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-2018-22 | null | OpenKMIP PyKMIP version All versions before 0.8.0 contains a CWE 399: Resource Management Errors (similar issue to CVE-2015-5262) vulnerability in PyKMIP server that can result in DOS: the server can be made unavailable by one or more clients opening all of the available sockets. This attack appear to be exploitable via A client or clients open sockets with the server and then never close them. This vulnerability appears to have been fixed in 0.8.0. | {'GHSA-gfv6-cj92-g3hx', 'CVE-2018-1000872'} | 2021-06-10T06:50:52.184344Z | 2018-12-20T17:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-gfv6-cj92-g3hx', 'https://github.com/OpenKMIP/PyKMIP/issues/430'} | null |
PyPI | PYSEC-2021-150 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. 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. 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-452g-f7fp-9jf7', 'CVE-2021-29513'} | 2021-08-27T03:22:23.682962Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-452g-f7fp-9jf7'} | null |
PyPI | PYSEC-2021-500 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer. The implementation(https://github.com/tensorflow/tensorflow/blob/60a45c8b6192a4699f2e2709a2645a751d435cc3/tensorflow/core/kernels/sdca_internal.cc) does not validate that the user supplied arguments satisfy all constraints expected by the op(https://www.tensorflow.org/api_docs/python/tf/raw_ops/SdcaOptimizer). 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-5gqf-456p-4836', 'CVE-2021-29572'} | 2021-12-09T06:34:54.530775Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5gqf-456p-4836', 'https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb'} | null |
PyPI | PYSEC-2020-279 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `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. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'GHSA-x5cp-9pcf-pp3h', 'CVE-2020-15199'} | 2021-12-09T06:34:41.569566Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x5cp-9pcf-pp3h'} | null |
PyPI | GHSA-mfg7-x5m7-6p8w | NULL Pointer Dereference in Google TensorFlow | NULL pointer dereference in Google TensorFlow before 1.12.2 could cause a denial of service via an invalid GIF file. | {'CVE-2019-9635'} | 2022-03-03T05:13:06.548466Z | 2019-04-30T15:37:17Z | MODERATE | null | {'CWE-476'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-9635', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2019-001.md'} | null |
PyPI | PYSEC-2021-629 | null | TensorFlow is an open source platform for machine learning. In affected versions the async implementation of `CollectiveReduceV2` suffers from a memory leak and a use after free. This occurs due to the asynchronous computation and the fact that objects that have been `std::move()`d from are still accessed. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. | {'GHSA-gpfh-jvf9-7wg5', 'CVE-2021-41220'} | 2021-12-09T06:35:10.358368Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gpfh-jvf9-7wg5', 'https://github.com/tensorflow/tensorflow/commit/ca38dab9d3ee66c5de06f11af9a4b1200da5ef75'} | null |
PyPI | PYSEC-2021-66 | null | This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the `_punctuation_re regex` operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory. | {'CVE-2020-28493', 'SNYK-PYTHON-JINJA2-1012994', 'GHSA-g3rq-g295-4j3m'} | 2021-03-22T16:34:00Z | 2021-02-01T20:15:00Z | null | null | null | {'https://github.com/pallets/jinja/blob/ab81fd9c277900c85da0c322a2ff9d68a235b2e6/src/jinja2/utils.py%23L20', 'https://github.com/advisories/GHSA-g3rq-g295-4j3m', 'https://github.com/pallets/jinja/pull/1343', 'https://snyk.io/vuln/SNYK-PYTHON-JINJA2-1012994', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PVAKCOO7VBVUBM3Q6CBBTPBFNP5NDXF4/'} | null |
PyPI | PYSEC-2021-279 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37657', 'GHSA-5xwc-mrhx-5g3m'} | 2021-08-27T03:22:44.622008Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m', 'https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09'} | null |
PyPI | PYSEC-2021-783 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. 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-5hj3-vjjf-f5m7', 'CVE-2021-37672'} | 2021-12-09T06:35:38.609873Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a4e138660270e7599793fa438cd7b2fc2ce215a6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hj3-vjjf-f5m7'} | null |
PyPI | PYSEC-2021-296 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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-7ghq-fvr3-pj2x', 'CVE-2021-37674'} | 2021-08-27T03:22:46.211223Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7ghq-fvr3-pj2x', 'https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475'} | null |
PyPI | GHSA-c45w-2wxr-pp53 | Heap OOB read in `tf.raw_ops.Dequantize` | ### Impact
Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data:
```python
import tensorflow as tf
input_tensor=tf.constant(
[75, 75, 75, 75, -6, -9, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,\
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,\
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,\
-10, -10, -10, -10], shape=[5, 10], dtype=tf.int32)
input_tensor=tf.cast(input_tensor, dtype=tf.quint8)
min_range = tf.constant([-10], shape=[1], dtype=tf.float32)
max_range = tf.constant([24, 758, 758, 758, 758], shape=[5], dtype=tf.float32)
tf.raw_ops.Dequantize(
input=input_tensor, min_range=min_range, max_range=max_range, mode='SCALED',
narrow_range=True, axis=0, dtype=tf.dtypes.float32)
```
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:
```cc
if (num_slices == 1) {
const float min_range = input_min_tensor.flat<float>()(0);
const float max_range = input_max_tensor.flat<float>()(0);
DequantizeTensor(ctx, input, min_range, max_range, &float_output);
} else {
...
auto min_ranges = input_min_tensor.vec<float>();
auto max_ranges = input_max_tensor.vec<float>();
for (int i = 0; i < num_slices; ++i) {
DequantizeSlice(ctx->eigen_device<Device>(), ctx,
input_tensor.template chip<1>(i), min_ranges(i),
max_ranges(i), output_tensor.template chip<1>(i));
...
}
}
```
### Patches
We have patched the issue in GitHub commit [5899741d0421391ca878da47907b1452f06aaf1b](https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b).
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-2021-29582'} | 2022-03-03T05:12:52.909210Z | 2021-05-21T14:26:32Z | LOW | null | {'CWE-125'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29582', 'https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53'} | null |
PyPI | GHSA-w4vg-rf63-f3j3 | Arbitrary code using "crafted image file" approach affecting Pillow | Pillow before 3.3.2 allows context-dependent attackers to execute arbitrary code by using the "crafted image file" approach, related to an "Insecure Sign Extension" issue affecting the ImagingNew in Storage.c component. | {'CVE-2016-9190'} | 2022-04-26T18:17:06.543150Z | 2018-07-12T14:45:42Z | HIGH | null | {'CWE-284'} | {'https://github.com/python-pillow/Pillow/issues/2105', 'http://www.securityfocus.com/bid/94234', 'https://nvd.nist.gov/vuln/detail/CVE-2016-9190', 'http://pillow.readthedocs.io/en/3.4.x/releasenotes/3.3.2.html', 'https://security.gentoo.org/glsa/201612-52', 'https://github.com/python-pillow/Pillow', 'http://www.debian.org/security/2016/dsa-3710', 'https://github.com/python-pillow/Pillow/pull/2146/commits/5d8a0be45aad78c5a22c8d099118ee26ef8144af', 'https://github.com/advisories/GHSA-w4vg-rf63-f3j3'} | null |
PyPI | PYSEC-2021-89 | null | Datasette is an open source multi-tool for exploring and publishing data. The `?_trace=1` debugging feature in Datasette does not correctly escape generated HTML, resulting in a [reflected cross-site scripting](https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks) vulnerability. This vulnerability is particularly relevant if your Datasette installation includes authenticated features using plugins such as [datasette-auth-passwords](https://datasette.io/plugins/datasette-auth-passwords) as an attacker could use the vulnerability to access protected data. Datasette 0.57 and 0.56.1 both include patches for this issue. If you run Datasette behind a proxy you can workaround this issue by rejecting any incoming requests with `?_trace=` or `&_trace=` in their query string parameters. | {'GHSA-gff3-739c-gxfq', 'GHSA-xw7c-jx9m-xh5g', 'CVE-2021-32670'} | 2021-06-09T05:01:28.246179Z | 2021-06-07T22:15:00Z | null | null | null | {'https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks', 'https://github.com/simonw/datasette/security/advisories/GHSA-xw7c-jx9m-xh5g', 'https://github.com/advisories/GHSA-gff3-739c-gxfq', 'https://pypi.org/project/datasette/', 'https://datasette.io/plugins/datasette-auth-passwords', 'https://github.com/simonw/datasette/issues/1360'} | null |
PyPI | GHSA-vgmw-9cww-qq99 | Incorrect Authorization in calibreweb | calibreweb prior to version 0.6.16 contains an Incorrect Authorization vulnerability. | {'CVE-2022-0273'} | 2022-03-03T05:13:46.990224Z | 2022-01-31T00:00:29Z | MODERATE | null | {'CWE-863', 'CWE-284'} | {'https://github.com/janeczku/calibre-web', 'https://nvd.nist.gov/vuln/detail/CVE-2022-0273', 'https://huntr.dev/bounties/8f27686f-d698-4ab6-8ef0-899125792f13', 'https://github.com/janeczku/calibre-web/commit/0c0313f375bed7b035c8c0482bbb09599e16bfcf'} | null |
PyPI | PYSEC-2020-296 | null | In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. | {'GHSA-xwhf-g6j5-j5gc', 'CVE-2020-15266'} | 2021-12-09T06:34:44.028853Z | 2020-10-21T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/issues/42129', 'https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xwhf-g6j5-j5gc'} | null |
PyPI | GHSA-x7wf-5mjc-6x76 | SSRF attacks via tracebacks in Plone | Plone before 5.2.3 allows SSRF attacks via the tracebacks feature (only available to the Manager role). | {'CVE-2020-28735'} | 2022-03-03T05:12:37.868251Z | 2021-04-07T21:13:44Z | HIGH | null | {'CWE-918'} | {'https://github.com/plone/Products.CMFPlone/issues/3209', 'https://nvd.nist.gov/vuln/detail/CVE-2020-28735', 'https://www.misakikata.com/codes/plone/python-en.html', 'https://dist.plone.org/release/5.2.3/RELEASE-NOTES.txt'} | null |
PyPI | PYSEC-2017-11 | null | Cross-site request forgery (CSRF) vulnerability in django CMS before 3.0.14, 3.1.x before 3.1.1 allows remote attackers to manipulate privileged users into performing unknown actions via unspecified vectors. | {'CVE-2015-5081'} | 2021-07-05T00:01:17.665929Z | 2017-08-18T18:29:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2015/06/28/1', 'https://www.django-cms.org/en/blog/2015/06/27/311-3014-release/', 'https://github.com/divio/django-cms/commit/f77cbc607d6e2a62e63287d37ad320109a2cc78a'} | null |
PyPI | GHSA-3qgw-p4fm-x7gf | Division by zero in TFLite's convolution code | ### Impact
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. For example:
```cc
const int input_size = NumElements(input) / SizeOfDimension(input, 0);
```
### Patches
We have patched the issue in GitHub commit [ff489d95a9006be080ad14feb378f2b4dac35552](https://github.com/tensorflow/tensorflow/commit/ff489d95a9006be080ad14feb378f2b4dac35552).
