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 | OSV-2021-1809 | Heap-buffer-overflow in ujson.cpython-38-x86_64-linux-gnu.so | OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=44973
```
Crash type: Heap-buffer-overflow WRITE 1
Crash state:
ujson.cpython-38-x86_64-linux-gnu.so
ujson.cpython-38-x86_64-linux-gnu.so
ujson.cpython-38-x86_64-linux-gnu.so
```
| null | 2022-04-13T03:04:31.104493Z | 2022-02-25T00:00:25.106722Z | HIGH | null | null | {'https://github.com/ultrajson/ultrajson/commit/550ba4d77294e61597a5259d00769c61281e0042', 'https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=44973'} | {'https://github.com/ultrajson/ultrajson/commit/b9275f7b001da11495040f1332f6c3adf3daa57b'} |
PyPI | PYSEC-2021-113 | null | Django Channels 3.x before 3.0.3 allows remote attackers to obtain sensitive information from a different request scope. The legacy channels.http.AsgiHandler class, used for handling HTTP type requests in an ASGI environment prior to Django 3.0, did not correctly separate request scopes in Channels 3.0. In many cases this would result in a crash but, with correct timing, responses could be sent to the wrong client, resulting in potential leakage of session identifiers and other sensitive data. Note that this affects only the legacy Channels provided class, and not Django's similar ASGIHandler, available from Django 3.0. | {'CVE-2020-35681', 'GHSA-v542-8q9x-cffc'} | 2021-02-26T12:36:00Z | 2021-02-22T03:15:00Z | null | null | null | {'https://channels.readthedocs.io/en/stable/releases/index.html', 'https://github.com/django/channels/releases', 'https://channels.readthedocs.io/en/stable/releases/3.0.3.html', 'https://github.com/advisories/GHSA-v542-8q9x-cffc'} | null |
PyPI | GHSA-756h-r2c9-qp5j | An authenticated user can execute arbitrary command in Gerapy | ### Impact
An authenticated user can execute arbitrary command, see more in https://github.com/Gerapy/Gerapy/issues/211.
### Patches
Fixed in 0.9.9 | {'CVE-2021-32849'} | 2022-03-03T05:13:27.640062Z | 2022-01-06T23:48:50Z | HIGH | null | {'CWE-78', 'CWE-77'} | {'https://github.com/Gerapy/Gerapy/issues/217', 'https://lgtm.com/projects/g/Gerapy/Gerapy?mode=tree&ruleFocus=1505994646253', 'https://github.com/Gerapy/Gerapy/issues/197', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32849', 'https://securitylab.github.com/advisories/GHSL-2021-076-gerapy/', 'https://github.com/Gerapy/Gerapy/security/advisories/GHSA-756h-r2c9-qp5j', 'https://github.com/Gerapy/Gerapy/'} | null |
PyPI | PYSEC-2021-543 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `ParseAttrValue`(https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/framework/attr_value_util.cc#L397-L453) can be tricked into stack overflow due to recursion by giving in a specially crafted input. 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-qw5h-7f53-xrp6', 'CVE-2021-29615'} | 2021-12-09T06:35:01.249240Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qw5h-7f53-xrp6', 'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1'} | null |
PyPI | GHSA-rgvq-pcvf-hx75 | Heap OOB and null pointer dereference in `RaggedTensorToTensor` | ### Impact
Due to lack of validation in `tf.raw_ops.RaggedTensorToTensor`, an attacker can exploit an undefined behavior if input arguments are empty:
```python
import tensorflow as tf
shape = tf.constant([-1, -1], shape=[2], dtype=tf.int64)
values = tf.constant([], shape=[0], dtype=tf.int64)
default_value = tf.constant(404, dtype=tf.int64)
row = tf.constant([269, 404, 0, 0, 0, 0, 0], shape=[7], dtype=tf.int64)
rows = [row]
types = ['ROW_SPLITS']
tf.raw_ops.RaggedTensorToTensor(
shape=shape, values=values, default_value=default_value,
row_partition_tensors=rows, row_partition_types=types)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L356-L360) only checks that one of the tensors is not empty, but does not check for the other ones.
There are multiple `DCHECK` validations to prevent heap OOB, but these are no-op in release builds, hence they don't prevent anything.
### Patches
We have patched the issue in GitHub commit [b761c9b652af2107cfbc33efd19be0ce41daa33e](https://github.com/tensorflow/tensorflow/commit/b761c9b652af2107cfbc33efd19be0ce41daa33e) followed by GitHub commit [f94ef358bb3e91d517446454edff6535bcfe8e4a](https://github.com/tensorflow/tensorflow/commit/f94ef358bb3e91d517446454edff6535bcfe8e4a) and GitHub commit [c4d7afb6a5986b04505aca4466ae1951686c80f6](https://github.com/tensorflow/tensorflow/commit/c4d7afb6a5986b04505aca4466ae1951686c80f6).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### 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-2021-29608'} | 2022-03-03T05:13:06.990646Z | 2021-05-21T14:28:27Z | MODERATE | null | {'CWE-131'} | {'https://github.com/tensorflow/tensorflow/commit/b761c9b652af2107cfbc33efd19be0ce41daa33e', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29608', 'https://github.com/tensorflow/tensorflow/commit/f94ef358bb3e91d517446454edff6535bcfe8e4a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rgvq-pcvf-hx75', 'https://github.com/tensorflow/tensorflow/commit/c4d7afb6a5986b04505aca4466ae1951686c80f6'} | null |
PyPI | PYSEC-2014-42 | null | The batch id change script (renameObjectsByPaths.py) in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to change the titles of content items by leveraging a valid CSRF token in a crafted request. | {'CVE-2012-5500'} | 2021-09-01T08:44:30.447394Z | 2014-11-03T22:55:00Z | null | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'http://rhn.redhat.com/errata/RHSA-2014-1194.html', 'https://plone.org/products/plone/security/advisories/20121106/16'} | null |
PyPI | GHSA-77gp-3h4r-6428 | Out of bounds read and write in Tensorflow | ### Impact
There is a typo in TensorFlow's [`SpecializeType`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L81-L102) which results in heap OOB read/write:
```cc
for (int i = 0; i < op_def.output_arg_size(); i++) {
// ...
for (int j = 0; j < t->args_size(); j++) {
auto* arg = t->mutable_args(i);
// ...
}
}
```
Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data.
### Patches
We have patched the issue in GitHub commit [0657c83d08845cc434175934c642299de2c0f042](https://github.com/tensorflow/tensorflow/commit/0657c83d08845cc434175934c642299de2c0f042).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23574'} | 2022-03-03T05:13:11.658649Z | 2022-02-09T23:25:40Z | HIGH | null | {'CWE-787', 'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/0657c83d08845cc434175934c642299de2c0f042', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23574', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L81-L102', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-77gp-3h4r-6428', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-810 | null | TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. 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-2021-41202', 'GHSA-xrqm-fpgr-6hhx'} | 2021-12-09T06:35:41.560413Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xrqm-fpgr-6hhx', 'https://github.com/tensorflow/tensorflow/commit/1b0e0ec27e7895b9985076eab32445026ae5ca94', 'https://github.com/tensorflow/tensorflow/issues/46912', 'https://github.com/tensorflow/tensorflow/commit/6d94002a09711d297dbba90390d5482b76113899', 'https://github.com/tensorflow/tensorflow/issues/46889'} | null |
PyPI | GHSA-v4x4-98cg-wr4g | Code injection in definitions | There is a vulnerability in load() method in definitions/parser.py in the Danijar Hafner definitions package for Python. It can execute arbitrary python commands resulting in command execution. | {'CVE-2018-20325'} | 2022-03-21T20:15:11.643551Z | 2018-12-26T17:45:19Z | CRITICAL | null | {'CWE-94'} | {'https://github.com/danijar/definitions/issues/14', 'https://github.com/danijar/definitions', 'https://nvd.nist.gov/vuln/detail/CVE-2018-20325'} | null |
PyPI | PYSEC-2020-113 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15190', 'GHSA-4g9f-63rx-5cw4'} | 2020-10-29T16:15:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/da8558533d925694483d2c136a9220d6d49d843c', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4g9f-63rx-5cw4'} | null |
PyPI | PYSEC-2013-5 | null | Directory traversal vulnerability in the _do_attachment_move function in the AttachFile action (action/AttachFile.py) in MoinMoin 1.9.3 through 1.9.5 allows remote attackers to overwrite arbitrary files via a .. (dot dot) in a file name. | {'CVE-2012-6080'} | 2021-07-05T00:01:22.941193Z | 2013-01-03T01:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2012/12/30/6', 'http://secunia.com/advisories/51676', 'http://www.debian.org/security/2012/dsa-2593', 'http://www.securityfocus.com/bid/57076', 'http://secunia.com/advisories/51696', 'http://moinmo.in/SecurityFixes', 'http://secunia.com/advisories/51663', 'https://bugs.launchpad.net/ubuntu/+source/moin/+bug/1094599', 'http://ubuntu.com/usn/usn-1680-1', 'http://hg.moinmo.in/moin/1.9/rev/3c27131a3c52'} | null |
PyPI | PYSEC-2018-61 | null | An issue was discovered in aubio 0.4.6. A SEGV signal can occur in aubio_source_avcodec_readframe in io/source_avcodec.c, as demonstrated by aubiomfcc. | {'CVE-2018-14521'} | 2021-08-25T04:29:55.761457Z | 2018-07-23T08:29:00Z | null | null | null | {'https://github.com/aubio/aubio/issues/187'} | null |
