ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2017-24 | null | In PyJWT 1.5.0 and below the `invalid_strings` check in `HMACAlgorithm.prepare_key` does not account for all PEM encoded public keys. Specifically, the PKCS1 PEM encoded format would be allowed because it is prefaced with the string `-----BEGIN RSA PUBLIC KEY-----` which is not accounted for. This enables symmetric/asymmetric key confusion attacks against users using the PKCS1 PEM encoded public keys, which would allow an attacker to craft JWTs from scratch. | {'CVE-2017-11424'} | 2021-07-05T00:01:24.915848Z | 2017-08-24T16:29:00Z | null | null | null | {'http://www.debian.org/security/2017/dsa-3979', 'https://github.com/jpadilla/pyjwt/pull/277'} | null |
PyPI | PYSEC-2020-309 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1." | {'CVE-2020-15194', 'GHSA-9mqp-7v2h-2382'} | 2021-12-09T06:35:12.701793Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54', '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-9mqp-7v2h-2382'} | null |
PyPI | GHSA-7cqx-92hp-x6wh | Heap buffer overflow in `MaxPool3DGradGrad` | ### Impact
The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow:
```python
import tensorflow as tf
values = [0.01] * 11
orig_input = tf.constant(values, shape=[11, 1, 1, 1, 1], dtype=tf.float32)
orig_output = tf.constant([0.01], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
grad = tf.constant([0.01], shape=[1, 1, 1, 1, 1], 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/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully:
```cc
Pool3dParameters params{context, ksize_, stride_,
padding_, data_format_, tensor_in.shape()};
```
Since [the constructor](https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values.
### Patches
We have patched the issue in GitHub commit [63c6a29d0f2d692b247f7bf81f8732d6442fad09](https://github.com/tensorflow/tensorflow/commit/63c6a29d0f2d692b247f7bf81f8732d6442fad09).
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-2021-29576'} | 2022-04-26T18:17:16.903104Z | 2021-05-21T14:26:16Z | LOW | null | {'CWE-787', 'CWE-119'} | {'https://github.com/tensorflow/tensorflow/commit/63c6a29d0f2d692b247f7bf81f8732d6442fad09', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29576', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7cqx-92hp-x6wh'} | null |
PyPI | PYSEC-2021-470 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements. If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29542', 'GHSA-4hrh-9vmp-2jgg'} | 2021-12-09T06:34:49.894355Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hrh-9vmp-2jgg'} | null |
PyPI | GHSA-27p5-7cw6-m45h | Server-Side Request Forgery in unoconv | The unoconv package before 0.9 mishandles untrusted pathnames, leading to SSRF and local file inclusion. | {'CVE-2019-17400'} | 2022-03-03T05:14:15.988097Z | 2019-10-24T20:46:54Z | HIGH | null | {'CWE-918'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-17400', 'https://buer.haus/2019/10/18/a-tale-of-exploitation-in-spreadsheet-file-conversions/', 'https://github.com/unoconv/unoconv/pull/510'} | null |
PyPI | GHSA-947x-pv47-pp3q | Cross-site scripting in pywb | Webrecorder pywb before 2.6.0 allows XSS because it does not ensure that Jinja2 templates are autoescaped. | {'CVE-2021-39286'} | 2022-03-03T05:13:35.590334Z | 2021-09-02T17:16:18Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-39286', 'https://github.com/webrecorder/pywb/compare/v-2.5.0...v-2.6.0', 'https://github.com/webrecorder/pywb', 'https://github.com/webrecorder/pywb/commit/f7bd84cdacdd665ff73ae8d09a202f60be2ebae9'} | null |
PyPI | GHSA-mfjm-vh54-3f96 | Cookie-setting is not restricted based on the public suffix list | ### Impact
Responses from domain names whose public domain name suffix contains 1 or more periods (e.g. responses from `example.co.uk`, given its public domain name suffix is `co.uk`) are able to set cookies that are included in requests to any other domain sharing the same domain name suffix.
### Patches
Upgrade to Scrapy 2.6.0, which restricts cookies with their domain set to any of those in the [public suffix list](https://publicsuffix.org/).
If you are using Scrapy 1.8 or a lower version, and upgrading to Scrapy 2.6.0 is not an option, you may upgrade to Scrapy 1.8.2 instead.
### Workarounds
The only workaround for unpatched versions of Scrapy is to [disable cookies altogether](https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#std-setting-COOKIES_ENABLED), or [limit target domains](https://docs.scrapy.org/en/latest/topics/spiders.html#scrapy.spiders.Spider.allowed_domains) to a subset that does not include domain names with one of the public domain suffixes affected (those with 1 or more periods).