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. | {'CVE-2021-29594'} | 2022-03-03T05:13:11.303735Z | 2021-05-21T14:27:45Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qgw-p4fm-x7gf', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29594', 'https://github.com/tensorflow/tensorflow/commit/ff489d95a9006be080ad14feb378f2b4dac35552'} | null |
PyPI | GHSA-6h52-4vmh-8x4f | Moderate severity vulnerability that affects feedparser | 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. | {'CVE-2011-1156'} | 2022-03-03T05:13:12.483440Z | 2018-07-23T19:50:33Z | MODERATE | null | null | {'https://nvd.nist.gov/vuln/detail/CVE-2011-1156', '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 | PYSEC-2022-60 | 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'} | 2022-03-09T00:17:31.305252Z | 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-5xvc-vgmp-jgc3 | Improper Access Control in jupyterhub-firstuseauthenticator | ### Impact
When JupyterHub is used with FirstUseAuthenticator, the vulnerability allows unauthorized access to any user's account if `create_users=True` and the username is known or guessed.
### Patches
Upgrade to jupyterhub-firstuseauthenticator to 1.0, or apply patch https://github.com/jupyterhub/firstuseauthenticator/pull/38.patch
### Workarounds
If you cannot upgrade, there is no complete workaround, but it can be mitigated.
If you cannot upgrade yet, you can disable user creation with `c.FirstUseAuthenticator.create_users = False`, which will only allow login with fully normalized usernames for already existing users prior to jupyterhub-firstuserauthenticator 1.0. If any users have never logged in with their normalized username (i.e. lowercase), they will still be vulnerable until you can patch or upgrade. | {'CVE-2021-41194'} | 2022-03-22T18:16:53.507087Z | 2021-10-28T23:13:57Z | CRITICAL | null | {'CWE-284'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41194', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/32b21898fb2b53b1a2e36270de6854ad70e9e9bf', 'https://github.com/jupyterhub/firstuseauthenticator', 'https://github.com/jupyterhub/firstuseauthenticator/security/advisories/GHSA-5xvc-vgmp-jgc3', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38.patch', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/9e200d974e0cb85d828a6afedb8ab90a37878f28'} | null |
PyPI | PYSEC-2021-453 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) does a division by a quantity that is controlled by the caller. 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-xm2v-8rrw-w9pm', 'CVE-2021-29525'} | 2021-12-09T06:34:47.241877Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xm2v-8rrw-w9pm', 'https://github.com/tensorflow/tensorflow/commit/2be2cdf3a123e231b16f766aa0e27d56b4606535'} | null |
PyPI | GHSA-3p4q-x8f3-p7vq | Moderate severity vulnerability that affects notebook | Jupyter Notebook before 5.7.2 allows XSS via a crafted directory name because notebook/static/tree/js/notebooklist.js handles certain URLs unsafely. | {'CVE-2018-19352'} | 2022-03-03T05:14:08.823743Z | 2018-11-21T22:19:22Z | MODERATE | null | {'CWE-79'} | {'https://github.com/advisories/GHSA-3p4q-x8f3-p7vq', 'https://github.com/jupyter/notebook', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst', 'https://pypi.org/project/notebook/#history', 'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648', 'https://nvd.nist.gov/vuln/detail/CVE-2018-19352'} | null |
PyPI | PYSEC-2018-100 | null | base/oi/doa.py in the Rope library in CPython (aka Python) allows remote attackers to execute arbitrary code by leveraging an unsafe call to pickle.load. | {'CVE-2014-3539', 'GHSA-r38r-qp28-2m63'} | 2021-08-27T03:22:19.565672Z | 2018-04-06T16:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=1116485', 'https://github.com/advisories/GHSA-r38r-qp28-2m63', 'http://www.openwall.com/lists/oss-security/2015/02/07/1'} | null |
PyPI | PYSEC-2014-17 | null | The parser cache functionality in parsergenerator.py in RPLY (aka python-rply) before 0.7.1 allows local users to spoof cache data by pre-creating a temporary rply-*.json file with a predictable name. | {'CVE-2014-1604'} | 2021-07-05T00:01:25.895879Z | 2014-01-28T00:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2014/01/18/4', 'http://secunia.com/advisories/56429', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=735263', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/90593', 'http://www.openwall.com/lists/oss-security/2014/01/17/8', 'http://www.osvdb.org/102202', 'https://github.com/alex/rply/commit/fc9bbcd25b0b4f09bbd6339f710ad24c129d5d7c'} | null |
PyPI | GHSA-pw4v-gr34-2553 | Denial of service (via resource exhaustion) due to improper input validation | ### Impact
Missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion.
### Patches
Fixed by 3175fd3.