PyPI | PYSEC-2022-35 | null | Weblate is a copyleft software web-based continuous localization system. Versions prior to 4.11 do not properly neutralize user input used in user name and language fields. Due to this improper neutralization it is possible to perform cross-site scripting via these fields. The issues were fixed in the 4.11 release. Users unable to upgrade are advised to add their own neutralize logic. | {'GHSA-6jp6-9rf9-gc66', 'CVE-2022-24710'} | 2022-03-08T17:35:37.351702Z | 2022-02-25T21:15:00Z | null | null | null | {'https://github.com/WeblateOrg/weblate/commit/9e19a8414337692cc90da2a91c9af5420f2952f1', 'https://github.com/WeblateOrg/weblate/commit/22d577b1f1e88665a88b4569380148030e0f8389', 'https://github.com/WeblateOrg/weblate/commit/f6753a1a1c63fade6ad418fbda827c6750ab0bda', 'https://github.com/WeblateOrg/weblate/security/advisories/GHSA-6jp6-9rf9-gc66'} | null |
PyPI | PYSEC-2019-155 | null | python-dbusmock before version 0.15.1 AddTemplate() D-Bus method call or DBusTestCase.spawn_server_template() method could be tricked into executing malicious code if an attacker supplies a .pyc file. | {'GHSA-74xw-82v7-hmrm', 'CVE-2015-1326'} | 2021-07-05T00:01:25.330872Z | 2019-04-22T16:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-74xw-82v7-hmrm', 'https://github.com/martinpitt/python-dbusmock/commit/4e7d0df9093'} | null |
PyPI | PYSEC-2009-2 | null | Multiple cross-site scripting (XSS) vulnerabilities in Buildbot 0.7.6 through 0.7.11p2 allow remote attackers to inject arbitrary web script or HTML via unspecified vectors, different vulnerabilities than CVE-2009-2959. | {'CVE-2009-2967'} | 2021-07-15T02:22:07.247020Z | 2009-08-26T14:24:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/52896', 'http://buildbot.net/trac#SecurityAlert', 'https://www.redhat.com/archives/fedora-package-announce/2009-August/msg00978.html', 'https://www.redhat.com/archives/fedora-package-announce/2009-August/msg00985.html', 'http://www.securityfocus.com/bid/36100', 'http://sourceforge.net/mailarchive/message.php?msg_name=42338fbf0908130837o86b77d6y725233076286226f%40mail.gmail.com', 'http://www.vupen.com/english/advisories/2009/2352', 'http://secunia.com/advisories/36418', 'http://secunia.com/advisories/36352'} | null |
PyPI | GHSA-vfr4-x8j2-3rf9 | Division by zero in TFLite's implementation of `TransposeConv` | ### Impact
The optimized implementation of the `TransposeConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L5221-L5222):
```cc
int height_col = (height + pad_t + pad_b - filter_h) / stride_h + 1;
int width_col = (width + pad_l + pad_r - filter_w) / stride_w + 1;
```
An attacker can craft a model such that `stride_{h,w}` values are 0. Code calling this function must validate these arguments.
### Patches
We have patched the issue in GitHub commit [801c1c6be5324219689c98e1bd3e0ca365ee834d](https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d).
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-2021-29588'} | 2022-03-03T05:13:23.243455Z | 2021-05-21T14:26:48Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vfr4-x8j2-3rf9', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29588', 'https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d'} | null |
PyPI | PYSEC-2021-406 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` has an undefined behavior due to binding a reference to `nullptr`. 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-vwhq-49r4-gj9v', 'CVE-2021-41214'} | 2021-11-13T06:52:44.328170Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vwhq-49r4-gj9v'} | null |
PyPI | PYSEC-2021-328 | null | mitmproxy is an interactive, SSL/TLS-capable intercepting proxy. In mitmproxy 7.0.2 and below, a malicious client or server is able to perform HTTP request smuggling attacks through mitmproxy. This means that a malicious client/server could smuggle a request/response through mitmproxy as part of another request/response's HTTP message body. While a smuggled request is still captured as part of another request's body, it does not appear in the request list and does not go through the usual mitmproxy event hooks, where users may have implemented custom access control checks or input sanitization. Unless one uses mitmproxy to protect an HTTP/1 service, no action is required. The vulnerability has been fixed in mitmproxy 7.0.3 and above. | {'GHSA-22gh-3r9q-xf38', 'CVE-2021-39214'} | 2021-09-23T00:11:00.900340Z | 2021-09-16T15:15:00Z | null | null | null | {'https://github.com/mitmproxy/mitmproxy/security/advisories/GHSA-22gh-3r9q-xf38'} | null |
PyPI | PYSEC-2021-778 | 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'} | 2021-12-09T06:35:38.165715Z | 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 | PYSEC-2021-282 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0. 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 `&&`. We have patched the issue in GitHub 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. | {'GHSA-cm5x-837x-jf3c', 'CVE-2021-37660'} | 2021-08-27T03:22:44.908068Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c'} | null |
PyPI | PYSEC-2020-328 | null | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. | {'CVE-2020-15213', 'GHSA-hjmq-236j-8m87'} | 2021-12-09T06:35:15.598802Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a'} | null |
PyPI | PYSEC-2020-282 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15202', 'GHSA-h6fg-mjxg-hqq4'} | 2021-12-09T06:34:41.876848Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575', 'https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4'} | null |
PyPI | GHSA-gpfh-jvf9-7wg5 | Use after free / memory leak in `CollectiveReduceV2` | ### Impact
The [async implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/collective_ops.cc#L604-L615) of `CollectiveReduceV2` suffers from a memory leak and a use after free:
```python
import tensorflow as tf
tf.raw_ops.CollectiveReduceV2(
input=[],
group_size=[-10, -10, -10],
group_key=[-10, -10],
instance_key=[-10],
ordering_token=[],
merge_op='Mul',
final_op='Div')
```
This occurs due to the asynchronous computation and the fact that objects that have been `std::move()`d from are still accessed:
```cc
auto done_with_cleanup = [col_params, done = std::move(done)]() {
done();
col_params->Unref();
};
OP_REQUIRES_OK_ASYNC(c,
FillCollectiveParams(col_params, REDUCTION_COLLECTIVE,
/*group_size*/ c->input(1),
/*group_key*/ c->input(2),
/*instance_key*/ c->input(3)),
done);
```
Here, `done` is already moved from by the time `OP_REQUIRES_OK_ASYNC` macro needs to invoke it in case of errors. In this case, we get an undefined behavior, which can manifest via crashes, `std::bad_alloc` throws or just memory leaks.
### Patches
We have patched the issue in GitHub commit [ca38dab9d3ee66c5de06f11af9a4b1200da5ef75](https://github.com/tensorflow/tensorflow/commit/ca38dab9d3ee66c5de06f11af9a4b1200da5ef75).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
| {'CVE-2021-41220'} | 2021-11-08T22:07:11Z | 2021-11-10T18:51:21Z | HIGH | null | {'CWE-416'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41220', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gpfh-jvf9-7wg5', 'https://github.com/tensorflow/tensorflow/commit/ca38dab9d3ee66c5de06f11af9a4b1200da5ef75'} | null |
PyPI | PYSEC-2021-797 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version. | {'CVE-2021-37686', 'GHSA-mhhc-q96p-mfm9'} | 2021-12-09T06:35:39.861916Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mhhc-q96p-mfm9'} | null |
PyPI | PYSEC-2022-7 | null | Django CMS 3.7.3 does not validate the plugin_type parameter while generating error messages for an invalid plugin type, resulting in a Cross Site Scripting (XSS) vulnerability. The vulnerability allows an attacker to execute arbitrary JavaScript code in the web browser of the affected user. | {'GHSA-hx7c-qpfq-xcrp', 'CVE-2021-44649'} | 2022-01-20T15:35:06.506852Z | 2022-01-12T13:15:00Z | null | null | null | {'https://sahildhar.github.io/blogpost/Django-CMS-Reflected-XSS-Vulnerability/', 'https://www.django-cms.org/en/blog/2020/07/22/django-cms-security-updates-1/', 'https://github.com/advisories/GHSA-hx7c-qpfq-xcrp'} | null |
PyPI | PYSEC-2021-72 | null | This affects the package pwntools before 4.3.1. The shellcraft generator for affected versions of this module are vulnerable to Server-Side Template Injection (SSTI), which can lead to remote code execution. | {'SNYK-PYTHON-PWNTOOLS-1047345', 'CVE-2020-28468', 'GHSA-7xc5-ggpp-g249'} | 2021-01-12T19:55:00Z | 2021-01-08T12:15:00Z | null | null | null | {'https://github.com/Gallopsled/pwntools/pull/1732', 'https://github.com/Gallopsled/pwntools/issues/1427', 'https://snyk.io/vuln/SNYK-PYTHON-PWNTOOLS-1047345', 'https://github.com/advisories/GHSA-7xc5-ggpp-g249'} | null |
PyPI | GHSA-rf3h-xgv5-2q39 | Division by zero in TFLite's implementation of `DepthwiseConv` | ### Impact
The implementation of the `DepthwiseConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288):
```cc
int num_input_channels = SizeOfDimension(input, 3);
TF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0);
```
An attacker can craft a model such that `input`'s fourth dimension would be 0.
### Patches
We have patched the issue in GitHub commit [cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0](https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0).