### References
* https://publicsuffix.org/
### For more information
If you have any questions or comments about this advisory:
* [Open an issue](https://github.com/scrapy/scrapy/issues)
* [Email us](mailto:opensource@zyte.com)
| null | 2022-03-07T20:47:42.301001Z | 2022-03-01T22:13:28Z | MODERATE | null | null | {'https://github.com/scrapy/scrapy/commit/e865c4430e58a4faa0e0766b23830f8423d6167a', 'https://github.com/scrapy/scrapy/security/advisories/GHSA-mfjm-vh54-3f96'} | null |
PyPI | GHSA-7q25-qrjw-6fg2 | Malicious package may avoid detection in python auditing | # Python Auditing Vulnerability
Demonstrates how a malicious package can insert a load-time poison pill to avoid detection by tools like Safety.
Tools that are designed to find vulnerable packages can not ever run in the same python environment that they are trying to protect.
## Usage
Install `safety`, `insecure-package`, and this package with pip in the same python environment. Order doesn't matter.
1. pip install safety
2. pip install insecure-package
3. pip install dist/malicious-0.1-py3-none-any.whl
Run the check
4. `safety check`
You should see both `Running my modified safety.check` and that `insecure-package` is not listed in the results!
## How it Works
Everything in Python is mutable. The trick is getting some code to run at interpreter load time in order to do some patching.
1. When you install this package, the `setup.py` settings installs a `malicious.pth` file to your `site-packages` directory.
2. The `malicious.pth` file gets loaded anytime Python starts, which in turn imports our `malicious` package.
3. The `malicious/__init__.py` patches the safety library with a custom function to avoid detection. | {'CVE-2020-5252'} | 2022-03-11T23:16:56.960727Z | 2020-03-24T15:07:56Z | MODERATE | null | {'CWE-807'} | {'https://github.com/akoumjian/python-safety-vuln', 'https://nvd.nist.gov/vuln/detail/CVE-2020-5252', 'https://pyup.io/posts/patched-vulnerability/', 'https://mulch.dev/blog/CVE-2020-5252-python-safety-vuln/', 'https://github.com/pyupio/safety', 'https://github.com/pyupio/safety/security/advisories/GHSA-7q25-qrjw-6fg2'} | null |
PyPI | PYSEC-2019-123 | null | SQLAlchemy through 1.2.17 and 1.3.x through 1.3.0b2 allows SQL Injection via the order_by parameter. | {'GHSA-887w-45rq-vxgf', 'CVE-2019-7164'} | 2021-01-20T15:15:00Z | 2019-02-20T00:29:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00087.html', 'https://github.com/sqlalchemy/sqlalchemy/issues/4481', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00016.html', 'https://access.redhat.com/errata/RHSA-2019:0984', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00010.html', 'https://www.oracle.com/security-alerts/cpujan2021.html', 'https://github.com/advisories/GHSA-887w-45rq-vxgf', 'https://access.redhat.com/errata/RHSA-2019:0981', 'https://lists.debian.org/debian-lts-announce/2019/03/msg00020.html'} | null |
PyPI | PYSEC-2022-43 | null | OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. In affected versions anyone with access to the chat environment can write messages disguised as another chat participant. | {'GHSA-gjj5-998g-v36v', 'CVE-2022-21692'} | 2022-03-09T00:16:43.273792Z | 2022-01-18T23:15:00Z | null | null | null | {'https://github.com/onionshare/onionshare/security/advisories/GHSA-gjj5-998g-v36v', 'https://github.com/onionshare/onionshare/releases/tag/v2.5'} | null |
PyPI | PYSEC-2018-17 | null | Jupyter Notebook before 5.7.1 allows XSS via an untrusted notebook because nbconvert responses are considered to have the same origin as the notebook server. In other words, nbconvert endpoints can execute JavaScript with access to the server API. In notebook/nbconvert/handlers.py, NbconvertFileHandler and NbconvertPostHandler do not set a Content Security Policy to prevent this. | {'CVE-2018-19351', 'GHSA-49qr-xh3w-h436'} | 2021-06-10T06:51:21.489049Z | 2018-11-18T17:29:00Z | null | null | null | {'https://pypi.org/project/notebook/#history', 'https://lists.debian.org/debian-lts-announce/2020/11/msg00033.html', 'https://github.com/jupyter/notebook/commit/107a89fce5f413fb5728c1c5d2c7788e1fb17491', 'https://groups.google.com/forum/#!topic/jupyter/hWzu2BSsplY', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst', 'https://github.com/advisories/GHSA-49qr-xh3w-h436'} | null |
PyPI | PYSEC-2020-91 | null | An issue was discovered in psd-tools before 1.9.4. The Cython implementation of RLE decoding did not check for malicious data. | {'CVE-2020-10571', 'GHSA-22jr-vc7j-g762'} | 2020-03-19T16:41:00Z | 2020-03-14T18:15:00Z | null | null | null | {'https://github.com/psd-tools/psd-tools/releases/tag/v1.9.4', 'https://github.com/psd-tools/psd-tools/pull/198', 'https://github.com/advisories/GHSA-22jr-vc7j-g762'} | null |
