXLCIFRD2JTXBYQEMAEF2B6XH/', 'https://saltproject.io/security_announcements/active-saltstack-cve-release-2021-feb-25/', 'http://packetstormsecurity.com/files/162058/SaltStack-Salt-API-Unauthenticated-Remote-Command-Execution.html', 'https://security.gentoo.org/glsa/202103-01', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7GRVZ5WAEI3XFN2BDTL6DDXFS5HYSDVB/'} | null |
PyPI | GHSA-7p79-6x2v-5h88 | Server crash if running Python 3.10 w/ Sanic 20.12 | **!!! ONLY APPLIES TO VERSIONS PRIOR TO Sanic v20.12 WHEN USING Python 3.10 !!!**
Sanic v20.12 officially supports Python versions 3.6, 3.7, 3.8, and 3.9. However, if you accidentally run it with version 3.10 (**which is not supported by Sanic 20.12**), your server is prone to crashing on an incoming web request.
### Impact
Anyone running Sanic server between 0.1.7 and 20.12 **using Python 3.10**.
### Patches
[Sanic v20.12.6](https://github.com/sanic-org/sanic/releases/tag/v20.12.6)
### Workarounds
Use a supported version of Python (v3.6 - v3.9)
### References
> In [asyncio](https://docs.python.org/3/library/asyncio.html#module-asyncio), the explicit passing of a loop argument has been deprecated and will be removed in version 3.10 for the following: ... [asyncio.Event](https://docs.python.org/3/library/asyncio-sync.html#asyncio.Event)
[Python 3.8 Release Notes](https://docs.python.org/3/whatsnew/3.8.html#deprecated)
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [the community forums](https://community.sanicframework.org/)
* Ping us on [the Discord server](https://discord.gg/FARQzAEMAA)
| null | 2022-03-03T05:13:35.921150Z | 2022-02-16T22:57:57Z | HIGH | null | null | {'https://github.com/sanic-org/sanic/security/advisories/GHSA-7p79-6x2v-5h88', 'https://github.com/sanic-org/sanic/releases/tag/v20.12.6', 'https://github.com/sanic-org/sanic'} | null |
PyPI | PYSEC-2014-8 | null | The default configuration for bccache.FileSystemBytecodeCache in Jinja2 before 2.7.2 does not properly create temporary files, which allows local users to gain privileges via a crafted .cache file with a name starting with __jinja2_ in /tmp. | {'CVE-2014-1402'} | 2021-07-05T00:01:22.043149Z | 2014-05-19T14:55:00Z | null | null | null | {'http://www.gentoo.org/security/en/glsa/glsa-201408-13.xml', 'http://advisories.mageia.org/MGASA-2014-0028.html', 'http://secunia.com/advisories/60738', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=734747', 'http://secunia.com/advisories/56287', 'http://rhn.redhat.com/errata/RHSA-2014-0748.html', 'http://secunia.com/advisories/59017', 'http://secunia.com/advisories/58918', 'http://openwall.com/lists/oss-security/2014/01/10/3', 'http://rhn.redhat.com/errata/RHSA-2014-0747.html', 'http://www.mandriva.com/security/advisories?name=MDVSA-2014:096', 'https://bugzilla.redhat.com/show_bug.cgi?id=1051421', 'http://secunia.com/advisories/58783', 'http://secunia.com/advisories/60770', 'https://oss.oracle.com/pipermail/el-errata/2014-June/004192.html', 'http://openwall.com/lists/oss-security/2014/01/10/2', 'http://jinja.pocoo.org/docs/changelog/'} | null |
PyPI | GHSA-8phj-f9w2-cjcc | Arbitrary file reading vulnerability in Aim | ### Impact
A path traversal attack aims to access files and directories that are stored outside the web root folder. By manipulating variables that reference files with “dot-dot-slash (../)” sequences and its variations or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system including application source code or configuration and critical system files.
Vulnerable code: https://github.com/aimhubio/aim/blob/0b99c6ca08e0ba7e7011453a2f68033e9b1d1bce/aim/web/api/views.py#L9-L16
### Patches
The vulnerability issue is resolved in Aim v3.1.0.