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-2021-29602'} | 2022-03-03T05:13:41.084874Z | 2021-05-21T14:28:12Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29602', 'https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rf3h-xgv5-2q39'} | null |
PyPI | PYSEC-2018-36 | null | Ansible before 1.2.1 makes it easier for remote attackers to conduct man-in-the-middle attacks by leveraging failure to cache SSH host keys. | {'CVE-2013-2233', 'GHSA-9x6q-5423-w5v9'} | 2021-07-02T02:41:32.885648Z | 2018-05-04T20:29:00Z | null | null | null | {'https://www.ansible.com/security', 'http://www.openwall.com/lists/oss-security/2013/07/02/6', 'https://github.com/advisories/GHSA-9x6q-5423-w5v9', 'https://github.com/ansible/ansible/issues/857', 'https://bugzilla.redhat.com/show_bug.cgi?id=980821', 'http://www.openwall.com/lists/oss-security/2013/07/01/2'} | null |
PyPI | PYSEC-2020-144 | null | In Tortoise ORM before versions 0.15.23 and 0.16.6, various forms of SQL injection have been found for MySQL and when filtering or doing mass-updates on char/text fields. SQLite & PostgreSQL are only affected when filtering with contains, starts_with, or ends_with filters (and their case-insensitive counterparts). | {'CVE-2020-11010', 'GHSA-9j2c-x8qm-qmjq'} | 2020-04-28T17:16:00Z | 2020-04-20T22:15:00Z | null | null | null | {'https://github.com/tortoise/tortoise-orm/commit/91c364053e0ddf77edc5442914c6f049512678b3', 'https://github.com/tortoise/tortoise-orm/security/advisories/GHSA-9j2c-x8qm-qmjq'} | null |
PyPI | PYSEC-2021-847 | null | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41206', 'GHSA-pgcq-h79j-2f69'} | 2021-12-13T06:20:52.886778Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69', 'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07', 'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d'} | null |
PyPI | PYSEC-2017-2 | null | The user module in ansible before 1.6.6 allows remote authenticated users to execute arbitrary commands. | {'CVE-2014-3498'} | 2021-07-02T02:41:33.064199Z | 2017-06-08T18:29:00Z | null | null | null | {'https://github.com/ansible/ansible/commit/8ed6350e65c82292a631f08845dfaacffe7f07f5', 'https://bugzilla.redhat.com/show_bug.cgi?id=1335551'} | null |
PyPI | PYSEC-2014-15 | null | Cross-site scripting (XSS) vulnerability in the history display in Roundup before 1.4.20 allows remote attackers to inject arbitrary web script or HTML via a username, related to generating a link. | {'CVE-2012-6130'} | 2021-07-05T00:01:25.790750Z | 2014-04-11T15:55:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/84189', 'https://bugzilla.redhat.com/show_bug.cgi?id=722672', 'https://pypi.python.org/pypi/roundup/1.4.20', 'http://www.openwall.com/lists/oss-security/2013/02/13/8', 'http://www.openwall.com/lists/oss-security/2012/11/10/2', 'http://issues.roundup-tracker.org/issue2550684'} | null |
PyPI | PYSEC-2016-28 | null | The convert extension in Mercurial before 3.8 might allow context-dependent attackers to execute arbitrary code via a crafted git repository name. | {'CVE-2016-3105'} | 2021-08-27T03:22:06.927942Z | 2016-05-09T20:59:00Z | null | null | null | {'https://selenic.com/hg/rev/a56296f55a5e', 'http://www.securityfocus.com/bid/90536', 'http://www.slackware.com/security/viewer.php?l=slackware-security&y=2016&m=slackware-security.533255', 'https://security.gentoo.org/glsa/201612-19', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_3.8_.2F_3.8.1_.282016-5-1.29', 'http://lists.opensuse.org/opensuse-updates/2016-05/msg00082.html', 'http://www.debian.org/security/2016/dsa-3570'} | null |
PyPI | PYSEC-2021-514 | null | TensorFlow is an end-to-end open source platform for machine learning. Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling `ComputePaddingHeightWidth`(https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90). Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero. 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-2021-29586', 'GHSA-26j7-6w8w-7922'} | 2021-12-09T06:34:56.717383Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-26j7-6w8w-7922'} | null |
PyPI | GHSA-4952-p58q-6crx | JupyterLab: XSS due to lack of sanitization of the action attribute of an html <form> | ### Impact
Untrusted notebook can execute code on load. This is a remote code execution, but requires user action to open a notebook.
### Patches
Patched in the following versions: 3.1.4, 3.0.17, 2.3.2, 2.2.10, 1.2.21.
### References
[OWASP Page on Restricting Form Submissions](https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet.html)
### For more information
If you have any questions or comments about this advisory, or vulnerabilities to report, please email our security list security@ipython.org.
Credit: Guillaume Jeanne from Google
| {'CVE-2021-32797'} | 2022-04-08T22:00:13.419205Z | 2021-08-23T19:40:22Z | HIGH | null | {'CWE-87', 'CWE-79', 'CWE-75'} | {'https://github.com/jupyterlab/jupyterlab/commit/504825938c0abfa2fb8ff8d529308830a5ae42ed', 'https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-4952-p58q-6crx', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32797', 'https://github.com/google/security-research/security/advisories/GHSA-c469-p3jp-2vhx'} | null |
PyPI | PYSEC-2021-144 | null | XML External Entities (XXE) in Quokka v0.4.0 allows remote attackers to execute arbitrary code via the component 'quokka/utils/atom.py'. | {'CVE-2020-18703', 'GHSA-3xg5-6c3j-vp8x'} | 2021-08-27T03:22:19.043898Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-3xg5-6c3j-vp8x', 'https://github.com/rochacbruno/quokka/issues/676'} | null |
PyPI | PYSEC-2021-451 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.AddManySparseToTensorsMap`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/kernels/sparse_tensors_map_ops.cc#L257) takes the values specified in `sparse_shape` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-2cpx-427x-q2c6', 'CVE-2021-29523'} | 2021-12-09T06:34:46.920888Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2cpx-427x-q2c6'} | null |
PyPI | PYSEC-2018-102 | null | A vulnerability was found in openstack-tripleo-heat-templates before version 8.0.2-40. When deployed using Director using default configuration, Opendaylight in RHOSP13 is configured with easily guessable default credentials. | {'CVE-2018-10898'} | 2021-08-27T03:22:48.494449Z | 2018-07-30T17:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10898', 'https://access.redhat.com/errata/RHSA-2018:2214'} | null |
PyPI | GHSA-xqxm-2rpm-3889 | Comment reply notifications sent to incorrect users | ### Impact
When notifications for new replies in comment threads are sent, they are sent to all users who have replied or commented anywhere on the site, rather than only in the relevant threads. This means that a user could listen in to new comment replies on pages they have not had editing access to, as long as they have left a comment or reply somewhere on the site.
### Patches
A patched version has been released as Wagtail 2.15.2 (for the current LTS), which restores the intended behaviour - to send notifications for new replies to the participants in the active thread only (editing permissions are not considered).
### Workarounds
New comments can be disabled by setting `WAGTAILADMIN_COMMENTS_ENABLED = False` in the Django settings file.
### Acknowledgements
Many thanks to Ihor Marhitych for identifying this issue.