PyPI | PYSEC-2021-866 | null | This affects all versions of package html-to-csv. When there is a formula embedded in a HTML page, it gets accepted without any validation and the same would be pushed while converting it into a CSV file. Through this a malicious actor can embed or generate a malicious link or execute commands via CSV files. | {'CVE-2021-23654', 'GHSA-fwf6-rw69-hhj4', 'SNYK-PYTHON-HTMLTOCSV-1582784'} | 2022-01-05T02:16:24.626882Z | 2021-11-26T20:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-fwf6-rw69-hhj4', 'https://snyk.io/vuln/SNYK-PYTHON-HTMLTOCSV-1582784', 'https://github.com/hanwentao/html2csv/blob/master/html2csv/converter.py'} | null |
PyPI | PYSEC-2014-34 | null | uid_catalog.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to obtain metadata about hidden objects via a crafted URL. | {'CVE-2012-5492'} | 2021-09-01T08:44:29.620104Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone-hotfix/releases/20121106', 'https://plone.org/products/plone/security/advisories/20121106/08', 'http://www.openwall.com/lists/oss-security/2012/11/10/1'} | null |
PyPI | PYSEC-2021-535 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. 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-gv26-jpj9-c8gq', 'CVE-2021-29607'} | 2021-12-09T06:35:00.010376Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq', 'https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2'} | null |
PyPI | PYSEC-2021-165 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29528', 'GHSA-6f84-42vf-ppwp'} | 2021-08-27T03:22:26.348588Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f84-42vf-ppwp'} | null |
PyPI | GHSA-rpcg-f9q6-2mq6 | Remote Code Execution via traversal in TAL expressions | This advisory extends the previous advisory at https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36 with additional cases of TAL expression traversal vulnerabilities.
### Impact
Most Python modules are not available for using in TAL expressions that you can add through-the-web, for example in Zope Page Templates. This restriction avoids file system access, for example via the 'os' module. But some of the untrusted modules are available indirectly through Python modules that are available for direct use.
By default, you need to have the Manager role to add or edit Zope Page Templates through the web. Only sites that allow untrusted users to add/edit Zope Page Templates through the web are at risk.
### Patches
The problem has been fixed in Zope 5.21 and 4.6.1.
### Workarounds
The workaround is the same as for https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36: A site administrator can restrict adding/editing Zope Page Templates through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing Zope Page Templates through the web should be restricted to trusted users only.
### References
* [The previous advisory (GHSA-5pr9-v234-jw36)](https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36)
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [Zope issue tracker](https://github.com/zopefoundation/Zope/issues)
* Email us at [security@plone.org](mailto:security@plone.org)
| null | 2022-03-03T05:12:53.590293Z | 2021-06-08T18:45:52Z | HIGH | null | {'CWE-22'} | {'https://github.com/zopefoundation/Zope/security/advisories/GHSA-rpcg-f9q6-2mq6'} | null |
PyPI | GHSA-r5qj-cvf9-p85h | Code Injection in PyTorch Lightning | PyTorch Lightning version 1.5.10 and prior is vulnerable to code injection. There is currently a [patch](https://github.com/pytorchlightning/pytorch-lightning/commit/8b7a12c52e52a06408e9231647839ddb4665e8ae) available, anticipated to be part of the `1.6.0` release. | {'CVE-2022-0845'} | 2022-03-18T21:31:59.050920Z | 2022-03-06T00:00:16Z | CRITICAL | null | {'CWE-94'} | {'https://github.com/PyTorchLightning/pytorch-lightning/pull/12212', 'https://nvd.nist.gov/vuln/detail/CVE-2022-0845', 'https://github.com/pytorchlightning/pytorch-lightning/', 'https://huntr.dev/bounties/a795bf93-c91e-4c79-aae8-f7d8bda92e2a', 'https://github.com/pytorchlightning/pytorch-lightning/commit/8b7a12c52e52a06408e9231647839ddb4665e8ae'} | null |
PyPI | GHSA-f5cx-5wr3-5qrc | Reference binding to nullptr in boosted trees | ### Impact
An attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature`:
```python
import tensorflow as tf
tf.raw_ops.BoostedTreesCalculateBestGainsPerFeature(
node_id_range=[],
stats_summary_list=[[1,2,3]],
l1=[1.0],
l2=[1.0],
tree_complexity =[1.0],
min_node_weight =[1.17],
max_splits=5)
```
A similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`:
```python
import tensorflow as tf
tf.raw_ops.BoostedTreesCalculateBestFeatureSplitV2(
node_id_range=[],
stats_summaries_list=[[1,2,3]],
split_types=[''],
candidate_feature_ids=[1,2,3,4],
l1=[1],
l2=[1],
tree_complexity=[1.0],
min_node_weight=[1.17],
logits_dimension=5)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values.
