ecosystem
stringclasses 14
values | vuln_id
stringlengths 10
19
| summary
stringlengths 4
267
⌀ | details
stringlengths 9
13.5k
| aliases
stringlengths 17
144
⌀ | modified_date
stringdate 2010-05-27 05:47:00
2022-05-10 08:46:52
| published_date
stringdate 2005-12-31 05:00:00
2022-05-10 08:46:50
| severity
stringclasses 5
values | score
float64 0
10
⌀ | cwe_id
stringclasses 988
values | refs
stringlengths 30
17.7k
⌀ | introduced
stringlengths 75
4.26k
⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI
|
PYSEC-2021-467
| null |
TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument.
|
{'GHSA-g4h2-gqm3-c9wq', 'CVE-2021-29539'}
|
2021-12-09T06:34:49.452107Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g4h2-gqm3-c9wq', 'https://github.com/tensorflow/tensorflow/commit/4f663d4b8f0bec1b48da6fa091a7d29609980fa4'}
| null |
PyPI
|
PYSEC-2021-172
| null |
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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-2021-29535', 'GHSA-m3f9-w3p3-p669'}
|
2021-08-27T03:22:27.629630Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669', 'https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87'}
| null |
PyPI
|
GHSA-qhx9-7hx7-cp4r
|
HTTP Request smuggling in bottle
|
The package bottle before 0.12.19 are vulnerable to Web Cache Poisoning by using a vector called parameter cloaking. When the attacker can separate query parameters using a semicolon (;), they can cause a difference in the interpretation of the request between the proxy (running with default configuration) and the server. This can result in malicious requests being cached as completely safe ones, as the proxy would usually not see the semicolon as a separator, and therefore would not include it in a cache key of an unkeyed parameter.
|
{'CVE-2020-28473'}
|
2022-03-03T05:12:40.159877Z
|
2021-04-07T21:05:21Z
|
MODERATE
| null |
{'CWE-444'}
|
{'https://snyk.io/blog/cache-poisoning-in-popular-open-source-packages/', 'https://snyk.io/vuln/SNYK-PYTHON-BOTTLE-1017108', 'https://lists.debian.org/debian-lts-announce/2021/01/msg00019.html', 'https://github.com/bottlepy/bottle/commit/57a2f22e0c1d2b328c4f54bf75741d74f47f1a6b', 'https://nvd.nist.gov/vuln/detail/CVE-2020-28473'}
| null |
PyPI
|
PYSEC-2021-488
| null |
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel. Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`. 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-8gv3-57p6-g35r', 'CVE-2021-29560'}
|
2021-12-09T06:34:52.680803Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8gv3-57p6-g35r'}
| null |
PyPI
|
PYSEC-2021-522
| null |
TensorFlow is an end-to-end open source platform for machine learning. TFLite's convolution code(https://github.com/tensorflow/tensorflow/blob/09c73bca7d648e961dd05898292d91a8322a9d45/tensorflow/lite/kernels/conv.cc) has multiple division where the divisor is controlled by the user and not checked to be non-zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
|
{'CVE-2021-29594', 'GHSA-3qgw-p4fm-x7gf'}
|
2021-12-09T06:34:57.958093Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qgw-p4fm-x7gf', 'https://github.com/tensorflow/tensorflow/commit/ff489d95a9006be080ad14feb378f2b4dac35552'}
| null |
PyPI
|
GHSA-7qqv-r2q4-jxhm
|
High severity vulnerability that affects privacyIDEA
|
privacyIDEA version 2.23.1 and earlier contains a Improper Input Validation vulnerability in token validation api that can result in Denial-of-Service. This attack appear to be exploitable via http request with user=<space>&pass= to /validate/check url. This vulnerability appears to have been fixed in 2.23.2.
|
{'CVE-2018-1000809'}
|
2022-03-03T05:13:06.315310Z
|
2019-01-14T16:19:31Z
|
HIGH
| null |
{'CWE-20'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2018-1000809', 'https://github.com/advisories/GHSA-7qqv-r2q4-jxhm', 'https://github.com/privacyidea/privacyidea/issues/1227', 'https://github.com/privacyidea/privacyidea', 'https://github.com/privacyidea/privacyidea/commit/a3edc09beffa2104f357fe24971ea3211ce40751'}
| null |
PyPI
|
PYSEC-2014-23
| null |
The (1) JpegImagePlugin.py and (2) EpsImagePlugin.py scripts in Python Image Library (PIL) 1.1.7 and earlier and Pillow before 2.3.1 uses the names of temporary files on the command line, which makes it easier for local users to conduct symlink attacks by listing the processes.
|
{'CVE-2014-1933', 'GHSA-r854-96gq-rfg3'}
|
2021-07-15T02:22:17.008543Z
|
2014-04-17T14:55:00Z
| null | null | null |
{'https://github.com/python-imaging/Pillow/commit/4e9f367dfd3f04c8f5d23f7f759ec12782e10ee7', 'http://www.ubuntu.com/usn/USN-2168-1', 'http://lists.opensuse.org/opensuse-updates/2014-05/msg00002.html', 'https://security.gentoo.org/glsa/201612-52', 'https://github.com/advisories/GHSA-r854-96gq-rfg3', 'http://www.openwall.com/lists/oss-security/2014/02/10/15', 'http://www.openwall.com/lists/oss-security/2014/02/11/1', 'http://www.securityfocus.com/bid/65513'}
| null |
PyPI
|
PYSEC-2020-172
| null |
There is a DoS vulnerability in Pillow before 6.2.2 caused by FpxImagePlugin.py calling the range function on an unvalidated 32-bit integer if the number of bands is large. On Windows running 32-bit Python, this results in an OverflowError or MemoryError due to the 2 GB limit. However, on Linux running 64-bit Python this results in the process being terminated by the OOM killer.
|
{'CVE-2019-19911', 'GHSA-5gm3-px64-rw72'}
|
2020-08-24T17:37:00Z
|
2020-01-05T22:15:00Z
| null | null | null |
{'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://github.com/advisories/GHSA-5gm3-px64-rw72', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631'}
| null |
PyPI
|
PYSEC-2020-86
| null |
An XSS issue in the title field in Plone 5.0 through 5.2.1 allows users with a certain privilege level to insert JavaScript that will be executed when other users access the site.
|
{'CVE-2020-7937'}
|
2020-01-24T23:07:00Z
|
2020-01-23T21:15:00Z
| null | null | null |
{'https://plone.org/security/hotfix/20200121', 'https://www.openwall.com/lists/oss-security/2020/01/22/1', 'http://www.openwall.com/lists/oss-security/2020/01/24/1', 'https://plone.org/security/hotfix/20200121/xss-in-the-title-field-on-plone-5-0-and-higher'}
| null |
PyPI
|
GHSA-xvjm-fvxx-q3hv
|
CHECK-fail due to integer overflow
|
### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape:
```python
import tensorflow as tf
input_layer = 2**60-1
sparse_data = tf.raw_ops.SparseSplit(
split_dim=1,
indices=[(0, 0), (0, 1), (0, 2),
(4, 3), (5, 0), (5, 1)],
values=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
shape=(input_layer, input_layer),
num_split=2,
name=None
)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow:
```cc
sparse::SparseTensor sparse_tensor;
OP_REQUIRES_OK(context,
sparse::SparseTensor::Create(
input_indices, input_values,
TensorShape(input_shape.vec<int64>()), &sparse_tensor));
```
The [`TensorShape` constructor](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when [`InitDims`](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status.
```cc
template <class Shape>
TensorShapeBase<Shape>::TensorShapeBase(gtl::ArraySlice<int64> dim_sizes) {
set_tag(REP16);
set_data_type(DT_INVALID);
TF_CHECK_OK(InitDims(dim_sizes));
}
```
In our scenario, this occurs when adding a dimension from the argument results in overflow:
```cc
template <class Shape>
Status TensorShapeBase<Shape>::InitDims(gtl::ArraySlice<int64> dim_sizes) {
...
Status status = Status::OK();
for (int64 s : dim_sizes) {
status.Update(AddDimWithStatus(internal::SubtleMustCopy(s)));
if (!status.ok()) {
return status;
}
}
}
template <class Shape>
Status TensorShapeBase<Shape>::AddDimWithStatus(int64 size) {
...
int64 new_num_elements;
if (kIsPartial && (num_elements() < 0 || size < 0)) {
new_num_elements = -1;
} else {
new_num_elements = MultiplyWithoutOverflow(num_elements(), size);
if (TF_PREDICT_FALSE(new_num_elements < 0)) {
return errors::Internal("Encountered overflow when multiplying ",
num_elements(), " with ", size,
", result: ", new_num_elements);
}
}
...
}
```
This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows.
### Patches
We have patched the issue in GitHub commit [4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60](https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60).
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 researchers from University of Virginia and University of California, Santa Barbara.
|
{'CVE-2021-29584'}
|
2022-03-03T05:13:43.995118Z
|
2021-05-21T14:26:38Z
|
LOW
| null |
{'CWE-190'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xvjm-fvxx-q3hv', 'https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29584'}
| null |
PyPI
|
PYSEC-2021-44
| null |
Products.PluggableAuthService is a pluggable Zope authentication and authorization framework. In Products.PluggableAuthService before version 2.6.0 there is an information disclosure vulnerability - everyone can list the names of roles defined in the ZODB Role Manager plugin if the site uses this plugin. The problem has been fixed in version 2.6.0. Depending on how you have installed Products.PluggableAuthService, you should change the buildout version pin to 2.6.0 and re-run the buildout, or if you used pip simply do `pip install "Products.PluggableAuthService>=2.6.0"`.
|
{'GHSA-p75f-g7gx-2r7p', 'CVE-2021-21336'}
|
2021-03-12T13:22:00Z
|
2021-03-08T21:15:00Z
| null | null | null |
{'https://pypi.org/project/Products.PluggableAuthService/', 'https://github.com/zopefoundation/Products.PluggableAuthService/commit/2dad81128250cb2e5d950cddc9d3c0314a80b4bb', 'https://github.com/zopefoundation/Products.PluggableAuthService/security/advisories/GHSA-p75f-g7gx-2r7p'}
| null |
PyPI
|
PYSEC-2011-8
| null |
The administrative interface in django.contrib.admin in Django before 1.1.3, 1.2.x before 1.2.4, and 1.3.x before 1.3 beta 1 does not properly restrict use of the query string to perform certain object filtering, which allows remote authenticated users to obtain sensitive information via a series of requests containing regular expressions, as demonstrated by a created_by__password__regex parameter.