### For more information
If you have any questions or comments about this advisory:
* Visit Wagtail's [support channels](https://docs.wagtail.io/en/stable/support.html)
* Email us at security@wagtail.io (if you wish to send encrypted email, the public key ID is `0x6ba1e1a86e0f8ce8`)
| {'CVE-2022-21683'} | 2022-03-03T05:14:03.080144Z | 2022-01-21T23:43:50Z | LOW | null | {'CWE-200'} | {'https://github.com/wagtail/wagtail', 'https://github.com/wagtail/wagtail/releases/tag/v2.15.2', 'https://github.com/wagtail/wagtail/security/advisories/GHSA-xqxm-2rpm-3889', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21683', 'https://github.com/wagtail/wagtail/commit/5fe901e5d86ed02dbbb63039a897582951266afd'} | null |
PyPI | PYSEC-2019-102 | null | Eval injection in the Math plugin of Limnoria (before 2019.11.09) and Supybot (through 2018-05-09) allows remote unprivileged attackers to disclose information or possibly have unspecified other impact via the calc and icalc IRC commands. | {'CVE-2019-19010', 'GHSA-6g88-vr3v-76mf'} | 2020-08-24T17:37:00Z | 2019-11-16T01:15:00Z | null | null | null | {'https://github.com/ProgVal/Limnoria/wiki/math-eval-vulnerability', 'https://github.com/advisories/GHSA-6g88-vr3v-76mf', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/54CQM2TEXRADLE77VOMCPHL5PBHR3ZWJ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/5P2AGND54UIJV3WHOYO2YINIXSDGAAPO/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DRNOUHFEN75QAIKT4Y3HDN3TT5LSIWN2/', 'https://github.com/ProgVal/Limnoria/commit/3848ae78de45b35c029cc333963d436b9d2f0a35'} | null |
PyPI | PYSEC-2022-62 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. 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-x4qx-4fjv-hmw6', 'CVE-2022-21738'} | 2022-03-09T00:17:31.553710Z | 2022-02-03T14:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x4qx-4fjv-hmw6', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/count_ops.cc#L168-L273', 'https://github.com/tensorflow/tensorflow/commit/6f4d3e8139ec724dbbcb40505891c81dd1052c4a'} | null |
PyPI | PYSEC-2020-294 | null | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. | {'CVE-2020-15214', 'GHSA-p2cq-cprg-frvm'} | 2021-12-09T06:34:43.930382Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a'} | null |
PyPI | PYSEC-2017-13 | null | FedMsg 0.18.1 and older is vulnerable to a message validation flaw resulting in message validation not being enabled if configured to be on. | {'CVE-2017-1000001', 'GHSA-p7xc-35m8-57pr'} | 2021-07-05T00:01:21.573658Z | 2017-07-17T13:18:00Z | null | null | null | {'https://github.com/fedora-infra/fedmsg/blob/0.18.2/CHANGELOG.rst', 'https://github.com/advisories/GHSA-p7xc-35m8-57pr'} | null |
PyPI | GHSA-hgg3-g7gr-66r7 | High severity vulnerability that affects pycryptodome | PyCryptodome before 3.6.6 has an integer overflow in the data_len variable in AESNI.c, related to the AESNI_encrypt and AESNI_decrypt functions, leading to the mishandling of messages shorter than 16 bytes. | {'CVE-2018-15560'} | 2022-03-03T05:13:35.599028Z | 2018-08-27T19:52:28Z | HIGH | null | {'CWE-190'} | {'https://whitehatck01.blogspot.com/2018/08/integer-overflow-vulnerability-in.html', 'https://nvd.nist.gov/vuln/detail/CVE-2018-15560', 'https://github.com/advisories/GHSA-hgg3-g7gr-66r7', 'https://github.com/Legrandin/pycryptodome', 'https://github.com/Legrandin/pycryptodome/issues/198'} | null |
PyPI | PYSEC-2021-294 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-5hj3-vjjf-f5m7', 'CVE-2021-37672'} | 2021-08-27T03:22:46.024313Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a4e138660270e7599793fa438cd7b2fc2ce215a6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hj3-vjjf-f5m7'} | null |
PyPI | GHSA-7v94-64hj-m82h | FPE in `ParallelConcat` | ### Impact
The [implementation of `ParallelConcat`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/inplace_ops.cc#L72-L97) misses some input validation and can produce a division by 0:
```python
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.ParallelConcat(values=[['tf']],shape=0)
return y
test()
```
### Patches
We have patched the issue in GitHub commit [f2c3931113eaafe9ef558faaddd48e00a6606235](https://github.com/tensorflow/tensorflow/commit/f2c3931113eaafe9ef558faaddd48e00a6606235).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41207'} | 2022-03-03T05:14:00.378314Z | 2021-11-10T19:02:57Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7v94-64hj-m82h', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41207', 'https://github.com/tensorflow/tensorflow/commit/f2c3931113eaafe9ef558faaddd48e00a6606235'} | null |
PyPI | GHSA-3gw4-m5w7-v89c | Uncontrolled Resource Consumption in Indy Node | # Summary
Indy Node has a bug in TAA handling code. The current primary can be crashed with a malformed transaction from a client, which leads to a view change. Repeated rapid view changes have the potential of bringing down the network.
# Discovery
On May 18, Evernym's monitoring of Sovrin StagingNet showed a report of StagingNet losing sufficient consensus to validate write transactions. The problem resolved itself within a few minutes. On May 20th we saw the alert multiple times, and we began analyzing the logs of our steward node. On May 21st we continued to see the alerts with increasing frequency.
It appears that someone is unknowingly sending a malformed transaction, and retrying when the transaction fails. The cause of the errors appear to be the TAA acceptance.
# Proposed actions
* Reproduce problem in integration tests and create a fix
* Do a hotfix release branching from last stable (current master have some things merged that are too risky)
* Upgrade BuilderNet, StagingNet and MainNet as soon as possible
* Improve testing strategy on Indy Node to reduce probability of such bugs
# Notes
* The journalctl logs also show an out-of-memory problem on the Australia node. We need to evaluate if this should be raised as a separate issue. | {'CVE-2020-11090'} | 2022-03-03T05:12:40.002966Z | 2020-06-11T00:04:15Z | HIGH | null | {'CWE-400'} | {'https://github.com/hyperledger/indy-node/blob/master/CHANGELOG.md#1123', 'https://github.com/hyperledger/indy-node/security/advisories/GHSA-3gw4-m5w7-v89c', 'https://pypi.org/project/indy-node/1.12.3/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-11090'} | null |
PyPI | GHSA-v2wc-pfq2-5cm6 | Possible XSS attack in Wagtail | ### Impact
A cross-site scripting (XSS) vulnerability exists on the page revision comparison view within the Wagtail admin interface. A user with a limited-permission editor account for the Wagtail admin could potentially craft a page revision history that, when viewed by a user with higher privileges, could perform actions with that user's credentials. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin.
### Patches
Patched versions have been released as Wagtail 2.7.2 (for the LTS 2.7 branch) and Wagtail 2.8.1 (for the current 2.8 branch).
### Workarounds
Site owners who are unable to upgrade to the new versions can disable the revision comparison view by adding the following URL route to the top of their project's `urls.py` configuration:
from django.views.generic.base import RedirectView
urlpatterns = [
url(r'^admin/pages/(\d+)/revisions/compare/', RedirectView.as_view(url='/admin/')),
# ...
]
### Acknowledgements
Many thanks to Vlad Gerasimenko for reporting this issue.
### For more information
If you have any questions or comments about this advisory:
* Visit Wagtail's [support channels](https://docs.wagtail.io/en/stable/support.html)
* Email us at [security@wagtail.io](mailto:security@wagtail.io) (if you wish to send encrypted email, the public key ID is `0x6ba1e1a86e0f8ce8`) | {'CVE-2020-11001'} | 2022-03-03T05:14:12.582949Z | 2020-04-14T23:09:29Z | MODERATE | null | {'CWE-80'} | {'https://github.com/wagtail/wagtail/security/advisories/GHSA-v2wc-pfq2-5cm6', 'https://nvd.nist.gov/vuln/detail/CVE-2020-11001', 'https://github.com/wagtail/wagtail/commit/61045ceefea114c40ac4b680af58990dbe732389', 'https://github.com/wagtail/wagtail/releases/tag/v2.8.1'} | null |
PyPI | GHSA-828x-qc2p-wprq | Undefined behavior in `MaxPool3DGradGrad` | ### Impact
The implementation of `tf.raw_ops.MaxPool3DGradGrad` exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors:
```python
import tensorflow as tf
orig_input = tf.constant([0.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
orig_output = tf.constant([0.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
grad = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
ksize = [1, 1, 1, 1, 1]
strides = [1, 1, 1, 1, 1]
padding = "SAME"
tf.raw_ops.MaxPool3DGradGrad(
orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize,
strides=strides, padding=padding)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/72fe792967e7fd25234342068806707bbc116618/tensorflow/core/kernels/pooling_ops_3d.cc#L679-L703) fails to validate that the 3 tensor inputs are not empty. If any of them is empty, then accessing the elements in the tensor results in dereferencing a null pointer.
### Patches
We have patched the issue in GitHub commit [a3d9f9be9ac2296615644061b40cefcee341dcc4](https://github.com/tensorflow/tensorflow/commit/a3d9f9be9ac2296615644061b40cefcee341dcc4).