### Patches
We have patched the issue in GitHub commit [9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad](https://github.com/tensorflow/tensorflow/commit/9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad) and in commit. [429f009d2b2c09028647dd4bb7b3f6f414bbaad7](https://github.com/tensorflow/tensorflow/commit/429f009d2b2c09028647dd4bb7b3f6f414bbaad7).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37662'} | 2022-03-03T05:14:14.804038Z | 2021-08-25T14:42:26Z | HIGH | null | {'CWE-824'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-37662', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f5cx-5wr3-5qrc', 'https://github.com/tensorflow/tensorflow/commit/9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/429f009d2b2c09028647dd4bb7b3f6f414bbaad7'} | null |
PyPI | GHSA-r4pj-74mg-8868 | Division by 0 in `Conv2DBackpropFilter` | ### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 1, 0], dtype=tf.float32)
filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32)
out_backprop = tf.constant([], shape=[0, 0, 1, 1], dtype=tf.float32)
tf.raw_ops.Conv2DBackpropFilter(input=input_tensor, filter_sizes=filter_sizes,
out_backprop=out_backprop,
strides=[1, 66, 18, 1], use_cudnn_on_gpu=True,
padding='SAME', explicit_paddings=[],
data_format='NHWC', dilations=[1, 1, 1, 1])
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130) does a modulus operation where the divisor is controlled by the caller:
```cc
if (dims->in_depth % filter_shape.dim_size(num_dims - 2)) { ... }
```
### Patches
We have patched the issue in GitHub commit [fca9874a9b42a2134f907d2fb46ab774a831404a](https://github.com/tensorflow/tensorflow/commit/fca9874a9b42a2134f907d2fb46ab774a831404a).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team. | {'CVE-2021-29524'} | 2022-03-03T05:14:19.072094Z | 2021-05-21T14:21:47Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r4pj-74mg-8868', 'https://github.com/tensorflow/tensorflow/commit/fca9874a9b42a2134f907d2fb46ab774a831404a', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29524'} | null |
PyPI | GHSA-98j8-c9q4-r38g | Memory exhaustion in Tensorflow | ### Impact
The [implementation of `StringNGrams`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161) can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:
```python
import tensorflow as tf
tf.raw_ops.StringNGrams(
data=['123456'],
data_splits=[0,1],
separator='a'*15,
ngram_widths=[],
left_pad='',
right_pad='',
pad_width=-5,
preserve_short_sequences=True)
```
We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output.
### Patches
We have patched the issue in GitHub commit [f68fdab93fb7f4ddb4eb438c8fe052753c9413e8](https://github.com/tensorflow/tensorflow/commit/f68fdab93fb7f4ddb4eb438c8fe052753c9413e8).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team. | {'CVE-2022-21733'} | 2022-03-03T05:14:01.870612Z | 2022-02-10T00:20:51Z | MODERATE | null | {'CWE-190', 'CWE-400'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98j8-c9q4-r38g', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21733', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161', 'https://github.com/tensorflow/tensorflow/commit/f68fdab93fb7f4ddb4eb438c8fe052753c9413e8', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-74w3-2r77-fw5h | Use of Externally-Controlled Format String in consoleme | A Python format string issue leading to information disclosure and potentially remote code execution in ConsoleMe for all versions prior to 1.2.2 | {'CVE-2022-27177'} | 2022-04-18T22:32:20.993308Z | 2022-04-03T00:00:58Z | CRITICAL | null | {'CWE-134'} | {'https://github.com/Netflix/ConsoleMe', 'https://nvd.nist.gov/vuln/detail/CVE-2022-27177', 'https://github.com/Netflix/security-bulletins/blob/master/advisories/nflx-2022-001.md'} | null |
PyPI | GHSA-w5gh-2wr2-pm6g | Denial of Service in Tensorflow | ### Impact
Changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments.
We have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode.
### Patches
We have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d.
