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-2019-211 | null | trytond 2.4: ModelView.button fails to validate authorization | {'CVE-2012-2238'} | 2021-08-27T03:22:48.643Z | 2019-11-21T14:15:00Z | null | null | null | {'http://www.securityfocus.com/bid/55503', 'https://security-tracker.debian.org/tracker/CVE-2012-2238', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/78435', 'http://www.openwall.com/lists/oss-security/2012/09/11/10', 'http://hg.tryton.org/2.4/trytond/rev/279f0031b461'} | null |
PyPI | PYSEC-2020-312 | null | In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15197', 'GHSA-qc53-44cj-vfvx'} | 2021-12-09T06:35:13.010994Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx'} | null |
PyPI | PYSEC-2011-4 | null | Django before 1.2.7 and 1.3.x before 1.3.1 uses a request's HTTP Host header to construct a full URL in certain circumstances, which allows remote attackers to conduct cache poisoning attacks via a crafted request. | {'CVE-2011-4139'} | 2021-07-05T00:01:18.041571Z | 2011-10-19T10:55:00Z | null | null | null | {'https://www.djangoproject.com/weblog/2011/sep/09/', 'http://openwall.com/lists/oss-security/2011/09/13/2', 'http://www.debian.org/security/2011/dsa-2332', 'https://hermes.opensuse.org/messages/14700881', 'http://openwall.com/lists/oss-security/2011/09/11/1', 'https://bugzilla.redhat.com/show_bug.cgi?id=737366', 'http://secunia.com/advisories/46614', 'https://www.djangoproject.com/weblog/2011/sep/10/127/'} | null |
PyPI | PYSEC-2021-191 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected. | {'GHSA-qg48-85hg-mqc5', 'CVE-2021-29554'} | 2021-08-27T03:22:31.001831Z | 2021-05-14T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5'} | null |
PyPI | GHSA-x84v-xcm2-53pg | Moderate severity vulnerability that affects requests | The Requests package through 2.19.1 before 2018-09-14 for Python sends an HTTP Authorization header to an http URI upon receiving a same-hostname https-to-http redirect, which makes it easier for remote attackers to discover credentials by sniffing the network. | {'CVE-2018-18074'} | 2022-03-03T05:13:34.123639Z | 2018-10-29T19:06:46Z | HIGH | null | {'CWE-522'} | {'http://lists.opensuse.org/opensuse-security-announce/2019-07/msg00024.html', 'https://usn.ubuntu.com/3790-1/', 'https://github.com/requests/requests/pull/4718', 'https://github.com/requests/requests/issues/4716', 'https://bugs.debian.org/910766', 'https://github.com/advisories/GHSA-x84v-xcm2-53pg', 'https://nvd.nist.gov/vuln/detail/CVE-2018-18074', 'http://docs.python-requests.org/en/master/community/updates/#release-and-version-history', 'https://github.com/requests/requests/commit/c45d7c49ea75133e52ab22a8e9e13173938e36ff', 'https://access.redhat.com/errata/RHSA-2019:2035', 'https://github.com/requests/requests', 'https://usn.ubuntu.com/3790-2/'} | null |
PyPI | GHSA-whr9-vfh2-7hm6 | Memory corruption in `DrawBoundingBoxesV2` | ### Impact
The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:
```python
import tensorflow as tf
images = tf.fill([10, 96, 0, 1], 0.)
boxes = tf.fill([10, 53, 0], 0.)
colors = tf.fill([0, 1], 0.)
tf.raw_ops.DrawBoundingBoxesV2(images=images, boxes=boxes, colors=colors)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption:
```cc
const auto tboxes = boxes.tensor<T, 3>();
for (int64 bb = 0; bb < num_boxes; ++bb) {
...
const int64 min_box_row = static_cast<float>(tboxes(b, bb, 0)) * (height - 1);
const int64 max_box_row = static_cast<float>(tboxes(b, bb, 2)) * (height - 1);
const int64 min_box_col = static_cast<float>(tboxes(b, bb, 1)) * (width - 1);
const int64 max_box_col = static_cast<float>(tboxes(b, bb, 3)) * (width - 1);
...
}
```
If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices.
### Patches
We have patched the issue in GitHub commit [79865b542f9ffdc9caeb255631f7c56f1d4b6517](https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517).
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-2021-29571'} | 2022-03-03T05:13:08.896921Z | 2021-05-21T14:25:28Z | MODERATE | null | {'CWE-787'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6', 'https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29571'} | null |
PyPI | GHSA-97wf-p777-86jq | Division by zero in TFLite's implementation of Split | ### Impact
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):
```cc
TF_LITE_ENSURE_MSG(context, input_size % num_splits == 0, "Not an even split");
const int slice_size = input_size / num_splits;
```
An attacker can craft a model such that `num_splits` would be 0.
### Patches
We have patched the issue in GitHub commit [b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d](https://github.com/tensorflow/tensorflow/commit/b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d).
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-2021-29599'} | 2022-03-03T05:13:40.775608Z | 2021-05-21T14:28:01Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-97wf-p777-86jq', 'https://github.com/tensorflow/tensorflow/commit/b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29599'} | null |
PyPI | PYSEC-2019-138 | null | In Waitress through version 1.4.0, if a proxy server is used in front of waitress, an invalid request may be sent by an attacker that bypasses the front-end and is parsed differently by waitress leading to a potential for HTTP request smuggling. Specially crafted requests containing special whitespace characters in the Transfer-Encoding header would get parsed by Waitress as being a chunked request, but a front-end server would use the Content-Length instead as the Transfer-Encoding header is considered invalid due to containing invalid characters. If a front-end server does HTTP pipelining to a backend Waitress server this could lead to HTTP request splitting which may lead to potential cache poisoning or unexpected information disclosure. This issue is fixed in Waitress 1.4.1 through more strict HTTP field validation. | {'GHSA-968f-66r5-5v74', 'CVE-2019-16789'} | 2020-02-25T17:15:00Z | 2019-12-26T17:15:00Z | null | null | null | {'https://github.com/github/advisory-review/pull/14604', 'https://docs.pylonsproject.org/projects/waitress/en/latest/#security-fixes', 'https://github.com/Pylons/waitress/commit/11d9e138125ad46e951027184b13242a3c1de017', 'https://github.com/advisories/GHSA-968f-66r5-5v74', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYEOTGWJZVKPRXX2HBNVIYWCX73QYPM5/', 'https://access.redhat.com/errata/RHSA-2020:0720', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GVDHR2DNKCNQ7YQXISJ45NT4IQDX3LJ7/'} | null |
PyPI | PYSEC-2022-58 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `MapStage` is vulnerable a `CHECK`-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-gcvh-66ff-4mwm', 'CVE-2022-21734'} | 2022-03-09T00:17:31.053811Z | 2022-02-03T13:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/map_stage_op.cc#L519-L550', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gcvh-66ff-4mwm', 'https://github.com/tensorflow/tensorflow/commit/f57315566d7094f322b784947093406c2aea0d7d'} | null |
PyPI | PYSEC-2020-65 | null | python-markdown2 through 2.3.8 allows XSS because element names are mishandled unless a \w+ match succeeds. For example, an attack might use elementname@ or elementname- with an onclick attribute. | {'GHSA-fv3h-8x5j-pvgq', 'CVE-2020-11888'} | 2020-05-25T06:15:00Z | 2020-04-20T16:15:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2020-05/msg00035.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/AQLRBGRVRRZK7P5SFL2MNGXFX37YHJAV/', 'https://github.com/advisories/GHSA-fv3h-8x5j-pvgq', 'http://lists.opensuse.org/opensuse-security-announce/2020-05/msg00031.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/6XOAIRJJCZNJUALXDHSIGH5PS2H63A3J/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PN6QSHRFZXRQAYZJQ4MOW5MKIXBYOMED/', 'https://github.com/trentm/python-markdown2/issues/348'} | null |
PyPI | GHSA-38fc-9xqv-7f7q | Moderate severity vulnerability that affects SQLAlchemy | SQLAlchemy 1.2.17 has SQL Injection when the group_by parameter can be controlled. | {'CVE-2019-7548'} | 2022-03-03T05:11:21.490875Z | 2019-04-16T15:50:39Z | HIGH | null | {'CWE-89'} | {'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00087.html', 'https://github.com/sqlalchemy/sqlalchemy/issues/4481#issuecomment-461204518', 'https://github.com/sqlalchemy/sqlalchemy', 'https://github.com/advisories/GHSA-38fc-9xqv-7f7q', 'https://lists.debian.org/debian-lts-announce/2021/11/msg00005.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00016.html', 'https://nvd.nist.gov/vuln/detail/CVE-2019-7548', 'https://access.redhat.com/errata/RHSA-2019:0984', 'https://www.oracle.com/security-alerts/cpujan2021.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00010.html', 'https://github.com/no-security/sqlalchemy_test', 'https://access.redhat.com/errata/RHSA-2019:0981', 'https://lists.debian.org/debian-lts-announce/2019/03/msg00020.html'} | null |
PyPI | PYSEC-2016-12 | null | Tryton 3.x before 3.2.17, 3.4.x before 3.4.14, 3.6.x before 3.6.12, 3.8.x before 3.8.8, and 4.x before 4.0.4 allow remote authenticated users to discover user password hashes via unspecified vectors. | {'CVE-2016-1241'} | 2021-10-12T02:55:35.373801Z | 2016-09-07T19:28:00Z | null | null | null | {'https://bugs.tryton.org/issue5795', 'http://www.debian.org/security/2016/dsa-3656', 'http://www.tryton.org/posts/security-release-for-issue5795-and-issue5808.html'} | null |
PyPI | PYSEC-2021-484 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-fxqh-cfjm-fp93', 'CVE-2021-29556'} | 2021-12-09T06:34:52.071121Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxqh-cfjm-fp93', 'https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1'} | null |
PyPI | PYSEC-2021-650 | 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.Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130) does a modulus operation where the divisor 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-r4pj-74mg-8868', 'CVE-2021-29524'} | 2021-12-09T06:35:18.930076Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r4pj-74mg-8868', 'https://github.com/tensorflow/tensorflow/commit/fca9874a9b42a2134f907d2fb46ab774a831404a'} | null |
PyPI | PYSEC-2021-200 | 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'} | 2021-08-27T03:22:32.655132Z | 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-q65m-pv3f-wr5r | XSS in Bleach when noscript and raw tag whitelisted | ### Impact
A [mutation XSS](https://cure53.de/fp170.pdf) affects users calling `bleach.clean` with `noscript` and a raw tag (see below) in the allowed/whitelisted tags option.