|
{'CVE-2010-4534', 'GHSA-fwr5-q9rx-294f'}
|
2021-07-15T02:22:08.091343Z
|
2011-01-10T20:00:00Z
| null | null | null |
{'http://www.vupen.com/english/advisories/2011/0098', 'http://secunia.com/advisories/42827', 'http://archives.neohapsis.com/archives/fulldisclosure/2010-12/0580.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=665373', 'http://www.ubuntu.com/usn/USN-1040-1', 'http://www.openwall.com/lists/oss-security/2010/12/23/4', 'http://www.openwall.com/lists/oss-security/2011/01/03/5', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-January/053072.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-January/053041.html', 'http://secunia.com/advisories/42715', 'http://secunia.com/advisories/42913', 'http://www.securityfocus.com/bid/45562', 'http://www.vupen.com/english/advisories/2011/0048', 'https://github.com/advisories/GHSA-fwr5-q9rx-294f', 'http://evilpacket.net/2010/dec/22/information-leakage-django-administrative-interfac/', 'http://code.djangoproject.com/changeset/15031', 'http://www.djangoproject.com/weblog/2010/dec/22/security/', 'http://www.securityfocus.com/archive/1/515446', 'http://ngenuity-is.com/advisories/2010/dec/22/information-leakage-in-django-administrative-inter/'}
| null |
PyPI
|
PYSEC-2017-33
| null |
Salt before 2015.5.10 and 2015.8.x before 2015.8.8, when PAM external authentication is enabled, allows attackers to bypass the configured authentication service by passing an alternate service with a command sent to LocalClient.
|
{'CVE-2016-3176'}
|
2021-07-05T00:01:26.354816Z
|
2017-01-31T19:59:00Z
| null | null | null |
{'https://docs.saltstack.com/en/latest/topics/releases/2015.5.10.html', 'https://docs.saltstack.com/en/latest/topics/releases/2015.8.8.html'}
| null |
PyPI
|
GHSA-xrx6-fmxq-rjj2
|
Timing attacks in python-rsa
|
It was found that python-rsa is vulnerable to Bleichenbacher timing attacks. An attacker can use this flaw via the RSA decryption API to decrypt parts of the cipher text encrypted with RSA.
|
{'CVE-2020-25658'}
|
2022-03-03T05:13:07.521047Z
|
2021-04-30T17:35:15Z
|
MODERATE
| null |
{'CWE-385', 'CWE-327'}
|
{'https://github.com/sybrenstuvel/python-rsa/issues/165', 'https://github.com/sybrenstuvel/python-rsa', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/APF364QJ2IYLPDNVFBOEJ24QP2WLVLJP/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2SAF67KDGSOHLVFTRDOHNEAFDRSSYIWA/', 'https://github.com/sybrenstuvel/python-rsa/commit/dae8ce0d85478e16f2368b2341632775313d41ed', 'https://nvd.nist.gov/vuln/detail/CVE-2020-25658', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QY4PJWTYSOV7ZEYZVMYIF6XRU73CY6O7/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-25658'}
| null |
PyPI
|
GHSA-x4cm-m36h-c6qj
|
Moderate severity vulnerability that affects ansible
|
An input validation vulnerability was found in Ansible's mysql_user module before 2.2.1.0, which may fail to correctly change a password in certain circumstances. Thus the previous password would still be active when it should have been changed.
|
{'CVE-2016-8647'}
|
2022-03-03T05:13:39.262223Z
|
2018-10-10T17:23:33Z
|
MODERATE
| null |
{'CWE-20'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2016-8647', 'https://github.com/advisories/GHSA-x4cm-m36h-c6qj', 'https://github.com/ansible/ansible'}
| null |
PyPI
|
PYSEC-2021-430
| null |
django-helpdesk is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
|
{'CVE-2021-3945', 'GHSA-vx6v-xg64-pmr8'}
|
2021-11-19T07:28:03.664110Z
|
2021-11-13T09:15:00Z
| null | null | null |
{'https://github.com/advisories/GHSA-vx6v-xg64-pmr8', 'https://github.com/django-helpdesk/django-helpdesk/commit/2c7065e0c4296e0c692fb4a7ee19c7357583af30', 'https://huntr.dev/bounties/745f483c-70ed-441f-ab2e-7ac1305439a4'}
| null |
PyPI
|
GHSA-6p56-wp2h-9hxr
|
Buffer Overflow in NumPy
|
A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service.
|
{'CVE-2021-33430'}
|
2022-03-03T05:13:06.724432Z
|
2022-01-07T00:09:39Z
|
MODERATE
| null |
{'CWE-120'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2021-33430', 'https://github.com/numpy/numpy/issues/18939', 'https://github.com/numpy/numpy/commit/ae317fd9ff3e79c0eac357d723bfc29cbd625f2e', 'https://github.com/numpy/numpy'}
| null |
PyPI
|
GHSA-fx5c-h9f6-rv7c
|
`CHECK`-fails due to attempting to build a reference tensor
|
### Impact
A malicious user can cause a denial of service by altering a `SavedModel` such that [Grappler optimizer would attempt to build a tensor using a reference `dtype`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L1328-L1402). This would result in a crash due to a `CHECK`-fail [in the `Tensor` constructor](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/tensor.cc#L733-L781) as reference types are not allowed.
### Patches
We have patched the issue in GitHub commit [6b5adc0877de832b2a7c189532dbbbc64622eeb6](https://github.com/tensorflow/tensorflow/commit/6b5adc0877de832b2a7c189532dbbbc64622eeb6).
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-2022-23588'}
|
2022-03-03T05:13:57.640120Z
|
2022-02-09T23:28:07Z
|
MODERATE
| null |
{'CWE-617'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fx5c-h9f6-rv7c', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L1328-L1402', 'https://github.com/tensorflow/tensorflow/commit/6b5adc0877de832b2a7c189532dbbbc64622eeb6', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/tensor.cc#L733-L781', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23588'}
| null |
PyPI
|
GHSA-gf88-j2mg-cc82
|
Crash caused by integer conversion to unsigned
|
### Impact
An attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments:
```python
import tensorflow as tf
from tensorflow.python.ops import gen_boosted_trees_ops
import numpy as np
v= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0])
gen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource(
quantile_stream_resource_handle = v.handle,
epsilon = [74.82224],
num_streams = [-49],
max_elements = np.int32(586))
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40):
```cc
class BoostedTreesQuantileStreamResource : public ResourceBase {
public:
BoostedTreesQuantileStreamResource(const float epsilon,
const int64 max_elements,
const int64 num_streams)
: are_buckets_ready_(false),
epsilon_(epsilon),
num_streams_(num_streams),
max_elements_(max_elements) {
streams_.reserve(num_streams_);
...
}
}
```
However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.
### Patches
We have patched the issue in GitHub commit [8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992](https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
|
{'CVE-2021-37661'}
|
2022-03-03T05:13:57.633880Z
|
2021-08-25T14:42:28Z
|
MODERATE
| null |
{'CWE-681'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37661', 'https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992'}
| null |
PyPI
|
PYSEC-2019-163
| null |
aubio v0.4.0 to v0.4.8 has a NULL pointer dereference in new_aubio_filterbank via invalid n_filters.
|
{'CVE-2018-19801', 'GHSA-7vvr-h4p5-m7fh'}
|
2021-08-25T04:29:55.933107Z
|
2019-06-07T17:29:00Z
| null | null | null |
{'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/IYIKPYXZIWYWWNNORSKWRCFFCP6AFMRZ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OHIRMWW4JQ6UHJK4AVBJLFRLE2TPKC2W/', 'https://github.com/aubio/aubio/blob/0.4.9/ChangeLog', 'https://github.com/advisories/GHSA-7vvr-h4p5-m7fh', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00063.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00067.html'}
| null |
PyPI
|
PYSEC-2018-57
| null |
In Jupyter Notebook before 5.4.1, a maliciously forged notebook file can bypass sanitization to execute JavaScript in the notebook context. Specifically, invalid HTML is 'fixed' by jQuery after sanitization, making it dangerous.
|
{'CVE-2018-8768', 'GHSA-6cwv-x26c-w2q4'}
|
2021-07-15T02:22:16.276473Z
|
2018-03-18T06:29:00Z
| null | null | null |
{'https://github.com/advisories/GHSA-6cwv-x26c-w2q4', 'https://lists.debian.org/debian-lts-announce/2020/11/msg00033.html', 'http://openwall.com/lists/oss-security/2018/03/15/2'}
| null |
PyPI
|
PYSEC-2020-125
| null |
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
|
{'CVE-2020-15202', 'GHSA-h6fg-mjxg-hqq4'}
|
2020-10-29T16:15:00Z
|
2020-09-25T19:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575', 'https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4'}
| null |
PyPI
|
PYSEC-2021-826
| null |
TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
|
{'CVE-2021-41219', 'GHSA-4f99-p9c2-3j8x'}
|
2021-12-09T06:35:44.063409Z
|
2021-11-05T21:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4f99-p9c2-3j8x', 'https://github.com/tensorflow/tensorflow/commit/e6cf28c72ba2eb949ca950d834dd6d66bb01cfae'}
| null |
PyPI
|
PYSEC-2014-74
| null |
The App.Undo.UndoSupport.get_request_var_or_attr function in Zope before 2.12.21 and 2.13.x before 2.13.11, as used in Plone before 4.2.3 and 4.3 before beta 1, allows remote authenticated users to gain access to restricted attributes via unspecified vectors.
|
{'GHSA-879r-7f3w-8jj3', 'CVE-2012-5489'}
|
2021-07-25T23:34:58.895470Z
|
2014-09-30T14:55:00Z
| null | null | null |
{'https://plone.org/products/plone-hotfix/releases/20121106', 'https://plone.org/products/plone/security/advisories/20121106/05', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://bugs.launchpad.net/zope2/+bug/1079238', 'https://github.com/advisories/GHSA-879r-7f3w-8jj3'}
| null |
PyPI
|
GHSA-f366-4rvv-95x2
|
Buffer overflow in deprecated USB HALs and stack overflow in USB enumeration
|
### Impact
1) If an application is making use of the deprecated kit protocol HALs as the communication channel to the target device an attacker can masquerade as a device and return malformed packets of arbitrary length which the protocol stack will write to the stack. HALs intended for production use are unaffected (I2C, SWI, & SPI) as well as the hidapi HAL (hal_all_platforms_kit_hidapi.c).
2) The hidapi HAL can be made to overrun the application stack by attaching more than 10 (real or virtual) devices likely resulting in an application crash as this does not allow arbitrary data to be written to the stack.
### Patches
USB kit enumeration has been patched in v3.2.3 for the hidapi HAL (hal_all_platforms_kit_hidapi.c).
### Removal of deprecated HALs
Deprecated usb kit HALs have been removed in v3.2.3.