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 Shuaike Dong, from Alipay Tian Qian Security Lab && Lab for Applied Security Research, CUHK. | {'CVE-2020-15206'} | 2022-03-03T05:13:13.746372Z | 2020-09-25T18:28:40Z | CRITICAL | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g', 'https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15206', 'https://github.com/tensorflow/tensorflow/commit/f760f88b4267d981e13f4b302c437ae800445968', 'https://github.com/tensorflow/tensorflow/commit/fcfef195637c6e365577829c4d67681695956e7d', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-m429-fhmv-c6q2 | Improper Verification of Cryptographic Signature | A flaw was found in the Ansible Engine, in ansible-engine 2.8.x before 2.8.15 and ansible-engine 2.9.x before 2.9.13, when installing packages using the dnf module. GPG signatures are ignored during installation even when disable_gpg_check is set to False, which is the default behavior. This flaw leads to malicious packages being installed on the system and arbitrary code executed via package installation scripts. The highest threat from this vulnerability is to integrity and system availability. | {'CVE-2020-14365'} | 2022-04-07T15:17:06.044520Z | 2021-04-20T16:44:07Z | HIGH | null | {'CWE-347'} | {'https://github.com/ansible/ansible', 'https://nvd.nist.gov/vuln/detail/CVE-2020-14365', 'https://www.debian.org/security/2021/dsa-4950', 'https://bugzilla.redhat.com/show_bug.cgi?id=1869154'} | null |
PyPI | PYSEC-2017-73 | null | sosreport in SoS 3.x allows local users to obtain sensitive information from sosreport files or gain privileges via a symlink attack on an archive file in a temporary directory, as demonstrated by sosreport-$hostname-$date.tar in /tmp/sosreport-$hostname-$date. | {'CVE-2015-7529'} | 2021-07-25T23:34:55.577295Z | 2017-11-06T17:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2016:0188', 'http://rhn.redhat.com/errata/RHSA-2016-0188.html', 'http://www.securityfocus.com/bid/83162', 'https://github.com/sosreport/sos/issues/696', 'http://rhn.redhat.com/errata/RHSA-2016-0152.html', 'https://access.redhat.com/errata/RHSA-2016:0152', 'http://www.ubuntu.com/usn/USN-2845-1', 'https://bugzilla.redhat.com/show_bug.cgi?id=1282542'} | null |
PyPI | GHSA-c5f8-35qr-q4fm | HTML injection in email and account expiry notifications | ### Impact
The notification emails sent for notifications for missed messages or for an expiring account are subject to HTML injection. In the case of the notification for missed messages, this could allow an attacker to insert forged content into the email.
The account expiry feature is not enabled by default and the HTML injection is not controllable by an attacker.
### Patches
This issue is fixed in #9200.
### Workarounds
For the missed messages notifications:
The `notif.html`, `notif_mail.html`, and `room.html` templates can be overridden with custom templates that manually escapes the variables using [JInja2's `escape` filter](https://jinja.palletsprojects.com/en/2.11.x/templates/#escape). See the `email.template_dir` setting.
For the account expiry notifications:
1. Account expiry can be disabled via the `account_validity.enabled` setting.
2. The `notice_expiry.html` template can be overridden with a custom template that manually escapes the variables using [JInja2's `escape` filter](https://jinja.palletsprojects.com/en/2.11.x/templates/#escape). See the `email.template_dir` setting. | {'CVE-2021-21333'} | 2022-03-03T05:13:04.847018Z | 2021-03-26T19:53:04Z | MODERATE | null | {'CWE-74'} | {'https://github.com/matrix-org/synapse/pull/9200', 'https://github.com/matrix-org/synapse/commit/e54746bdf7d5c831eabe4dcea76a7626f1de73df', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21333', 'https://github.com/matrix-org/synapse/releases/tag/v1.27.0', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-c5f8-35qr-q4fm', 'https://github.com/matrix-org/synapse', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TNNAJOZNMVMXM6AS7RFFKB4QLUJ4IFEY/'} | null |
PyPI | PYSEC-2013-30 | null | bson/_cbsonmodule.c in the mongo-python-driver (aka. pymongo) before 2.5.2, as used in MongoDB, allows context-dependent attackers to cause a denial of service (NULL pointer dereference and crash) via vectors related to decoding of an "invalid DBRef." | {'CVE-2013-2132'} | 2021-08-27T03:22:17.455260Z | 2013-08-15T17:55:00Z | null | null | null | {'http://ubuntu.com/usn/usn-1897-1', 'https://github.com/mongodb/mongo-python-driver/commit/a060c15ef87e0f0e72974c7c0e57fe811bbd06a2', 'http://lists.opensuse.org/opensuse-updates/2013-06/msg00180.html', 'http://www.osvdb.org/93804', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=710597', 'http://www.debian.org/security/2013/dsa-2705', 'https://jira.mongodb.org/browse/PYTHON-532', 'http://seclists.org/oss-sec/2013/q2/447', 'http://www.securityfocus.com/bid/60252'} | null |
PyPI | GHSA-f8mr-jv2c-v8mg | Invalid root may become trusted root in The Update Framework (TUF) | ### Impact
The Python TUF reference implementation `tuf<0.12` will incorrectly trust a previously downloaded root metadata file which failed verification at download time. This allows an attacker who is able to serve multiple new versions of root metadata (i.e. by a man-in-the-middle attack) culminating in a version which has not been correctly signed to control the trust chain for future updates.
While investigating the reported vulnerability, we discovered that the detailed client workflow was not fully implemented. Specifically, for step 1.3 the newly downloaded root metadata was not being verified with a threshold of keys specified in the new root metadata file.
This missing step of the client workflow has been implemented in [PR #1101](https://github.com/theupdateframework/tuf/pull/1101), which is included in [v0.14.0](https://github.com/theupdateframework/tuf/releases/tag/v0.14.0) of tuf.