### Patches
v3.1.1
### Workarounds
* modify `bleach.clean` calls to not whitelist `noscript` and one or more of the following raw tags:
```
title
textarea
script
style
noembed
noframes
iframe
xmp
```
* A strong [Content-Security-Policy](https://developer.mozilla.org/en-US/docs/Web/HTTP/CSP) without `unsafe-inline` and `unsafe-eval` [`script-src`s](https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Content-Security-Policy/script-src)) will also help mitigate the risk.
### References
* https://bugzilla.mozilla.org/show_bug.cgi?id=1615315
* https://cure53.de/fp170.pdf
* https://nvd.nist.gov/vuln/detail/CVE-2020-6802
* https://www.checkmarx.com/blog/vulnerabilities-discovered-in-mozilla-bleach
### Credits
* Reported by [Yaniv Nizry](https://twitter.com/ynizry) from the CxSCA AppSec group at Checkmarx
### For more information
If you have any questions or comments about this advisory:
* Open an issue at [https://github.com/mozilla/bleach/issues](https://github.com/mozilla/bleach/issues)
* Email us at [security@mozilla.org](mailto:security@mozilla.org)
| {'CVE-2020-6802'} | 2022-03-03T05:12:38.876936Z | 2020-02-24T17:33:44Z | MODERATE | null | {'CWE-79'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/72R4VFFHDRSQMNT7IZU3X2755ZP4HGNI/', 'https://www.checkmarx.com/blog/vulnerabilities-discovered-in-mozilla-bleach', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YTULPQB7HVPPYWEYVNHJGDTSPVIDHIZX/', 'https://cure53.de/fp170.pdf', 'https://github.com/mozilla/bleach/security/advisories/GHSA-q65m-pv3f-wr5r', 'https://bugzilla.mozilla.org/show_bug.cgi?id=1615315', 'https://advisory.checkmarx.net/advisory/CX-2020-4276', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OCNLM2MGQTOLCIVVYS2Z5S7KOQJR5JC4/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-6802', 'https://github.com/mozilla/bleach/commit/f77e0f6392177a06e46a49abd61a4d9f035e57fd'} | null |
PyPI | PYSEC-2017-87 | null | A HTTP/2 implementation built using any version of the Python HPACK library between v1.0.0 and v2.2.0 could be targeted for a denial of service attack, specifically a so-called "HPACK Bomb" attack. This attack occurs when an attacker inserts a header field that is exactly the size of the HPACK dynamic header table into the dynamic header table. The attacker can then send a header block that is simply repeated requests to expand that field in the dynamic table. This can lead to a gigantic compression ratio of 4,096 or better, meaning that 16kB of data can decompress to 64MB of data on the target machine. | {'GHSA-ffq8-576r-v26g', 'CVE-2016-6581'} | 2021-08-27T03:22:04.412157Z | 2017-01-10T15:59:00Z | null | null | null | {'http://www.securityfocus.com/bid/92315', 'https://github.com/advisories/GHSA-ffq8-576r-v26g', 'https://python-hyper.org/hpack/en/latest/security/CVE-2016-6581.html'} | null |
PyPI | GHSA-g25h-jr74-qp5j | Incomplete validation in `QuantizeV2` | ### Impact
Due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays:
```python
import tensorflow as tf
tf.raw_ops.QuantizeV2(
input=[1,2,3],
min_range=[1,2],
max_range=[],
T=tf.qint32,
mode='SCALED',
round_mode='HALF_AWAY_FROM_ZERO',
narrow_range=False,
axis=1,
ensure_minimum_range=3)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor.
### Patches
We have patched the issue in GitHub commit [6da6620efad397c85493b8f8667b821403516708](https://github.com/tensorflow/tensorflow/commit/6da6620efad397c85493b8f8667b821403516708).
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-2021-37663'} | 2022-03-03T05:12:48.390795Z | 2021-08-25T14:42:23Z | HIGH | null | {'CWE-20'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-37663', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g25h-jr74-qp5j', 'https://github.com/tensorflow/tensorflow/commit/6da6620efad397c85493b8f8667b821403516708', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-qc55-vm3j-74gp | JSNAPy allows unprivileged local users to alter files under the directory | JSNAPy is an open source python version of Junos Snapshot Administrator developed by Juniper available through github. The default configuration and sample files of JSNAPy automation tool versions prior to 1.3.0 are created world writable. This insecure file and directory permission allows unprivileged local users to alter the files under this directory including inserting operations not intended by the package maintainer, system administrator, or other users. This issue only affects users who downloaded and installed JSNAPy from github. | {'CVE-2018-0023'} | 2022-04-26T18:17:08.136319Z | 2018-07-12T20:30:36Z | MODERATE | null | {'CWE-276'} | {'https://kb.juniper.net/JSA10856', 'https://nvd.nist.gov/vuln/detail/CVE-2018-0023', 'https://github.com/advisories/GHSA-qc55-vm3j-74gp', 'http://www.securityfocus.com/bid/103745'} | null |
PyPI | PYSEC-2020-200 | null | The vault subsystem in Ansible before 1.5.5 does not set the umask before creation or modification of a vault file, which allows local users to obtain sensitive key information by reading a file. | {'CVE-2014-4658'} | 2021-07-02T02:41:33.150700Z | 2020-02-20T15:15:00Z | null | null | null | {'https://www.securityfocus.com/bid/68233', 'https://github.com/ansible/ansible/blob/release1.5.5/CHANGELOG.md'} | null |
PyPI | PYSEC-2017-68 | null | The Recurly Client Python Library before 2.0.5, 2.1.16, 2.2.22, 2.3.1, 2.4.5, 2.5.1, 2.6.2 is vulnerable to a Server-Side Request Forgery vulnerability in the "Resource.get" method that could result in compromise of API keys or other critical resources. | {'CVE-2017-0906', 'GHSA-38rv-5jqc-m2cv'} | 2021-07-25T23:34:52.943535Z | 2017-11-13T17:29:00Z | null | null | null | {'https://github.com/recurly/recurly-client-python/commit/049c74699ce93cf126feff06d632ea63fba36742', 'https://github.com/advisories/GHSA-38rv-5jqc-m2cv', 'https://dev.recurly.com/page/python-updates', 'https://hackerone.com/reports/288635'} | null |
PyPI | GHSA-x64g-wjmw-w328 | Moderate severity vulnerability that affects ironic-discoverd | OpenStack Ironic Inspector (aka ironic-inspector or ironic-discoverd), when debug mode is enabled, might allow remote attackers to access the Flask console and execute arbitrary Python code by triggering an error. | {'CVE-2015-5306'} | 2020-06-16T22:02:22Z | 2019-07-05T21:10:52Z | MODERATE | null | null | {'http://rhn.redhat.com/errata/RHSA-2015-2685.html', 'https://github.com/advisories/GHSA-x64g-wjmw-w328', 'https://access.redhat.com/errata/RHSA-2015:1929', 'https://bugzilla.redhat.com/show_bug.cgi?id=1273698', 'https://nvd.nist.gov/vuln/detail/CVE-2015-5306', 'https://bugs.launchpad.net/ironic-inspector/+bug/1506419'} | null |
PyPI | PYSEC-2015-3 | null | The admin command in ceph-deploy before 1.5.25 uses world-readable permissions for /etc/ceph/ceph.client.admin.keyring, which allows local users to obtain sensitive information by reading the file. | {'CVE-2015-4053'} | 2021-07-05T00:01:17.307671Z | 2015-06-08T14:59:00Z | null | null | null | {'http://tracker.ceph.com/issues/11694', 'http://www.openwall.com/lists/oss-security/2015/04/09/9', 'http://www.securityfocus.com/bid/74775', 'http://www.openwall.com/lists/oss-security/2015/05/22/1', 'http://rhn.redhat.com/errata/RHSA-2015-1092.html'} | null |
PyPI | PYSEC-2021-715 | null | TensorFlow is an end-to-end open source platform for machine learning. The reference implementation of the `GatherNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966). An attacker can craft a model such that `params` input would be an empty tensor. In turn, `params_shape.Dims(.)` would be zero, in at least one dimension. 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-3w67-q784-6w7c', 'CVE-2021-29589'} | 2021-12-09T06:35:30.233507Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3w67-q784-6w7c'} | null |
PyPI | PYSEC-2011-16 | null | plone.app.users in Plone 4.0 and 4.1 allows remote authenticated users to modify the properties of arbitrary accounts via unspecified vectors, as exploited in the wild in June 2011. | {'CVE-2011-1950', 'GHSA-2qx8-589j-gcpx'} | 2021-07-25T23:34:43.220669Z | 2011-06-06T19:55:00Z | null | null | null | {'http://plone.org/products/plone/security/advisories/CVE-2011-1950', 'http://secunia.com/advisories/44775', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/67695', 'http://www.securityfocus.com/archive/1/518155/100/0/threaded', 'http://securityreason.com/securityalert/8269', 'http://osvdb.org/72729', 'https://github.com/advisories/GHSA-2qx8-589j-gcpx', 'http://www.securityfocus.com/bid/48005'} | null |
PyPI | PYSEC-2021-345 | null | The rencode package through 1.0.6 for Python allows an infinite loop in typecode decoding (such as via ;\x2f\x7f), enabling a remote attack that consumes CPU and memory. | {'GHSA-gh8j-2pgf-x458', 'CVE-2021-40839'} | 2021-09-26T23:32:54.963571Z | 2021-09-10T02:15:00Z | null | null | null | {'https://github.com/aresch/rencode/pull/29', 'https://github.com/advisories/GHSA-gh8j-2pgf-x458', 'https://pypi.org/project/rencode/#history', 'https://github.com/aresch/rencode/commit/572ff74586d9b1daab904c6f7f7009ce0143bb75', 'https://seclists.org/fulldisclosure/2021/Sep/16'} | null |
PyPI | PYSEC-2020-32 | null | An issue was discovered in Django 2.2 before 2.2.13 and 3.0 before 3.0.7. Query parameters generated by the Django admin ForeignKeyRawIdWidget were not properly URL encoded, leading to a possibility of an XSS attack. | {'GHSA-2m34-jcjv-45xf', 'CVE-2020-13596'} | 2021-01-20T15:15:00Z | 2020-06-03T14:15:00Z | null | null | null | {'https://security.netapp.com/advisory/ntap-20200611-0002/', 'https://www.djangoproject.com/weblog/2020/jun/03/security-releases/', 'https://docs.djangoproject.com/en/3.0/releases/security/', 'https://www.debian.org/security/2020/dsa-4705', 'https://github.com/advisories/GHSA-2m34-jcjv-45xf', 'https://groups.google.com/forum/#!msg/django-announce/pPEmb2ot4Fo/X-SMalYSBAAJ', 'https://usn.ubuntu.com/4381-2/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4A2AP4T7RKPBCLTI2NNQG3T6MINDUUMZ/', 'https://www.oracle.com/security-alerts/cpujan2021.html', 'https://usn.ubuntu.com/4381-1/'} | null |
PyPI | GHSA-xw7c-jx9m-xh5g | Reflected cross-site scripting issue in Datasette | ### Impact
The `?_trace=1` debugging feature in Datasette does not correctly escape generated HTML, resulting in a [reflected cross-site scripting](https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks) vulnerability.