### References
https://owasp.org/www-community/attacks/Path_Traversal
| {'CVE-2021-43775'} | 2022-03-03T05:12:59.139597Z | 2021-11-23T22:03:23Z | HIGH | null | {'CWE-22'} | {'https://github.com/aimhubio/aim/issues/999', 'https://github.com/aimhubio/aim', 'https://github.com/aimhubio/aim/pull/1003/commits/f01266a1a479ef11d7d6c539e7dd89e9d5639738', 'https://github.com/aimhubio/aim/blob/0b99c6ca08e0ba7e7011453a2f68033e9b1d1bce/aim/web/api/views.py#L9-L16', 'https://github.com/aimhubio/aim/pull/1003', 'https://github.com/aimhubio/aim/security/advisories/GHSA-8phj-f9w2-cjcc', 'https://nvd.nist.gov/vuln/detail/CVE-2021-43775'} | null |
PyPI | GHSA-x38q-xg2h-rxgx | Regular Expression Denial of Service in Leo Editor | Leo Editor v6.2.1 was discovered to contain a regular expression denial of service (ReDoS) vulnerability in the component plugins/importers/dart.py. | {'CVE-2020-23478'} | 2022-03-03T05:13:26.692060Z | 2021-09-23T23:14:28Z | HIGH | null | {'CWE-697'} | {'https://github.com/leo-editor/leo-editor/', 'https://github.com/leo-editor/leo-editor/issues/1597', 'https://nvd.nist.gov/vuln/detail/CVE-2020-23478'} | null |
PyPI | GHSA-43q8-3fv7-pr5x | Improper Validation of Integrity Check Value in TensorFlow | ### Impact
The implementation of [`tf.sparse.split`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_split_op.cc#L26-L102) does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read:
```python
import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = [1, 2]
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x,3, axis=axis)
```
The code assumes `axis` is a scalar. This is another instance of [TFSA-2021-190](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-190.md) (CVE-2021-41206).
### Patches
We have patched the issue in GitHub commit [61bf91e768173b001d56923600b40d9a95a04ad5](https://github.com/tensorflow/tensorflow/commit/61bf91e768173b001d56923600b40d9a95a04ad5) (merging [#53695](https://github.com/tensorflow/tensorflow/pull/53695)).
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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/53660). | null | 2022-03-03T05:11:25.282486Z | 2022-02-09T23:37:55Z | HIGH | null | {'CWE-354'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69', 'https://github.com/tensorflow/tensorflow/pull/53695', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-43q8-3fv7-pr5x', 'https://github.com/tensorflow/tensorflow/commit/61bf91e768173b001d56923600b40d9a95a04ad5'} | null |
PyPI | PYSEC-2018-81 | null | In ansible it was found that inventory variables are loaded from current working directory when running ad-hoc command which are under attacker's control, allowing to run arbitrary code as a result. | {'CVE-2018-10874'} | 2021-11-11T23:46:36.679476Z | 2018-07-02T13:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2019:0054', 'https://access.redhat.com/errata/RHSA-2018:2152', 'https://access.redhat.com/errata/RHSA-2018:2585', 'http://www.securitytracker.com/id/1041396', 'https://access.redhat.com/errata/RHSA-2018:2166', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10874', 'https://usn.ubuntu.com/4072-1/', 'https://access.redhat.com/errata/RHSA-2018:2321', 'https://access.redhat.com/errata/RHSA-2018:2150', 'https://access.redhat.com/errata/RHBA-2018:3788', 'https://access.redhat.com/errata/RHSA-2018:2151'} | null |
PyPI | PYSEC-2021-409 | null | TensorFlow is an open source platform for machine learning. In affected versions the process of building the control flow graph for a TensorFlow model is vulnerable to a null pointer exception when nodes that should be paired are not. This occurs because the code assumes that the first node in the pairing (e.g., an `Enter` node) always exists when encountering the second node (e.g., an `Exit` node). When this is not the case, `parent` is `nullptr` so dereferencing it causes a crash. 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-2021-41217', 'GHSA-5crj-c72x-m7gq'} | 2021-11-13T06:52:44.799831Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/05cbebd3c6bb8f517a158b0155debb8df79017ff', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5crj-c72x-m7gq'} | null |