### Patches
A [fix](https://github.com/theupdateframework/tuf/pull/885), is available in version [0.12](https://github.com/theupdateframework/tuf/releases/tag/v0.12.0) and newer.
### Workarounds
No workarounds are known for this issue.
### References
* Pull request resolving the invalid root becoming trusted issue [PR 885](https://github.com/theupdateframework/tuf/pull/885)
* Pull request implementing self verification of newly downloaded root metadata [PR 1101](https://github.com/theupdateframework/tuf/pull/1101) | {'CVE-2020-15163'} | 2022-03-03T05:12:35.740359Z | 2020-09-09T17:29:27Z | HIGH | null | {'CWE-863', 'CWE-345'} | {'https://github.com/theupdateframework/tuf', 'https://github.com/theupdateframework/tuf/pull/885', 'https://github.com/theupdateframework/tuf/commit/3d342e648fbacdf43a13d7ba8886aaaf07334af7', 'https://github.com/theupdateframework/tuf/security/advisories/GHSA-f8mr-jv2c-v8mg', 'https://pypi.org/project/tuf', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15163', 'https://github.com/theupdateframework/tuf/releases/tag/v0.12.0'} | null |
PyPI | PYSEC-2020-29 | null | A buffer overflow exists in the Brotli library versions prior to 1.0.8 where an attacker controlling the input length of a "one-shot" decompression request to a script can trigger a crash, which happens when copying over chunks of data larger than 2 GiB. It is recommended to update your Brotli library to 1.0.8 or later. If one cannot update, we recommend to use the "streaming" API as opposed to the "one-shot" API, and impose chunk size limits. | {'CVE-2020-8927'} | 2020-12-02T12:15:00Z | 2020-09-15T10:15:00Z | null | null | null | {'https://github.com/google/brotli/releases/tag/v1.0.9', 'https://usn.ubuntu.com/4568-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/356JOYTWW4BWSZ42SEFLV7NYHL3S3AEH/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/J4E265WKWKYMK2RYYSIXBEGZTDY5IQE6/', 'https://www.debian.org/security/2020/dsa-4801', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/M4VCDOJGL6BK3HB4XRD2WETBPYX2ITF6/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MMBKACMLSRX7JJSKBTR35UOEP2WFR6QP/', 'http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00108.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/W23CUADGMVMQQNFKHPHXVP7RPZJZNN6I/', 'https://lists.debian.org/debian-lts-announce/2020/12/msg00003.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WW62OZEY2GHJL4JCOLJRBSRETXDHMWRK/'} | null |
PyPI | PYSEC-2022-14 | null | Improper Privilege Management in Conda loguru prior to 0.5.3. | {'CVE-2022-0338'} | 2022-01-28T21:25:28.417398Z | 2022-01-25T09:15:00Z | null | null | null | {'https://huntr.dev/bounties/359bea50-2bc6-426a-b2f9-175d401b1ed0', 'https://github.com/delgan/loguru/commit/ea39375e62f9b8f18e2ca798a5c0fb8c972b7eaa'} | null |
PyPI | GHSA-rwv7-3v45-hg29 | Out-of-bounds Read | An issue was discovered in Pillow before 8.2.0. There is an out-of-bounds read in J2kDecode, in j2ku_gray_i. This dates to Pillow 2.4.0. | {'CVE-2021-25288'} | 2022-03-07T20:47:09.921948Z | 2021-06-08T18:49:28Z | CRITICAL | null | {'CWE-125'} | {'https://github.com/python-pillow/Pillow/commit/3bf5eddb89afdf690eceaa52bc4d3546ba9a5f87', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow/pull/5377#issuecomment-833821470', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25288', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MQHA5HAIBOYI3R6HDWCLAGFTIQP767FL/', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.2.0.html#cve-2021-25287-cve-2021-25288-fix-oob-read-in-jpeg2kdecode', 'https://github.com/python-pillow/Pillow'} | null |
PyPI | GHSA-wp77-4gmm-7cq8 | Incorrect validation of `SaveV2` inputs | ### Impact
The code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference:
```python
import tensorflow as tf
tf.raw_ops.SaveV2(
prefix=['tensorflow'],
tensor_name=['v'],
shape_and_slices=[],
tensors=[1,2,3])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above.
However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation.