This vulnerability is particularly relevant if your Datasette installation includes authenticated features using plugins such as [datasette-auth-passwords](https://datasette.io/plugins/datasette-auth-passwords) as an attacker could use the vulnerability to access protected data.
### Patches
Datasette 0.57 and 0.56.1 both include patches for this issue.
### Workarounds
If you run Datasette behind a proxy you can workaround this issue by rejecting any incoming requests with `?_trace=` or `&_trace=` in their query string parameters.
### References
- [OWASP guide to reflected cross-site scripting](https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks)
- [Datasette issue #1360](https://github.com/simonw/datasette/issues/1360)
### For more information
If you have any questions or comments about this advisory:
* Open a discussion in [simonw/datasette](https://github.com/simonw/datasette/discussions)
* Email us at `swillison+datasette @ gmail.com`
| null | 2022-03-03T05:13:04.556536Z | 2021-06-07T21:47:41Z | HIGH | null | {'CWE-79'} | {'https://github.com/simonw/datasette', 'https://github.com/simonw/datasette/security/advisories/GHSA-xw7c-jx9m-xh5g'} | null |
PyPI | PYSEC-2021-596 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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-2021-37683', 'GHSA-rhrq-64mq-hf9h'} | 2021-12-09T06:35:06.073182Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rhrq-64mq-hf9h', 'https://github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28'} | null |
PyPI | PYSEC-2022-120 | null | Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-428x-9xc2-m8mj', 'CVE-2022-21741'} | 2022-03-09T00:18:25.119172Z | 2022-02-03T15:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e5b0eec199c2d03de54fd6a7fd9275692218e2bc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-428x-9xc2-m8mj', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/depthwise_conv.cc#L96'} | null |
PyPI | PYSEC-2014-97 | null | Libcloud 0.12.3 through 0.13.2 does not set the scrub_data parameter for the destroy DigitalOcean API, which allows local users to obtain sensitive information by leveraging a new VM. | {'CVE-2013-6480'} | 2021-11-22T04:57:51.510127Z | 2014-01-07T18:55:00Z | null | null | null | {'https://github.com/fog/fog/issues/2525', 'https://digitalocean.com/blog_posts/transparency-regarding-data-security', 'http://lists.opensuse.org/opensuse-updates/2014-02/msg00015.html', 'http://libcloud.apache.org/security.html', 'http://www.securityfocus.com/bid/64617', 'http://www.securityfocus.com/archive/1/530624/100/0/threaded'} | null |
PyPI | PYSEC-2020-6 | null | A flaw was found in the pipe lookup plugin of ansible. Arbitrary commands can be run, when the pipe lookup plugin uses subprocess.Popen() with shell=True, by overwriting ansible facts and the variable is not escaped by quote plugin. An attacker could take advantage and run arbitrary commands by overwriting the ansible facts. | {'GHSA-h39q-95q5-9jfp', 'CVE-2020-1734'} | 2020-05-29T14:11:00Z | 2020-03-03T22:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-h39q-95q5-9jfp', 'https://github.com/ansible/ansible/issues/67792', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1734'} | null |
PyPI | GHSA-7f92-rr6w-cq64 | Storage corruption due to variables overwritten by re-entrancy locks | ### Background
When attempting to use the v0.2.14 release, @pandadefi discovered an issue using the `@nonreentrant` decorator.
### Impact
Reentrancy protection storage slots get allocated to the same slots as storage variables, leading to the corruption of storage variables when using the `@nonreentrant` decorator.
### Patches
This issue was fixed in v0.2.15 in #2391, #2379
### Workarounds
Don't use the `@nonreentrant` decorator in these versions. | null | 2022-03-03T05:13:53.756213Z | 2021-08-05T16:57:42Z | HIGH | null | null | {'https://github.com/vyperlang/vyper/security/advisories/GHSA-7f92-rr6w-cq64', 'https://github.com/vyperlang/vyper/pull/2379', 'https://github.com/vyperlang/vyper/pull/2391'} | null |
PyPI | PYSEC-2021-129 | null | The package bottle from 0 and 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. | {'SNYK-PYTHON-BOTTLE-1017108', 'CVE-2020-28473', 'GHSA-qhx9-7hx7-cp4r'} | 2021-08-27T03:21:56.437494Z | 2021-01-18T12:15:00Z | null | null | null | {'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/advisories/GHSA-qhx9-7hx7-cp4r', 'https://github.com/bottlepy/bottle'} | null |
PyPI | GHSA-6757-jp84-gxfx | Improper Input Validation in PyYAML | A vulnerability was discovered in the PyYAML library in versions before 5.3.1, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor. | {'CVE-2020-1747'} | 2022-03-03T05:13:26.132451Z | 2021-04-20T16:14:24Z | HIGH | null | {'CWE-20'} | {'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00017.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1747', 'https://github.com/yaml/pyyaml', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/K5HEPD7LEVDPCITY5IMDYWXUMX37VFMY/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZBJA3SGNJKCAYPSHOHWY3KBCWNM5NYK2/', 'https://github.com/yaml/pyyaml/pull/386', 'http://lists.opensuse.org/opensuse-security-announce/2020-05/msg00017.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7PPAS6C4SZRDQLR7C22A5U3QOLXY33JX/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1747', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MMQXSZXNJT6ERABJZAAICI3DQSQLCP3D/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WORRFHPQVAFKKXXWLSSW6XKUYLWM6CSH/'} | null |
PyPI | GHSA-55j9-849x-26h4 | Remote Code Execution in Red Discord Bot | ### Impact
A RCE exploit has been discovered in the Trivia module: this exploit allows Discord users with specifically crafted usernames to inject code into the Trivia module's leaderboard command. By abusing this exploit, it's possible to perform destructive actions and/or access sensitive information.
### Patches
This critical exploit has been fixed on version 3.3.11.
### Workarounds
Unloading the Trivia module with ``unload trivia`` can render this exploit not accessible. We still highly recommend updating to 3.3.11 to completely patch this issue.