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-2021-29574'} | 2022-03-03T05:11:38.042452Z | 2021-05-21T14:26:10Z | LOW | null | {'CWE-476'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29574', 'https://github.com/tensorflow/tensorflow/commit/a3d9f9be9ac2296615644061b40cefcee341dcc4', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-828x-qc2p-wprq'} | null |
PyPI | PYSEC-2021-64 | null | django-filter is a generic system for filtering Django QuerySets based on user selections. In django-filter before version 2.4.0, automatically generated `NumberFilter` instances, whose value was later converted to an integer, were subject to potential DoS from maliciously input using exponential format with sufficiently large exponents. Version 2.4.0+ applies a `MaxValueValidator` with a a default `limit_value` of 1e50 to the form field used by `NumberFilter` instances. In addition, `NumberFilter` implements the new `get_max_validator()` which should return a configured validator instance to customise the limit, or else `None` to disable the additional validation. Users may manually apply an equivalent validator if they are not able to upgrade. | {'GHSA-x7gm-rfgv-w973', 'CVE-2020-15225'} | 2021-05-10T17:55:00Z | 2021-04-29T21:15:00Z | null | null | null | {'https://github.com/carltongibson/django-filter/security/advisories/GHSA-x7gm-rfgv-w973', 'https://pypi.org/project/django-filter/', 'https://github.com/carltongibson/django-filter/commit/340cf7a23a2b3dcd7183f6a0d6c383e85b130d2b', 'https://github.com/carltongibson/django-filter/releases/tag/2.4.0'} | null |
PyPI | PYSEC-2021-781 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-9697-98pf-4rw7', 'CVE-2021-37670'} | 2021-12-09T06:35:38.435010Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9697-98pf-4rw7'} | null |
PyPI | GHSA-5gm3-px64-rw72 | Uncontrolled Resource Consumption in Pillow | There is a DoS vulnerability in Pillow before 6.2.2 caused by FpxImagePlugin.py calling the range function on an unvalidated 32-bit integer if the number of bands is large. On Windows running 32-bit Python, this results in an OverflowError or MemoryError due to the 2 GB limit. However, on Linux running 64-bit Python this results in the process being terminated by the OOM killer. | {'CVE-2019-19911'} | 2022-03-03T05:13:26.301897Z | 2020-04-01T16:36:44Z | HIGH | null | {'CWE-190'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://github.com/python-pillow/Pillow/commit/774e53bb132461d8d5ebefec1162e29ec0ebc63d', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631', 'https://nvd.nist.gov/vuln/detail/CVE-2019-19911', 'https://github.com/python-pillow/Pillow/blob/master/CHANGES.rst#622-2020-01-02'} | null |
PyPI | GHSA-9236-8w7q-rmrv | archivy is vulnerable to Cross-Site Request Forgery (CSRF) | archivy is vulnerable to Cross-Site Request Forgery (CSRF). There is [a fix](https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d) available in the master branch. | {'CVE-2021-4162'} | 2022-03-03T05:13:53.359632Z | 2022-01-06T21:59:50Z | MODERATE | null | {'CWE-352'} | {'https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d', 'https://nvd.nist.gov/vuln/detail/CVE-2021-4162', 'https://huntr.dev/bounties/e204a768-2129-4b6f-abad-e436309c7c32', 'https://github.com/archivy/archivy/'} | null |
PyPI | GHSA-j38c-25fj-mr84 | Stored XSS in Apache Airflow | An issue was found in Apache Airflow versions 1.10.10 and below. A stored XSS vulnerability was discovered in the Chart pages of the the "classic" UI. | {'CVE-2020-9485'} | 2022-03-03T05:13:44.543440Z | 2020-07-27T16:57:34Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-9485', 'https://lists.apache.org/thread.html/r7255cf0be3566f23a768e2a04b40fb09e52fcd1872695428ba9afe91%40%3Cusers.airflow.apache.org%3E'} | null |
PyPI | GHSA-6g88-vr3v-76mf | Eval injection in Supybot/Limnoria | Eval injection in the Math plugin of Limnoria (before 2019.11.09) and Supybot (through 2018-05-09) allows remote unprivileged attackers to disclose information or possibly have unspecified other impact via the calc and icalc IRC commands. | {'CVE-2019-19010'} | 2022-03-03T05:13:38.000662Z | 2019-11-20T01:31:31Z | CRITICAL | null | {'CWE-94'} | {'https://github.com/ProgVal/Limnoria/wiki/math-eval-vulnerability', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/54CQM2TEXRADLE77VOMCPHL5PBHR3ZWJ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/5P2AGND54UIJV3WHOYO2YINIXSDGAAPO/', 'https://nvd.nist.gov/vuln/detail/CVE-2019-19010', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DRNOUHFEN75QAIKT4Y3HDN3TT5LSIWN2/', 'https://github.com/ProgVal/Limnoria/commit/3848ae78de45b35c029cc333963d436b9d2f0a35'} | null |
PyPI | PYSEC-2021-152 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not validate that the tensor arguments are non-empty. 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-2021-29515', 'GHSA-hc6c-75p4-hmq4'} | 2021-08-27T03:22:24.038004Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a7116dd3913c4a4afd2a3a938573aa7c785fdfc6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hc6c-75p4-hmq4'} | null |
PyPI | PYSEC-2021-502 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors. The implementation(https://github.com/tensorflow/tensorflow/blob/72fe792967e7fd25234342068806707bbc116618/tensorflow/core/kernels/pooling_ops_3d.cc#L679-L703) fails to validate that the 3 tensor inputs are not empty. If any of them is empty, then accessing the elements in the tensor results in dereferencing a null pointer. 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-828x-qc2p-wprq', 'CVE-2021-29574'} | 2021-12-09T06:34:54.849798Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a3d9f9be9ac2296615644061b40cefcee341dcc4', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-828x-qc2p-wprq'} | null |
PyPI | PYSEC-2021-851 | null | Flask-AppBuilder is a development framework built on top of Flask. Verions prior to 3.3.4 contain an improper authentication vulnerability in the REST API. The issue allows for a malicious actor with a carefully crafted request to successfully authenticate and gain access to existing protected REST API endpoints. This only affects non database authentication types and new REST API endpoints. Users should upgrade to Flask-AppBuilder 3.3.4 to receive a patch. | {'CVE-2021-41265', 'GHSA-m3rf-7m4w-r66q'} | 2021-12-15T19:23:46.849981Z | 2021-12-09T17:15:00Z | null | null | null | {'https://github.com/dpgaspar/Flask-AppBuilder/commit/eba517aab121afa3f3f2edb011ec6bc4efd61fbc', 'https://github.com/dpgaspar/Flask-AppBuilder/security/advisories/GHSA-m3rf-7m4w-r66q', 'https://github.com/dpgaspar/Flask-AppBuilder/releases/tag/v3.3.4'} | null |
PyPI | PYSEC-2008-6 | null | Unspecified vulnerability in Trac before 0.11.2 allows attackers to cause a denial of service via unknown attack vectors related to "certain wiki markup." | {'CVE-2008-5646'} | 2021-07-16T01:31:34.451441Z | 2008-12-17T18:30:00Z | null | null | null | {'http://secunia.com/advisories/32652', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/46492', 'http://www.securityfocus.com/bid/32226', 'http://trac.edgewall.org/wiki/ChangeLog', 'http://www.vupen.com/english/advisories/2008/3080'} | null |
PyPI | PYSEC-2020-152 | null | In Wagtail before versions 2.8.1 and 2.7.2, a cross-site scripting (XSS) vulnerability exists on the page revision comparison view within the Wagtail admin interface. A user with a limited-permission editor account for the Wagtail admin could potentially craft a page revision history that, when viewed by a user with higher privileges, could perform actions with that user's credentials. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin. Patched versions have been released as Wagtail 2.7.2 (for the LTS 2.7 branch) and Wagtail 2.8.1 (for the current 2.8 branch). | {'GHSA-v2wc-pfq2-5cm6', 'CVE-2020-11001'} | 2020-04-15T19:15:00Z | 2020-04-14T23:15:00Z | null | null | null | {'https://github.com/wagtail/wagtail/security/advisories/GHSA-v2wc-pfq2-5cm6', 'https://github.com/wagtail/wagtail/commit/61045ceefea114c40ac4b680af58990dbe732389', 'https://github.com/wagtail/wagtail/releases/tag/v2.8.1'} | null |
PyPI | PYSEC-2018-20 | null | privacyIDEA version 2.23.1 and earlier contains a Improper Input Validation vulnerability in token validation api that can result in Denial-of-Service. This attack appear to be exploitable via http request with user=<space>&pass= to /validate/check url. This vulnerability appears to have been fixed in 2.23.2. | {'GHSA-7qqv-r2q4-jxhm', 'CVE-2018-1000809'} | 2021-06-10T06:51:13.416740Z | 2018-10-08T15:29:00Z | null | null | null | {'https://github.com/privacyidea/privacyidea/commit/a3edc09beffa2104f357fe24971ea3211ce40751', 'https://github.com/privacyidea/privacyidea/issues/1227', 'https://github.com/advisories/GHSA-7qqv-r2q4-jxhm'} | null |
PyPI | GHSA-g67g-hvc3-xmvf | Inconsistent input sanitisation leads to XSS vectors | ### Background
A variety of templates do not perform proper sanitization through HTML escaping.
Due to the lack of sanitization and use of ``jQuery.html()``, there are a whole host of XSS possibilities with specially crafted input to a variety of fields.
### Impact
OMERO.web before 5.11.0 and OMERO.figure before 4.4.1.