PyPI | PYSEC-2022-115 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseTensorSliceDataset` has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value. The 3 input arguments to `SparseTensorSliceDataset` represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. 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-pfjj-m3jj-9jc9', 'CVE-2022-21736'} | 2022-03-09T00:18:24.478314Z | 2022-02-03T12:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9'} | null |
PyPI | GHSA-cvhw-2593-5j2q | Double Free in OpenCV | OpenCV 3.0.0 has a double free issue that allows attackers to execute arbitrary code. This issue was fixed in OpenCV version 3.3.1 (corresponding to OpenCV-Python and and OpenCV-Contrib-Python 3.3.1.11). | {'CVE-2016-1516'} | 2022-03-03T05:13:49.555711Z | 2021-10-12T22:00:08Z | HIGH | null | {'CWE-415'} | {'https://arxiv.org/pdf/1701.04739.pdf', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://nvd.nist.gov/vuln/detail/CVE-2016-1516', 'https://github.com/opencv/opencv/issues/5956', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | GHSA-8jxq-75rw-fhj9 | Eve allows execution of arbitrary code via Code Injection in the where parameter | io/mongo/parser.py in Eve (aka pyeve) before 0.7.5 allows remote attackers to execute arbitrary code via Code Injection in the where parameter. | {'CVE-2018-8097'} | 2022-04-26T18:17:13.379436Z | 2018-07-12T20:29:35Z | CRITICAL | null | {'CWE-94'} | {'https://github.com/pyeve/eve/issues/1101', 'https://github.com/advisories/GHSA-8jxq-75rw-fhj9', 'https://github.com/pyeve/eve/commit/f8f7019ffdf9b4e05faf95e1f04e204aa4c91f98', 'https://nvd.nist.gov/vuln/detail/CVE-2018-8097', 'https://github.com/pyeve/eve'} | null |
PyPI | GHSA-9988-f88m-mr42 | Exposure of Sensitive Information to an Unauthorized Actor in FreeTAKServer-UI | FreeTAKServer-UI v1.9.8 was discovered to leak sensitive API and Websocket keys. | {'CVE-2022-25512'} | 2022-03-28T22:46:57.936516Z | 2022-03-12T00:00:37Z | HIGH | null | {'CWE-200'} | {'https://github.com/FreeTAKTeam/UI/issues/26', 'https://github.com/FreeTAKTeam/UI', 'https://nvd.nist.gov/vuln/detail/CVE-2022-25512'} | null |
PyPI | GHSA-3p3h-qghp-hvh2 | Open Redirect in werkzeug | Open redirect vulnerability in werkzeug before 0.11.6 via a double slash in the URL. | {'CVE-2020-28724'} | 2022-03-03T05:13:09.831117Z | 2021-04-20T16:30:26Z | MODERATE | null | {'CWE-601'} | {'https://github.com/pallets/werkzeug/pull/890/files', 'https://nvd.nist.gov/vuln/detail/CVE-2020-28724', 'https://github.com/pallets/werkzeug/issues/822', 'https://github.com/pallets/flask/issues/1639'} | null |
PyPI | GHSA-xqvg-xm9m-p2c4 | Moderate severity vulnerability that affects mailman | An issue was discovered in GNU Mailman before 2.1.28. A crafted URL can cause arbitrary text to be displayed on a web page from a trusted site. | {'CVE-2018-13796'} | 2022-03-03T05:13:56.938383Z | 2018-09-11T18:57:16Z | MODERATE | null | {'CWE-20'} | {'https://usn.ubuntu.com/4348-1/', 'https://nvd.nist.gov/vuln/detail/CVE-2018-13796', 'https://github.com/advisories/GHSA-xqvg-xm9m-p2c4', 'https://bugs.launchpad.net/mailman/+bug/1780874', 'https://www.mail-archive.com/mailman-users@python.org/msg71003.html', 'https://security.gentoo.org/glsa/201904-10', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00034.html'} | null |
PyPI | PYSEC-2021-235 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SVDF` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/7f283ff806b2031f407db64c4d3edcda8fb9f9f5/tensorflow/lite/kernels/svdf.cc#L99-L102). An attacker can craft a model such that `params->rank` 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-2021-29598', 'GHSA-pmpr-55fj-r229'} | 2021-08-27T03:22:38.832523Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pmpr-55fj-r229', 'https://github.com/tensorflow/tensorflow/commit/6841e522a3e7d48706a02e8819836e809f738682'} | null |
PyPI | GHSA-rww7-2gpw-fv6j | Crash when type cannot be specialized in Tensorflow | ### Impact
Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174):
```cc
void InferenceContext::PreInputInit(
const OpDef& op_def, const std::vector<const Tensor*>& input_tensors,
const std::vector<ShapeHandle>& input_tensors_as_shapes) {
const auto ret = full_type::SpecializeType(attrs_, op_def);
DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status();
ret_types_ = ret.ValueOrDie();
// ...