### References
https://github.com/Cog-Creators/Red-DiscordBot/pull/4175
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [Cog-Creators/Red-DiscordBot](https://github.com/Cog-Creators/Red-DiscordBot)
* Over on our [Discord server](https://discord.gg/red) | {'CVE-2020-15140'} | 2022-03-03T05:10:56.501261Z | 2020-08-21T16:30:52Z | HIGH | null | {'CWE-74'} | {'https://github.com/Cog-Creators/Red-DiscordBot/security/advisories/GHSA-55j9-849x-26h4', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15140', 'https://github.com/Cog-Creators/Red-DiscordBot/pull/4175/commits/9ab536235bafc2b42c3c17d7ce26f1cc64482a81', 'https://github.com/Cog-Creators/Red-DiscordBot'} | null |
PyPI | PYSEC-2021-579 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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-2021-37666', 'GHSA-w4xf-2pqw-5mq7'} | 2021-12-09T06:35:04.618744Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/be7a4de6adfbd303ce08be4332554dff70362612', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w4xf-2pqw-5mq7'} | null |
PyPI | PYSEC-2014-78 | null | Cross-site scripting (XSS) vulnerability in util/templatetags/djblets_js.py in Djblets before 0.7.30 and 0.8.x before 0.8.3 for Django, as used in Review Board, allows remote attackers to inject arbitrary web script or HTML via a JSON object, as demonstrated by the name field when changing a user name. | {'CVE-2014-3994'} | 2021-08-27T03:22:03.219875Z | 2014-06-16T18:55:00Z | null | null | null | {'http://seclists.org/oss-sec/2014/q2/494', 'http://secunia.com/advisories/58691', 'http://www.securityfocus.com/bid/67932', 'https://github.com/djblets/djblets/commit/77a68c03cd619a0996f3f37337b8c39ca6643d6e', 'https://github.com/djblets/djblets/commit/e2c79117efd925636acd871a5f473512602243cf', 'https://code.google.com/p/reviewboard/issues/detail?id=3406', 'https://github.com/djblets/djblets/commit/50000d0bbb983fa8c097b588d06b64df8df483bd', 'http://seclists.org/oss-sec/2014/q2/498'} | null |
PyPI | PYSEC-2020-129 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15206', 'GHSA-w5gh-2wr2-pm6g'} | 2020-10-29T16:15:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g', 'https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2019-180 | null | A code injection issue was discovered in ipycache through 2016-05-31. | {'GHSA-gcm4-q2pg-xw89', 'CVE-2019-7539'} | 2021-08-27T03:22:04.582276Z | 2019-03-21T21:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-gcm4-q2pg-xw89', 'https://github.com/rossant/ipycache/issues/47'} | null |
PyPI | PYSEC-2020-216 | null | The Beaker library through 1.11.0 for Python is affected by deserialization of untrusted data, which could lead to arbitrary code execution. | {'CVE-2013-7489'} | 2021-07-25T23:34:27.636176Z | 2020-06-26T20:15:00Z | null | null | null | {'https://github.com/bbangert/beaker/issues/191', 'https://www.openwall.com/lists/oss-security/2020/05/14/11', 'https://bugzilla.redhat.com/show_bug.cgi?id=1850105'} | null |
PyPI | GHSA-rprw-h62v-c2w7 | High severity vulnerability that affects pyyaml | In PyYAML before 4.1, the yaml.load() API could execute arbitrary code. In other words, yaml.safe_load is not used. | {'CVE-2017-18342'} | 2022-03-23T20:15:05.833162Z | 2019-01-04T17:45:26Z | CRITICAL | null | {'CWE-502'} | {'https://security.gentoo.org/glsa/202003-45', 'https://github.com/yaml/pyyaml/wiki/PyYAML-yaml.load(input)-Deprecation', 'https://github.com/marshmallow-code/apispec/issues/278', 'https://github.com/yaml/pyyaml', 'https://github.com/yaml/pyyaml/blob/master/CHANGES', 'https://nvd.nist.gov/vuln/detail/CVE-2017-18342', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JEX7IPV5P2QJITAMA5Z63GQCZA5I6NVZ/', 'https://github.com/yaml/pyyaml/issues/193', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/KSQQMRUQSXBSUXLCRD3TSZYQ7SEZRKCE/', 'https://github.com/yaml/pyyaml/pull/74', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/M6JCFGEIEOFMWWIXGHSELMKQDD4CV2BA/'} | null |
PyPI | PYSEC-2017-91 | null | In Mercurial before 4.1.3, "hg serve --stdio" allows remote authenticated users to launch the Python debugger, and consequently execute arbitrary code, by using --debugger as a repository name. | {'GHSA-ghjx-3jg5-h6r2', 'CVE-2017-9462'} | 2021-08-27T03:22:07.149994Z | 2017-06-06T21:29:00Z | null | null | null | {'http://www.securityfocus.com/bid/99123', 'https://github.com/advisories/GHSA-ghjx-3jg5-h6r2', 'https://www.mercurial-scm.org/repo/hg/rev/77eaf9539499', 'https://bugs.debian.org/861243', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_4.1.3_.282017-4-18.29', 'http://www.debian.org/security/2017/dsa-3963', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00005.html', 'https://security.gentoo.org/glsa/201709-18', 'https://access.redhat.com/errata/RHSA-2017:1576'} | null |
PyPI | GHSA-q4qf-3fc6-8x34 | Segfault and data corruption in tensorflow-lite | ### Impact
To mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72
If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.
### Patches
We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a 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.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15207'} | 2022-03-03T05:11:52.408012Z | 2020-09-25T18:28:43Z | HIGH | null | {'CWE-787', 'CWE-119'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15207', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34', 'https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2021-216 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-79fv-9865-4qcv', 'CVE-2021-29579'} | 2021-08-27T03:22:35.384566Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79fv-9865-4qcv', 'https://github.com/tensorflow/tensorflow/commit/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7'} | null |
PyPI | PYSEC-2021-646 | null | TensorFlow is an end-to-end open source platform for machine learning. Missing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the `input`, `filter_sizes` and `out_backprop` tensors have the same shape, as they are accessed in parallel. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29520', 'GHSA-wcv5-qrj6-9pfm'} | 2021-12-09T06:35:18.334867Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wcv5-qrj6-9pfm', 'https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197'} | null |
PyPI | PYSEC-2019-3 | null | A flaw was found in ansible 2.8.0 before 2.8.4. Fields managing sensitive data should be set as such by no_log feature. Some of these fields in GCP modules are not set properly. service_account_contents() which is common class for all gcp modules is not setting no_log to True. Any sensitive data managed by that function would be leak as an output when running ansible playbooks. | {'GHSA-p75j-wc34-527c', 'CVE-2019-10217'} | 2020-04-13T00:15:00Z | 2019-11-25T16:15:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00021.html', 'https://github.com/ansible/ansible/issues/56269', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00026.html', 'https://github.com/advisories/GHSA-p75j-wc34-527c', 'https://github.com/ansible/ansible/pull/59427', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-10217'} | null |
PyPI | PYSEC-2021-353 | null | furlongm openvpn-monitor through 1.1.3 allows %0a command injection via the OpenVPN management interface socket. This can shut down the server via signal%20SIGTERM. | {'CVE-2021-31605'} | 2021-09-30T23:26:26.808242Z | 2021-09-27T06:15:00Z | null | null | null | {'http://packetstormsecurity.com/files/164278/OpenVPN-Monitor-1.1.3-Command-Injection.html', 'https://github.com/furlongm/openvpn-monitor/releases'} | null |
PyPI | PYSEC-2021-703 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. 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-v6r6-84gr-92rm', 'CVE-2021-29577'} | 2021-12-09T06:35:28.044558Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6r6-84gr-92rm'} | null |
PyPI | GHSA-9x4c-63pf-525f | Arbitrary Code Generation | ### Impact
Clients generated with a maliciously crafted OpenAPI Document can generate arbitrary Python code. Subsequent execution of this malicious client is arbitrary code execution.
Giving this a CVSS of 8.0 (high) with CVSS:3.0/AV:N/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:H/E:P/RL:U/RC:C .
### Patches
Fix will be included in version 0.5.3
### Workarounds
Inspect OpenAPI documents before generating, or inspect generated code before executing.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [openapi-python-client](https://github.com/triaxtec/openapi-python-client/issues)
* Email us at [danthony@triaxtec.com](mailto:danthony@triaxtec.com) | {'CVE-2020-15142'} | 2022-03-03T05:13:26.062571Z | 2020-08-20T14:38:24Z | HIGH | null | {'CWE-94'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-15142', 'https://github.com/triaxtec/openapi-python-client/security/advisories/GHSA-9x4c-63pf-525f', 'https://github.com/triaxtec/openapi-python-client/blob/main/CHANGELOG.md#053---2020-08-13', 'https://pypi.org/project/openapi-python-client/', 'https://github.com/triaxtec/openapi-python-client/commit/f7a56aae32cba823a77a84a1f10400799b19c19a'} | null |
PyPI | GHSA-wvcv-832q-fjg7 | RSA weakness in tslite-ng | ### Impact
The code that performs decryption and padding check in RSA PKCS#1 v1.5 decryption is data dependant.
In particular, code in current (as of 0.8.0-alpha38) master
https://github.com/tlsfuzzer/tlslite-ng/blob/0812ed60860fa61a6573b2c0e18771414958f46d/tlslite/utils/rsakey.py#L407-L441
and code in 0.7.5 branch
https://github.com/tlsfuzzer/tlslite-ng/blob/acdde3161124d6ae37c506b3476aea9996d12e97/tlslite/utils/rsakey.py#L394-L425
has multiple ways in which it leaks information (for one, it aborts as soon as the plaintext doesn't start with 0x00, 0x02) about the decrypted ciphertext (both the bit length of the decrypted message as well as where the first unexpected byte lays).
All TLS servers that enable RSA key exchange as well as applications that use the RSA decryption API directly are vulnerable.
All previous versions of tlslite-ng are vulnerable.
### Patches
The patches to fix it are proposed in
https://github.com/tlsfuzzer/tlslite-ng/pull/438
https://github.com/tlsfuzzer/tlslite-ng/pull/439
Note: the patches depend on Python processing the individual bytes in side-channel free manner, this is known to not be the case: https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/
As such, users that require side-channel resistance are recommended to use different TLS implementations, as stated in the [security policy](https://github.com/tlsfuzzer/tlslite-ng/blob/master/SECURITY.md) of tlslite-ng.
### Workarounds
There is no way to workaround this issue.
### References
https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/
### For more information
If you have any questions or comments about this advisory please open an issue in [tlslite-ng](https://github.com/tlsfuzzer/tlslite-ng/issues). | {'CVE-2020-26263'} | 2022-03-03T05:13:09.290965Z | 2020-12-21T16:56:37Z | LOW | null | {'CWE-326'} | {'https://pypi.org/project/tlslite-ng/', 'https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/', 'https://github.com/tlsfuzzer/tlslite-ng/pull/439', 'https://github.com/tlsfuzzer/tlslite-ng/security/advisories/GHSA-wvcv-832q-fjg7', 'https://github.com/tlsfuzzer/tlslite-ng/pull/438', 'https://github.com/tlsfuzzer/tlslite-ng/commit/c28d6d387bba59d8bd5cb3ba15edc42edf54b368', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26263'} | null |
PyPI | PYSEC-2014-81 | null | httplib2 0.7.2, 0.8, and earlier, after an initial connection is made, does not verify that the server hostname matches a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate, which allows man-in-the-middle attackers to spoof SSL servers via an arbitrary valid certificate. | {'CVE-2013-2037'} | 2021-08-27T03:42:09.595120Z | 2014-01-18T21:55:00Z | null | null | null | {'http://code.google.com/p/httplib2/issues/detail?id=282', 'http://seclists.org/oss-sec/2013/q2/257', 'http://www.securityfocus.com/bid/52179', 'https://bugs.launchpad.net/httplib2/+bug/1175272', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=706602', 'http://www.ubuntu.com/usn/USN-1948-1'} | null |
PyPI | PYSEC-2022-136 | null | Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range. | {'GHSA-rww7-2gpw-fv6j', 'CVE-2022-23572'} | 2022-03-09T00:18:27.267952Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j'} | null |
PyPI | PYSEC-2021-580 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. 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-2021-37667', 'GHSA-w74j-v8xh-3w5h'} | 2021-12-09T06:35:04.699565Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w74j-v8xh-3w5h', 'https://github.com/tensorflow/tensorflow/commit/2e0ee46f1a47675152d3d865797a18358881d7a6'} | null |
PyPI | GHSA-9w2p-5mgw-p94c | Integer overflow due to conversion to unsigned | ### Impact
The implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value.