### Patches
We have patched the issue in GitHub commit [9728c60e136912a12d99ca56e106b7cce7af5986](https://github.com/tensorflow/tensorflow/commit/9728c60e136912a12d99ca56e106b7cce7af5986).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-37648'} | 2022-03-03T05:13:32.840734Z | 2021-08-25T14:43:29Z | HIGH | null | {'CWE-476'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-37648', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wp77-4gmm-7cq8', 'https://github.com/tensorflow/tensorflow/commit/9728c60e136912a12d99ca56e106b7cce7af5986'} | null |
PyPI | PYSEC-2019-174 | null | Multiple CSRF issues exist in MicroPyramid Django CRM 0.2.1 via /change-password-by-admin/, /api/settings/add/, /cases/create/, /change-password-by-admin/, /comment/add/, /documents/1/view/, /documents/create/, /opportunities/create/, and /login/. | {'CVE-2019-11457', 'GHSA-pg2f-r7pc-6fxx'} | 2021-08-27T03:21:57.382280Z | 2019-08-27T15:15:00Z | null | null | null | {'https://www.netsparker.com/blog/web-security/', 'http://seclists.org/fulldisclosure/2019/Aug/30', 'https://github.com/advisories/GHSA-pg2f-r7pc-6fxx', 'http://packetstormsecurity.com/files/154219/Django-CRM-0.2.1-Cross-Site-Request-Forgery.html'} | null |
PyPI | GHSA-h6fg-mjxg-hqq4 | Integer truncation in Shard API usage | ### Impact
The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60
However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318
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.
### Patches
We have patched the issue in 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575. We 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-2020-15202'} | 2022-03-03T05:14:22.856243Z | 2020-09-25T18:28:35Z | CRITICAL | null | {'CWE-197', 'CWE-754'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-15202', 'https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575', 'https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-3v7g-4pg3-7r6j | OS Command injection in Apache Airflow | In Apache Airflow, prior to version 2.2.4, some example DAGs did not properly sanitize user-provided params, making them susceptible to OS Command Injection from the web UI. | {'CVE-2022-24288'} | 2022-03-07T20:47:34.694453Z | 2022-02-26T00:00:44Z | HIGH | null | {'CWE-78'} | {'https://lists.apache.org/thread/dbw5ozcmr0h0lhs0yjph7xdc64oht23t', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24288', 'https://github.com/apache/airflow'} | null |
PyPI | PYSEC-2021-427 | null | A Regular Expression Denial of Service (ReDOS) vulnerability was discovered in Mpmath v1.0.0 when the mpmathify function is called. | {'CVE-2021-29063', 'GHSA-f865-m6cq-j9vx'} | 2021-11-16T21:20:29.021535Z | 2021-06-21T20:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-f865-m6cq-j9vx', 'https://github.com/fredrik-johansson/mpmath/commit/46d44c3c8f3244017fe1eb102d564eb4ab8ef750', 'https://www.npmjs.com/package/hosted-git-info', 'https://github.com/npm/hosted-git-info/pull/76', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MS2U6GLXQSRZJE2HVUAUMVFR2DWQLCZG/', 'https://github.com/yetingli/PoCs/blob/main/CVE-2021-29063/Mpmath.md', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3M5O55E7VUDMXCPQR6MQTOIFDKHP36AA/', 'https://github.com/yetingli/SaveResults/blob/main/js/hosted-git-info.js'} | null |
PyPI | PYSEC-2021-132 | null | Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.25.0, a malicious homeserver could redirect requests to their .well-known file to a large file. This can lead to a denial of service attack where homeservers will consume significantly more resources when requesting the .well-known file of a malicious homeserver. This affects any server which accepts federation requests from untrusted servers. Issue is resolved in version 1.25.0. As a workaround the `federation_domain_whitelist` setting can be used to restrict the homeservers communicated with over federation. | {'CVE-2021-21274', 'GHSA-2hwx-mjrm-v3g8'} | 2021-08-27T03:22:06.616674Z | 2021-02-26T18:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/releases/tag/v1.25.0', 'https://github.com/matrix-org/synapse/commit/ff5c4da1289cb5e097902b3e55b771be342c29d6', 'https://github.com/matrix-org/synapse/pull/8950', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-2hwx-mjrm-v3g8'} | null |
PyPI | PYSEC-2021-562 | null | TensorFlow is an end-to-end open source platform for machine learning. The code for `tf.raw_ops.UncompressElement` can be made to trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/compression_ops.cc#L50-L53) obtains a pointer to a `CompressedElement` from a `Variant` tensor and then proceeds to dereference it for decompressing. There is no check that the `Variant` tensor contained a `CompressedElement`, so the pointer is actually `nullptr`. We have patched the issue in GitHub commit 7bdf50bb4f5c54a4997c379092888546c97c3ebd. 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-2021-37649', 'GHSA-6gv8-p3vj-pxvr'} | 2021-12-09T06:35:03.183506Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gv8-p3vj-pxvr', 'https://github.com/tensorflow/tensorflow/commit/7bdf50bb4f5c54a4997c379092888546c97c3ebd'} | null |
PyPI | GHSA-74hv-qjjq-h7g5 | datasette-graphql leaks details of the schema of private database files | ### Impact
When running against a Datasette instance with private databases, `datasette-graphql` would expose the schema of those database tables - but not the table contents.
### Patches
Patched in version 1.2.