}
```
However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure.
### Patches
We have patched the issue in GitHub commit [cb164786dc891ea11d3a900e90367c339305dc7b](https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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. | {'CVE-2022-23572'} | 2022-03-03T05:13:19.339539Z | 2022-02-09T23:28:29Z | MODERATE | null | {'CWE-754'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23572', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j', 'https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-665 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument. | {'GHSA-g4h2-gqm3-c9wq', 'CVE-2021-29539'} | 2021-12-09T06:35:21.512777Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g4h2-gqm3-c9wq', 'https://github.com/tensorflow/tensorflow/commit/4f663d4b8f0bec1b48da6fa091a7d29609980fa4'} | null |
PyPI | PYSEC-2020-235 | null | python-markdown2 before 1.0.1.14 has multiple cross-site scripting (XSS) issues. | {'SNYK-PYTHON-PYRAD-40000', 'CVE-2009-3724'} | 2021-08-27T03:22:06.220553Z | 2020-01-15T21:15:00Z | null | null | null | {'https://snyk.io/vuln/SNYK-PYTHON-PYRAD-40000', 'https://www.openwall.com/lists/oss-security/2009/10/29/5'} | null |
PyPI | PYSEC-2021-370 | null | Zope is an open-source web application server. Zope versions prior to versions 4.6.3 and 5.3 have a remote code execution security issue. In order to be affected, one must use Python 3 for one's Zope deployment, run Zope 4 below version 4.6.3 or Zope 5 below version 5.3, and have the optional `Products.PythonScripts` add-on package installed. By default, one must 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 are at risk. Zope releases 4.6.3 and 5.3 are not vulnerable. As a workaround, 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. | {'GHSA-g4gq-j4p2-j8fr', 'CVE-2021-32811', 'GHSA-qcx9-j53g-ccgf'} | 2021-10-12T02:55:32.357329Z | 2021-08-02T22:15:00Z | null | null | null | {'https://github.com/zopefoundation/Zope/security/advisories/GHSA-g4gq-j4p2-j8fr', 'https://github.com/zopefoundation/Zope/commit/f72a18dda8e9bf2aedb46168761668464a4be988', 'https://github.com/zopefoundation/AccessControl/security/advisories/GHSA-qcx9-j53g-ccgf'} | null |
PyPI | PYSEC-2011-23 | null | virtualenv.py in virtualenv before 1.5 allows local users to overwrite arbitrary files via a symlink attack on a certain file in /tmp/. | {'CVE-2011-4617'} | 2021-08-27T03:22:49.873439Z | 2011-12-31T01:55:00Z | null | null | null | {'http://secunia.com/advisories/47240', 'https://bitbucket.org/ianb/virtualenv/changeset/8be37c509fe5', 'http://lists.fedoraproject.org/pipermail/package-announce/2012-January/071638.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2012-January/071643.html', 'http://openwall.com/lists/oss-security/2011/12/19/2', 'http://openwall.com/lists/oss-security/2011/12/19/4', 'http://openwall.com/lists/oss-security/2011/12/19/5'} | null |