### Patches
Users should upgrade OMERO.web to 5.11.0 or higher and OMERO.figure to 4.4.1 or higher. | {'CVE-2021-41132'} | 2022-03-22T21:32:00.913617Z | 2021-10-14T21:19:23Z | CRITICAL | null | {'CWE-79', 'CWE-116'} | {'https://github.com/ome/omero-web', 'https://www.openmicroscopy.org/security/advisories/2021-SV3/', 'https://github.com/ome/omero-web/commit/0168067accde5e635341b3c714b1d53ae92ba424', 'https://github.com/ome/omero-web/security/advisories/GHSA-g67g-hvc3-xmvf', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41132'} | null |
PyPI | PYSEC-2022-74 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a `SavedModel` on disk such that `AttrDef`s of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23565', 'GHSA-4v5p-v5h9-6xjx'} | 2022-03-09T00:17:33.047887Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4v5p-v5h9-6xjx', 'https://github.com/tensorflow/tensorflow/commit/c2b31ff2d3151acb230edc3f5b1832d2c713a9e0'} | null |
PyPI | PYSEC-2020-49 | null | ** DISPUTED ** jsonpickle through 1.4.1 allows remote code execution during deserialization of a malicious payload through the decode() function. Note: It has been argued that this is expected and clearly documented behaviour. pickle is known to be capable of causing arbitrary code execution, and must not be used with un-trusted data. | {'CVE-2020-22083'} | 2020-12-23T15:38:00Z | 2020-12-17T16:15:00Z | null | null | null | {'https://github.com/jsonpickle/jsonpickle/issues/332#issuecomment-747807494', 'https://github.com/j0lt-github/python-deserialization-attack-payload-generator', 'https://versprite.com/blog/application-security/into-the-jar-jsonpickle-exploitation/', 'https://github.com/jsonpickle/jsonpickle/issues/332', 'https://gist.github.com/j0lt-github/bb543e77a1a10c33cb56cf23d0837874', 'https://access.redhat.com/security/cve/CVE-2020-22083'} | null |
PyPI | GHSA-vqp6-j452-j6wp | Open Redirect in CPython that affects users of OpenStack Nova | A vulnerability was found in CPython which is used by openstack-nova's console proxy, noVNC. By crafting a malicious URL, noVNC could be made to redirect to any desired URL. | {'CVE-2021-3654'} | 2022-03-11T22:31:58.845712Z | 2022-03-04T00:00:22Z | MODERATE | null | {'CWE-601'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-3654', 'https://opendev.org/openstack/nova', 'https://www.openwall.com/lists/oss-security/2021/07/29/2', 'https://security.openstack.org/ossa/OSSA-2021-002.html', 'https://bugs.python.org/issue32084', 'https://opendev.org/openstack/nova/commit/04d48527b62a35d912f93bc75613a6cca606df66', 'https://bugs.launchpad.net/nova/+bug/1927677', 'https://bugzilla.redhat.com/show_bug.cgi?id=1961439', 'https://opendev.org/openstack/nova/commit/8906552cfc2525a44251d4cf313ece61e57251eb'} | null |
PyPI | PYSEC-2019-114 | null | Prior to Spark 2.3.3, in certain situations Spark would write user data to local disk unencrypted, even if spark.io.encryption.enabled=true. This includes cached blocks that are fetched to disk (controlled by spark.maxRemoteBlockSizeFetchToMem); in SparkR, using parallelize; in Pyspark, using broadcast and parallelize; and use of python udfs. | {'CVE-2019-10099'} | 2020-06-23T00:15:00Z | 2019-08-07T17:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/c2a39c207421797f82823a8aff488dcd332d9544038307bf69a2ba9e@%3Cuser.spark.apache.org%3E', 'https://lists.apache.org/thread.html/ra216b7b0dd82a2c12c2df9d6095e689eb3f3d28164e6b6587da69fae@%3Ccommits.spark.apache.org%3E', 'https://lists.apache.org/thread.html/rabe1d47e2bf8b8f6d9f3068c8d2679731d57fa73b3a7ed1fa82406d2@%3Cissues.spark.apache.org%3E'} | null |
PyPI | PYSEC-2012-1 | null | Beaker before 1.6.4, when using PyCrypto to encrypt sessions, uses AES in ECB cipher mode, which might allow remote attackers to obtain portions of sensitive session data via unspecified vectors. | {'CVE-2012-3458'} | 2021-07-05T00:01:17.212849Z | 2012-09-15T17:55:00Z | null | null | null | {'http://secunia.com/advisories/50226', 'https://bugzilla.redhat.com/show_bug.cgi?id=809267', 'http://www.debian.org/security/2012/dsa-2541', 'http://www.openwall.com/lists/oss-security/2012/08/13/10', 'https://github.com/bbangert/beaker/commit/91becae76101cf87ce8cbfabe3af2622fc328fe5', 'http://secunia.com/advisories/50520'} | null |
PyPI | PYSEC-2018-114 | null | Jubatus 1.0.2 and earlier allows remote code execution via unspecified vectors. | {'CVE-2018-0524'} | 2021-12-14T08:16:39.417454Z | 2018-03-09T16:29:00Z | null | null | null | {'https://pypi.org/project/jubatus', 'https://jvn.jp/en/jp/JVN56132776/index.html', 'https://nvd.nist.gov/vuln/detail/CVE-2018-0524', 'https://github.com/jubatus/jubatus/blob/master/ChangeLog.rst'} | null |
PyPI | PYSEC-2021-447 | null | TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. 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-772j-h9xw-ffp5', 'CVE-2021-29519'} | 2021-12-09T06:34:46.373650Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5'} | null |
PyPI | GHSA-xr38-w74q-r8jv | Permissions not properly checked in Invenio-Drafts-Resources | ### Impact
Invenio-Drafts-Resources does not properly check permissions when a record is published. The vulnerability is exploitable in a default installation of InvenioRDM. An authenticated user is able via REST API calls to publish draft records of other users if they know the record identifier and the draft validates (e.g. all require fields filled out). An attacker is not able to modify the data in the record, and thus e.g. *cannot* change a record from restricted to public.
### Details
The service's ``publish()`` method contains the following permission check:
```python
def publish(..):
self.require_permission(identity, "publish")
```
However, the record should have been passed into the permission check so that the need generators have access to e.g. the record owner.
```python
def publish(..):
self.require_permission(identity, "publish", record=record)
```
The bug is activated in Invenio-RDM-Records which has a need generator called ``RecordOwners()``, which when no record is passed in defaults to allow any authenticated user:
```python
class RecordOwners(Generator):
def needs(self, record=None, **kwargs):
if record is None:
return [authenticated_user]
# ...
```
### Patches
The problem is patched in Invenio-Drafts-Resources v0.13.7 and 0.14.6+, which is part of InvenioRDM v6.0.1 and InvenioRDM v7.0 respectively.
You can verify the version installed of Invenio-Drafts-Resources via PIP:
```console
cd ~/src/my-site
pipenv run pip freeze | grep invenio-drafts-resources
```
### References
- [Security policy](https://invenio.readthedocs.io/en/latest/community/security-policy.html)
### For more information
If you have any questions or comments about this advisory:
* Chat with us on Discord: https://discord.gg/8qatqBC
| {'CVE-2021-43781'} | 2022-03-03T05:14:00.978142Z | 2021-12-06T23:57:59Z | MODERATE | null | {'CWE-862'} | {'https://github.com/inveniosoftware/invenio-drafts-resources/commit/039b0cff1ad4b952000f4d8c3a93f347108b6626', 'https://nvd.nist.gov/vuln/detail/CVE-2021-43781', 'https://github.com/inveniosoftware/invenio-drafts-resources/security/advisories/GHSA-xr38-w74q-r8jv'} | null |
PyPI | PYSEC-2021-369 | null | The Unicorn framework before 0.36.1 for Django allows XSS via a component. NOTE: this issue exists because of an incomplete fix for CVE-2021-42053. | {'CVE-2021-42134', 'GHSA-ggmv-6q9p-9gm6'} | 2021-10-11T05:26:07.255634Z | 2021-10-11T01:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-ggmv-6q9p-9gm6', 'https://github.com/adamghill/django-unicorn/commit/3a832a9e3f6455ddd3b87f646247269918ad10c6', 'https://github.com/adamghill/django-unicorn/compare/0.36.0...0.36.1'} | null |
PyPI | PYSEC-2021-693 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.SparseDenseCwiseMul`, an attacker can trigger denial of service via `CHECK`-fails or accesses to outside the bounds of heap allocated data. Since the implementation(https://github.com/tensorflow/tensorflow/blob/38178a2f7a681a7835bb0912702a134bfe3b4d84/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L68-L80) only validates the rank of the input arguments but no constraints between dimensions(https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseDenseCwiseMul), an attacker can abuse them to trigger internal `CHECK` assertions (and cause program termination, denial of service) or to write to memory outside of bounds of heap allocated tensor buffers. 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-2021-29567', 'GHSA-wp3c-xw9g-gpcg'} | 2021-12-09T06:35:26.340630Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/7ae2af34087fb4b5c8915279efd03da3b81028bc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wp3c-xw9g-gpcg'} | null |
PyPI | GHSA-4j82-5ccr-4r8v | `CHECK`-failures in `TensorByteSize` in Tensorflow | ### Impact
A malicious user can cause a denial of service by altering a `SavedModel` such that [`TensorByteSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50) would trigger `CHECK` failures.
```cc
int64_t TensorByteSize(const TensorProto& t) {
// num_elements returns -1 if shape is not fully defined.
int64_t num_elems = TensorShape(t.tensor_shape()).num_elements();
return num_elems < 0 ? -1 : num_elems * DataTypeSize(t.dtype());
}
```
`TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`.