### For more information
If you have any questions or comments about this advisory, email us at security@matrix.org. | {'CVE-2021-29433'} | 2022-03-03T05:14:01.787497Z | 2021-04-16T19:53:37Z | MODERATE | null | {'CWE-20', 'CWE-400'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29433', 'https://pypi.org/project/matrix-sydent/', 'https://github.com/matrix-org/sydent/commit/3175fd358ebc2c310eab7a3dbf296ce2bd54c1da', 'https://github.com/matrix-org/sydent/security/advisories/GHSA-pw4v-gr34-2553'} | null |
PyPI | PYSEC-2021-516 | null | TensorFlow is an end-to-end open source platform for machine learning. The optimized implementation of the `TransposeConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L5221-L5222). An attacker can craft a model such that `stride_{h,w}` values are 0. Code calling this function must validate these arguments. 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-vfr4-x8j2-3rf9', 'CVE-2021-29588'} | 2021-12-09T06:34:57.029977Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vfr4-x8j2-3rf9', 'https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d'} | null |
PyPI | PYSEC-2021-146 | null | All versions of package reportlab are vulnerable to Server-side Request Forgery (SSRF) via img tags. In order to reduce risk, use trustedSchemes & trustedHosts (see in Reportlab's documentation) Steps to reproduce by Karan Bamal: 1. Download and install the latest package of reportlab 2. Go to demos -> odyssey -> dodyssey 3. In the text file odyssey.txt that needs to be converted to pdf inject <img src="http://127.0.0.1:5000" valign="top"/> 4. Create a nc listener nc -lp 5000 5. Run python3 dodyssey.py 6. You will get a hit on your nc showing we have successfully proceded to send a server side request 7. dodyssey.py will show error since there is no img file on the url, but we are able to do SSRF | {'SNYK-PYTHON-REPORTLAB-1022145', 'GHSA-mpvw-25mg-59vx', 'CVE-2020-28463'} | 2021-08-27T03:22:19.297131Z | 2021-02-18T16:15:00Z | null | null | null | {'https://www.reportlab.com/docs/reportlab-userguide.pdf', 'https://snyk.io/vuln/SNYK-PYTHON-REPORTLAB-1022145', 'https://github.com/advisories/GHSA-mpvw-25mg-59vx'} | null |
PyPI | PYSEC-2018-34 | null | (1) core/tests/test_memmap.py, (2) core/tests/test_multiarray.py, (3) f2py/f2py2e.py, and (4) lib/tests/test_io.py in NumPy before 1.8.1 allow local users to write to arbitrary files via a symlink attack on a temporary file. | {'CVE-2014-1859'} | 2021-06-29T22:52:17.858494Z | 2018-01-08T19:29:00Z | null | null | null | {'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128358.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128781.html', 'https://github.com/numpy/numpy/blob/maintenance/1.8.x/doc/release/1.8.1-notes.rst', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737778', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/91317', 'https://github.com/numpy/numpy/pull/4262', 'https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15', 'http://www.securityfocus.com/bid/65440', 'https://bugzilla.redhat.com/show_bug.cgi?id=1062009', 'http://www.openwall.com/lists/oss-security/2014/02/08/3'} | null |
PyPI | PYSEC-2020-146 | null | TUF (aka The Update Framework) 0.7.2 through 0.12.1 allows Uncontrolled Resource Consumption. | {'CVE-2020-6173', 'GHSA-2828-9vh6-9m6j'} | 2020-01-21T19:55:00Z | 2020-01-14T19:15:00Z | null | null | null | {'https://github.com/theupdateframework/tuf/issues/973', 'https://github.com/theupdateframework/tuf/commits/develop', 'https://github.com/advisories/GHSA-2828-9vh6-9m6j'} | null |
PyPI | PYSEC-2021-845 | null | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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-2021-41206', 'GHSA-pgcq-h79j-2f69'} | 2021-12-13T06:20:24.360595Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69', 'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07', 'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d'} | null |
PyPI | PYSEC-2021-795 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). 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-q7f7-544h-67h9', 'CVE-2021-37684'} | 2021-12-09T06:35:39.693273Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q7f7-544h-67h9'} | null |
PyPI | PYSEC-2022-5 | null | nltk is vulnerable to Inefficient Regular Expression Complexity | {'GHSA-rqjh-jp2r-59cj', 'CVE-2021-3842'} | 2022-01-12T23:31:32.837727Z | 2022-01-04T15:15:00Z | null | null | null | {'https://github.com/nltk/nltk/commit/2a50a3edc9d35f57ae42a921c621edc160877f4d', 'https://huntr.dev/bounties/761a761e-2be2-430a-8d92-6f74ffe9866a', 'https://github.com/advisories/GHSA-rqjh-jp2r-59cj'} | null |
PyPI | PYSEC-2021-70 | null | In Pillow before 8.1.0, TiffDecode has a heap-based buffer overflow when decoding crafted YCbCr files because of certain interpretation conflicts with LibTIFF in RGBA mode. | {'GHSA-vqcj-wrf2-7v73', 'CVE-2020-35654'} | 2021-03-22T15:48:00Z | 2021-01-12T09:15:00Z | null | null | null | {'https://pillow.readthedocs.io/en/stable/releasenotes/index.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZTSY25UJU7NJUFHH3HWT575LT4TDFWBZ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TQQY6472RX4J2SUJENWDZAWKTJJGP2ML/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BF553AMNNNBW7SH4IM4MNE4M6GNZQ7YD/', 'https://github.com/advisories/GHSA-vqcj-wrf2-7v73', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/6BYVI5G44MRIPERKYDQEL3S3YQCZTVHE/'} | null |
PyPI | GHSA-j3mj-fhpq-qqjj | Reachable Assertion in Tensorflow | ### Impact
When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments, if the tensors have an invalid `dtype` and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes.
### Patches
We have patched the issue in GitHub commit [5b491cd5e41ad63735161cec9c2a568172c8b6a3](https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3).
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. | {'CVE-2022-23571'} | 2022-03-03T05:13:41.114572Z | 2022-02-09T23:28:57Z | MODERATE | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j3mj-fhpq-qqjj', 'https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23571'} | null |
PyPI | GHSA-r8hm-w5f7-wj39 | Cross-site scripting vulnerability in TinyMCE plugins | ### Impact
A cross-site scripting (XSS) vulnerability was discovered in the URL processing logic of the `image` and `link` plugins. The vulnerability allowed arbitrary JavaScript execution when updating an image or link using a specially crafted URL. This issue only impacted users while editing and the dangerous URLs were stripped in any content extracted from the editor. This impacts all users who are using TinyMCE 5.9.2 or lower.
### Patches
This vulnerability has been patched in TinyMCE 5.10.0 by improved sanitization logic when updating URLs in the relevant plugins.
### Workarounds
To work around this vulnerability, either:
- Upgrade to TinyMCE 5.10.0 or higher
- Disable the `image` and `link` plugins
### Acknowledgements
Tiny Technologies would like to thank Yakir6 for discovering this vulnerability.
### References
https://www.tiny.cloud/docs/release-notes/release-notes510/#securityfixes
### For more information
If you have any questions or comments about this advisory:
* Email us at [infosec@tiny.cloud](mailto:infosec@tiny.cloud)
* Open an issue in the [TinyMCE repo](https://github.com/tinymce/tinymce/issues) | null | 2022-03-03T05:13:05.261265Z | 2021-11-02T15:42:52Z | MODERATE | null | {'CWE-64', 'CWE-79'} | {'https://github.com/jazzband/django-tinymce/releases/tag/3.4.0', 'https://pypi.org/project/django-tinymce/3.4.0/', 'https://github.com/tinymce/tinymce', 'https://github.com/jazzband/django-tinymce/issues/366', 'https://github.com/tinymce/tinymce/security/advisories/GHSA-r8hm-w5f7-wj39'} | null |
PyPI | GHSA-vqgp-4jgj-5j64 | Low severity vulnerability that affects py-evm | Py-EVM v0.2.0-alpha.33 allows attackers to make a vm.execute_bytecode call that triggers computation._stack.values with '"stack": [100, 100, 0]' where b'\x' was expected, resulting in an execution failure because of an invalid opcode. This is reportedly related to "smart contracts can be executed indefinitely without gas being paid." | {'CVE-2018-18920'} | 2022-03-03T05:13:15.741084Z | 2018-11-21T22:23:04Z | HIGH | null | {'CWE-119'} | {'https://github.com/ethereum/py-evm', 'https://nvd.nist.gov/vuln/detail/CVE-2018-18920', 'https://www.reddit.com/r/ethereum/comments/9vkk2g/netta_labs_claim_to_have_found_a_vulnerability_in/e9d3wyx/', 'https://github.com/advisories/GHSA-vqgp-4jgj-5j64', 'https://twitter.com/NettaLab/status/1060889400102383617', 'https://twitter.com/AlexanderFisher/status/1060923428641878019', 'https://github.com/ethereum/py-evm/issues/1448'} | null |
PyPI | PYSEC-2019-229 | null | Invalid memory access and/or a heap buffer overflow in the TensorFlow XLA compiler in Google TensorFlow before 1.7.1 could cause a crash or read from other parts of process memory via a crafted configuration file. | {'CVE-2018-10055'} | 2021-12-09T06:35:11.612649Z | 2019-04-24T17:29:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-006.md'} | null |
PyPI | GHSA-p3w6-jcg4-52xh | High severity vulnerability that affects django-rest-registration | ## Misusing the Django Signer API leads to predictable signatures used in verification emails
### Impact
The vulnerability is a high severity one. Anyone using Django REST Registration library versions `0.2.*` - `0.4.*` with e-mail verification option (which is recommended, but needs [additional configuration](https://django-rest-registration.readthedocs.io/en/latest/quickstart.html#preferred-configuration)) is affected.
In the worst case, the attacker can take over any Django user by resetting his/her password without even receiving the reset password verification link, just by guessing the signature from publicly available data (more detailed description below).