### Workarounds
This vulnerability is limited to users of the kit protocol which is used with Microchip kits and kit firmware to bridge communication from USB-HID to I2C or SWI. It is not expected that kits would be used in an production environment. This is an optional component for users as well so they can always compile the library without the usb support option.
### Special python packaging notes
The python package for cryptoauthlib uses date codes for identifying versions. The patched version for python packages is 20200912
### References
Please see [Microchip PSIRT](https://www.microchip.com/design-centers/embedded-security/how-to-report-potential-product-security-vulnerabilities) for Microchip's security policy and reporting procedures
### Credits
Special thanks to Ruben Santamarta of [IOActive](https://blogs.ioactive.com/) for reporting
| null |
2022-03-03T05:13:41.634950Z
|
2020-10-02T16:33:19Z
|
LOW
| null |
{'CWE-120'}
|
{'https://github.com/MicrochipTech/cryptoauthlib/security/advisories/GHSA-f366-4rvv-95x2', 'https://github.com/MicrochipTech/cryptoauthlib'}
| null |
PyPI
|
PYSEC-2021-575
| null |
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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-2021-37662', 'GHSA-f5cx-5wr3-5qrc'}
|
2021-12-09T06:35:04.272005Z
|
2021-08-12T21:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/429f009d2b2c09028647dd4bb7b3f6f414bbaad7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f5cx-5wr3-5qrc', 'https://github.com/tensorflow/tensorflow/commit/9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad'}
| null |
PyPI
|
GHSA-pfjj-m3jj-9jc9
|
Undefined behavior in `SparseTensorSliceDataset`
|
### Impact
The [implementation of `SparseTensorSliceDataset`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292) has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value:
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.SparseTensorSliceDataset(
indices=[[]],
values=[],
dense_shape=[1,1])
```
The 3 input arguments represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation.
### Patches
We have patched the issue in GitHub commit [965b97e4a9650495cda5a8c210ef6684b4b9eceb](https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
|
{'CVE-2022-21736'}
|
2022-03-03T05:13:47.536491Z
|
2022-02-09T23:43:27Z
|
HIGH
| null |
{'CWE-476'}
|
{'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', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21736', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb'}
| null |
PyPI
|
PYSEC-2021-125
| null |
A flaw was found in Ansible where the secret information present in async_files are getting disclosed when the user changes the jobdir to a world readable directory. Any secret information in an async status file will be readable by a malicious user on that system. This flaw affects Ansible Tower 3.7 and Ansible Automation Platform 1.2.
|
{'CVE-2021-3532'}
|
2022-05-04T22:49:28.055029Z
|
2021-06-09T12:15:00Z
| null | null | null |
{'https://bugzilla.redhat.com/show_bug.cgi?id=1956464'}
| null |
PyPI
|
GHSA-qhmp-h54x-38qr
|
CWE-730 Regex injection with IFTTT Plugin
|
### Impact
Anyone _publicly_ hosting the Apprise library and granting them access to the IFTTT notification service.
### Patches
Update to Apprise v0.9.5.1
```bash
# Install Apprise v0.9.5.1 from PyPI
pip install apprise==0.9.5.1
```
The patch to the problem was performed [here](https://github.com/caronc/apprise/pull/436/files).
### Workarounds
Alternatively, if upgrading is not an option, you can safely remove the following file:
- `apprise/plugins/NotifyIFTTT.py`
The above will eliminate the ability to use IFTTT, but everything else will work smoothly.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [Apprise](https://github.com/caronc/apprise/issues)
* Email me at [lead2gold@gmail.com](mailto:lead2gold@gmail.com)
### Additional Credit
Github would not allow me to additionally credit **Rasmus Petersen**, but I would like to put that here at the very least - thank you for finding and reporting this issue along with those already credited
## Additional Notes:
- Github would not allow me to add/tag the 2 CWE's this issue is applicable to (only CWE-400). The other is: CWE-730 (placed in the title)
|
{'CVE-2021-39229'}
|
2022-03-03T05:12:55.143444Z
|
2021-09-20T20:57:02Z
|
HIGH
| null |
{'CWE-400'}
|
{'https://github.com/caronc/apprise/security/advisories/GHSA-qhmp-h54x-38qr', 'https://github.com/caronc/apprise/releases/tag/v0.9.5.1', 'https://github.com/caronc/apprise/commit/e20fce630d55e4ca9b0a1e325a5fea6997489831', 'https://github.com/caronc/apprise/blob/0007eade20934ddef0aba38b8f1aad980cfff253/apprise/plugins/NotifyIFTTT.py#L356-L359', 'https://github.com/caronc/apprise', 'https://github.com/caronc/apprise/pull/436', 'https://nvd.nist.gov/vuln/detail/CVE-2021-39229'}
| null |
PyPI
|
PYSEC-2021-13
| null |
The Flask-Caching extension through 1.10.1 for Flask relies on Pickle for serialization, which may lead to remote code execution or local privilege escalation. If an attacker gains access to cache storage (e.g., filesystem, Memcached, Redis, etc.), they can construct a crafted payload, poison the cache, and execute Python code.
|
{'CVE-2021-33026', 'GHSA-656c-6cxf-hvcv'}
|
2021-05-13T23:15:00Z
|
2021-05-13T23:15:00Z
| null | null | null |
{'https://github.com/advisories/GHSA-656c-6cxf-hvcv', 'https://github.com/sh4nks/flask-caching/pull/209'}
| null |
PyPI
|
PYSEC-2021-349
| null |
XXE vulnerability in 'XML2Dict' version 0.2.2 allows an attacker to cause a denial of service.
|
{'GHSA-gp6m-vqhm-5cm5', 'CVE-2021-25951'}
|
2021-09-26T23:33:39.694828Z
|
2021-06-30T12:15:00Z
| null | null | null |
{'https://github.com/advisories/GHSA-gp6m-vqhm-5cm5', 'https://www.whitesourcesoftware.com/vulnerability-database/CVE-2021-25951'}
| null |
PyPI
|
PYSEC-2013-27
| null |
Unspecified vulnerability in salt-ssh in Salt (aka SaltStack) 0.17.0 has unspecified impact and vectors related to "insecure Usage of /tmp."
|
{'CVE-2013-4437'}
|
2021-07-25T23:34:53.727680Z
|
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-2021-719
| null |
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `BatchToSpaceNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/b5ed552fe55895aee8bd8b191f744a069957d18d/tensorflow/lite/kernels/batch_to_space_nd.cc#L81-L82). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
|
{'GHSA-cfx7-2xpc-8w4h', 'CVE-2021-29593'}
|
2021-12-09T06:35:30.927051Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/2c74674348a4708ced58ad6eb1b23354df8ee044', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfx7-2xpc-8w4h'}
| null |
PyPI
|
GHSA-7ghq-fvr3-pj2x
|
Incomplete validation in `MaxPoolGrad`
|
### Impact
An attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation:
```python
import tensorflow as tf
tf.raw_ops.MaxPoolGrad(
orig_input = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
orig_output = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
ksize = [1, 16, 16, 1],
strides = [1, 16, 18, 1],
padding = "EXPLICIT",
explicit_paddings = [0, 0, 14, 3, 15, 5, 0, 0])
```
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](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md) were incomplete.
### Patches
We have patched the issue in GitHub commit [136b51f10903e044308cf77117c0ed9871350475](https://github.com/tensorflow/tensorflow/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.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security.
|
{'CVE-2021-37674'}
|
2022-03-03T05:13:27.100453Z
|
2021-08-25T14:41:33Z
|
MODERATE
| null |
{'CWE-20'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7ghq-fvr3-pj2x', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md', 'https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37674'}
| null |
PyPI
|
PYSEC-2017-64
| null |
Cross-site scripting (XSS) vulnerability in the manage_findResult component in the search feature in Zope ZMI in Plone before 4.3.12 and 5.x before 5.0.7 allows remote attackers to inject arbitrary web script or HTML via vectors involving double quotes, as demonstrated by the obj_ids:tokens parameter. NOTE: this vulnerability exists because of an incomplete fix for CVE-2016-7140.
|
{'CVE-2016-7147'}
|
2021-07-25T23:34:49.702847Z
|
2017-02-04T05:59:00Z
| null | null | null |
{'https://plone.org/security/hotfix/20170117', 'https://www.curesec.com/blog/article/blog/Plone-XSS-186.html', 'http://www.securityfocus.com/bid/96117', 'https://plone.org/security/hotfix/20170117/non-persistent-xss-in-zope2'}
| null |
PyPI
|
PYSEC-2020-28
| null |
In Mozilla Bleach before 3.12, a mutation XSS in bleach.clean when RCDATA and either svg or math tags are whitelisted and the keyword argument strip=False.
|
{'CVE-2020-6816', 'GHSA-m6xf-fq7q-8743'}
|
2021-03-30T23:15:00Z
|
2020-03-24T22:15:00Z
| null | null | null |
{'https://www.checkmarx.com/blog/vulnerabilities-discovered-in-mozilla-bleach', 'https://advisory.checkmarx.net/advisory/CX-2020-4277', 'https://github.com/mozilla/bleach/security/advisories/GHSA-m6xf-fq7q-8743', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/EDQU2SZLZMSSACCBUBJ6NOSRNNBDYFW5/'}
| null |
PyPI
|
PYSEC-2019-175
| null |
An eval() vulnerability exists in Python Software Foundation Djblets 0.7.21 and Beanbag Review Board before 1.7.15 when parsing JSON requests.
|
{'CVE-2013-4409'}
|
2021-08-27T03:22:03.149747Z
|
2019-11-04T21:15:00Z
| null | null | null |
{'https://access.redhat.com/security/cve/cve-2013-4409', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-November/120619.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2013-4409', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-October/119831.html', 'https://security-tracker.debian.org/tracker/CVE-2013-4409', 'http://www.securityfocus.com/bid/63029', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-October/119820.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-October/119819.html', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/88059', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-October/119830.html'}
| null |
PyPI
|
GHSA-5r76-cjf4-c9qx
|
Moderate severity vulnerability that affects mayan-edms
|
An issue was discovered in Mayan EDMS before 3.0.2. The Cabinets app has XSS via a crafted cabinet label.