PyPI | PYSEC-2021-720 | null | TensorFlow is an end-to-end open source platform for machine learning. TFLite's convolution code(https://github.com/tensorflow/tensorflow/blob/09c73bca7d648e961dd05898292d91a8322a9d45/tensorflow/lite/kernels/conv.cc) has multiple division where the divisor is controlled by the user and not checked to be non-zero. 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-2021-29594', 'GHSA-3qgw-p4fm-x7gf'} | 2021-12-09T06:35:31.088691Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qgw-p4fm-x7gf', 'https://github.com/tensorflow/tensorflow/commit/ff489d95a9006be080ad14feb378f2b4dac35552'} | null |
PyPI | GHSA-xjjg-vmw6-c2p9 | Open Redirect in httpie | All versions of the HTTPie package prior to version 1.0.3 are vulnerable to Open Redirect that allows an attacker to write an arbitrary file with supplied filename and content to the current directory, by redirecting a request from HTTP to a crafted URL pointing to a server in his or hers control. | {'CVE-2019-10751'} | 2022-03-03T05:14:13.641213Z | 2019-08-27T17:44:33Z | HIGH | null | {'CWE-601'} | {'https://snyk.io/vuln/SNYK-PYTHON-HTTPIE-460107', 'https://nvd.nist.gov/vuln/detail/CVE-2019-10751'} | null |
PyPI | PYSEC-2022-142 | null | Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. 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-8r7c-3cm2-3h8f', 'CVE-2022-23578'} | 2022-03-09T00:18:28.101919Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8r7c-3cm2-3h8f', 'https://github.com/tensorflow/tensorflow/commit/c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/common_runtime/immutable_executor_state.cc#L84-L262'} | null |
PyPI | GHSA-wcv5-qrj6-9pfm | Heap buffer overflow in `Conv3DBackprop*` | ### Impact
Missing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows:
```python
import tensorflow as tf
input_sizes = tf.constant([1, 1, 1, 1, 2], shape=[5], dtype=tf.int32)
filter_tensor = tf.constant([734.6274508233133, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,
-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,
-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[4, 1, 6, 1, 1], dtype=tf.float32)
out_backprop = tf.constant([-10.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
tf.raw_ops.Conv3DBackpropInputV2(input_sizes=input_sizes, filter=filter_tensor, out_backprop=out_backprop, strides=[1, 89, 29, 89, 1], padding='SAME', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
```
```python
import tensorflow as tf
input_values = [-10.0] * (7 * 7 * 7 * 7 * 7)
input_values[0] = 429.6491056791816
input_sizes = tf.constant(input_values, shape=[7, 7, 7, 7, 7], dtype=tf.float32)
filter_tensor = tf.constant([7, 7, 7, 1, 1], shape=[5], dtype=tf.int32)
out_backprop = tf.constant([-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[7, 1, 1, 1, 1], dtype=tf.float32)
tf.raw_ops.Conv3DBackpropFilterV2(input=input_sizes, filter_sizes=filter_tensor, out_backprop=out_backprop, strides=[1, 37, 65, 93, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
```
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.
### Patches
We have patched the issue in GitHub commit [8f37b52e1320d8d72a9529b2468277791a261197](https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197).