### Patches
The problem has been patched in version `0.5.0`. All library users should upgrade to version `0.5.0` or higher.
The fix will invalidate all previously generated signatures , and in consequence, all verification links in previously sent verification e-mails. Therefore semi-major version `0.5.0` was released instead of version `0.4.6` to mark that incompatibility.
### Workarounds
The easiest way way is to disable the verification options by using something like the minimal configuration described [here](https://django-rest-registration.readthedocs.io/en/latest/quickstart.html#minimal-configuration). This will unfortunately disable checking whether the given e-mail is valid and make unable to users who registered an account but didn't verify it before config change.
Less harsh way is to temporarily disable just the the reset password functionality:
```python
REST_REGISTRATION = {
# ...
'RESET_PASSWORD_VERIFICATION_ENABLED': False,
# ...
}
```
Which should disallow the worst case, which is account takeover by an attacker. The attacker can still use the register-email endpoint to change the email to its own (but it is less critical than resetting the password in this case).
If one already set `'RESET_PASSWORD_VERIFICATION_ONE_TIME_USE'` setting key to `True` in `REST_REGISTRATION` Django setting (which is not the default setting) then it should mitigate the security issue in case of password reset (in this case, the signature is much harder to guess by the attacker). But even in this case upgrade to newest version is highly recommended.
### Technical description
After the code [was refactored](https://github.com/apragacz/django-rest-registration/commit/b6d921e9decc9bb36a4c6d58bc607471aa824a2e) to use the [official Signer class](https://docs.djangoproject.com/en/dev/topics/signing/) the salt
was passed wrongly as secret key, replacing the `SECRET_KEY` set in
Django settings file. This leads to the Django `SECRET_KEY` not being used by the signer object. The secret key of the signer ends to be the salt which in most cases is a static string which is publicly available.
In consequence this allows, with verification enabled, to guess
the signature contained in the verification link (which is sent in a verification e-mail) by a potential attacker very easily.
The bug went unnoticed for very long time so multiple versions are affected:
this bug affects versions `0.2.*`, `0.3.*`, `0.4.*`; version `0.1.*` is not affected.
Recently released version `0.5.0` contains the [fix](https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5) which correctly passes the salt to the Signer constructor as keyword argument instead as a positonal argument. It also contains additonal test so this problem should not reappear in the future.
### Thanks
I'd like to thank @peterthomassen from https://desec.io DNS security project for finding the bug. I'd like also to thank his employer, SSE (https://www.securesystems.de) for funding his work.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [GitHub issues project page](https://github.com/apragacz/django-rest-registration/issues)
* Email @apragacz, author of the library | {'CVE-2019-13177'} | 2022-03-21T21:31:54.619518Z | 2019-07-02T15:43:41Z | CRITICAL | null | {'CWE-347'} | {'https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5', 'https://github.com/advisories/GHSA-p3w6-jcg4-52xh', 'https://github.com/apragacz/django-rest-registration/security/advisories/GHSA-p3w6-jcg4-52xh', 'https://github.com/apragacz/django-rest-registration/releases/tag/0.5.0', 'https://nvd.nist.gov/vuln/detail/CVE-2019-13177', 'https://github.com/apragacz/django-rest-registration'} | null |
PyPI | PYSEC-2020-280 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15200', 'GHSA-x7rp-74x2-mjf3'} | 2021-12-09T06:34:41.630526Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3'} | null |
PyPI | PYSEC-2019-19 | null | django-js-reverse (aka Django JS Reverse) before 0.9.1 has XSS via js_reverse_inline. | {'GHSA-vx6v-2rg6-865h', 'CVE-2019-15486'} | 2019-08-26T17:39:00Z | 2019-08-23T13:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-vx6v-2rg6-865h', 'https://github.com/ierror/django-js-reverse/compare/v0.9.0...v0.9.1', 'https://github.com/ierror/django-js-reverse/pull/81'} | null |
PyPI | PYSEC-2021-280 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37658', 'GHSA-6p5r-g9mq-ggh2'} | 2021-08-27T03:22:44.725554Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2'} | null |
PyPI | GHSA-m87f-39q9-6f55 | Sensitive Auth & Cookie data stored in Jupyter server logs | Anytime a 5xx error is triggered, the auth cookie and other header values are recorded in Jupyter server logs by default. Considering these logs do not require root access, an attacker can monitor these logs, steal sensitive auth/cookie information, and gain access to the Jupyter server.
Upgrade to notebook version 6.4.10
### For more information
If you have any questions or comments about this advisory, or vulnerabilities to report, please email our security list [security@ipython.org](mailto:security@ipython.org).
Credit: @3coins for reporting. Thank you!
| {'CVE-2022-24758'} | 2022-04-05T18:00:16.250969Z | 2022-04-05T17:47:26Z | HIGH | null | {'CWE-532'} | {'https://github.com/jupyter/notebook', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24758', 'https://github.com/jupyter/notebook/security/advisories/GHSA-m87f-39q9-6f55'} | null |
PyPI | PYSEC-2022-118 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. 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-3mw4-6rj6-74g5', 'CVE-2022-21739'} | 2022-03-09T00:18:24.872174Z | 2022-02-03T14:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5', 'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130'} | null |
PyPI | GHSA-2fch-jvg5-crf6 | Moderate severity vulnerability that affects python-gnupg | python-gnupg 0.4.3 allows context-dependent attackers to trick gnupg to decrypt other ciphertext than intended. To perform the attack, the passphrase to gnupg must be controlled by the adversary and the ciphertext should be trusted. Related to a "CWE-20: Improper Input Validation" issue affecting the affect functionality component. | {'CVE-2019-6690'} | 2022-03-03T05:13:22.528953Z | 2019-03-25T16:17:53Z | HIGH | null | {'CWE-20'} | {'https://usn.ubuntu.com/3964-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/W6KYZMN2PWXY4ENZVJUVTGFBVYEVY7II/', 'http://www.securityfocus.com/bid/106756', 'https://lists.debian.org/debian-lts-announce/2019/02/msg00021.html', 'https://nvd.nist.gov/vuln/detail/CVE-2019-6690', 'http://lists.opensuse.org/opensuse-security-announce/2019-02/msg00058.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/X4VFRUG56542LTYK4444TPJBGR57MT25/', 'https://pypi.org/project/python-gnupg/#history', 'https://seclists.org/bugtraq/2019/Jan/41', 'https://blog.hackeriet.no/cve-2019-6690-python-gnupg-vulnerability/', 'http://lists.opensuse.org/opensuse-security-announce/2019-02/msg00008.html', 'http://packetstormsecurity.com/files/151341/Python-GnuPG-0.4.3-Improper-Input-Validation.html', 'https://lists.debian.org/debian-lts-announce/2021/12/msg00027.html', 'https://github.com/advisories/GHSA-2fch-jvg5-crf6', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3WMV6XNPPL3VB3RQRFFOBCJ3AGWC4K47/'} | null |
PyPI | PYSEC-2021-404 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-fr77-rrx3-cp7g', 'CVE-2021-41212'} | 2021-11-13T06:52:43.991676Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fr77-rrx3-cp7g'} | null |
PyPI | PYSEC-2022-37 | null | An issue was discovered in Cobbler before 3.3.1. In the templar.py file, the function check_for_invalid_imports can allow Cheetah code to import Python modules via the "#from MODULE import" substring. (Only lines beginning with #import are blocked.) | {'GHSA-6cm4-gm85-972c', 'CVE-2021-45082'} | 2022-03-09T00:15:58.932039Z | 2022-02-19T00:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-6cm4-gm85-972c', 'https://github.com/cobbler/cobbler/releases', 'https://bugzilla.suse.com/show_bug.cgi?id=1193678'} | null |