|
{'CVE-2018-16406'}
|
2022-03-03T05:13:50.673377Z
|
2018-09-06T03:24:57Z
|
MODERATE
| null |
{'CWE-79'}
|
{'https://gitlab.com/mayan-edms/mayan-edms/commit/48dfc06e49c7f773749e063f8cc69c95509d1c32', 'https://nvd.nist.gov/vuln/detail/CVE-2018-16406', 'https://gitlab.com/mayan-edms/mayan-edms/issues/495', 'https://gitlab.com/mayan-edms/mayan-edms', 'https://gitlab.com/mayan-edms/mayan-edms/blob/master/HISTORY.rst', 'https://github.com/advisories/GHSA-5r76-cjf4-c9qx'}
| null |
PyPI
|
GHSA-8xjq-8fcg-g5hw
|
Out-of-bounds Write in Pillow
|
An issue was discovered in Pillow before 8.1.1. In TiffDecode.c, there is a negative-offset memcpy with an invalid size.
|
{'CVE-2021-25290'}
|
2022-03-03T05:13:02.853238Z
|
2021-03-29T16:35:36Z
|
HIGH
| null |
{'CWE-787'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2021-25290', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://lists.debian.org/debian-lts-announce/2021/07/msg00018.html', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow/commit/86f02f7c70862a0954bfe8133736d352db978eaa'}
| null |
PyPI
|
GHSA-xgc3-m89p-vr3x
|
Heap buffer overflow in `Conv2DBackpropFilter`
|
### Impact
An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`:
```python
import tensorflow as tf
input_tensor = tf.constant([386.078431372549, 386.07843139643234],
shape=[1, 1, 1, 2], dtype=tf.float32)
filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32)
out_backprop = tf.constant([386.078431372549], shape=[1, 1, 1, 1],
dtype=tf.float32)
tf.raw_ops.Conv2DBackpropFilter(
input=input_tensor,
filter_sizes=filter_sizes,
out_backprop=out_backprop,
strides=[1, 66, 49, 1],
use_cudnn_on_gpu=True,
padding='VALID',
explicit_paddings=[],
data_format='NHWC',
dilations=[1, 1, 1, 1]
)
```
Alternatively, passing empty tensors also results in similar behavior:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 1, 1, 5], dtype=tf.float32)
filter_sizes = tf.constant([3, 8, 1, 1], shape=[4], dtype=tf.int32)
out_backprop = tf.constant([], shape=[0, 1, 1, 1], dtype=tf.float32)
tf.raw_ops.Conv2DBackpropFilter(
input=input_tensor,
filter_sizes=filter_sizes,
out_backprop=out_backprop,
strides=[1, 66, 49, 1],
use_cudnn_on_gpu=True,
padding='VALID',
explicit_paddings=[],
data_format='NHWC',
dilations=[1, 1, 1, 1]
)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor.
### Patches
We have patched the issue in GitHub commit [c570e2ecfc822941335ad48f6e10df4e21f11c96](https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96).
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-2021-29540'}
|
2022-03-03T05:12:50.923287Z
|
2021-05-21T14:23:09Z
|
LOW
| null |
{'CWE-120', 'CWE-787'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xgc3-m89p-vr3x', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29540', 'https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96'}
| null |
PyPI
|
GHSA-3c45-wgjp-7v9r
|
A single version of twisted does not respect the trustedRoot setting
|
Python Twisted 14.0 trustRoot is not respected in HTTP client
|
{'CVE-2014-7143'}
|
2021-08-19T16:07:48Z
|
2019-12-17T22:52:34Z
|
HIGH
| null |
{'CWE-295'}
|
{'https://exchange.xforce.ibmcloud.com/vulnerabilities/96135', 'https://security-tracker.debian.org/tracker/CVE-2014-7143', 'http://www.openwall.com/lists/oss-security/2014/09/22/2', 'https://nvd.nist.gov/vuln/detail/CVE-2014-7143', 'https://github.com/twisted/twisted/commit/3b5942252f5f3e45862a0e12b266ab29e243cc33', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2014-7143'}
| null |
PyPI
|
GHSA-pq3x-96c3-xgjg
|
Moderate severity vulnerability that affects Products.PlonePAS
|
The PlonePAS product 3.x before 3.9 and 3.2.x before 3.2.2, a product for Plone, does not properly handle the login form, which allows remote authenticated users to acquire the identity of an arbitrary user via unspecified vectors.
|
{'CVE-2009-0662'}
|
2022-03-03T05:13:50.823143Z
|
2018-07-23T19:50:29Z
|
MODERATE
| null |
{'CWE-287'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2009-0662', 'http://plone.org/products/plone/security/advisories/cve-2009-0662', 'http://secunia.com/advisories/34840', 'http://www.securityfocus.com/bid/34664', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/50061', 'https://github.com/advisories/GHSA-pq3x-96c3-xgjg', 'http://osvdb.org/53975'}
| null |
PyPI
|
GHSA-22jr-vc7j-g762
|
Potential buffer overflow in psd-tools
|
### Impact
An issue was discovered in psd-tools before 1.9.4.
The Cython implementation of RLE decoding did not check for malformed PSD input data
during decoding to the PIL.Image or NumPy format, leading to a Buffer Overflow.
### Patches
Users of psd-tools version v1.8.37 to v1.9.3 should upgrade to v1.9.4.
### Workarounds
Without Cython present on installation, buffer overflow does not occur but IndexError will be thrown. However, already installed psd-tools with Cython extention should be upgraded.
### References
https://github.com/psd-tools/psd-tools/pull/198
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [psd-tools](https://github.com/psd-tools/psd-tools/issues)
|
{'CVE-2020-10571'}
|
2022-03-23T18:15:05.888953Z
|
2020-03-16T22:46:19Z
|
CRITICAL
| null |
{'CWE-754'}
|
{'https://github.com/psd-tools/psd-tools/security/advisories/GHSA-22jr-vc7j-g762', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10571', 'https://github.com/psd-tools/psd-tools/pull/198', 'https://github.com/psd-tools/psd-tools/releases/tag/v1.9.4'}
| null |
PyPI
|
PYSEC-2021-426
| null |
The verify function in the Stark Bank Python ECDSA library (ecdsa-python) 2.0.0 fails to check that the signature is non-zero, which allows attackers to forge signatures on arbitrary messages.
|
{'CVE-2021-43572', 'GHSA-92vm-mxjf-jqf3'}
|
2021-11-16T03:58:45.828098Z
|
2021-11-09T22:15:00Z
| null | null | null |
{'https://research.nccgroup.com/2021/11/08/technical-advisory-arbitrary-signature-forgery-in-stark-bank-ecdsa-libraries/', 'https://github.com/advisories/GHSA-92vm-mxjf-jqf3', 'https://github.com/starkbank/ecdsa-python/releases/tag/v2.0.1'}
| null |
PyPI
|
PYSEC-2021-133
| 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 1.27.0, the password reset endpoint served via Synapse was vulnerable to cross-site scripting (XSS) attacks. The impact depends on the configuration of the domain that Synapse is deployed on, but may allow access to cookies and other browser data, CSRF vulnerabilities, and access to other resources served on the same domain or parent domains. This is fixed in version 1.27.0.
|
{'GHSA-246w-56m2-5899', 'CVE-2021-21332'}
|
2021-08-27T03:22:06.660066Z
|
2021-03-26T20:15:00Z
| null | null | null |
{'https://github.com/matrix-org/synapse/pull/9200', 'https://github.com/matrix-org/synapse/commit/e54746bdf7d5c831eabe4dcea76a7626f1de73df', 'https://github.com/matrix-org/synapse/releases/tag/v1.27.0', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-246w-56m2-5899'}
| null |
PyPI
|
GHSA-mr4x-c4v9-x729
|
Moderate severity vulnerability that affects aiohttp-session
|
aio-libs aiohttp-session version 2.6.0 and earlier contains a Other/Unknown vulnerability in EncryptedCookieStorage and NaClCookieStorage that can result in Non-expiring sessions / Infinite lifespan. This attack appear to be exploitable via Recreation of a cookie post-expiry with the same value.
|
{'CVE-2018-1000814'}
|
2022-03-03T05:13:31.167134Z
|
2018-12-20T22:01:46Z
|
MODERATE
| null |
{'CWE-613'}
|
{'https://github.com/aio-libs/aiohttp-session/issues/325', 'https://github.com/aio-libs/aiohttp-session', 'https://github.com/aio-libs/aiohttp-session/pull/331', 'https://github.com/advisories/GHSA-mr4x-c4v9-x729', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000814'}
| null |
PyPI
|
GHSA-77gc-v2xv-rvvh
|
Out-of-bounds Read in Pillow
|
An issue was discovered in Pillow before 8.2.0. There is an out-of-bounds read in J2kDecode, in j2ku_graya_la.
|
{'CVE-2021-25287'}
|
2022-03-07T20:48:08.139905Z
|
2021-06-08T18:49:02Z
|
CRITICAL
| null |
{'CWE-125'}
|
{'https://github.com/python-pillow/Pillow/commit/3bf5eddb89afdf690eceaa52bc4d3546ba9a5f87', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow/pull/5377#issuecomment-833821470', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25287', 'https://github.com/python-pillow/Pillow/pull/5377/commits/3bf5eddb89afdf690eceaa52bc4d3546ba9a5f87', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MQHA5HAIBOYI3R6HDWCLAGFTIQP767FL/', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.2.0.html#cve-2021-25287-cve-2021-25288-fix-oob-read-in-jpeg2kdecode', 'https://github.com/python-pillow/Pillow'}
| null |
PyPI
|
PYSEC-2021-563
| null |
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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-2021-37650', 'GHSA-f8h4-7rgh-q2gm'}
|
2021-12-09T06:35:03.262683Z
|
2021-08-12T21:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f8h4-7rgh-q2gm', 'https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876'}
| null |
PyPI
|
PYSEC-2014-62
| null |
mail_password.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allows remote authenticated users to bypass the prohibition on password changes via the forgotten password email functionality.
|
{'CVE-2013-4198'}
|
2021-07-25T23:34:47.220560Z
|
2014-03-11T19:37:00Z
| null | null | null |
{'https://bugzilla.redhat.com/show_bug.cgi?id=978480', 'http://plone.org/products/plone-hotfix/releases/20130618', 'http://seclists.org/oss-sec/2013/q3/261', 'http://plone.org/products/plone/security/advisories/20130618-announcement'}
| null |
PyPI
|
PYSEC-2010-21
| null |
FTPServer.py in pyftpdlib before 0.2.0 does not increment the attempted_logins count for a USER command that specifies an invalid username, which makes it easier for remote attackers to obtain access via a brute-force attack.