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 securityguide](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 and Ying Wang of Baidu X-Team. | {'CVE-2021-29520'} | 2022-04-26T18:16:56.604479Z | 2021-05-21T14:21:12Z | LOW | null | {'CWE-120', 'CWE-787'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wcv5-qrj6-9pfm', 'https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29520'} | null |
PyPI | GHSA-49qr-xh3w-h436 | Moderate severity vulnerability that affects notebook | Jupyter Notebook before 5.7.1 allows XSS via an untrusted notebook because nbconvert responses are considered to have the same origin as the notebook server. In other words, nbconvert endpoints can execute JavaScript with access to the server API. In notebook/nbconvert/handlers.py, NbconvertFileHandler and NbconvertPostHandler do not set a Content Security Policy to prevent this. | {'CVE-2018-19351'} | 2022-03-03T05:14:13.270276Z | 2018-11-21T22:15:47Z | MODERATE | null | {'CWE-79'} | {'https://lists.debian.org/debian-lts-announce/2020/11/msg00033.html', 'https://nvd.nist.gov/vuln/detail/CVE-2018-19351', 'https://github.com/jupyter/notebook', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst', 'https://github.com/advisories/GHSA-49qr-xh3w-h436', 'https://github.com/jupyter/notebook/commit/107a89fce5f413fb5728c1c5d2c7788e1fb17491', 'https://pypi.org/project/notebook/#history', 'https://groups.google.com/forum/#!topic/jupyter/hWzu2BSsplY'} | null |
PyPI | PYSEC-2020-50 | null | The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. In Jupyter Server before version 1.1.1, an open redirect vulnerability could cause the jupyter server to redirect the browser to a different malicious website. All jupyter servers running without a base_url prefix are technically affected, however, these maliciously crafted links can only be reasonably made for known jupyter server hosts. A link to your jupyter server may *appear* safe, but ultimately redirect to a spoofed server on the public internet. This same vulnerability was patched in upstream notebook v5.7.8. This is fixed in jupyter_server 1.1.1. If upgrade is not available, a workaround can be to run your server on a url prefix: "jupyter server --ServerApp.base_url=/jupyter/". | {'CVE-2020-26275', 'GHSA-9f66-54xg-pc2c'} | 2021-03-30T19:15:00Z | 2020-12-21T18:15:00Z | null | null | null | {'https://advisory.checkmarx.net/advisory/CX-2020-4291', 'https://pypi.org/project/jupyter-server/', 'https://github.com/jupyter-server/jupyter_server/security/advisories/GHSA-9f66-54xg-pc2c', 'https://github.com/jupyter-server/jupyter_server/commit/85e4abccf6ea9321d29153f73b0bd72ccb3a6bca'} | null |
PyPI | GHSA-vjg4-v33c-ggc4 | Out of bounds read in Tensorflow | ### Impact
The [implementation of `FractionalAvgPoolGrad`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360) does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap:
```python
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.FractionalAvgPoolGrad(
orig_input_tensor_shape=[2,2,2,2],
out_backprop=[[[[1,2], [3, 4], [5, 6]], [[7, 8], [9,10], [11,12]]]],
row_pooling_sequence=[-10,1,2,3],
col_pooling_sequence=[1,2,3,4],
overlapping=True)
return y
test()
```
### Patches
We have patched the issue in GitHub commit [002408c3696b173863228223d535f9de72a101a9](https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9).
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-2022-21730'} | 2022-03-03T05:14:14.640464Z | 2022-02-09T18:29:45Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21730'} | null |
PyPI | GHSA-fvgf-6h6h-3322 | Improper Limitation of a Pathname to a Restricted Directory | In Django 2.2 before 2.2.18, 3.0 before 3.0.12, and 3.1 before 3.1.6, the django.utils.archive.extract method (used by "startapp --template" and "startproject --template") allows directory traversal via an archive with absolute paths or relative paths with dot segments. | {'CVE-2021-3281'} | 2022-03-03T05:12:27.394989Z | 2021-03-18T20:29:49Z | MODERATE | null | {'CWE-22'} | {'https://docs.djangoproject.com/en/3.1/releases/security/', 'https://groups.google.com/forum/#!forum/django-announce', 'https://docs.djangoproject.com/en/3.1/releases/3.0.12/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-3281', 'https://github.com/django/django/commit/05413afa8c18cdb978fcdf470e09f7a12b234a23', 'https://www.djangoproject.com/weblog/2021/feb/01/security-releases/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YF52FKEH5S2P5CM4X7IXSYG67YY2CDOO/', 'https://security.netapp.com/advisory/ntap-20210226-0004/'} | null |
PyPI | GHSA-8434-v7xw-8m9x | Improper Neutralization of Argument Delimiters in a Decompiling Package Process in APKLeaks | APKLeaks prior to v2.0.4 allows remote authenticated attackers to execute arbitrary OS commands via package name inside application manifest.