PyPI | GHSA-8q59-q68h-6hv4 | Improper Input Validation in PyYAML | A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747. | {'CVE-2020-14343'} | 2022-04-22T18:30:50.414390Z | 2021-03-25T21:26:26Z | CRITICAL | null | {'CWE-20'} | {'https://github.com/yaml/pyyaml/issues/420#issuecomment-663673966', 'https://bugzilla.redhat.com/show_bug.cgi?id=1860466', 'https://github.com/yaml/pyyaml', 'https://pypi.org/project/PyYAML/', 'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://github.com/yaml/pyyaml/commit/a001f2782501ad2d24986959f0239a354675f9dc', 'https://nvd.nist.gov/vuln/detail/CVE-2020-14343'} | null |
PyPI | PYSEC-2019-157 | null | Jupyter Notebook before 5.5.0 does not use a CSP header to treat served files as belonging to a separate origin. Thus, for example, an XSS payload can be placed in an SVG document. | {'CVE-2018-21030', 'GHSA-jqwc-jm56-wcwj'} | 2021-07-15T02:22:16.244467Z | 2019-10-31T15:15:00Z | null | null | null | {'https://github.com/jupyter/notebook/pull/3341', 'https://lists.debian.org/debian-lts-announce/2020/11/msg00033.html', 'https://github.com/jupyter/notebook/releases/tag/5.5.0', 'https://github.com/advisories/GHSA-jqwc-jm56-wcwj'} | null |
PyPI | GHSA-vx6v-2rg6-865h | Cross-site Scripting in django-js-reverse | django-js-reverse (aka Django JS Reverse) before 0.9.1 has XSS via js_reverse_inline. | {'CVE-2019-15486'} | 2022-03-03T05:12:56.362322Z | 2019-08-27T17:39:33Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-15486', 'https://github.com/ierror/django-js-reverse/compare/v0.9.0...v0.9.1', 'https://github.com/ierror/django-js-reverse/pull/81'} | null |
PyPI | PYSEC-2021-812 | null | TensorFlow is an open source platform for machine learning. In affected versions during TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change. 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. | {'GHSA-786j-5qwq-r36x', 'CVE-2021-41204'} | 2021-12-09T06:35:41.878388Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-786j-5qwq-r36x', 'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} | null |
PyPI | PYSEC-2020-111 | null | The svglib package through 0.9.3 for Python allows XXE attacks via an svg2rlg call. | {'CVE-2020-10799', 'GHSA-3vcg-8p79-jpcv'} | 2020-03-24T20:38:00Z | 2020-03-20T23:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-3vcg-8p79-jpcv', 'https://github.com/deeplook/svglib/issues/229'} | null |
PyPI | GHSA-8ch4-58qp-g3mp | Observable Timing Discrepancy in aaugustin websockets library | The aaugustin websockets library before 9.1 for Python has an Observable Timing Discrepancy on servers when HTTP Basic Authentication is enabled with basic_auth_protocol_factory(credentials=...). An attacker may be able to guess a password via a timing attack. | {'CVE-2021-33880'} | 2022-04-22T16:01:59.328330Z | 2021-06-11T17:43:14Z | MODERATE | null | {'CWE-203', 'CWE-208'} | {'https://www.oracle.com/security-alerts/cpujan2022.html', 'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://github.com/aaugustin/websockets/commit/547a26b685d08cac0aa64e5e65f7867ac0ea9bc0', 'https://nvd.nist.gov/vuln/detail/CVE-2021-33880', 'https://github.com/aaugustin/websockets/'} | null |
PyPI | PYSEC-2018-63 | null | An issue was discovered in aubio 0.4.6. A buffer over-read can occur in new_aubio_pitchyinfft in pitch/pitchyinfft.c, as demonstrated by aubionotes. | {'CVE-2018-14523'} | 2021-08-25T04:29:55.843499Z | 2018-07-23T08:29:00Z | null | null | null | {'https://github.com/aubio/aubio/issues/189', 'http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00071.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-03/msg00031.html'} | null |
PyPI | PYSEC-2013-7 | null | Multiple directory traversal vulnerabilities in the (1) twikidraw (action/twikidraw.py) and (2) anywikidraw (action/anywikidraw.py) actions in MoinMoin before 1.9.6 allow remote authenticated users with write permissions to overwrite arbitrary files via unspecified vectors. NOTE: this can be leveraged with CVE-2012-6081 to execute arbitrary code. | {'CVE-2012-6495'} | 2021-07-05T00:01:23.010630Z | 2013-01-03T01:55:00Z | null | null | null | {'http://www.debian.org/security/2012/dsa-2593', 'http://www.openwall.com/lists/oss-security/2012/12/29/6', 'http://secunia.com/advisories/51696', 'http://moinmo.in/SecurityFixes', 'http://moinmo.in/MoinMoinRelease1.9', 'http://www.openwall.com/lists/oss-security/2012/12/30/4', 'https://bugs.launchpad.net/ubuntu/+source/moin/+bug/1094599', 'http://ubuntu.com/usn/usn-1680-1', 'http://hg.moinmo.in/moin/1.9/rev/7e7e1cbb9d3f'} | null |
PyPI | PYSEC-2021-111 | null | `projen` is a project generation tool that synthesizes project configuration files such as `package.json`, `tsconfig.json`, `.gitignore`, GitHub Workflows, `eslint`, `jest`, and more, from a well-typed definition written in JavaScript. Users of projen's `NodeProject` project type (including any project type derived from it) include a `.github/workflows/rebuild-bot.yml` workflow that may allow any GitHub user to trigger execution of un-trusted code in the context of the "main" repository (as opposed to that of a fork). In some situations, such untrusted code may potentially be able to commit to the "main" repository. The rebuild-bot workflow is triggered by comments including `@projen rebuild` on pull-request to trigger a re-build of the projen project, and updating the pull request with the updated files. This workflow is triggered by an `issue_comment` event, and thus always executes with a `GITHUB_TOKEN` belonging to the repository into which the pull-request is made (this is in contrast with workflows triggered by `pull_request` events, which always execute with a `GITHUB_TOKEN` belonging to the repository from which the pull-request is made). Repositories that do not have branch protection configured on their default branch (typically `main` or `master`) could possibly allow an untrusted user to gain access to secrets configured on the repository (such as NPM tokens, etc). Branch protection prohibits this escalation, as the managed `GITHUB_TOKEN` would not be able to modify the contents of a protected branch and affected workflows must be defined on the default branch. | {'CVE-2021-21423', 'GHSA-gg2g-m5wc-vccq'} | 2021-07-08T03:14:29.411085Z | 2021-04-06T19:15:00Z | null | null | null | {'https://github.com/projen/projen/commit/36030c6a4b1acd0054673322612e7c70e9446643', 'https://github.com/projen/projen/security/advisories/GHSA-gg2g-m5wc-vccq', 'https://www.npmjs.com/package/projen'} | null |
PyPI | GHSA-2p78-8hh6-96xc | Moderate severity vulnerability that affects feedparser | Cross-site scripting (XSS) vulnerability in feedparser.py in Universal Feed Parser (aka feedparser or python-feedparser) 5.x before 5.0.1 allows remote attackers to inject arbitrary web script or HTML via malformed XML comments. | {'CVE-2011-1157'} | 2022-03-03T05:13:28.203958Z | 2018-07-23T19:52:21Z | MODERATE | null | {'CWE-79'} | {'http://lists.opensuse.org/opensuse-updates/2011-04/msg00026.html', 'http://secunia.com/advisories/44074', 'https://github.com/advisories/GHSA-2p78-8hh6-96xc', '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', 'http://secunia.com/advisories/43730', 'https://bugzilla.redhat.com/show_bug.cgi?id=684877', 'http://support.novell.com/security/cve/CVE-2011-1157.html', 'http://www.securityfocus.com/bid/46867', 'https://nvd.nist.gov/vuln/detail/CVE-2011-1157', 'https://code.google.com/p/feedparser/issues/detail?id=254'} | null |
PyPI | PYSEC-2021-541 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `tf.raw_ops.CTCLoss` allows an attacker to trigger an OOB read from heap. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits 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-vvg4-vgrv-xfr7', 'CVE-2021-29613'} | 2021-12-09T06:35:00.939983Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vvg4-vgrv-xfr7', 'https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c', 'https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b'} | null |