```python
import tensorflow as tf
tf.raw_ops.QuantizeAndDequantizeV4Grad(
gradients=[1.0,2.0],
input=[1.0,1.0],
input_min=[0.0],
input_max=[10.0],
axis=-100)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer.
### Patches
We have patched the issue in GitHub commit [96f364a1ca3009f98980021c4b32be5fdcca33a1](https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.
### 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-2021-37645'} | 2022-03-03T05:14:08.591493Z | 2021-08-25T14:43:37Z | MODERATE | null | {'CWE-681'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c', 'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37645'} | null |
PyPI | PYSEC-2019-179 | null | The Pallets Project Flask before 1.0 is affected by: unexpected memory usage. The impact is: denial of service. The attack vector is: crafted encoded JSON data. The fixed version is: 1. NOTE: this may overlap CVE-2018-1000656. | {'CVE-2019-1010083', 'GHSA-5wv5-4vpf-pj6m'} | 2021-08-27T03:22:03.986184Z | 2019-07-17T14:15:00Z | null | null | null | {'https://www.palletsprojects.com/blog/flask-1-0-released/', 'https://github.com/advisories/GHSA-5wv5-4vpf-pj6m'} | null |
PyPI | PYSEC-2020-24 | null | asyncpg before 0.21.0 allows a malicious PostgreSQL server to trigger a crash or execute arbitrary code (on a database client) via a crafted server response, because of access to an uninitialized pointer in the array data decoder. | {'CVE-2020-17446', 'GHSA-2xpj-f5g2-8p7m'} | 2020-09-03T01:15:00Z | 2020-08-12T16:15:00Z | null | null | null | {'https://lists.debian.org/debian-lts-announce/2020/09/msg00002.html', 'https://github.com/advisories/GHSA-2xpj-f5g2-8p7m', 'https://github.com/MagicStack/asyncpg/releases/tag/v0.21.0'} | null |
PyPI | PYSEC-2022-19 | null | The {% debug %} template tag in Django 2.2 before 2.2.27, 3.2 before 3.2.12, and 4.0 before 4.0.2 does not properly encode the current context. This may lead to XSS. | {'GHSA-95rw-fx8r-36v6', 'CVE-2022-22818'} | 2022-02-03T06:35:22.988491Z | 2022-02-03T02:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://github.com/advisories/GHSA-95rw-fx8r-36v6', 'https://docs.djangoproject.com/en/4.0/releases/security/', 'https://www.djangoproject.com/weblog/2022/feb/01/security-releases/'} | null |
PyPI | GHSA-cm5x-837x-jf3c | Division by 0 in inplace operations | ### Impact
An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:
```python
import tensorflow as tf
tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`.
### Patches
We have patched the issue in GitHub commit [e86605c0a336c088b638da02135ea6f9f6753618](https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618).
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-2021-37660'} | 2022-03-03T05:12:57.003702Z | 2021-08-25T14:42:44Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37660', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c'} | null |
PyPI | PYSEC-2019-196 | null | While investigating UBSAN errors in https://github.com/apache/arrow/pull/5365 it was discovered Apache Arrow versions 0.12.0 to 0.14.1, left memory Array data uninitialized when reading RLE null data from parquet. This affected the C++, Python, Ruby and R implementations. The uninitialized memory could potentially be shared if are transmitted over the wire (for instance with Flight) or persisted in the streaming IPC and file formats. | {'CVE-2019-12410'} | 2021-08-27T03:22:16.568373Z | 2019-11-08T19:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2019/11/08/1', 'https://lists.apache.org/thread.html/49f067b1c5fb7493d952580f0d2d032819ba351f7a78743c21126269@%3Cdev.arrow.apache.org%3E', 'https://lists.apache.org/thread.html/efd8bbf57427d3c303b5316d208a335f8d0c0dbe0dc4c87cfa995073@%3Cannounce.apache.org%3E'} | null |
PyPI | GHSA-5j2h-h5hg-3wf8 | Moderate severity vulnerability that affects django | Django 1.1.x before 1.1.4 and 1.2.x before 1.2.5 does not properly validate HTTP requests that contain an X-Requested-With header, which makes it easier for remote attackers to conduct cross-site request forgery (CSRF) attacks via forged AJAX requests that leverage a "combination of browser plugins and redirects," a related issue to CVE-2011-0447. | {'CVE-2011-0696'} | 2022-03-03T05:13:44.452929Z | 2018-07-23T19:51:10Z | MODERATE | null | {'CWE-352'} | {'http://www.vupen.com/english/advisories/2011/0372', 'http://www.djangoproject.com/weblog/2011/feb/08/security/', 'http://openwall.com/lists/oss-security/2011/02/09/6', 'http://www.securityfocus.com/bid/46296', 'https://nvd.nist.gov/vuln/detail/CVE-2011-0696', 'http://www.debian.org/security/2011/dsa-2163', 'http://www.vupen.com/english/advisories/2011/0441', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-February/054207.html', 'http://secunia.com/advisories/43230', 'http://secunia.com/advisories/43382', 'http://www.vupen.com/english/advisories/2011/0388', 'http://www.mandriva.com/security/advisories?name=MDVSA-2011:031', 'http://secunia.com/advisories/43426', 'http://secunia.com/advisories/43297', 'https://github.com/advisories/GHSA-5j2h-h5hg-3wf8', 'https://bugzilla.redhat.com/show_bug.cgi?id=676357', 'http://www.ubuntu.com/usn/USN-1066-1', 'http://www.vupen.com/english/advisories/2011/0429', 'http://www.vupen.com/english/advisories/2011/0439', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-February/054208.html'} | null |
PyPI | GHSA-2wx6-wc87-rmjm | GitHub personal access token leaking into temporary EasyBuild (debug) logs | ### Impact
The GitHub Personal Access Token (PAT) used by EasyBuild for the GitHub integration features (like `--new-pr`, `--from-pr`, etc.) is shown in plain text in EasyBuild debug log files.
Scope:
* the log message only appears in the top-level log file, *not* in the individual software installation logs (see https://easybuild.readthedocs.io/en/latest/Logfiles.html);
- as a consequence, tokens are *not* included in the partial log files that are uploaded into a gist when using `--upload-test-report` in combination with `--from-pr`, nor in the installation logs that are copied to the software installation directories;
* the message is only logged when using `--debug`, so it will not appear when using the default EasyBuild configuration (only info messages are logged by default);
* the log message is triggered via `--from-pr`, but also via various other GitHub integration options like `--new-pr`, `--merge-pr`, `--close-pr`, etc., but usually only appears in the temporary log file that is cleaned up automatically as soon as eb completes successfully;
* you may have several debug log files that include your GitHub token in `/tmp` (or a different location if you've set the `--tmpdir` EasyBuild configuration option) on the systems where you use EasyBuild, but they are located in a subdirectory that is only accessible to your account (permissions set to 700);
* the only way that a log file that may include your token could have been made public is *if you shared it yourself*, for example by copying the contents of the log file into a gist manually, or by sending a log file to someone;
* for log files uploaded to GitHub, your token would be revoked automatically when GitHub notices it;
### Patches
The issue is fixed with the changes in https://github.com/easybuilders/easybuild-framework/pull/3248.
This fix is included in EasyBuild v4.1.2 (released on Mon Mar 16th 2020), and in the `master`+ `develop` branches of the `easybuild-framework` repository since Mon Mar 16th 2020 (see https://github.com/easybuilders/easybuild-framework/pull/3248 and https://github.com/easybuilders/easybuild-framework/pull/3249 resp.).
**Make sure you revoke the existing GitHub tokens you're using with EasyBuild** (via https://github.com/settings/tokens), and install new ones using "`eb --install-github-token --force`" (see also https://easybuild.readthedocs.io/en/latest/Integration_with_GitHub.html#installing-a-github-token-install-github-token).