|
{'CVE-2007-6737'}
|
2010-10-20T04:00:00Z
|
2010-10-19T20:00:00Z
| null | null | null |
{'http://code.google.com/p/pyftpdlib/issues/detail?id=20', 'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY', 'http://code.google.com/p/pyftpdlib/source/diff?spec=svn23&r=23&format=side&path=/trunk/pyftpdlib/FTPServer.py', 'http://code.google.com/p/pyftpdlib/source/detail?r=23'}
| null |
PyPI
|
PYSEC-2021-830
| null |
TensorFlow is an open source platform for machine learning. In affected versions the implementation of `FusedBatchNorm` kernels is vulnerable to a heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
|
{'CVE-2021-41223', 'GHSA-f54p-f6jp-4rhr'}
|
2021-12-09T06:35:44.623762Z
|
2021-11-05T21:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/aab9998916c2ffbd8f0592059fad352622f89cda', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f54p-f6jp-4rhr'}
| null |
PyPI
|
PYSEC-2020-133
| null |
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
|
{'CVE-2020-15210', 'GHSA-x9j7-x98r-r4w2'}
|
2020-10-29T16:15:00Z
|
2020-09-25T19:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2', 'https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'}
| null |
PyPI
|
PYSEC-2018-41
| null |
Ansible before versions 2.3.1.0 and 2.4.0.0 fails to properly mark lookup-plugin results as unsafe. If an attacker could control the results of lookup() calls, they could inject Unicode strings to be parsed by the jinja2 templating system, resulting in code execution. By default, the jinja2 templating language is now marked as 'unsafe' and is not evaluated.
|
{'GHSA-w578-j992-554x', 'CVE-2017-7481'}
|
2021-07-02T02:41:33.849138Z
|
2018-07-19T13:29:00Z
| null | null | null |
{'https://access.redhat.com/errata/RHSA-2017:1244', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2017-7481', 'https://usn.ubuntu.com/4072-1/', 'https://access.redhat.com/errata/RHSA-2017:1476', 'https://access.redhat.com/errata/RHSA-2017:1599', 'https://github.com/ansible/ansible/commit/ed56f51f185a1ffd7ea57130d260098686fcc7c2', 'https://access.redhat.com/errata/RHSA-2017:2524', 'https://access.redhat.com/errata/RHSA-2017:1334', 'https://github.com/advisories/GHSA-w578-j992-554x', 'https://access.redhat.com/errata/RHSA-2017:1499', 'https://lists.debian.org/debian-lts-announce/2021/01/msg00023.html', 'http://www.securityfocus.com/bid/98492'}
| null |
PyPI
|
GHSA-f248-v4qh-x2r6
|
Improper Certificate Validation in blackduck
|
Synopsys hub-rest-api-python (aka blackduck on PyPI) version 0.0.25 - 0.0.52 does not validate SSL certificates in certain cases.
|
{'CVE-2020-27589'}
|
2022-03-03T05:13:47.871644Z
|
2021-04-20T16:29:41Z
|
HIGH
| null |
{'CWE-295'}
|
{'https://www.optiv.com/explore-optiv-insights/source-zero/certificate-validation-disabled-black-duck-api-wrapper', 'https://github.com/blackducksoftware/hub-rest-api-python/pull/113/commits/273b27d0de1004389dd8cf43c40b1197c787e7cd', 'https://community.synopsys.com/s/question/0D52H00005JCZAXSA5/announcement-black-duck-defect-identified', 'https://pypi.org/project/blackduck/', 'https://github.com/blackducksoftware/hub-rest-api-python', 'https://nvd.nist.gov/vuln/detail/CVE-2020-27589'}
| null |
PyPI
|
PYSEC-2017-72
| null |
sosreport 3.2 uses weak permissions for generated sosreport archives, which allows local users with access to /var/tmp/ to obtain sensitive information by reading the contents of the archive.
|
{'CVE-2015-3171'}
|
2021-07-25T23:34:55.539428Z
|
2017-07-25T18:29:00Z
| null | null | null |
{'https://bugzilla.redhat.com/show_bug.cgi?id=1218658', 'https://github.com/sosreport/sos/commit/d7759d3ddae5fe99a340c88a1d370d65cfa73fd6'}
| null |
PyPI
|
PYSEC-2013-31
| null |
The X509Extension in pyOpenSSL before 0.13.1 does not properly handle a '\0' character in a domain name in the Subject Alternative Name field of an X.509 certificate, which allows man-in-the-middle attackers to spoof arbitrary SSL servers via a crafted certificate issued by a legitimate Certification Authority.
|
{'CVE-2013-4314'}
|
2021-08-27T03:22:17.495539Z
|
2013-09-30T21:55:00Z
| null | null | null |
{'https://mail.python.org/pipermail/pyopenssl-users/2013-September/000478.html', 'http://www.openwall.com/lists/oss-security/2013/09/06/2', 'http://www.debian.org/security/2013/dsa-2763', 'https://bugzilla.redhat.com/show_bug.cgi?id=1005325', 'http://lists.opensuse.org/opensuse-updates/2013-11/msg00015.html', 'http://www.ubuntu.com/usn/USN-1965-1'}
| null |
PyPI
|
PYSEC-2021-471
| null |
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.CTCGreedyDecoder`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1615440b17b364b875eb06f43d087381f1460a65/tensorflow/core/kernels/ctc_decoder_ops.cc#L37-L50) has a `CHECK_LT` inserted to validate some invariants. When this condition is false, the program aborts, instead of returning a valid error to the user. This abnormal termination can be weaponized in denial of service attacks. 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-fphq-gw9m-ghrv', 'CVE-2021-29543'}
|
2021-12-09T06:34:50.046503Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fphq-gw9m-ghrv', 'https://github.com/tensorflow/tensorflow/commit/ea3b43e98c32c97b35d52b4c66f9107452ca8fb2'}
| null |
PyPI
|
GHSA-p86x-652p-6385
|
Incorrect Default Permissions in keyring
|
Python keyring lib before 0.10 created keyring files with world-readable permissions.
|
{'CVE-2012-5577'}
|
2022-03-03T05:13:31.123119Z
|
2020-03-11T21:36:38Z
|
HIGH
| null |
{'CWE-276'}
|
{'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2012-5577', 'https://bitbucket.org/kang/python-keyring-lib/commits/049cd181470f1ee6c540e1d64acf1def7b1de0c1', 'http://www.openwall.com/lists/oss-security/2012/11/27/3', 'https://nvd.nist.gov/vuln/detail/CVE-2012-5577', 'https://bitbucket.org/kang/python-keyring-lib/issue/67/set-go-rwx-on-keyring_passcfg', 'https://security-tracker.debian.org/tracker/CVE-2012-5577'}
| null |
PyPI
|
PYSEC-2019-122
| null |
Sqla_yaml_fixtures 0.9.1 allows local users to execute arbitrary python code via the fixture_text argument in sqla_yaml_fixtures.load.
|
{'GHSA-2x54-j4m3-r6wx', 'CVE-2019-3575'}
|
2019-01-31T18:00:00Z
|
2019-01-03T19:29:00Z
| null | null | null |
{'https://github.com/advisories/GHSA-2x54-j4m3-r6wx', 'https://github.com/schettino72/sqla_yaml_fixtures/issues/20'}
| null |
PyPI
|
GHSA-mwgj-7x7j-6966
|
Deserialization of Untrusted Data in ParlAI
|
Due to use of unsafe YAML deserialization logic, an attacker with the ability to modify local YAML configuration files could provide malicious input, resulting in remote code execution or similar risks. This issue affects ParlAI prior to v1.1.0.
|
{'CVE-2021-24040'}
|
2022-03-03T05:13:40.087571Z
|
2021-09-13T20:06:14Z
|
MODERATE
| null |
{'CWE-502'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2021-24040', 'https://github.com/facebookresearch/ParlAI', 'https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg', 'https://github.com/facebookresearch/ParlAI/releases/tag/v1.1.0', 'http://packetstormsecurity.com/files/164136/Facebook-ParlAI-1.0.0-Code-Execution-Deserialization.html'}
| null |
PyPI
|
GHSA-85rr-4rh9-hhwh
|
Memory leak in Nanopb
|
### Impact
Decoding specifically formed message can leak memory if dynamic allocation is enabled and an oneof field contains a static submessage that contains a dynamic field, and the message being decoded contains the submessage multiple times. This is rare in normal messages, but it is a concern when untrusted data is parsed.
### Patches
Preliminary patch is [available on git](https://github.com/nanopb/nanopb/commit/edf6dcbffee4d614ac0c2c1b258ab95185bdb6e9) and problem will be patched in versions 0.3.9.7 and 0.4.4 once testing has been completed.
### Workarounds
Following workarounds are available:
* Set the option `no_unions` for the oneof field. This will generate fields as separate instead of C union, and avoids triggering the problematic code.
* Set the type of the submessage field inside oneof to `FT_POINTER`. This way the whole submessage will be dynamically allocated and the problematic code is not executed.
* Use an arena allocator for nanopb, to make sure all memory can be released afterwards.
### References
Bug report: https://github.com/nanopb/nanopb/issues/615
### For more information
If you have any questions or comments about this advisory, comment on the bug report linked above.
|
{'CVE-2020-26243'}
|
2022-03-03T05:14:19.479674Z
|
2020-11-25T16:53:27Z
|
MODERATE
| null |
{'CWE-20', 'CWE-119'}
|
{'https://github.com/nanopb/nanopb/security/advisories/GHSA-85rr-4rh9-hhwh', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26243', 'https://github.com/nanopb/nanopb/blob/2b48a361786dfb1f63d229840217a93aae064667/CHANGELOG.txt', 'https://github.com/nanopb/nanopb/issues/615', 'https://github.com/nanopb/nanopb/commit/4fe23595732b6f1254cfc11a9b8d6da900b55b0c'}
| null |
PyPI
|
GHSA-384w-5v3f-q499
|
Base class whitelist configuration ignored in OAuthenticator
|
### Impact
__What goes wrong?__
The deprecated (in jupyterhub 1.2) configuration `Authenticator.whitelist`, which should be transparently mapped to `Authenticator.allowed_users` with a warning, is instead ignored by OAuthenticator classes, resulting in the same behavior as if this configuration has not been set. If this is the only mechanism of authorization restriction (i.e. no group or team restrictions in configuration) then all authenticated users will be allowed. Provider-based restrictions, including deprecated values such as `GitHubOAuthenticator.org_whitelist` are **not** affected.
__Who is impacted?__
All users of OAuthenticator 0.12.0 and 0.12.1 with JupyterHub 1.2 (JupyterHub Helm chart 0.10.0-0.10.5) who use the `admin.whitelist.users` configuration in the jupyterhub helm chart or the `c.Authenticator.whitelist` configuration directly. Users of other deprecated configuration, e.g. `c.GitHubOAuthenticator.team_whitelist` are **not** affected.
If you see a log line like this and expect a specific list of allowed usernames:
```
[I 2020-11-27 16:51:54.528 JupyterHub app:1717] Not using allowed_users. Any authenticated user will be allowed.