PyPI | PYSEC-2014-40 | null | queryCatalog.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to bypass caching and cause a denial of service via a crafted request to a collection. | {'CVE-2012-5498'} | 2021-09-01T08:44:30.217052Z | 2014-09-30T14:55:00Z | null | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'http://www.openwall.com/lists/oss-security/2012/11/09/7', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'http://rhn.redhat.com/errata/RHSA-2014-1194.html', 'https://plone.org/products/plone/security/advisories/20121106/14'} | null |
PyPI | GHSA-vcg8-98q8-g7mj | Exposure of Sensitive Information to an Unauthorized Actor and Insecure Temporary File in Ansible | A flaw was found in Ansible Engine when using Ansible Vault for editing encrypted files. When a user executes "ansible-vault edit", another user on the same computer can read the old and new secret, as it is created in a temporary file with mkstemp and the returned file descriptor is closed and the method write_data is called to write the existing secret in the file. This method will delete the file before recreating it insecurely. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1740'} | 2022-03-03T05:13:18.887783Z | 2021-04-07T21:47:31Z | LOW | null | {'CWE-200', 'CWE-377'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQVOQD4VAIXXTVQAJKTN7NUGTJFE2PCB/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1740', 'https://lists.debian.org/debian-lts-announce/2020/05/msg00005.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MRRYUU5ZBLPBXCYG6CFP35D64NP2UB2S/', 'https://github.com/ansible/ansible/commit/28f9fbdb5e281976e33f443193047068afb97a9b', 'https://github.com/ansible/ansible', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DKPA4KC3OJSUFASUYMG66HKJE7ADNGFW/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1740', 'https://security.gentoo.org/glsa/202006-11', 'https://github.com/ansible/ansible/issues/67798'} | null |
PyPI | PYSEC-2020-238 | null | AuthRestServlet in Matrix Synapse before 1.21.0 is vulnerable to XSS due to unsafe interpolation of the session GET parameter. This allows a remote attacker to execute an XSS attack on the domain Synapse is hosted on, by supplying the victim user with a malicious URL to the /_matrix/client/r0/auth/*/fallback/web or /_matrix/client/unstable/auth/*/fallback/web Synapse endpoints. | {'GHSA-3x8c-fmpc-5rmq', 'CVE-2020-26891'} | 2021-08-27T03:22:06.522203Z | 2020-10-19T17:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/security/advisories/GHSA-3x8c-fmpc-5rmq', 'https://github.com/matrix-org/synapse/pull/8444', 'https://matrix.org/blog/2020/10/15/synapse-1-21-2-released-and-security-advisory', 'https://github.com/matrix-org/synapse/releases/tag/v1.21.2'} | null |
PyPI | PYSEC-2021-668 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. 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. 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]`. 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-2021-29542', 'GHSA-4hrh-9vmp-2jgg'} | 2021-12-09T06:35:22.008829Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hrh-9vmp-2jgg'} | null |
PyPI | PYSEC-2021-392 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.image.resize` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. 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-2021-41199', 'GHSA-5hx2-qx8j-qjqm'} | 2021-11-13T06:52:42.174686Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hx2-qx8j-qjqm', 'https://github.com/tensorflow/tensorflow/issues/46914'} | null |
PyPI | PYSEC-2021-27 | null | Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.28.0 Synapse is missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion. Note that the groups feature is not part of the Matrix specification and the chosen maximum lengths are arbitrary. Not all clients might abide by them. Refer to referenced GitHub security advisory for additional details including workarounds. | {'GHSA-w9fg-xffh-p362', 'CVE-2021-21394'} | 2021-04-21T17:02:00Z | 2021-04-12T21:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/pull/9393', 'https://github.com/matrix-org/synapse/pull/9321', 'https://pypi.org/project/matrix-synapse/', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-w9fg-xffh-p362'} | null |
PyPI | PYSEC-2021-238 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. 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-2021-29601', 'GHSA-9c84-4hx6-xmm4'} | 2021-08-27T03:22:39.383979Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c84-4hx6-xmm4'} | null |
PyPI | PYSEC-2013-13 | null | Salt (aka SaltStack) before 0.17.1 allows remote attackers to execute arbitrary YAML code via unspecified vectors. NOTE: the vendor states that this might not be a vulnerability because the YAML to be loaded has already been determined to be safe. | {'CVE-2013-4438'} | 2021-07-05T00:01:26.005200Z | 2013-11-05T18:55:00Z | null | null | null | {'http://docs.saltstack.com/topics/releases/0.17.1.html', 'http://www.openwall.com/lists/oss-security/2013/10/18/3'} | null |
PyPI | PYSEC-2021-687 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29561', 'GHSA-gvm4-h8j3-rjrq'} | 2021-12-09T06:35:25.291953Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq', 'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} | null |
PyPI | GHSA-m8qc-mf6p-pfq9 | Link Following in rply | python-rply before 0.7.4 insecurely creates temporary files. | {'CVE-2014-1938'} | 2022-03-03T05:13:33.531617Z | 2020-03-11T20:56:34Z | MODERATE | null | {'CWE-59'} | {'https://github.com/alex/rply/commit/76d268a38c627bf4aebebcd064f5b6d380eb8b20', 'https://nvd.nist.gov/vuln/detail/CVE-2014-1938', 'https://security-tracker.debian.org/tracker/CVE-2014-1938', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737627', 'https://github.com/alex/rply/issues/42', 'http://www.openwall.com/lists/oss-security/2014/02/11/1'} | null |
PyPI | GHSA-vp9j-rghq-8jhh | Exposure of Resource to Wrong Sphere and Insecure Temporary File in Ansible | An incomplete fix was found for the fix of the flaw CVE-2020-1733 ansible insecure temporary directory when running become_user from become directive. The provided fix is insufficient to prevent the race condition on systems using ACLs and FUSE filesystems. Ansible Engine 2.7.18, 2.8.12, and 2.9.9 as well as previous versions are affected and Ansible Tower 3.4.5, 3.5.6 and 3.6.4 as well as previous versions are affected. | {'CVE-2020-10744'} | 2022-03-03T05:13:08.898421Z | 2022-02-09T21:59:42Z | MODERATE | null | {'CWE-668', 'CWE-377'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-10744', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-10744'} | null |
PyPI | PYSEC-2017-50 | null | Lemur 0.1.4 does not use sufficient entropy in its IV when encrypting AES in CBC mode. | {'CVE-2015-7764'} | 2019-12-11T21:22:00Z | 2017-08-09T16:29:00Z | null | null | null | {'https://github.com/Netflix/lemur/issues/117', 'http://www.openwall.com/lists/oss-security/2015/10/20/3', 'https://github.com/kvesteri/sqlalchemy-utils/issues/166'} | null |
PyPI | PYSEC-2021-869 | null | archivy is vulnerable to Cross-Site Request Forgery (CSRF) | {'CVE-2021-4162', 'GHSA-9236-8w7q-rmrv'} | 2022-01-13T03:02:27.086269Z | 2021-12-25T12:15:00Z | null | null | null | {'https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d', 'https://huntr.dev/bounties/e204a768-2129-4b6f-abad-e436309c7c32', 'https://github.com/advisories/GHSA-9236-8w7q-rmrv'} | null |
PyPI | GHSA-r82c-j4mq-5xfw | Update bitlyshortener to >=0.5.0 to prevent generating some invalid short URLs | ### Impact
Due to a sudden upstream breaking change by Bitly, versions of `bitlyshortener` <0.5.0 can generate an invalid short URL when a vanity domain exists.
### Patches
Upgrading `bitlyshortener` to 0.5.0 or newer will prevent the generation of any such invalid short URLs.