### Impact
An attacker could include arguments that allow unintended commands or code to be executed, allow sensitive data to be read or modified or could cause other unintended behavior through malicious package name.
### Patches
The problem is fixed in version v2.0.4 and above.
### Workarounds
```bash
> git fetch --tags; git checkout v2.0.6-dev
```
Or pull to the latest version:
```bash
> git pull origin master
```
### References
- a966e781499ff6fd4eea66876d7532301b13a382
### For more information
If you have any questions or comments about this advisory:
* Email me at [me@dw1.io](mailto:me@dw1.io)
| {'CVE-2021-21386'} | 2022-01-21T21:03:01Z | 2022-01-21T23:03:39Z | CRITICAL | null | {'CWE-78', 'CWE-88'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-21386', 'https://github.com/dwisiswant0/apkleaks', 'https://github.com/dwisiswant0/apkleaks/security/advisories/GHSA-8434-v7xw-8m9x', 'https://github.com/dwisiswant0/apkleaks/commit/a966e781499ff6fd4eea66876d7532301b13a382'} | null |
PyPI | GHSA-v6wp-4m6f-gcjg | Open redirect vulnerability in `aiohttp` (`normalize_path_middleware` middleware) | ### Impact
_What kind of vulnerability is it? Who is impacted?_
Open redirect vulnerability — a maliciously crafted link to an aiohttp-based web-server could redirect the browser to a different website.
It is caused by a bug in the `aiohttp.web_middlewares.normalize_path_middleware` middleware.
### Patches
_Has the problem been patched? What versions should users upgrade to?_
This security problem has been fixed in v3.7.4. Upgrade your dependency as follows:
[`pip install aiohttp >= 3.7.4`]
### Workarounds
_Is there a way for users to fix or remediate the vulnerability without upgrading?_
If upgrading is not an option for you, a workaround can be to avoid using `aiohttp.web_middlewares.normalize_path_middleware` in your applications.
### References
_Are there any links users can visit to find out more?_
* [aiohttp @ PyPI]
* [GHSA-v6wp-4m6f-gcjg]
* [OWASP page on open redirects]
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [aiohttp repo](https://github.com/aio-libs/aiohttp/issues/new/choose)
* Email us at wk+aio-libs-security@sydorenko.org.ua and/or andrew.svetlov+aio-libs-security@gmail.com
Credit: [Jelmer Vernooij] and [Beast Glatisant].
[aiohttp @ PyPI]: https://pypi.org/p/aiohttp
[`pip install aiohttp >= 3.7.4`]: https://pypi.org/project/aiohttp/3.7.4/
[GHSA-v6wp-4m6f-gcjg]: https://github.com/aio-libs/aiohttp/security/advisories/GHSA-v6wp-4m6f-gcjg
[OWASP page on open redirects]:
https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html
[Jelmer Vernooij]: https://jelmer.uk
[Beast Glatisant]: https://github.com/g147 | {'CVE-2021-21330'} | 2022-03-03T05:12:52.241808Z | 2021-02-26T02:11:57Z | LOW | null | {'CWE-601'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-21330', 'https://github.com/aio-libs/aiohttp/blob/master/CHANGES.rst#374-2021-02-25', 'https://github.com/aio-libs/aiohttp/security/advisories/GHSA-v6wp-4m6f-gcjg', 'https://pypi.org/project/aiohttp/', 'https://github.com/aio-libs/aiohttp/commit/2545222a3853e31ace15d87ae0e2effb7da0c96b', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JN3V7CZJRT4QFCVXB6LDPCJH7NAOFCA5/', 'https://www.debian.org/security/2021/dsa-4864', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FU7ENI54JNEK3PHEFGCE46DGMFNTVU6L/'} | null |
PyPI | PYSEC-2021-848 | null | Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. Sockeye uses YAML to store model and data configurations on disk. Versions below 2.3.24 use unsafe YAML loading, which can be made to execute arbitrary code embedded in config files. An attacker can add malicious code to the config file of a trained model and attempt to convince users to download and run it. If users run the model, the embedded code will run locally. The issue is fixed in version 2.3.24. | {'GHSA-ggmr-44cv-24pm', 'CVE-2021-43811'} | 2021-12-13T21:28:21.588606Z | 2021-12-08T23:15:00Z | null | null | null | {'https://github.com/awslabs/sockeye/releases/tag/2.3.24', 'https://github.com/awslabs/sockeye/security/advisories/GHSA-ggmr-44cv-24pm', 'https://github.com/awslabs/sockeye/pull/964'} | null |