### Workarounds
* avoid using the GitHub integration features (see https://easybuild.readthedocs.io/en/latest/Integration_with_GitHub.html) with EasyBuild versions older than version 4.1.2;
* don't share top-level EasyBuild (debug) log files with others, unless you are sure your GitHub token is not included in them;
* clean up temporary EasyBuild log files in `/tmp`on the system(s) where you`re using EasyBuild
### References
* https://github.com/easybuilders/easybuild-framework/pull/3248 (PR that fixes the issue)
* (release announcement to EasyBuild mailing list)
### For more information
* Open an issue in [the `easybuild-framework` repository](https://github.com/easybuilders/easybuild-framework)
* Email us at [easybuild-admin@lists.ugent.be](mailto:easybuild-admin@lists.ugent.be) | {'CVE-2020-5262'} | 2022-03-03T05:09:52.633203Z | 2020-03-19T17:29:58Z | MODERATE | null | {'CWE-532'} | {'https://github.com/easybuilders/easybuild-framework/commit/210743d0e3618a8ac0a56eb9c0f4fa4fd8ae53b9', 'https://github.com/easybuilders/easybuild-framework/pull/3248', 'https://github.com/easybuilders/easybuild-framework/security/advisories/GHSA-2wx6-wc87-rmjm', 'https://nvd.nist.gov/vuln/detail/CVE-2020-5262', 'https://github.com/easybuilders/easybuild-framework/pull/3249'} | null |
PyPI | GHSA-8554-jxcw-454q | High severity vulnerability that affects webargs | An issue was discovered in webargs before 5.1.3, as used with marshmallow and other products. JSON parsing uses a short-lived cache to store the parsed JSON body. This cache is not thread-safe, meaning that incorrect JSON payloads could have been parsed for concurrent requests. | {'CVE-2019-9710'} | 2022-03-03T05:13:11.274487Z | 2019-03-12T15:16:12Z | HIGH | null | {'CWE-362'} | {'https://github.com/marshmallow-code/webargs', 'https://webargs.readthedocs.io/en/latest/changelog.html', 'https://github.com/advisories/GHSA-8554-jxcw-454q', 'https://nvd.nist.gov/vuln/detail/CVE-2019-9710', 'https://github.com/marshmallow-code/webargs/issues/371'} | null |
PyPI | PYSEC-2012-10 | null | security/__init__.py in MoinMoin 1.9 through 1.9.4 does not properly handle group names that contain virtual group names such as "All," "Known," or "Trusted," which allows remote authenticated users with virtual group membership to be treated as a member of the group. | {'CVE-2012-4404'} | 2021-07-25T23:34:40.223243Z | 2012-09-10T22:55:00Z | null | null | null | {'http://www.debian.org/security/2012/dsa-2538', 'http://www.openwall.com/lists/oss-security/2012/09/05/2', 'http://www.openwall.com/lists/oss-security/2012/09/04/4', 'http://secunia.com/advisories/50474', 'http://hg.moinmo.in/moin/1.9/rev/7b9f39289e16', 'http://moinmo.in/SecurityFixes', 'http://secunia.com/advisories/50885', 'http://www.ubuntu.com/usn/USN-1604-1', 'http://secunia.com/advisories/50496'} | null |
PyPI | PYSEC-2021-611 | null | TensorFlow is an open source platform for machine learning. In affeced versions during execution, `EinsumHelper::ParseEquation()` is supposed to set the flags in `input_has_ellipsis` vector and `*output_has_ellipsis` boolean to indicate whether there is ellipsis in the corresponding inputs and output. However, the code only changes these flags to `true` and never assigns `false`. This results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags. 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-2021-41201', 'GHSA-j86v-p27c-73fm'} | 2021-12-09T06:35:07.767696Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j86v-p27c-73fm', 'https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6'} | null |
PyPI | PYSEC-2021-241 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of hashtable lookup is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/hashtable_lookup.cc#L114-L115) An attacker can craft a model such that `values`'s first dimension 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. | {'GHSA-8rm6-75mf-7r7r', 'CVE-2021-29604'} | 2021-08-27T03:22:39.893665Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5117e0851348065ed59c991562c0ec80d9193db2', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8rm6-75mf-7r7r'} | null |
PyPI | GHSA-3x8c-fmpc-5rmq | Cross-site scripting (XSS) vulnerability in the fallback authentication endpoint | ### Impact
The fallback authentication 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.
### Patches
This is fixed by #8444, which is included in Synapse v1.21.0.
### Workarounds
If the homeserver is not configured to use reCAPTCHA, consent (terms of service), or single sign-on then the affected endpoint can be blocked at a reverse proxy:
* `/_matrix/client/r0/auth/.*/fallback/web`
* `/_matrix/client/unstable/auth/.*/fallback/web` | {'CVE-2020-26891'} | 2022-03-03T05:14:01.554659Z | 2020-10-16T16:56:04Z | MODERATE | null | {'CWE-79'} | {'https://github.com/matrix-org/synapse/security/advisories/GHSA-3x8c-fmpc-5rmq', 'https://github.com/matrix-org/synapse/pull/8444', 'https://github.com/matrix-org/synapse/releases', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26891', 'https://matrix.org/blog/2020/10/15/synapse-1-21-2-released-and-security-advisory', 'https://github.com/matrix-org/synapse/releases/tag/v1.21.2'} | null |
PyPI | GHSA-xw93-v57j-fcgh | Division by 0 in `SparseMatMul` | ### Impact
An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`:
```python
import tensorflow as tf
a = tf.constant([100.0, 100.0, 100.0, 100.0], shape=[2, 2], dtype=tf.float32)
b = tf.constant([], shape=[0, 2], dtype=tf.float32)
tf.raw_ops.SparseMatMul(
a=a, b=b, transpose_a=True, transpose_b=True,
a_is_sparse=True, b_is_sparse=True)
```
The division by 0 occurs deep in Eigen code because the `b` tensor is empty.
### Patches
We have patched the issue in GitHub commit [7f283ff806b2031f407db64c4d3edcda8fb9f9f5](https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5).
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-2021-29557'} | 2022-03-03T05:14:10.416499Z | 2021-05-21T14:24:48Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29557', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xw93-v57j-fcgh'} | null |
PyPI | GHSA-f8q4-jwww-x3wv | Race Condition in Paramiko | In Paramiko before 2.10.1, a race condition (between creation and chmod) in the write_private_key_file function could allow unauthorized information disclosure. | {'CVE-2022-24302'} | 2022-04-18T22:32:22.773225Z | 2022-03-19T00:01:03Z | MODERATE | null | {'CWE-362'} | {'https://lists.debian.org/debian-lts-announce/2022/03/msg00032.html', 'https://github.com/paramiko/paramiko', 'https://github.com/pypa/advisory-database/tree/main/vulns/paramiko/PYSEC-2022-166.yaml', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24302', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TPMKRUS4HO3P7NR7P4Y6CLHB4MBEE3AI/', 'https://github.com/paramiko/paramiko/blob/363a28d94cada17f012c1604a3c99c71a2bda003/paramiko/pkey.py#L546', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LUEUEGILZ7MQXRSUF5VMMO4SWJQVPTQL/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/U63MJ2VOLLQ35R7CYNREUHSXYLWNPVSB/', 'https://www.paramiko.org/changelog.html', 'https://github.com/advisories/GHSA-f8q4-jwww-x3wv', 'https://github.com/paramiko/paramiko/commit/4c491e299c9b800358b16fa4886d8d94f45abe2e'} | null |
PyPI | PYSEC-2014-7 | null | The administrative interface (contrib.admin) in Django before 1.4.14, 1.5.x before 1.5.9, 1.6.x before 1.6.6, and 1.7 before release candidate 3 does not check if a field represents a relationship between models, which allows remote authenticated users to obtain sensitive information via a to_field parameter in a popup action to an admin change form page, as demonstrated by a /admin/auth/user/?pop=1&t=password URI. | {'CVE-2014-0483'} | 2021-07-05T00:01:19.203370Z | 2014-08-26T14:55:00Z | null | null | null | {'http://www.debian.org/security/2014/dsa-3010', 'http://secunia.com/advisories/61276', 'https://www.djangoproject.com/weblog/2014/aug/20/security/', 'http://lists.opensuse.org/opensuse-updates/2014-09/msg00023.html', 'http://secunia.com/advisories/61281', 'https://github.com/django/django/commit/2b31342cdf14fc20e07c43d258f1e7334ad664a6', 'http://secunia.com/advisories/59782'} | null |
PyPI | PYSEC-2020-241 | null | MoinMoin is a wiki engine. In MoinMoin before version 1.9.11, an attacker with write permissions can upload an SVG file that contains malicious javascript. This javascript will be executed in a user's browser when the user is viewing that SVG file on the wiki. Users are strongly advised to upgrade to a patched version. MoinMoin Wiki 1.9.11 has the necessary fixes and also contains other important fixes. | {'GHSA-4q96-6xhq-ff43', 'CVE-2020-15275'} | 2021-08-27T03:22:07.834309Z | 2020-11-11T16:15:00Z | null | null | null | {'https://github.com/moinwiki/moin-1.9/security/advisories/GHSA-4q96-6xhq-ff43', 'https://github.com/moinwiki/moin-1.9/releases/tag/1.9.11', 'https://advisory.checkmarx.net/advisory/CX-2020-4285', 'https://github.com/moinwiki/moin-1.9/commit/31de9139d0aabc171e94032168399b4a0b2a88a2'} | null |
PyPI | PYSEC-2015-14 | null | The _validaterepo function in sshpeer in Mercurial before 3.2.4 allows remote attackers to execute arbitrary commands via a crafted repository name in a clone command. | {'CVE-2014-9462'} | 2021-07-05T00:01:22.697962Z | 2015-03-31T14:59:00Z | null | null | null | {'http://chargen.matasano.com/chargen/2015/3/17/this-new-vulnerability-mercurial-command-injection-cve-2014-9462.html', 'http://www.oracle.com/technetwork/topics/security/bulletinjul2015-2511963.html', 'http://www.debian.org/security/2015/dsa-3257', 'https://security.gentoo.org/glsa/201612-19', 'http://www.osvdb.org/119816', 'http://mercurial.selenic.com/wiki/WhatsNew', 'http://lists.opensuse.org/opensuse-updates/2015-03/msg00085.html'} | null |
PyPI | PYSEC-2017-29 | null | modules/serverdensity_device.py in SaltStack before 2014.7.4 does not properly handle files in /tmp. | {'CVE-2015-1838'} | 2021-07-05T00:01:26.175371Z | 2017-04-13T14:59:00Z | null | null | null | {'http://lists.fedoraproject.org/pipermail/package-announce/2016-January/175568.html', 'https://docs.saltstack.com/en/latest/topics/releases/2014.7.4.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=1212784', 'https://github.com/saltstack/salt/commit/e11298d7155e9982749483ca5538e46090caef9c'} | null |
PyPI | PYSEC-2020-304 | null | TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decoder in core/kernels/decode_bmp_op.cc. | {'CVE-2018-21233'} | 2021-12-09T06:35:11.657729Z | 2020-05-04T15:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/49f73c55d56edffebde4bca4a407ad69c1cae433', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-001.md'} | null |
PyPI | PYSEC-2019-207 | null | Memcpy parameter overlap in Google Snappy library 1.1.4, as used in Google TensorFlow before 1.7.1, could result in a crash or read from other parts of process memory. | {'GHSA-qx2v-j445-g354', 'CVE-2018-7577'} | 2021-08-27T03:22:22.362937Z | 2019-04-24T17:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-qx2v-j445-g354', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-005.md'} | null |
PyPI | GHSA-cqxx-66wh-8pjw | Improper Removal of Sensitive Information Before Storage or Transfer in irrd | IRRd did not always filter password hashes in query responses relating to `mntner` objects and database exports. This may have allowed adversaries to retrieve some of these hashes, perform a brute-force search for the clear-text passphrase, and use these to make unauthorised changes to affected IRR objects. This issue only affected instances that process password hashes, which means it is limited to IRRd instances that serve authoritative databases. IRRd instances operating solely as mirrors of other IRR databases are not affected.