### References
* [Release notes](https://github.com/impredicative/bitlyshortener/releases) | null | 2022-03-03T05:13:06.521725Z | 2020-10-27T19:19:56Z | HIGH | null | {'CWE-601'} | {'https://github.com/impredicative/bitlyshortener/security/advisories/GHSA-r82c-j4mq-5xfw', 'https://github.com/impredicative/bitlyshortener/commit/3d412feb77f3daf6f71536463734c2119a55968d', 'https://pypi.org/project/bitlyshortener/', 'https://github.com/impredicative/bitlyshortener/releases/tag/0.5.0'} | null |
PyPI | GHSA-h95j-h2rv-qrg4 | Moderate severity vulnerability that affects django | The CSRF protection mechanism in Django through 1.2.7 and 1.3.x through 1.3.1 does not properly handle web-server configurations supporting arbitrary HTTP Host headers, which allows remote attackers to trigger unauthenticated forged requests via vectors involving a DNS CNAME record and a web page containing JavaScript code. | {'CVE-2011-4140'} | 2022-03-03T05:14:10.579547Z | 2018-07-23T19:51:19Z | MODERATE | null | {'CWE-352'} | {'https://github.com/django/django', 'https://nvd.nist.gov/vuln/detail/CVE-2011-4140', 'https://www.djangoproject.com/weblog/2011/sep/09/', 'http://openwall.com/lists/oss-security/2011/09/13/2', 'https://www.djangoproject.com/weblog/2011/sep/10/127/', 'http://www.debian.org/security/2011/dsa-2332', 'https://github.com/advisories/GHSA-h95j-h2rv-qrg4', 'http://openwall.com/lists/oss-security/2011/09/11/1', 'https://bugzilla.redhat.com/show_bug.cgi?id=737366', 'http://secunia.com/advisories/46614', 'https://hermes.opensuse.org/messages/14700881'} | null |
PyPI | PYSEC-2018-18 | null | Jupyter Notebook before 5.7.2 allows XSS via a crafted directory name because notebook/static/tree/js/notebooklist.js handles certain URLs unsafely. | {'GHSA-3p4q-x8f3-p7vq', 'CVE-2018-19352'} | 2021-06-10T06:52:01.452566Z | 2018-11-18T17:29:00Z | null | null | null | {'https://pypi.org/project/notebook/#history', 'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648', 'https://github.com/advisories/GHSA-3p4q-x8f3-p7vq', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst'} | null |
PyPI | GHSA-gcm4-q2pg-xw89 | Moderate severity vulnerability that affects ipycache | A code injection issue was discovered in ipycache through 2016-05-31. | {'CVE-2019-7539'} | 2022-03-03T05:13:39.857046Z | 2019-03-25T16:16:55Z | HIGH | null | {'CWE-94', 'CWE-502'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-7539', 'https://github.com/advisories/GHSA-gcm4-q2pg-xw89', 'https://github.com/rossant/ipycache/issues/47'} | null |
PyPI | PYSEC-2021-490 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`. 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-2021-29562', 'GHSA-36vm-xw34-x4pj'} | 2021-12-09T06:34:52.986581Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-36vm-xw34-x4pj'} | null |
PyPI | PYSEC-2022-163 | null | The package libvcs before 0.11.1 are vulnerable to Command Injection via argument injection. When calling the update_repo function (when using hg), the url parameter is passed to the hg clone command. By injecting some hg options it was possible to get arbitrary command execution. | {'SNYK-PYTHON-LIBVCS-2421204', 'CVE-2022-21187'} | 2022-03-14T20:32:58.020706Z | 2022-03-14T18:15:00Z | null | null | null | {'https://github.com/vcs-python/libvcs/pull/306', 'https://github.com/vcs-python/libvcs/blob/v0.11.1/CHANGES%23libvcs-0111-2022-03-12', 'https://snyk.io/vuln/SNYK-PYTHON-LIBVCS-2421204'} | null |
PyPI | GHSA-4mg4-wvmx-5332 | Server-Side Request Forgery in Plone | Plone through 5.2.4 allows remote authenticated managers to conduct SSRF attacks via an event ical URL, to read one line of a file. | {'CVE-2021-33510'} | 2022-03-03T05:12:57.802295Z | 2021-06-15T16:11:47Z | MODERATE | null | {'CWE-918'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-33510', 'http://www.openwall.com/lists/oss-security/2021/05/22/1', 'https://plone.org/security/hotfix/20210518/server-side-request-forgery-via-event-ical-url'} | null |
PyPI | GHSA-p5f8-gfw5-33w4 | Heap buffer overflow in Tensorflow | ### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, this code is prone to heap buffer overflow:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L251
If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large.
### 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 has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15201'} | 2021-08-26T15:13:48Z | 2020-09-25T18:28:34Z | MODERATE | null | {'CWE-20', 'CWE-787', 'CWE-122'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-15201', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} | null |
PyPI | PYSEC-2021-185 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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-2021-29548', 'GHSA-p45v-v4pw-77jr'} | 2021-08-27T03:22:29.986611Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr'} | null |
PyPI | PYSEC-2020-71 | null | In openapi-python-client before version 0.5.3, clients generated with a maliciously crafted OpenAPI Document can generate arbitrary Python code. Subsequent execution of this malicious client is arbitrary code execution. | {'CVE-2020-15142', 'GHSA-9x4c-63pf-525f'} | 2020-08-20T18:11:00Z | 2020-08-14T17:15:00Z | null | null | null | {'https://github.com/triaxtec/openapi-python-client/security/advisories/GHSA-9x4c-63pf-525f', 'https://pypi.org/project/openapi-python-client/', 'https://github.com/triaxtec/openapi-python-client/blob/main/CHANGELOG.md#053---2020-08-13', 'https://github.com/triaxtec/openapi-python-client/commit/f7a56aae32cba823a77a84a1f10400799b19c19a'} | null |
PyPI | PYSEC-2021-756 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. | {'CVE-2021-37645', 'GHSA-9w2p-5mgw-p94c'} | 2021-12-09T06:35:36.218671Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c', 'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1'} | null |
PyPI | PYSEC-2007-1 | null | The internationalization (i18n) framework in Django 0.91, 0.95, 0.95.1, and 0.96, and as used in other products such as PyLucid, when the USE_I18N option and the i18n component are enabled, allows remote attackers to cause a denial of service (memory consumption) via many HTTP requests with large Accept-Language headers. | {'CVE-2007-5712'} | 2021-07-15T02:22:07.728618Z | 2007-10-30T19:46:00Z | null | null | null | {'http://secunia.com/advisories/31961', 'http://www.debian.org/security/2008/dsa-1640', 'http://sourceforge.net/forum/forum.php?forum_id=749199', 'http://www.vupen.com/english/advisories/2007/3660', 'http://www.vupen.com/english/advisories/2007/3661', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/38143', 'https://www.redhat.com/archives/fedora-package-announce/2007-November/msg00257.html', 'http://www.securityfocus.com/bid/26227', 'http://secunia.com/advisories/27435', 'https://www.redhat.com/archives/fedora-package-announce/2007-November/msg00243.html', 'http://secunia.com/advisories/27597', 'http://www.djangoproject.com/weblog/2007/oct/26/security-fix'} | null |
PyPI | PYSEC-2021-306 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). 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-q7f7-544h-67h9', 'CVE-2021-37684'} | 2021-08-27T03:22:47.149147Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q7f7-544h-67h9'} | null |
PyPI | GHSA-26j7-6w8w-7922 | Division by zero in optimized pooling implementations in TFLite | ### Impact
Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling [`ComputePaddingHeightWidth`](https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90).
Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero.
### Patches
We have patched the issue in GitHub commit [5f7975d09eac0f10ed8a17dbb6f5964977725adc](https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc).
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. | {'CVE-2021-29586'} | 2022-03-03T05:13:45.088991Z | 2021-05-21T14:26:43Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29586', 'https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-26j7-6w8w-7922'} | null |
PyPI | GHSA-278g-rq84-9hmg | `CHECK`-fail in `MapStage` | ### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`:
```python
import tensorflow as tf
tf.raw_ops.MapStage(
key=tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64),
indices=tf.constant((0), dtype=tf.int32),
values=[tf.constant((0), dtype=tf.int32)],
dtypes=[tf.int32,
tf.int64],
capacity=0,
memory_limit=0,
container='',
shared_name='')
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor.
### Patches
We have patched the issue in GitHub commit [d7de67733925de196ec8863a33445b73f9562d1d](https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37673'} | 2022-03-03T05:13:08.313939Z | 2021-08-25T14:41:36Z | MODERATE | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37673', 'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-278g-rq84-9hmg'} | null |
PyPI | PYSEC-2020-306 | null | In Tensorflow before versions 2.2.1 and 2.3.1, 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. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | {'GHSA-q8qj-fc9q-cphr', 'CVE-2020-15191'} | 2021-12-09T06:35:12.260463Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2015-16 | null | Pillow before 2.7.0 allows remote attackers to cause a denial of service via a compressed text chunk in a PNG image that has a large size when it is decompressed. | {'CVE-2014-9601'} | 2021-07-05T00:01:23.853626Z | 2015-01-16T16:59:00Z | null | null | null | {'http://www.oracle.com/technetwork/topics/security/bulletinjul2015-2511963.html', 'https://www.djangoproject.com/weblog/2015/jan/02/pillow-security-release/', 'http://www.securityfocus.com/bid/77758', 'https://github.com/python-pillow/Pillow/pull/1060', 'http://pillow.readthedocs.org/releasenotes/2.7.0.html', 'http://lists.opensuse.org/opensuse-updates/2015-04/msg00056.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-January/148442.html'} | null |
PyPI | PYSEC-2019-205 | null | Google TensorFlow 1.7.x and earlier is affected by a Buffer Overflow vulnerability. The type of exploitation is context-dependent. | {'GHSA-mw6v-crh8-8533', 'CVE-2018-7575'} | 2021-08-27T03:22:22.242054Z | 2019-04-24T21:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-mw6v-crh8-8533', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-004.md'} | null |
PyPI | GHSA-pghf-347x-c2gj | SQL Injection via in django-debug-toolbar | ### Impact
With Django Debug Toolbar attackers are able to execute SQL by changing the `raw_sql` input of the SQL explain, analyze or select forms and submitting the form.
**NOTE:** This is a high severity issue for anyone using the toolbar in a **production environment**.
Generally the Django Debug Toolbar team only maintains the latest version of django-debug-toolbar, but an exception was made because of the high severity of this issue.