### Patches
We have patched the issue in GitHub commit [c2426bba00a01de6913738df8fa78e0215fcce02](https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23582'} | 2022-03-03T05:13:22.456322Z | 2022-02-10T00:34:01Z | MODERATE | null | {'CWE-617'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23582', 'https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-739 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `tf.raw_ops.CTCLoss` allows an attacker to trigger an OOB read from heap. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-vvg4-vgrv-xfr7', 'CVE-2021-29613'} | 2021-12-09T06:35:34.219918Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vvg4-vgrv-xfr7', 'https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c', 'https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b'} | null |
PyPI | PYSEC-2017-44 | null | In Django 1.10.x before 1.10.8 and 1.11.x before 1.11.5, HTML autoescaping was disabled in a portion of the template for the technical 500 debug page. Given the right circumstances, this allowed a cross-site scripting attack. This vulnerability shouldn't affect most production sites since you shouldn't run with "DEBUG = True" (which makes this page accessible) in your production settings. | {'CVE-2017-12794', 'GHSA-9r8w-6x8c-6jr9'} | 2021-07-15T02:22:10.638315Z | 2017-09-07T13:29:00Z | null | null | null | {'https://usn.ubuntu.com/3559-1/', 'http://www.securitytracker.com/id/1039264', 'http://www.securityfocus.com/bid/100643', 'https://www.djangoproject.com/weblog/2017/sep/05/security-releases/', 'https://github.com/advisories/GHSA-9r8w-6x8c-6jr9'} | null |
PyPI | GHSA-cf3c-fffp-34qh | High severity vulnerability that affects conference-scheduler-cli | In conference-scheduler-cli, a pickle.load call on imported data allows remote attackers to execute arbitrary code via a crafted .pickle file, as demonstrated by Python code that contains an os.system call. | {'CVE-2018-14572'} | 2022-03-03T05:13:14.145609Z | 2018-10-29T19:05:38Z | HIGH | null | {'CWE-78', 'CWE-502'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-14572', 'https://joel-malwarebenchmark.github.io/blog/2020/04/25/cve-2018-14572-conference-scheduler-cli/', 'https://github.com/PyconUK/ConferenceScheduler-cli', 'https://github.com/PyconUK/ConferenceScheduler-cli/issues/19', 'https://github.com/advisories/GHSA-cf3c-fffp-34qh'} | null |
PyPI | PYSEC-2021-386 | null | JupyterHub is an open source multi-user server for Jupyter notebooks. In affected versions users who have multiple JupyterLab tabs open in the same browser session, may see incomplete logout from the single-user server, as fresh credentials (for the single-user server only, not the Hub) reinstated after logout, if another active JupyterLab session is open while the logout takes place. Upgrade to JupyterHub 1.5. For distributed deployments, it is jupyterhub in the _user_ environment that needs patching. There are no patches necessary in the Hub environment. The only workaround is to make sure that only one JupyterLab tab is open when you log out. | {'CVE-2021-41247', 'GHSA-cw7p-q79f-m2v7'} | 2021-11-10T19:23:06.087408Z | 2021-11-04T18:15:00Z | null | null | null | {'https://github.com/jupyterhub/jupyterhub/commit/5ac9e7f73a6e1020ffddc40321fc53336829fe27', 'https://github.com/jupyterhub/jupyterhub/security/advisories/GHSA-cw7p-q79f-m2v7'} | null |
PyPI | PYSEC-2021-33 | null | LinkedIn Oncall through 1.4.0 allows reflected XSS via /query because of mishandling of the "No results found for" message in the search bar. | {'GHSA-rfw2-x9f8-2f6m', 'CVE-2021-26722'} | 2021-02-08T20:54:00Z | 2021-02-05T18:15:00Z | null | null | null | {'https://github.com/linkedin/oncall/issues/341', 'https://github.com/advisories/GHSA-rfw2-x9f8-2f6m'} | null |
PyPI | GHSA-jfq2-rj7f-9gvf | Null pointer dereference in TensorFlow leads to exploitation | Google TensorFlow 1.6.x and earlier is affected by: Null Pointer Dereference. The type of exploitation is: context-dependent. | {'CVE-2018-7576'} | 2022-03-03T05:14:10.969109Z | 2019-04-24T16:11:27Z | MODERATE | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-002.md', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7576'} | null |
PyPI | GHSA-g4c2-ghfg-g5rh | Cross-site Scripting and Open Redirect in Products.ATContentTypes | ### Impact
Plone is vulnerable to reflected cross site scripting and open redirect when an attacker can get a compromised version of the image_view_fullscreen page in a cache, for example in Varnish.
The technique is known as cache poisoning.
Any later visitor can get redirected when clicking on a link on this page.
Usually only anonymous users are affected, but this depends on your cache settings.
### Patches
A new version 3.0.6 of Products.ATContentTypes has been released with a fix.
This version works on Plone 5.2 (Python 2 only) and will be included in Plone 5.2.7.
Note that the Products.CMFPlone package has the same problem in the 4.3 series.
`plone.app.contenttypes` has the same problem in all versions, see [advisory](https://github.com/plone/plone.app.contenttypes/security/advisories/GHSA-f7qw-5fgj-247x).
For all unpatched versions of the three packages, you can use the following workaround.
### Workaround
Make sure the image_view_fullscreen page is not stored in the cache.
In Plone:
* Login as Manager and go to Site Setup.
* Go to the 'Caching' control panel. If this does not exist, or 'Enable caching' is not checked, you should normally not be vulnerable.
* Click on the tab 'Caching operations'.
* Under 'Legacy template mappings' locate the ruleset 'Content item view'.
* From the last column ('Templates') remove 'image_view_fullscreen'.
* Click on Save.
### Reporter
This vulnerability was responsibly disclosed to the Plone Security Team by Gustav Hansen, F-Secure Consulting. Thank you!
### For more information
If you have any questions or comments about this advisory, email us at [security@plone.org](mailto:security@plone.org)
This is also the correct address to use when you want to report a possible vulnerability.
See [our security report policy](https://plone.org/security/report). | {'CVE-2022-23599'} | 2022-03-03T05:13:09.714324Z | 2022-01-28T23:10:37Z | MODERATE | null | {'CWE-79'} | {'https://github.com/plone/Products.ATContentTypes/commit/fc793f88f35a15a68b52e4abed77af0da5fdbab8', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23599', 'https://github.com/plone/Products.ATContentTypes/', 'https://github.com/plone/Products.ATContentTypes/security/advisories/GHSA-g4c2-ghfg-g5rh'} | null |
PyPI | PYSEC-2018-77 | null | The client in Tryton 5.x before 5.0.1 tries to make a connection to the bus in cleartext instead of encrypted under certain circumstances in bus.py and jsonrpc.py. This connection attempt fails, but it contains in the header the current session of the user. This session could then be stolen by a man-in-the-middle. | {'GHSA-32w7-9whp-cjp9', 'CVE-2018-19443'} | 2021-08-25T04:30:34.252835Z | 2018-11-22T19:29:00Z | null | null | null | {'https://discuss.tryton.org/t/security-release-for-issue7792/830', 'https://github.com/advisories/GHSA-32w7-9whp-cjp9', 'https://bugs.tryton.org/issue7792'} | null |
PyPI | PYSEC-2020-105 | null | The TLS module within SaltStack Salt through 3002 creates certificates with weak file permissions. | {'CVE-2020-17490'} | 2021-03-30T13:44:00Z | 2020-11-06T08:15:00Z | null | null | null | {'https://www.saltstack.com/blog/on-november-3-2020-saltstack-publicly-disclosed-three-new-cves/', 'https://security.gentoo.org/glsa/202011-13', 'https://www.debian.org/security/2021/dsa-4837', 'https://lists.debian.org/debian-lts-announce/2020/12/msg00007.html', 'https://docs.saltstack.com/en/latest/topics/releases/index.html#latest-branch-release', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TPOGB2F6XUAIGFDTOCQDNB2VIXFXHWMA/', 'http://lists.opensuse.org/opensuse-security-announce/2020-11/msg00029.html'} | null |
PyPI | PYSEC-2021-806 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.tile` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-2p25-55c9-h58q', 'CVE-2021-41198'} | 2021-12-09T06:35:40.903537Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f', 'https://github.com/tensorflow/tensorflow/issues/46911', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2p25-55c9-h58q'} | null |
PyPI | GHSA-mxjj-953w-2c2v | Data corruption in tensorflow-lite | ### Impact
When determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442
Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.
### Patches
We have patched the issue in 8ee24e7949a20 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-2020-15208'} | 2022-03-03T05:13:53.988672Z | 2020-09-25T18:28:44Z | HIGH | null | {'CWE-787', 'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15208', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2010-17 | null | Multiple cross-site scripting (XSS) vulnerabilities in MoinMoin 1.7.3 and earlier, and 1.9.x before 1.9.3, allow remote attackers to inject arbitrary web script or HTML via crafted content, related to (1) action/LikePages.py, (2) action/chart.py, and (3) action/userprofile.py, a similar issue to CVE-2010-2487. | {'CVE-2010-2969'} | 2021-07-16T01:31:23.735889Z | 2010-08-05T13:22:00Z | null | null | null | {'http://moinmo.in/MoinMoinBugs/1.9.2UnescapedInputForThemeAddMsg', 'http://hg.moinmo.in/moin/1.9/raw-file/1.9.3/docs/CHANGES', 'http://marc.info/?l=oss-security&m=127809682420259&w=2', 'http://www.vupen.com/english/advisories/2010/1981', 'http://www.securityfocus.com/bid/40549', 'http://hg.moinmo.in/moin/1.9/rev/e50b087c4572', 'http://marc.info/?l=oss-security&m=127799369406968&w=2', 'http://moinmo.in/SecurityFixes', 'http://moinmo.in/MoinMoinRelease1.9', 'http://secunia.com/advisories/40836', 'http://hg.moinmo.in/moin/1.7/rev/37306fba2189', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=584809', 'http://www.debian.org/security/2010/dsa-2083'} | null |
PyPI | GHSA-vqw6-72r7-fgw7 | OOB read in `MatrixTriangularSolve` | ### Impact
The implementation of [`MatrixTriangularSolve`](https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails:
```cc
void ValidateInputTensors(OpKernelContext* ctx, const Tensor& in0,
const Tensor& in1) override {
OP_REQUIRES(
ctx, in0.dims() >= 2,
errors::InvalidArgument("In[0] ndims must be >= 2: ", in0.dims()));
OP_REQUIRES(
ctx, in1.dims() >= 2,
errors::InvalidArgument("In[0] ndims must be >= 2: ", in1.dims()));
}
void Compute(OpKernelContext* ctx) override {
const Tensor& in0 = ctx->input(0);
const Tensor& in1 = ctx->input(1);
ValidateInputTensors(ctx, in0, in1);
MatMulBCast bcast(in0.shape().dim_sizes(), in1.shape().dim_sizes());
...