The issue occurred:
* For `mntner` objects where all password hash names (`MD5-PW` and `CRYPT-PW`) were in lower or mixed case in the `auth` attribute. For these objects, hashes remained in the output of all queries of any method and all database exports made with the `export_destination` setting. Fortunately, objects in the common public IRR database virtually all use uppercase hash names which means very few of those objects were affected.
* For any GraphQL queries that queried the `auth` field on `mntner` objects.
* For any GraphQL queries that queried the `objectText` field on the `journal` field on `mntner` objects, if the `nrtm_access_list` setting permitted journal access.
The two GraphQL cases are visible in logs, allowing users to determine whether any existing objects had their hashes exposed.
This has been fixed in IRRd 4.2.3 and the main branch. Versions in the 4.1.x series never were affected. Users of the 4.2.x series are strongly recommended to upgrade. All users running a more recent version from the main branch should update to the latest version. Alternatively, but not recommended, apply the patch manually [for 4.2.x] | {'CVE-2022-24798'} | 2022-04-13T01:30:11.714249Z | 2022-04-01T13:59:17Z | HIGH | null | {'CWE-212'} | {'https://github.com/irrdnet/irrd/commit/fdffaf8dd71713f06e99dff417e6aa1e6fa84b70', 'https://github.com/irrdnet/irrd/security/advisories/GHSA-cqxx-66wh-8pjw', 'https://irrd.readthedocs.io/en/stable/releases/4.2.3/', 'https://github.com/irrdnet/irrd/commit/0e41bae8d3d27316381a2fc7b466597230e35ec6', 'https://github.com/irrdnet/irrd', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24798'} | null |
PyPI | PYSEC-2007-3 | null | Trac before 0.10.3.1 does not send a Content-Disposition HTTP header specifying an attachment in certain "unsafe" situations, which has unknown impact and remote attack vectors. | {'CVE-2007-1406'} | 2021-07-16T01:31:34.212521Z | 2007-03-10T22:19:00Z | null | null | null | {'http://trac.edgewall.org/wiki/ChangeLog'} | null |
PyPI | PYSEC-2021-754 | null | TensorFlow is an end-to-end open source platform for machine learning. If a user does not provide a valid padding value to `tf.raw_ops.MatrixDiagPartOp`, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L89) reads the first value from a tensor buffer without first checking that the tensor has values to read from. We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988. 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-2021-37643', 'GHSA-fcwc-p4fc-c5cc'} | 2021-12-09T06:35:36.031970Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/482da92095c4d48f8784b1f00dda4f81c28d2988', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fcwc-p4fc-c5cc'} | null |
PyPI | PYSEC-2021-304 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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-2021-37682', 'GHSA-4c4g-crqm-xrxw'} | 2021-08-27T03:22:46.967506Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/537bc7c723439b9194a358f64d871dd326c18887', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4c4g-crqm-xrxw', 'https://github.com/tensorflow/tensorflow/commit/8933b8a21280696ab119b63263babdb54c298538', 'https://github.com/tensorflow/tensorflow/commit/4a91f2069f7145aab6ba2d8cfe41be8a110c18a5'} | null |
PyPI | PYSEC-2020-73 | null | ** DISPUTED ** pandas through 1.0.3 can unserialize and execute commands from an untrusted file that is passed to the read_pickle() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the read_pickle() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner. | {'CVE-2020-13091'} | 2020-05-19T19:12:00Z | 2020-05-15T19:15:00Z | null | null | null | {'https://github.com/0FuzzingQ/vuln/blob/master/pandas%20unserialize.md', 'https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_pickle.html'} | null |
PyPI | PYSEC-2022-161 | null | Open Redirect in GitHub repository archivy/archivy prior to 1.7.0. | {'GHSA-28mg-98xm-q493', 'CVE-2022-0697'} | 2022-03-11T17:31:40.885093Z | 2022-03-06T23:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-28mg-98xm-q493', 'https://github.com/archivy/archivy/commit/2d8cb29853190d42572b36deb61127e68d6be574', 'https://huntr.dev/bounties/2d0301a2-10ff-48f4-a346-5a0e8707835b'} | null |
PyPI | PYSEC-2021-187 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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-f78g-q7r4-9wcv', 'CVE-2021-29550'} | 2021-08-27T03:22:30.332227Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv'} | null |
PyPI | PYSEC-2021-168 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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-2021-29531', 'GHSA-3qxp-qjq7-w4hf'} | 2021-08-27T03:22:26.851089Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf', 'https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1'} | null |
PyPI | PYSEC-2021-2 | null | Improper Access Control on Configurations Endpoint for the Stable API of Apache Airflow allows users with Viewer or User role to get Airflow Configurations including sensitive information even when `[webserver] expose_config` is set to `False` in `airflow.cfg`. This allowed a privilege escalation attack. This issue affects Apache Airflow 2.0.0. | {'CVE-2021-26559', 'GHSA-ffw3-6mp6-jmvj'} | 2021-02-23T17:48:00Z | 2021-02-17T15:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/r3b3787700279ec361308cbefb7c2cce2acb26891a12ce864e4a13c8d%40%3Cusers.airflow.apache.org%3E', 'https://github.com/advisories/GHSA-ffw3-6mp6-jmvj', 'https://lists.apache.org/thread.html/rd142565996d7ee847b9c14b8a9921dcf80bc6bc160e3d9dca6dfc2f8@%3Cannounce.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2021/02/17/1'} | null |
PyPI | GHSA-6mww-xvh7-fq4f | Koji hub call does not perform correct access checks | Koji version 1.12, 1.13, 1.14 and 1.15 contain an incorrect access control vulnerability resulting in arbitrary filesystem read/write access. This vulnerability has been fixed in versions 1.12.1, 1.13.1, 1.14.1 and 1.15.1. | {'CVE-2018-1002150'} | 2022-04-26T18:16:55.774348Z | 2018-07-12T20:29:40Z | CRITICAL | null | {'CWE-732'} | {'https://pagure.io/koji', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1002150', 'https://pagure.io/koji/issue/850', 'https://docs.pagure.org/koji/CVE-2018-1002150/', 'https://pagure.io/koji/c/ab1ade7'} | null |
PyPI | PYSEC-2021-492 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters. 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-2021-29564', 'GHSA-75f6-78jr-4656'} | 2021-12-09T06:34:53.290029Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-75f6-78jr-4656'} | null |
PyPI | PYSEC-2021-538 | null | TensorFlow is an end-to-end open source platform for machine learning. The validation in `tf.raw_ops.QuantizeAndDequantizeV2` allows invalid values for `axis` argument:. The validation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74-L77) uses `||` to mix two different conditions. If `axis_ < -1` the condition in `OP_REQUIRES` will still be true, but this value of `axis_` results in heap underflow. This allows attackers to read/write to other data on the heap. 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-mq5c-prh3-3f3h', 'CVE-2021-29610'} | 2021-12-09T06:35:00.479412Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mq5c-prh3-3f3h', 'https://github.com/tensorflow/tensorflow/commit/c5b0d5f8ac19888e46ca14b0e27562e7fbbee9a9'} | null |
PyPI | PYSEC-2014-39 | null | membership_tool.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to enumerate user account names via a crafted URL. | {'CVE-2012-5497'} | 2021-09-01T08:44:30.107520Z | 2014-09-30T14:55:00Z | null | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://plone.org/products/plone/security/advisories/20121106/13', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'http://rhn.redhat.com/errata/RHSA-2014-1194.html'} | null |
PyPI | GHSA-pg2f-r7pc-6fxx | Cross-Site Request Forgery in MicroPyramid Django CRM | Multiple CSRF issues exist in MicroPyramid Django CRM 0.2.1 via /change-password-by-admin/, /api/settings/add/, /cases/create/, /change-password-by-admin/, /comment/add/, /documents/1/view/, /documents/create/, /opportunities/create/, and /login/. | {'CVE-2019-11457'} | 2022-03-03T05:13:31.201761Z | 2019-09-11T22:57:57Z | HIGH | null | {'CWE-352'} | {'https://www.netsparker.com/blog/web-security/', 'https://nvd.nist.gov/vuln/detail/CVE-2019-11457', 'http://seclists.org/fulldisclosure/2019/Aug/30', 'http://packetstormsecurity.com/files/154219/Django-CRM-0.2.1-Cross-Site-Request-Forgery.html'} | null |
PyPI | GHSA-m8gq-83gh-v42v | XML External Entities Vulnerability in CVRF-CSAF-Converter | CVRF-CSAF-Converter before 1.0.0-rc2 resolves XML External Entities (XXE). This leads to the inclusion of arbitrary (local) file content into the generated output document. An attacker can exploit this to disclose information from the system running the converter. | {'CVE-2022-27193'} | 2022-03-28T17:31:58.173696Z | 2022-03-16T00:00:49Z | MODERATE | null | {'CWE-611', 'CWE-552'} | {'https://github.com/csaf-tools/CVRF-CSAF-Converter/releases/tag/1.0.0-rc2', 'https://nvd.nist.gov/vuln/detail/CVE-2022-27193', 'https://github.com/csaf-tools/CVRF-CSAF-Converter'} | null |
PyPI | GHSA-m87f-9fvv-2mgg | Deserialization of Untrusted Data in parlai | ### Impact
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.