```
you are likely affected.
### Patches
- Replacing deprecated `c.Authenticator.whitelist = ...` with `c.Authenticator.allowed_users = ...` avoids the issue.
- Update oauthenticator to 0.12.2
- Update jupyterhub helm chart to 0.10.6
If any users have been authorized during this time who should not have been, they must be deleted via the API or admin interface, [per the documentation](https://jupyterhub.readthedocs.io/en/1.2.2/getting-started/authenticators-users-basics.html#add-or-remove-users-from-the-hub).
### Workarounds
Replacing `c.Authenticator.whitelist = ...` with `c.Authenticator.allowed_users = ...` avoids the issue.
In the jupyterhub helm chart prior to 0.10.6, this can be done via `hub.extraConfig`:
```yaml
auth:
allowedUsers:
- user1
- user2
hub:
extraConfig:
allowedUsers: |
# set new field not exposed in helm chart < 0.10.6
set_config_if_not_none(c.Authenticator, "allowed_users", "auth.allowedUsers")
```
### For more information
If you have any questions or comments about this advisory:
* Open a thread [on the Jupyter forum](http://discourse.jupyter.org)
* Email us at [security@ipython.org](mailto:security@ipython.org)
|
{'CVE-2020-26250'}
|
2022-03-03T05:12:02.627667Z
|
2020-12-01T20:25:00Z
|
HIGH
| null |
{'CWE-863'}
|
{'https://github.com/jupyterhub/oauthenticator/security/advisories/GHSA-384w-5v3f-q499', 'https://github.com/jupyterhub/oauthenticator/blob/master/docs/source/changelog.md#0122---2020-11-30', 'https://github.com/jupyterhub/oauthenticator/commit/a4aac191c16cf6281f3d346615aefa75702b02d7', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26250', 'https://jupyterhub.readthedocs.io/en/1.2.2/getting-started/authenticators-users-basics.html#add-or-remove-users-from-the-hub'}
| null |
PyPI
|
PYSEC-2022-42
| null |
OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. In affected versions chat participants can spoof their channel leave message, tricking others into assuming they left the chatroom.
|
{'CVE-2022-21691', 'GHSA-w9m4-7w72-r766'}
|
2022-03-09T00:16:43.223227Z
|
2022-01-18T22:15:00Z
| null | null | null |
{'https://github.com/onionshare/onionshare/releases/tag/v2.5', 'https://github.com/onionshare/onionshare/security/advisories/GHSA-w9m4-7w72-r766'}
| null |
PyPI
|
GHSA-gcvh-66ff-4mwm
|
`CHECK`-failures in Tensorflow
|
### Impact
The [implementation of `MapStage`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/map_stage_op.cc#L519-L550) is vulnerable a `CHECK`-fail if the key tensor is not a scalar:
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.MapStage(
key = tf.constant(value=[4], shape= (1,2), dtype=tf.int64),
indices = np.array([[6]]),
values = np.array([-60]),
dtypes = [tf.int64], capacity=0, memory_limit=0,
container='', shared_name='', name=None
)
```
### Patches
We have patched the issue in GitHub commit [f57315566d7094f322b784947093406c2aea0d7d](https://github.com/tensorflow/tensorflow/commit/f57315566d7094f322b784947093406c2aea0d7d).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
~
|
{'CVE-2022-21734'}
|
2022-03-03T05:13:56.683466Z
|
2022-02-10T00:21:12Z
|
MODERATE
| null |
{'CWE-617', 'CWE-843'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gcvh-66ff-4mwm', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21734', 'https://github.com/tensorflow/tensorflow/commit/f57315566d7094f322b784947093406c2aea0d7d', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/map_stage_op.cc#L519-L550'}
| null |
PyPI
|
PYSEC-2020-90
| null |
A privilege escalation issue in plone.app.contenttypes in Plone 4.3 through 5.2.1 allows users to PUT (overwrite) some content without needing write permission.
|
{'CVE-2020-7941'}
|
2020-01-24T22:44:00Z
|
2020-01-23T21:15:00Z
| null | null | null |
{'https://plone.org/security/hotfix/20200121', 'https://plone.org/security/hotfix/20200121/privilege-escalation-for-overwriting-content', 'http://www.openwall.com/lists/oss-security/2020/01/24/1', 'https://www.openwall.com/lists/oss-security/2020/01/22/1'}
| null |
PyPI
|
PYSEC-2018-16
| null |
An issue was discovered in Mayan EDMS before 3.0.2. The Appearance app sets window.location directly, leading to XSS.
|
{'CVE-2018-16405'}
|
2021-06-16T00:03:23.682256Z
|
2018-09-03T19:29:00Z
| null | null | null |
{'https://gitlab.com/mayan-edms/mayan-edms/issues/494', 'https://gitlab.com/mayan-edms/mayan-edms/blob/master/HISTORY.rst', 'https://gitlab.com/mayan-edms/mayan-edms/commit/9ebe80595afe4fdd1e2c74358d6a9421f4ce130e'}
| null |
PyPI
|
PYSEC-2021-867
| null |
Gerapy is a distributed crawler management framework. Gerapy prior to version 0.9.8 is vulnerable to remote code execution, and this issue is patched in version 0.9.8.
|
{'CVE-2021-43857', 'GHSA-9w7f-m4j4-j3xw'}
|
2022-01-07T19:22:06.271375Z
|
2021-12-27T19:15:00Z
| null | null | null |
{'https://github.com/Gerapy/Gerapy/issues/219', 'http://packetstormsecurity.com/files/165459/Gerapy-0.9.7-Remote-Code-Execution.html', 'https://github.com/Gerapy/Gerapy/security/advisories/GHSA-9w7f-m4j4-j3xw', 'https://github.com/Gerapy/Gerapy/commit/49bcb19be5e0320e7e1535f34fe00f16a3cf3b28'}
| null |
PyPI
|
PYSEC-2014-35
| null |
gtbn.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote authenticated users with certain permissions to bypass the Python sandbox and execute arbitrary Python code via unspecified vectors.
|
{'CVE-2012-5493'}
|
2021-09-01T08:44:29.732595Z
|
2014-09-30T14:55:00Z
| null | null | null |
{'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone/security/advisories/20121106/09', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone-hotfix/releases/20121106'}
| null |
PyPI
|
PYSEC-2021-534
| 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'}
|
2021-12-09T06:34:59.860176Z
|
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-8h2j-cgx8-6xv7
|
Cross-Site Request Forgery (CSRF) in FastAPI
|
### Impact
FastAPI versions lower than `0.65.2` that used cookies for authentication in path operations that received JSON payloads sent by browsers were vulnerable to a Cross-Site Request Forgery (CSRF) attack.
In versions lower than `0.65.2`, FastAPI would try to read the request payload as JSON even if the `content-type` header sent was not set to `application/json` or a compatible JSON media type (e.g. `application/geo+json`).
So, a request with a content type of `text/plain` containing JSON data would be accepted and the JSON data would be extracted.
But requests with content type `text/plain` are exempt from [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) preflights, for being considered [Simple requests](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS#simple_requests). So, the browser would execute them right away including cookies, and the text content could be a JSON string that would be parsed and accepted by the FastAPI application.
### Patches
This is fixed in FastAPI `0.65.2`.
The request data is now parsed as JSON only if the `content-type` header is `application/json` or another JSON compatible media type like `application/geo+json`.
### Workarounds
It's best to upgrade to the latest FastAPI.
But still, it would be possible to add a middleware or a dependency that checks the `content-type` header and aborts the request if it is not `application/json` or another JSON compatible content type.
### References
* [CORS on Mozilla web docs](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS)
* [This answer on StackExchange](https://security.stackexchange.com/questions/157528/ways-to-bypass-browsers-cors-policy/157531#157531)
* [OWASP CSRF](https://owasp.org/www-community/attacks/csrf)
* Fixed in PR [#2118](https://github.com/tiangolo/fastapi/pull/2118)
### For more information
If you have any questions or comments, write to [security@tiangolo.com](mailto:security@tiangolo.com)
|
{'CVE-2021-32677'}
|
2022-03-03T05:13:41.740751Z
|
2021-06-10T15:43:54Z
|
HIGH
| null |
{'CWE-352'}
|
{'https://github.com/tiangolo/fastapi/security/advisories/GHSA-8h2j-cgx8-6xv7', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32677', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MATAWX25TYKNEKLDMKWNLYDB34UWTROA/', 'https://github.com/tiangolo/fastapi/commit/fa7e3c996edf2d5482fff8f9d890ac2390dede4d'}
| null |
PyPI
|
PYSEC-2021-164
| 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.QuantizedConv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/00e9a4d67d76703fa1aee33dac582acf317e0e81/tensorflow/core/kernels/quantized_conv_ops.cc#L257-L259) 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-x4g7-fvjj-prg8', 'CVE-2021-29527'}
|
2021-08-27T03:22:26.181060Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x4g7-fvjj-prg8', 'https://github.com/tensorflow/tensorflow/commit/cfa91be9863a91d5105a3b4941096044ab32036b'}
| null |
PyPI
|
GHSA-6cwv-x26c-w2q4
|
Jupyter Notebook file bypasses sanitization, executes JavaScript
|
In Jupyter Notebook before 5.4.1, a maliciously forged notebook file can bypass sanitization to execute JavaScript in the notebook context. Specifically, invalid HTML is 'fixed' by jQuery after sanitization, making it dangerous.
|
{'CVE-2018-8768'}
|
2022-04-26T20:45:14.420136Z
|
2018-07-12T12:00:00Z
|
HIGH
| null | null |
{'https://lists.debian.org/debian-lts-announce/2020/11/msg00033.html', 'https://nvd.nist.gov/vuln/detail/CVE-2018-8768', 'http://openwall.com/lists/oss-security/2018/03/15/2'}
| null |
PyPI
|
PYSEC-2021-52
| null |
An issue was discovered in through SaltStack Salt before 3002.5. The jinja renderer does not protect against server side template injection attacks.
|
{'CVE-2021-25283'}
|
2021-03-31T14:15:00Z
|
2021-02-27T05:15:00Z
| null | null | null |
{'https://github.com/saltstack/salt/releases', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YOGNT2XWPOYV7YT75DN7PS4GIYWFKOK5/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FUGLOJ6NXLCIFRD2JTXBYQEMAEF2B6XH/', 'https://saltproject.io/security_announcements/active-saltstack-cve-release-2021-feb-25/', 'https://security.gentoo.org/glsa/202103-01', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7GRVZ5WAEI3XFN2BDTL6DDXFS5HYSDVB/'}
| null |
PyPI
|
PYSEC-2021-308
| null |
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version.