PyPI | PYSEC-2018-39 | null | Ansible before versions 2.1.4, 2.2.1 is vulnerable to an improper input validation in Ansible's handling of data sent from client systems. An attacker with control over a client system being managed by Ansible and the ability to send facts back to the Ansible server could use this flaw to execute arbitrary code on the Ansible server using the Ansible server privileges. | {'CVE-2016-9587', 'GHSA-m956-frf4-m2wr'} | 2021-07-02T02:41:33.713953Z | 2018-04-24T16:29:00Z | null | null | null | {'http://rhn.redhat.com/errata/RHSA-2017-0195.html', 'https://security.gentoo.org/glsa/201701-77', 'http://rhn.redhat.com/errata/RHSA-2017-0260.html', 'https://access.redhat.com/errata/RHSA-2017:0448', 'https://access.redhat.com/errata/RHSA-2017:1685', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2016-9587', 'https://access.redhat.com/errata/RHSA-2017:0515', 'http://www.securityfocus.com/bid/95352', 'https://github.com/advisories/GHSA-m956-frf4-m2wr', 'https://www.exploit-db.com/exploits/41013/'} | null |
PyPI | PYSEC-2022-82 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. 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-2022-23573', 'GHSA-q85f-69q7-55h2'} | 2022-03-09T00:17:34.035553Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q85f-69q7-55h2', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143', 'https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b'} | null |
PyPI | GHSA-mfv8-q39f-mgfg | Cross-site Scripting in invenio-communities | ## Cross-Site Scripting (XSS) vulnerability in Jinja templates
### Impact
A Cross-Site Scripting (XSS) vulnerability was discovered in two Jinja templates in the Invenio-Communities module. The vulnerability allows a user to create a new community and include script element tags inside the description and page fields.
### Patches
The problem has been patched in v1.0.0a20.
### For more information
If you have any questions or comments about this advisory:
* Email us at [info@inveniosoftware.org](mailto:info@inveniosoftware.org) | {'CVE-2019-1020005'} | 2022-03-03T05:13:21.854822Z | 2019-07-16T00:52:26Z | MODERATE | null | {'CWE-79'} | {'https://github.com/inveniosoftware/invenio-communities/security/advisories/GHSA-mfv8-q39f-mgfg', 'https://github.com/advisories/GHSA-mfv8-q39f-mgfg', 'https://nvd.nist.gov/vuln/detail/CVE-2019-1020005'} | null |
PyPI | PYSEC-2016-27 | null | Mercurial before 3.7.3 allows remote attackers to execute arbitrary code via a crafted name when converting a Git repository. | {'CVE-2016-3069'} | 2021-08-27T03:22:06.881570Z | 2016-04-13T16:59:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00018.html', 'http://www.debian.org/security/2016/dsa-3542', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00016.html', 'https://selenic.com/repo/hg-stable/rev/b732e7f2aba4', 'http://www.oracle.com/technetwork/topics/security/linuxbulletinapr2016-2952096.html', 'https://security.gentoo.org/glsa/201612-19', 'http://rhn.redhat.com/errata/RHSA-2016-0706.html', 'https://selenic.com/repo/hg-stable/rev/ae279d4a19e9', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/181505.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/181542.html', 'https://selenic.com/repo/hg-stable/rev/cdda7b96afff', 'https://selenic.com/repo/hg-stable/rev/80cac1de6aea', 'http://www.oracle.com/technetwork/topics/security/bulletinapr2016-2952098.html', 'https://selenic.com/repo/hg-stable/rev/197eed39e3d5', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00017.html', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00043.html', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_3.7.3_.282016-3-29.29'} | null |
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