### Patches
The issue can be patched by upgrading to v1.1.0 or later. It can also be patched by replacing YAML deserialization with equivalent safe_load calls.
### References
- https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725
- https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879
- https://anon-artist.github.io/blogs/blog3.html | {'CVE-2021-39207'} | 2022-03-03T05:14:11.580279Z | 2021-09-13T20:05:39Z | HIGH | null | {'CWE-502'} | {'https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725', 'https://github.com/facebookresearch/ParlAI', 'https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg', 'https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879', 'https://nvd.nist.gov/vuln/detail/CVE-2021-39207'} | null |
PyPI | PYSEC-2017-52 | null | Plone 3.3.0 through 3.3.6, 4.0.0 through 4.0.10, 4.1.0 through 4.1.6, 4.2.0 through 4.2.7, 4.3.0 through 4.3.6, and 5.0rc1 allows remote attackers to add a new member to a Plone site with registration enabled, without acknowledgment of site administrator. | {'CVE-2015-7315'} | 2021-07-25T23:34:48.187458Z | 2017-09-25T17:29:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2015/09/22/13', 'https://plone.org/security/hotfix/20150910/anonymous-is-able-to-create-plone-members', 'https://github.com/zopefoundation/Products.CMFCore/commit/e1d981bfa14b664317285f0f36498f4be4a23406', 'https://bugzilla.redhat.com/show_bug.cgi?id=1264791'} | null |
PyPI | GHSA-rjjg-hgv6-h69v | Memory corruption in Tensorflow | ### Impact
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:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/tfe_wrapper.cc#L1361
However, there is nothing stopping users from passing in a Python object instead of a tensor.
```python
In [2]: tf.experimental.dlpack.to_dlpack([2])
==1720623==WARNING: MemorySanitizer: use-of-uninitialized-value
#0 0x55b0ba5c410a in tensorflow::(anonymous namespace)::GetTensorFromHandle(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:46:7
#1 0x55b0ba5c38f4 in tensorflow::TFE_HandleToDLPack(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:252:26
...
```
The uninitialized memory address is due to a `reinterpret_cast`
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/eager/pywrap_tensor.cc#L848-L850
Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails.
### Patches
We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15193'} | 2021-08-26T15:11:03Z | 2020-09-25T18:28:27Z | HIGH | null | {'CWE-908'} | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15193', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2013-11 | null | The Python client library for Glance (python-glanceclient) before 0.10.0 does not properly check the preverify_ok value, which prevents the server hostname from being verified with a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate and allows man-in-the-middle attackers to spoof SSL servers via an arbitrary valid certificate. | {'CVE-2013-4111'} | 2021-07-05T00:01:25.393576Z | 2013-08-28T21:55:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-updates/2013-08/msg00019.html', 'https://github.com/openstack/python-glanceclient/blob/master/doc/source/index.rst', 'http://secunia.com/advisories/54313', 'http://rhn.redhat.com/errata/RHSA-2013-1200.html', 'https://bugs.launchpad.net/ossa/+bug/1192229', 'http://www.ubuntu.com/usn/USN-2004-1', 'http://secunia.com/advisories/54525'} | null |
PyPI | PYSEC-2021-685 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse 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. | {'CVE-2021-29559', 'GHSA-59q2-x2qc-4c97'} | 2021-12-09T06:35:24.947926Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/51300ba1cc2f487aefec6e6631fef03b0e08b298', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-59q2-x2qc-4c97'} | null |
PyPI | PYSEC-2021-25 | null | Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.28.0 requests to user provided domains were not restricted to external IP addresses when transitional IPv6 addresses were used. Outbound requests to federation, identity servers, when calculating the key validity for third-party invite events, sending push notifications, and generating URL previews are affected. This could cause Synapse to make requests to internal infrastructure on dual-stack networks. See referenced GitHub security advisory for details and workarounds. | {'GHSA-5wrh-4jwv-5w78', 'CVE-2021-21392'} | 2021-04-26T18:40:00Z | 2021-04-12T22:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/pull/9240', 'https://pypi.org/project/matrix-synapse/', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-5wrh-4jwv-5w78'} | null |
PyPI | GHSA-8xjv-v9xq-m5h9 | Moderate severity vulnerability that affects Pillow | Buffer overflow in the ImagingFliDecode function in libImaging/FliDecode.c in Pillow before 3.1.1 allows remote attackers to cause a denial of service (crash) via a crafted FLI file. | {'CVE-2016-0775'} | 2022-03-03T05:13:11.215565Z | 2018-07-24T20:15:36Z | MODERATE | null | {'CWE-119'} | {'https://github.com/python-pillow/Pillow/blob/c3cb690fed5d4bf0c45576759de55d054916c165/CHANGES.rst', 'https://nvd.nist.gov/vuln/detail/CVE-2016-0775', 'https://security.gentoo.org/glsa/201612-52', 'https://github.com/advisories/GHSA-8xjv-v9xq-m5h9', 'https://github.com/python-pillow/Pillow/commit/893a40850c2d5da41537958e40569c029a6e127b', 'https://github.com/python-pillow/Pillow', 'http://www.debian.org/security/2016/dsa-3499'} | null |
PyPI | PYSEC-2021-390 | null | TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-prcg-wp5q-rv7p', 'CVE-2021-41197'} | 2021-11-13T06:52:41.833730Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/7c1692bd417eb4f9b33ead749a41166d6080af85', 'https://github.com/tensorflow/tensorflow/commit/a871989d7b6c18cdebf2fb4f0e5c5b62fbc19edf', 'https://github.com/tensorflow/tensorflow/issues/51908', 'https://github.com/tensorflow/tensorflow/issues/46890', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-prcg-wp5q-rv7p', 'https://github.com/tensorflow/tensorflow/commit/d81b1351da3e8c884ff836b64458d94e4a157c15'} | null |
PyPI | GHSA-pg36-wpm5-g57p | HTTP Request Smuggling: LF vs CRLF handling in Waitress | ### Impact
Waitress implemented a &quot;MAY&quot; part of the RFC7230 (https://tools.ietf.org/html/rfc7230#section-3.5) which states:
Although the line terminator for the start-line and header fields is
the sequence CRLF, a recipient MAY recognize a single LF as a line
terminator and ignore any preceding CR.
Unfortunately if a front-end server does not parse header fields with an LF the same way as it does those with a CRLF it can lead to the front-end and the back-end server parsing the same HTTP message in two different ways. This can lead to a potential for HTTP request smuggling/splitting whereby Waitress may see two requests while the front-end server only sees a single HTTP message.
Example:
```
Content-Length: 100[CRLF]
X-Header: x[LF]Content-Length: 0[CRLF]
```
Would get treated by Waitress as if it were:
```
Content-Length: 100
X-Header: x
Content-Length: 0
```
This could potentially get used by attackers to split the HTTP request and smuggle a second request in the body of the first.
### Patches
This issue is fixed in Waitress 1.4.0. This brings a range of changes to harden Waitress against potential HTTP request confusions, and may change the behaviour of Waitress behind non-conformist proxies.
Waitress no longer implements the MAY part of the specification and instead requires that all lines are terminated correctly with CRLF. If any lines are found with a bare CR or LF a 400 Bad Request is sent back to the requesting entity.
The Pylons Project recommends upgrading as soon as possible, while validating that the changes in Waitress don&#39;t cause any changes in behavior.
### Workarounds
Various reverse proxies may have protections against sending potentially bad HTTP requests to the backend, and or hardening against potential issues like this. If the reverse proxy doesn&#39;t use HTTP/1.1 for connecting to the backend issues are also somewhat mitigated, as HTTP pipelining does not exist in HTTP/1.0 and Waitress will close the connection after every single request (unless the Keep Alive header is explicitly sent... so this is not a fool proof security method)
### Issues/more security issues:
* open an issue at https://github.com/Pylons/waitress/issues (if not sensitive or security related)
* email the Pylons Security mailing list: pylons-project-security@googlegroups.com (if security related) | {'CVE-2019-16785'} | 2022-04-25T23:17:05.279169Z | 2019-12-20T23:03:57Z | HIGH | null | {'CWE-444'} | {'https://docs.pylonsproject.org/projects/waitress/en/latest/#security-fixes', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16785', 'https://github.com/Pylons/waitress/security/advisories/GHSA-pg36-wpm5-g57p', 'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://github.com/Pylons/waitress', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYEOTGWJZVKPRXX2HBNVIYWCX73QYPM5/', 'https://access.redhat.com/errata/RHSA-2020:0720', 'https://github.com/Pylons/waitress/commit/8eba394ad75deaf9e5cd15b78a3d16b12e6b0eba', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GVDHR2DNKCNQ7YQXISJ45NT4IQDX3LJ7/'} | null |
PyPI | GHSA-hp4c-x6r7-6555 | Floating point exception in `SparseDenseCwiseDiv` | ### Impact
The implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error:
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.SparseDenseCwiseDiv(
sp_indices=np.array([[4]]),
sp_values=np.array([-400]),
sp_shape=np.array([647.]),
dense=np.array([0]))
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately.
### Patches
We have patched the issue in GitHub commit [d9204be9f49520cdaaeb2541d1dc5187b23f31d9](https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9).
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-2021-37636'} | 2022-03-03T05:12:25.706071Z | 2021-08-25T14:44:14Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hp4c-x6r7-6555', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37636'} | null |
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