|
{'CVE-2021-37686', 'GHSA-mhhc-q96p-mfm9'}
|
2021-08-27T03:22:47.333103Z
|
2021-08-12T22:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mhhc-q96p-mfm9'}
| null |
PyPI
|
GHSA-57h3-9rgr-c24m
|
Out of bounds write in Pillow
|
An issue was discovered in Pillow before 8.1.1. TiffDecode has a heap-based buffer overflow when decoding crafted YCbCr files because of certain interpretation conflicts with LibTIFF in RGBA mode. NOTE: this issue exists because of an incomplete fix for CVE-2020-35654.
|
{'CVE-2021-25289'}
|
2021-12-02T17:48:12Z
|
2021-03-29T16:35:16Z
|
HIGH
| null |
{'CWE-787'}
|
{'https://github.com/python-pillow/Pillow/', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow/commit/3fee28eb9479bf7d59e0fa08068f9cc4a6e2f04c', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25289'}
| null |
PyPI
|
PYSEC-2021-758
| null |
TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
|
{'GHSA-c5x2-p679-95wc', 'CVE-2021-37647'}
|
2021-12-09T06:35:36.390179Z
|
2021-08-12T19:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc', 'https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7'}
| null |
PyPI
|
PYSEC-2017-25
| null |
XML External Entity (XXE) vulnerability in PySAML2 4.4.0 and earlier allows remote attackers to read arbitrary files via a crafted SAML XML request or response.
|
{'GHSA-c2vx-49jm-h3f6', 'CVE-2016-10149'}
|
2021-07-05T00:01:25.139700Z
|
2017-03-24T14:59:00Z
| null | null | null |
{'http://www.securityfocus.com/bid/97692', 'http://www.debian.org/security/2017/dsa-3759', 'https://access.redhat.com/errata/RHSA-2017:0937', 'https://github.com/rohe/pysaml2/issues/366', 'https://github.com/rohe/pysaml2/commit/6e09a25d9b4b7aa7a506853210a9a14100b8bc9b', 'http://www.openwall.com/lists/oss-security/2017/01/19/5', 'https://github.com/advisories/GHSA-c2vx-49jm-h3f6', 'https://github.com/rohe/pysaml2/pull/379', 'https://access.redhat.com/errata/RHSA-2017:0938', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=850716', 'https://access.redhat.com/errata/RHSA-2017:0936'}
| null |
PyPI
|
PYSEC-2015-18
| null |
The utils.html.strip_tags function in Django 1.6.x before 1.6.11, 1.7.x before 1.7.7, and 1.8.x before 1.8c1, when using certain versions of Python, allows remote attackers to cause a denial of service (infinite loop) by increasing the length of the input string.
|
{'CVE-2015-2316'}
|
2021-09-01T08:35:41.398239Z
|
2015-03-25T14:59:00Z
| null | null | null |
{'http://lists.opensuse.org/opensuse-updates/2015-04/msg00001.html', 'http://www.oracle.com/technetwork/topics/security/bulletinapr2015-2511959.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-April/155421.html', 'https://www.djangoproject.com/weblog/2015/mar/18/security-releases/', 'http://www.ubuntu.com/usn/USN-2539-1', 'http://www.securityfocus.com/bid/73322'}
| null |
PyPI
|
PYSEC-2020-308
| null |
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
|
{'CVE-2020-15193', 'GHSA-rjjg-hgv6-h69v'}
|
2021-12-09T06:35:12.446415Z
|
2020-09-25T19:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'}
| null |
PyPI
|
PYSEC-2013-9
| null |
pip before 1.3 allows local users to overwrite arbitrary files via a symlink attack on a file in the /tmp/pip-build temporary directory.
|
{'CVE-2013-1888'}
|
2021-07-05T00:01:24.378636Z
|
2013-08-17T06:54:00Z
| null | null | null |
{'http://lists.fedoraproject.org/pipermail/package-announce/2013-May/105952.html', 'https://github.com/pypa/pip/pull/780/files', 'https://github.com/pypa/pip/pull/734/files', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-May/105989.html', 'https://github.com/pypa/pip/issues/725', 'http://www.openwall.com/lists/oss-security/2013/03/22/10', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-May/106311.html'}
| null |
PyPI
|
GHSA-fpcp-9h7m-ffpx
|
Null pointer dereference in TensorFlow
|
### Impact
When [building an XLA compilation cache](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/jit/xla_platform_info.cc#L43-L104), if default settings are used, TensorFlow triggers a null pointer dereference:
```cc
string allowed_gpus =
flr->config_proto()->gpu_options().visible_device_list();
```
In the default scenario, all devices are allowed, so `flr->config_proto` is `nullptr`.
### Patches
We have patched the issue in GitHub commit [e21af685e1828f7ca65038307df5cc06de4479e8](https://github.com/tensorflow/tensorflow/commit/e21af685e1828f7ca65038307df5cc06de4479e8).
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-2022-23595'}
|
2022-03-03T05:13:33.436421Z
|
2022-02-09T23:33:17Z
|
MODERATE
| null |
{'CWE-476'}
|
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fpcp-9h7m-ffpx', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23595', 'https://github.com/tensorflow/tensorflow/commit/e21af685e1828f7ca65038307df5cc06de4479e8', 'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/jit/xla_platform_info.cc#L43-L104'}
| null |
PyPI
|
PYSEC-2022-116
| null |
Tensorflow is an Open Source Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
|
{'CVE-2022-21737', 'GHSA-f2vv-v9cg-qhh7'}
|
2022-03-09T00:18:24.620644Z
|
2022-02-03T14:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc', 'https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2vv-v9cg-qhh7'}
| null |
PyPI
|
PYSEC-2019-159
| null |
An XSSI (cross-site inclusion) vulnerability in Jupyter Notebook before 5.7.6 allows inclusion of resources on malicious pages when visited by users who are authenticated with a Jupyter server. Access to the content of resources has been demonstrated with Internet Explorer through capturing of error messages, though not reproduced with other browsers. This occurs because Internet Explorer's error messages can include the content of any invalid JavaScript that was encountered.
|
{'CVE-2019-9644'}
|
2021-07-15T02:22:16.344384Z
|
2019-03-12T09:29:00Z
| null | null | null |
{'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/VMDPJBVXOVO6LYGAT46VZNHH6JKSCURO/', 'https://github.com/jupyter/notebook/compare/f3f00df...05aa4b2', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UP5RLEES2JBBNSNLBR65XM6PCD4EMF7D/'}
| null |
PyPI
|
PYSEC-2022-39
| null |
OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. Affected versions of the desktop application were found to be vulnerable to denial of service via an undisclosed vulnerability in the QT image parsing. Roughly 20 bytes lead to 2GB memory consumption and this can be triggered multiple times. To be abused, this vulnerability requires rendering in the history tab, so some user interaction is required. An adversary with knowledge of the Onion service address in public mode or with authentication in private mode can perform a Denial of Service attack, which quickly results in out-of-memory for the server. This requires the desktop application with rendered history, therefore the impact is only elevated. This issue has been patched in version 2.5.
|
{'CVE-2022-21688', 'GHSA-x7wr-283h-5h2v'}
|
2022-03-09T00:16:43.060055Z
|
2022-01-18T22:15:00Z
| null | null | null |
{'https://github.com/onionshare/onionshare/security/advisories/GHSA-x7wr-283h-5h2v', 'https://github.com/onionshare/onionshare/releases/tag/v2.5'}
| null |
PyPI
|
PYSEC-2018-82
| null |
There is a vulnerability in load() method in definitions/parser.py in the Danijar Hafner definitions package for Python. It can execute arbitrary python commands resulting in command execution.
|
{'GHSA-v4x4-98cg-wr4g', 'CVE-2018-20325'}
|
2021-08-27T03:21:57.237018Z
|
2018-12-21T23:29:00Z
| null | null | null |
{'https://github.com/danijar/definitions/issues/14', 'https://github.com/advisories/GHSA-v4x4-98cg-wr4g'}
| null |
PyPI
|
PYSEC-2021-373
| null |
Cobbler before 3.3.0 allows log poisoning, and resultant Remote Code Execution, via an XMLRPC method that logs to the logfile for template injection.
|
{'CVE-2021-40323', 'GHSA-cpqf-3c3r-c9g2'}
|
2021-10-19T21:47:31.690816Z
|
2021-10-04T06:15:00Z
| null | null | null |
{'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://github.com/advisories/GHSA-cpqf-3c3r-c9g2', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0'}
| null |
PyPI
|
GHSA-6qgm-fv6v-rfpv
|
Overflow/denial of service in `tf.raw_ops.ReverseSequence`
|
### Impact
The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service.
```python
import tensorflow as tf
input = tf.zeros([1, 1, 1], dtype=tf.int32)
seq_lengths = tf.constant([0], shape=[1], dtype=tf.int32)
tf.raw_ops.ReverseSequence(
input=input, seq_lengths=seq_lengths, seq_dim=-2, batch_dim=0)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid.
Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`.
### Patches
We have patched the issue in GitHub commit [ecf768cbe50cedc0a45ce1ee223146a3d3d26d23](https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
|
{'CVE-2021-29575'}
|
2022-03-03T05:13:20.049464Z
|
2021-05-21T14:26:13Z
|
LOW
| null |
{'CWE-120', 'CWE-119'}
|
{'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29575'}
| null |
PyPI
|
PYSEC-2021-689
| 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.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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-ph87-fvjr-v33w', 'CVE-2021-29563'}
|
2021-12-09T06:35:25.642142Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w'}
| null |
PyPI
|
GHSA-vqj2-4v8m-8vrq
|
Insecure Temporary File in mlflow
|
mlflow prior to 1.23.1 contains an insecure temporary file. The insecure function `tempfile.mktemp()` is deprecated and `mkstemp()` should be used instead.
|
{'CVE-2022-0736'}
|
2022-03-07T20:47:28.413101Z
|
2022-02-24T00:00:54Z
|
HIGH
| null |
{'CWE-668', 'CWE-377'}
|
{'https://github.com/mlflow/mlflow', 'https://nvd.nist.gov/vuln/detail/CVE-2022-0736', 'https://huntr.dev/bounties/e5384764-c583-4dec-a1d8-4697f4e12f75', 'https://github.com/mlflow/mlflow/commit/61984e6843d2e59235d82a580c529920cd8f3711'}
| null |
PyPI
|
PYSEC-2011-20
| null |
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.