### Patches
Please upgrade to one of the following versions, depending on the major version you're using:
- Version 1.x: [django-debug-toolbar 1.11.1](https://pypi.org/project/django-debug-toolbar/1.11.1/)
- Version 2.x: [django-debug-toolbar 2.2.1](https://pypi.org/project/django-debug-toolbar/2.2.1/)
- Version 3.x: [django-debug-toolbar 3.2.1](https://pypi.org/project/django-debug-toolbar/3.2.1/)
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [django-debug-toolbar repo](https://github.com/jazzband/django-debug-toolbar/issues/new) (Please NO SENSITIVE INFORMATION, send an email instead!)
* Email us at [security@jazzband.co](mailto:security@jazzband.co) | {'CVE-2021-30459'} | 2022-03-03T05:13:01.787362Z | 2021-04-16T19:53:28Z | HIGH | null | {'CWE-89'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-30459', 'https://github.com/jazzband/django-debug-toolbar/releases', 'https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-30459', 'https://github.com/jazzband/django-debug-toolbar/security/advisories/GHSA-pghf-347x-c2gj', 'https://www.djangoproject.com/weblog/2021/apr/14/debug-toolbar-security-releases/'} | null |
PyPI | PYSEC-2014-5 | null | The default configuration for the file upload handling system in Django before 1.4.14, 1.5.x before 1.5.9, 1.6.x before 1.6.6, and 1.7 before release candidate 3 uses a sequential file name generation process when a file with a conflicting name is uploaded, which allows remote attackers to cause a denial of service (CPU consumption) by unloading a multiple files with the same name. | {'CVE-2014-0481'} | 2021-07-05T00:01:18.973883Z | 2014-08-26T14:55:00Z | null | null | null | {'http://www.debian.org/security/2014/dsa-3010', 'http://lists.opensuse.org/opensuse-updates/2014-09/msg00023.html', 'http://secunia.com/advisories/59782', 'http://secunia.com/advisories/61281', 'https://www.djangoproject.com/weblog/2014/aug/20/security/', 'http://secunia.com/advisories/61276'} | null |
PyPI | GHSA-9g8h-pjm4-q92p | Out-of-bounds Write in OpenCV. | In OpenCV 3.3.1 (corresponding with OpenCV-Python 3.3.1.11), a heap-based buffer overflow happens in cv::Jpeg2KDecoder::readComponent8u in modules/imgcodecs/src/grfmt_jpeg2000.cpp when parsing a crafted image file. | {'CVE-2018-5268'} | 2022-03-03T05:13:11.150261Z | 2021-10-12T22:23:41Z | MODERATE | null | {'CWE-787'} | {'https://lists.debian.org/debian-lts-announce/2018/04/msg00019.html', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'http://www.securityfocus.com/bid/106945', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://github.com/opencv/opencv/issues/10541', 'https://nvd.nist.gov/vuln/detail/CVE-2018-5268', 'https://github.com/opencv/opencv/pull/10566/commits/435a3e337bd9d4e11af61cf8b8afca067bf1a8aa', 'https://github.com/opencv/opencv-python'} | null |
PyPI | GHSA-4fjv-pmhg-3rfg | Multiple cryptographic issues in Python oic | ### Impact
* Client implementations using this library
### Issues
1) The IdToken signature algorithm was not checked automatically, but only if the expected algorithm was passed in as a kwarg.
2) JWA `none` algorithm was allowed in all flows.
3) `oic.consumer.Consumer.parse_authz` returns an unverified IdToken. The verification of the token was left to the discretion of the implementator.
4) `iat` claim was not checked for sanity (i.e. it could be in the future)
### Patches
1) IdToken signature is now always checked.
2) JWA `none` algorithm is now allowed only if using the `response_type` `code`
3) IdToken verification is now done automatically.
4) `iat` claim is now checked for sanity. | {'CVE-2020-26244'} | 2022-03-03T05:13:09.226121Z | 2020-12-04T16:47:12Z | MODERATE | null | {'CWE-325', 'CWE-347'} | {'https://github.com/OpenIDC/pyoidc/security/advisories/GHSA-4fjv-pmhg-3rfg', 'https://pypi.org/project/oic/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26244', 'https://github.com/OpenIDC/pyoidc/commit/62f8d753fa17c8b1f29f8be639cf0b33afb02498', 'https://github.com/OpenIDC/pyoidc/releases/tag/1.2.1'} | null |
PyPI | PYSEC-2020-243 | null | An issue was discovered in Guest.migrate in virt/libvirt/guest.py in OpenStack Nova before 19.3.1, 20.x before 20.3.1, and 21.0.0. By performing a soft reboot of an instance that has previously undergone live migration, a user may gain access to destination host devices that share the same paths as host devices previously referenced by the virtual machine on the source host. This can include block devices that map to different Cinder volumes at the destination than at the source. Only deployments allowing host-based connections (for instance, root and ephemeral devices) are affected. | {'CVE-2020-17376'} | 2021-08-27T03:22:09.410263Z | 2020-08-26T19:15:00Z | null | null | null | {'https://security.openstack.org/ossa/OSSA-2020-006.html', 'http://www.openwall.com/lists/oss-security/2020/08/25/4', 'https://launchpad.net/bugs/1890501'} | null |
PyPI | PYSEC-2021-613 | null | TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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-2021-41203', 'GHSA-7pxj-m4jf-r6h2'} | 2021-12-09T06:35:08.067216Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad', 'https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7pxj-m4jf-r6h2', 'https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578', 'https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2'} | null |
PyPI | PYSEC-2021-243 | null | TensorFlow is an end-to-end open source platform for machine learning. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of `Split_V`(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the `SizeOfDimension` function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape array. 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-2021-29606', 'GHSA-h4pc-gx2w-f2xv'} | 2021-08-27T03:22:40.241160Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h4pc-gx2w-f2xv'} | null |
PyPI | GHSA-89px-ww3j-g2mm | 2FA bypass in Wagtail through new device path | ## 2FA bypass through new device path
### Impact
If someone gains access to someone's Wagtail login credentials, they can log into the CMS and bypass the 2FA check by changing the URL. They can then add a new device and gain full access to the CMS.
### Patches
This problem has been patched in version 1.3.0.
### Workarounds
There is no workaround at the moment.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [github.com/labd/wagtail-2fa](https://github.com/labd/wagtail-2fa)
* Email us at [security@labdigital.nl](mailto:security@labdigital.nl) | {'CVE-2019-16766'} | 2022-03-03T05:13:37.620316Z | 2019-11-29T17:05:59Z | HIGH | null | {'CWE-290', 'CWE-304'} | {'https://github.com/advisories/GHSA-89px-ww3j-g2mm', 'https://github.com/labd/wagtail-2fa/security/advisories/GHSA-89px-ww3j-g2mm', 'https://github.com/labd/wagtail-2fa/commit/a6711b29711729005770ff481b22675b35ff5c81', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16766', 'https://github.com/labd/wagtail-2fa/commit/13b12995d35b566df08a17257a23863ab6efb0ca'} | null |
PyPI | PYSEC-2019-194 | null | An access-control flaw was found in the Octavia service when the cloud platform was deployed using Red Hat OpenStack Platform Director. An attacker could cause new amphorae to run based on any arbitrary image. This meant that a remote attacker could upload a new amphorae image and, if requested to spawn new amphorae, Octavia would then pick up the compromised image. | {'CVE-2019-3895'} | 2021-08-27T03:22:09.805726Z | 2019-06-03T19:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-3895', 'https://access.redhat.com/errata/RHSA-2019:1742', 'https://access.redhat.com/errata/RHSA-2019:1683'} | null |
PyPI | GHSA-hj69-c76v-86wr | Out-of-bounds Read in Pillow | libImaging/FliDecode.c in Pillow before 6.2.2 has an FLI buffer overflow. | {'CVE-2020-5313'} | 2022-03-03T05:13:50.761817Z | 2020-04-01T16:36:00Z | HIGH | null | {'CWE-125'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2MMU3WT2X64GS5WHDPKKC2WZA7UIIQ3A/', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-5313', 'https://github.com/python-pillow/Pillow/commit/a09acd0decd8a87ccce939d5ff65dab59e7d365b', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631', 'https://github.com/python-pillow/Pillow/blob/master/CHANGES.rst#622-2020-01-02'} | null |
PyPI | PYSEC-2012-12 | null | Apache Libcloud before 0.11.1 uses an incorrect regular expression during verification of whether the server hostname matches a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate, which allows man-in-the-middle attackers to spoof SSL servers via a crafted certificate. | {'CVE-2012-3446'} | 2021-08-27T03:21:55.557676Z | 2012-11-04T22:55:00Z | null | null | null | {'https://svn.apache.org/repos/asf/libcloud/trunk/CHANGES', 'http://www.cs.utexas.edu/~shmat/shmat_ccs12.pdf'} | null |
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