}
```
Since `OP_REQUIRES` only sets `ctx->status()` to a non-OK value and calls `return`, this allows malicious attackers to trigger an out of bounds read:
```python
import tensorflow as tf
import numpy as np
matrix_array = np.array([])
matrix_tensor = tf.convert_to_tensor(np.reshape(matrix_array,(1,0)),dtype=tf.float32)
rhs_array = np.array([])
rhs_tensor = tf.convert_to_tensor(np.reshape(rhs_array,(0,1)),dtype=tf.float32)
tf.raw_ops.MatrixTriangularSolve(matrix=matrix_tensor,rhs=rhs_tensor,lower=False,adjoint=False)
```
As the two input tensors are empty, the `OP_REQUIRES` in `ValidateInputTensors` should fire and interrupt execution. However, given the implementation of `OP_REQUIRES`, after the `in0.dims() >= 2` fails, execution moves to the initialization of the `bcast` object. This initialization is done with invalid data and results in heap OOB read.
### Patches
We have patched the issue in GitHub commit [480641e3599775a8895254ffbc0fc45621334f68](https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68).
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 Ye Zhang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29551'} | 2022-03-03T05:14:11.910094Z | 2021-05-21T14:23:44Z | LOW | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29551'} | null |
PyPI | PYSEC-2014-54 | null | Multiple cross-site scripting (XSS) vulnerabilities in (1) spamProtect.py, (2) pts.py, and (3) request.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allow remote attackers to inject arbitrary web script or HTML via unspecified vectors. | {'CVE-2013-4190'} | 2021-07-25T23:34:46.028547Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'https://bugzilla.redhat.com/show_bug.cgi?id=978451', 'http://seclists.org/oss-sec/2013/q3/261', 'http://plone.org/products/plone/security/advisories/20130618-announcement'} | null |
PyPI | PYSEC-2021-555 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_variable_ops.cc#L865) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit 4aacb30888638da75023e6601149415b39763d76. 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-2021-37642', 'GHSA-ch4f-829c-v5pw'} | 2021-12-09T06:35:02.576943Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ch4f-829c-v5pw', 'https://github.com/tensorflow/tensorflow/commit/4aacb30888638da75023e6601149415b39763d76'} | null |
PyPI | PYSEC-2021-105 | null | A flaw was found in the use of insufficiently random values in Ansible. Two random password lookups of the same length generate the equal value as the template caching action for the same file since no re-evaluation happens. The highest threat from this vulnerability would be that all passwords are exposed at once for the file. This flaw affects Ansible Engine versions before 2.9.6. | {'CVE-2020-10729', 'GHSA-r6h7-5pq2-j77h'} | 2021-07-02T02:41:34.811883Z | 2021-05-27T19:15:00Z | null | null | null | {'https://github.com/ansible/ansible/issues/34144', 'https://github.com/advisories/GHSA-r6h7-5pq2-j77h', 'https://bugzilla.redhat.com/show_bug.cgi?id=1831089'} | null |
PyPI | PYSEC-2021-410 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `AllToAll` can be made to execute a division by 0. This occurs whenever the `split_count` argument is 0. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41218', 'GHSA-9crf-c6qr-r273'} | 2021-11-13T06:52:44.955817Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273'} | null |
PyPI | GHSA-786j-5qwq-r36x | Segfault while copying constant resource tensor | ### Impact
During TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change.
### Patches
We have patched the issue in GitHub commit [7731e8dfbe4a56773be5dc94d631611211156659](https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions | {'CVE-2021-41204'} | 2022-03-03T05:14:03.106377Z | 2021-11-10T19:12:14Z | MODERATE | null | {'CWE-824'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41204', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-786j-5qwq-r36x', 'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} | null |
PyPI | PYSEC-2016-6 | null | 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. | {'GHSA-8xjv-v9xq-m5h9', 'CVE-2016-0775'} | 2021-07-05T00:01:23.974761Z | 2016-04-13T16:59:00Z | null | null | null | {'https://security.gentoo.org/glsa/201612-52', 'https://github.com/advisories/GHSA-8xjv-v9xq-m5h9', 'https://github.com/python-pillow/Pillow/commit/893a40850c2d5da41537958e40569c029a6e127b', 'http://www.debian.org/security/2016/dsa-3499', 'https://github.com/python-pillow/Pillow/blob/c3cb690fed5d4bf0c45576759de55d054916c165/CHANGES.rst'} | null |
PyPI | PYSEC-2019-143 | null | The LDAP auth backend (airflow.contrib.auth.backends.ldap_auth) prior to Apache Airflow 1.10.1 was misconfigured and contained improper checking of exceptions which disabled server certificate checking. | {'GHSA-77rc-x84q-pv4f', 'CVE-2018-20245'} | 2021-06-10T06:51:25.502672Z | 2019-01-23T17:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-77rc-x84q-pv4f', 'https://lists.apache.org/thread.html/b549c7573b342a6e457e5a3225c33054244343927bbfb2a4cdc4cf73@%3Cdev.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2022-23 | null | Server-Side Request Forgery (SSRF) in Pypi calibreweb prior to 0.6.16. | {'CVE-2022-0339', 'GHSA-4w8p-x6g8-fv64'} | 2022-02-04T19:19:26.704356Z | 2022-01-30T14:15:00Z | null | null | null | {'https://huntr.dev/bounties/499688c4-6ac4-4047-a868-7922c3eab369', 'https://github.com/janeczku/calibre-web/commit/3b216bfa07ec7992eff03e55d61732af6df9bb92', 'https://github.com/advisories/GHSA-4w8p-x6g8-fv64'} | null |
PyPI | PYSEC-2018-98 | null | A SQL injection vulnerability in pycsw all versions before 2.0.2, 1.10.5 and 1.8.6 that leads to read and extract of any data from any table in the pycsw database that the database user has access to. Also on PostgreSQL (at least) it is possible to perform updates/inserts/deletes and database modifications to any table the database user has access to. | {'CVE-2016-8640', 'GHSA-hg4c-rgvm-964g'} | 2021-08-27T03:22:16.790168Z | 2018-08-01T18:29:00Z | null | null | null | {'http://seclists.org/oss-sec/2016/q4/406', 'https://github.com/geopython/pycsw/pull/474/files', 'https://github.com/advisories/GHSA-hg4c-rgvm-964g', 'https://patch-diff.githubusercontent.com/raw/geopython/pycsw/pull/474.patch', 'http://www.securityfocus.com/bid/94302'} | null |
PyPI | PYSEC-2020-69 | null | Python oic is a Python OpenID Connect implementation. In Python oic before version 1.2.1, there are several related cryptographic issues affecting client implementations that use the library. The issues are: 1) The IdToken signature algorithm was not checked automatically, but only if the expected algorithm was passed in as a kwarg. 2) JWA `none` algorithm was allowed in all flows. 3) oic.consumer.Consumer.parse_authz returns an unverified IdToken. The verification of the token was left to the discretion of the implementator. 4) iat claim was not checked for sanity (i.e. it could be in the future). These issues are patched in version 1.2.1. | {'CVE-2020-26244', 'GHSA-4fjv-pmhg-3rfg'} | 2020-12-08T02:37:00Z | 2020-12-02T20:15:00Z | null | null | null | {'https://github.com/OpenIDC/pyoidc/security/advisories/GHSA-4fjv-pmhg-3rfg', 'https://pypi.org/project/oic/', 'https://github.com/OpenIDC/pyoidc/commit/62f8d753fa17c8b1f29f8be639cf0b33afb02498', 'https://github.com/OpenIDC/pyoidc/releases/tag/1.2.1'} | null |
PyPI | PYSEC-2022-54 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-vjg4-v33c-ggc4', 'CVE-2022-21730'} | 2022-03-09T00:17:30.562457Z | 2022-02-03T11:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360'} | null |
PyPI | GHSA-74vq-h4q8-x6jv | Critical severity vulnerability that affects ansible | Ansible fetch module before versions 2.5.15, 2.6.14, 2.7.8 has a path traversal vulnerability which allows copying and overwriting files outside of the specified destination in the local ansible controller host, by not restricting an absolute path. | {'CVE-2019-3828'} | 2022-03-03T05:13:53.482927Z | 2019-04-15T16:19:19Z | MODERATE | null | {'CWE-22'} | {'https://github.com/advisories/GHSA-74vq-h4q8-x6jv', 'https://nvd.nist.gov/vuln/detail/CVE-2019-3828'} | null |
PyPI | PYSEC-2019-134 | null | The validators package 0.12.2 through 0.12.5 for Python enters an infinite loop when validators.domain is called with a crafted domain string. This is fixed in 0.12.6. | {'GHSA-5qcg-w2cc-xffw', 'CVE-2019-19588'} | 2020-08-24T17:37:00Z | 2019-12-05T01:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-5qcg-w2cc-xffw', 'https://github.com/kvesteri/validators/issues/86'} | null |
PyPI | GHSA-428x-9xc2-m8mj | Division by zero in TFLite | ### Impact
An attacker can craft a TFLite model that would trigger a division by zero in [the implementation of depthwise convolutions](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/depthwise_conv.cc#L96).
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 stricly positive.
### Patches
We have patched the issue in GitHub commit [e5b0eec199c2d03de54fd6a7fd9275692218e2bc](https://github.com/tensorflow/tensorflow/commit/e5b0eec199c2d03de54fd6a7fd9275692218e2bc).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team. | {'CVE-2022-21741'} | 2022-03-03T05:13:55.518660Z | 2022-02-09T23:47:30Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-428x-9xc2-m8mj', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/depthwise_conv.cc#L96', 'https://github.com/tensorflow/tensorflow/commit/e5b0eec199c2d03de54fd6a7fd9275692218e2bc', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21741'} | null |
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