|
{'GHSA-2p78-8hh6-96xc', 'CVE-2011-1157'}
|
2021-08-27T03:22:03.796807Z
|
2011-04-11T18:55:00Z
| null | null | null |
{'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://support.novell.com/security/cve/CVE-2011-1157.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=684877', 'http://secunia.com/advisories/43730', 'http://www.securityfocus.com/bid/46867', 'https://code.google.com/p/feedparser/issues/detail?id=254'}
| null |
PyPI
|
PYSEC-2021-723
| null |
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SpaceToBatchNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
|
{'GHSA-v52p-hfjf-wg88', 'CVE-2021-29597'}
|
2021-12-09T06:35:31.566408Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v52p-hfjf-wg88', 'https://github.com/tensorflow/tensorflow/commit/6d36ba65577006affb272335b7c1abd829010708'}
| null |
PyPI
|
GHSA-232r-66cg-79px
|
Paramiko not properly checking authention before processing other requests
|
transport.py in the SSH server implementation of Paramiko before 1.17.6, 1.18.x before 1.18.5, 2.0.x before 2.0.8, 2.1.x before 2.1.5, 2.2.x before 2.2.3, 2.3.x before 2.3.2, and 2.4.x before 2.4.1 does not properly check whether authentication is completed before processing other requests, as demonstrated by channel-open. A customized SSH client can simply skip the authentication step.
|
{'CVE-2018-7750'}
|
2022-04-26T20:45:08.475857Z
|
2018-07-12T20:29:30Z
|
CRITICAL
| null |
{'CWE-287'}
|
{'https://github.com/paramiko/paramiko', 'https://access.redhat.com/errata/RHSA-2018:1525', 'https://lists.debian.org/debian-lts-announce/2021/12/msg00025.html', 'https://access.redhat.com/errata/RHSA-2018:1125', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7750', 'https://access.redhat.com/errata/RHSA-2018:1328', 'https://access.redhat.com/errata/RHSA-2018:1274', 'https://usn.ubuntu.com/3603-2/', 'https://lists.debian.org/debian-lts-announce/2018/10/msg00018.html', 'https://access.redhat.com/errata/RHSA-2018:1213', 'https://access.redhat.com/errata/RHSA-2018:0646', 'https://access.redhat.com/errata/RHSA-2018:1124', 'https://www.exploit-db.com/exploits/45712/', 'https://github.com/paramiko/paramiko/issues/1175', 'https://github.com/paramiko/paramiko/blob/master/sites/www/changelog.rst', 'https://access.redhat.com/errata/RHSA-2018:1972', 'https://github.com/advisories/GHSA-232r-66cg-79px', 'https://usn.ubuntu.com/3603-1/', 'https://github.com/paramiko/paramiko/commit/fa29bd8446c8eab237f5187d28787727b4610516', 'http://www.securityfocus.com/bid/103713', 'https://access.redhat.com/errata/RHSA-2018:0591'}
| null |
PyPI
|
GHSA-xcwj-wfcm-m23c
|
Invalid validation in `SparseMatrixSparseCholesky`
|
### Impact
An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`:
```python
import tensorflow as tf
import numpy as np
from tensorflow.python.ops.linalg.sparse import sparse_csr_matrix_ops
indices_array = np.array([[0, 0]])
value_array = np.array([-10.0], dtype=np.float32)
dense_shape = [1, 1]
st = tf.SparseTensor(indices_array, value_array, dense_shape)
input = sparse_csr_matrix_ops.sparse_tensor_to_csr_sparse_matrix(
st.indices, st.values, st.dense_shape)
permutation = tf.constant([], shape=[1, 0], dtype=tf.int32)
tf.raw_ops.SparseMatrixSparseCholesky(input=input, permutation=permutation, type=tf.float32)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments:
```cc
void Compute(OpKernelContext* ctx) final {
...
const Tensor& input_permutation_indices = ctx->input(1);
...
ValidateInputs(ctx, *input_matrix, input_permutation_indices, &batch_size, &num_rows);
...
}
void ValidateInputs(OpKernelContext* ctx,
const CSRSparseMatrix& sparse_matrix,
const Tensor& permutation_indices, int* batch_size,
int64* num_rows) {
OP_REQUIRES(ctx, sparse_matrix.dtype() == DataTypeToEnum<T>::value, ...)
...
}
```
Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since [`OP_REQUIRES`](https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function.
```cc
#define OP_REQUIRES(CTX, EXP, STATUS) \
do { \
if (!TF_PREDICT_TRUE(EXP)) { \
CheckNotInComputeAsync((CTX), "OP_REQUIRES_ASYNC"); \
(CTX)->CtxFailure(__FILE__, __LINE__, (STATUS)); \
return; \
} \
} while (0)
```
Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`.
### Patches
We have patched the issue in GitHub commit [e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd](https://github.com/tensorflow/tensorflow/commit/e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
|
{'CVE-2021-29530'}
|
2022-03-03T05:14:10.768316Z
|
2021-05-21T14:22:09Z
|
LOW
| null |
{'CWE-476'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2021-29530', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xcwj-wfcm-m23c', 'https://github.com/tensorflow/tensorflow/commit/e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd'}
| null |
PyPI
|
PYSEC-2020-236
| null |
Matrix is an ecosystem for open federated Instant Messaging and VoIP. Synapse is a reference "homeserver" implementation of Matrix. A malicious or poorly-implemented homeserver can inject malformed events into a room by specifying a different room id in the path of a `/send_join`, `/send_leave`, `/invite` or `/exchange_third_party_invite` request. This can lead to a denial of service in which future events will not be correctly sent to other servers over federation. This affects any server which accepts federation requests from untrusted servers. The Matrix Synapse reference implementation before version 1.23.1 the implementation is vulnerable to this injection attack. Issue is fixed in version 1.23.1. As a workaround homeserver administrators could limit access to the federation API to trusted servers (for example via `federation_domain_whitelist`).
|
{'CVE-2020-26257', 'GHSA-hxmp-pqch-c8mm'}
|
2021-08-27T03:22:06.434071Z
|
2020-12-09T19:15:00Z
| null | null | null |
{'https://github.com/matrix-org/synapse/security/advisories/GHSA-hxmp-pqch-c8mm', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QR4MMYZKX5N5GYGH4H5LBUUC5TLAFHI7/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DBTIU3ZNBFWZ56V4X7JIAD33V5H2GOMC/', 'https://github.com/matrix-org/synapse/blob/develop/CHANGES.md#synapse-1231-2020-12-09', 'https://github.com/matrix-org/synapse/commit/3ce2f303f15f6ac3dc352298972dc6e04d9b7a8b', 'https://github.com/matrix-org/synapse/pull/8776'}
| null |
PyPI
|
GHSA-c4qh-4vgv-qc6g
|
Uncontrolled Resource Consumption in Django
|
An issue was discovered in Django 1.11.x before 1.11.23, 2.1.x before 2.1.11, and 2.2.x before 2.2.4. If django.utils.text.Truncator's chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable.
|
{'CVE-2019-14232'}
|
2022-03-03T05:13:16.194751Z
|
2019-08-06T01:43:29Z
|
HIGH
| null |
{'CWE-400'}
|
{'https://github.com/django/django', 'https://seclists.org/bugtraq/2019/Aug/15', 'https://nvd.nist.gov/vuln/detail/CVE-2019-14232', 'https://groups.google.com/forum/#!topic/django-announce/jIoju2-KLDs', 'https://security.netapp.com/advisory/ntap-20190828-0002/', 'https://security.gentoo.org/glsa/202004-17', 'https://www.debian.org/security/2019/dsa-4498', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00006.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00025.html', 'https://github.com/pypa/advisory-db/tree/main/vulns/django/PYSEC-2019-11.yaml', 'https://docs.djangoproject.com/en/dev/releases/security/', 'https://www.djangoproject.com/weblog/2019/aug/01/security-releases/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/STVX7X7IDWAH5SKE6MBMY3TEI6ZODBTK/'}
| null |
PyPI
|
GHSA-24x6-8c7m-hv3f
|
Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`
|
### Impact
The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty.
This is because [the broadcasting implementation](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds:
```cc
auto maxmin_func = [&](int indexes[N]) {
output_data[SubscriptToIndex(output_desc, indexes)] =
op(input1_data[SubscriptToIndex(desc1, indexes)],
input2_data[SubscriptToIndex(desc2, indexes)]);
};
```
### Patches
We have patched the issue in GitHub commit [953f28dca13c92839ba389c055587cfe6c723578](https://github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578).
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-2021-29590'}
|
2022-03-03T05:13:08.168895Z
|
2021-05-21T14:26:53Z
|
LOW
| null |
{'CWE-125'}
|
{'https://nvd.nist.gov/vuln/detail/CVE-2021-29590', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-24x6-8c7m-hv3f', 'https://github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578'}
| null |
PyPI
|
PYSEC-2021-236
| null |
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `Split` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e2752089ef7ce9bcf3db0ec618ebd23ea119d0c7/tensorflow/lite/kernels/split.cc#L63-L65). An attacker can craft a model such that `num_splits` would be 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
|
{'CVE-2021-29599', 'GHSA-97wf-p777-86jq'}
|
2021-08-27T03:22:39.020093Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-97wf-p777-86jq', 'https://github.com/tensorflow/tensorflow/commit/b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d'}
| null |
PyPI
|
GHSA-ph87-fvjr-v33w
|
CHECK-fail in `tf.raw_ops.RFFT`
|
### Impact
An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`:
```python
import tensorflow as tf
inputs = tf.constant([1], shape=[1], dtype=tf.float32)
fft_length = tf.constant([0], shape=[1], dtype=tf.int32)
tf.raw_ops.RFFT(input=inputs, fft_length=fft_length)
```
The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.
### Patches
We have patched the issue in GitHub commit [31bd5026304677faa8a0b77602c6154171b9aec1](https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1).
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-2021-29563'}
|
2022-03-03T05:12:46.533412Z
|
2021-05-21T14:25:05Z
|
LOW
| null |
{'CWE-617'}
|
{'https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29563'}
| null |
PyPI
|
PYSEC-2021-29
| null |
The Logging subsystem in OctoPrint before 1.6.0 has incorrect access control because it attempts to manage files that are not *.log files.
|
{'CVE-2021-32560'}
|
2021-05-11T15:18:00Z
|
2021-05-11T14:15:00Z
| null | null | null |
{'https://www.brzozowski.io', 'https://octoprint.org/blog/2021/04/27/new-release-1.6.0/', 'https://github.com/OctoPrint/OctoPrint/releases/tag/1.6.0'}
| null |
PyPI
|
PYSEC-2021-666
| null |
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
|
{'GHSA-xgc3-m89p-vr3x', 'CVE-2021-29540'}
|
2021-12-09T06:35:21.673979Z
|
2021-05-14T20:15:00Z
| null | null | null |
{'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xgc3-m89p-vr3x', 'https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96'}
| null |
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