### Workarounds
This issue is only present if a Datasette instance that includes private databases and has the `datasette-graphql` plugin installed is available on the public internet. Uninstalling the `datasette-graphql` plugin or preventing public access to the instance can workaround this issue.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [datasette-graphql](https://github.com/simonw/datasette-graphql)
* Contact [@simonw](https://twitter.com/simonw) by Twitter direct message | null | 2022-03-03T05:13:34.960525Z | 2020-11-24T22:59:08Z | LOW | null | {'CWE-200'} | {'https://github.com/simonw/datasette-graphql/security/advisories/GHSA-74hv-qjjq-h7g5', 'https://pypi.org/project/datasette-graphql/'} | null |
PyPI | PYSEC-2014-63 | null | (1) cb_decode.py and (2) linkintegrity.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 authenticated users to cause a denial of service (resource consumption) via a large zip archive, which is expanded (decompressed). | {'CVE-2013-4199'} | 2021-07-25T23:34:47.359775Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'http://seclists.org/oss-sec/2013/q3/261', 'https://bugzilla.redhat.com/show_bug.cgi?id=978482', 'http://plone.org/products/plone/security/advisories/20130618-announcement'} | null |
PyPI | PYSEC-2021-831 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseFillEmptyRows` can be made to trigger a heap OOB access. This occurs whenever the size of `indices` does not match the size of `values`. 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-rg3m-hqc5-344v', 'CVE-2021-41224'} | 2021-12-09T06:35:44.787766Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rg3m-hqc5-344v', 'https://github.com/tensorflow/tensorflow/commit/67bfd9feeecfb3c61d80f0e46d89c170fbee682b'} | null |
PyPI | PYSEC-2010-20 | null | Multiple directory traversal vulnerabilities in FTPServer.py in pyftpdlib before 0.2.0 allow remote authenticated users to access arbitrary files and directories via a .. (dot dot) in a (1) LIST, (2) STOR, or (3) RETR command. | {'CVE-2007-6736'} | 2010-10-20T04:00:00Z | 2010-10-19T20:00:00Z | null | null | null | {'http://code.google.com/p/pyftpdlib/source/diff?spec=svn16&r=16&format=side&path=/trunk/pyftpdlib/FTPServer.py', 'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY', 'http://code.google.com/p/pyftpdlib/source/detail?r=16', 'http://code.google.com/p/pyftpdlib/issues/detail?id=9'} | null |
PyPI | PYSEC-2020-132 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference. The issue is patched in commit 0b5662bc, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'GHSA-qh32-6jjc-qprm', 'CVE-2020-15209'} | 2020-10-29T16:15:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/0b5662bc2be13a8c8f044d925d87fb6e56247cd8', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qh32-6jjc-qprm', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-w96g-3p64-63wr | Improper Restriction of Operations within the Bounds of a Memory Buffer in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to OpenCV-Python 3.3.0.9) has a buffer overflow in the cv::BmpDecoder::readData function in modules/imgcodecs/src/grfmt_bmp.cpp when reading an image file by using cv::imread, as demonstrated by the 4-buf-overflow-readData-memcpy test case. | {'CVE-2017-12601'} | 2022-03-03T05:13:17.210240Z | 2021-10-12T22:01:23Z | HIGH | null | {'CWE-120', 'CWE-119'} | {'https://github.com/opencv/opencv-python/releases/tag/11', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://github.com/opencv/opencv/issues/9309', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12601', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://security.gentoo.org/glsa/201712-02', 'https://github.com/xiaoqx/pocs/blob/master/opencv.md', 'https://github.com/opencv/opencv-python/releases/tag/9', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2018-40 | null | Ansible before version 2.3 has an input validation vulnerability in the handling of data sent from client systems. An attacker with control over a client system being managed by Ansible, and the ability to send facts back to the Ansible server, could use this flaw to execute arbitrary code on the Ansible server using the Ansible server privileges. | {'CVE-2017-7466'} | 2021-07-02T02:41:33.763354Z | 2018-06-22T13:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2017:1244', 'http://www.securityfocus.com/bid/97595', 'https://access.redhat.com/errata/RHSA-2017:1685', 'https://access.redhat.com/errata/RHSA-2017:1476', 'https://access.redhat.com/errata/RHSA-2017:1599', 'https://access.redhat.com/errata/RHSA-2017:1334', 'https://access.redhat.com/errata/RHSA-2017:1499', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2017-7466'} | null |
PyPI | GHSA-wc4g-r73w-x8mm | Insecure temporary file in Tensorflow | ### Impact
In multiple places, TensorFlow uses `tempfile.mktemp` to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in `mktemp` and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness).
In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the `mktemp` function usage.
### Patches
We have patched the issue in several commits, replacing `mktemp` with the safer `mkstemp`/`mkdtemp` functions, according to the usage pattern.
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 on huntr.dev for one scenario and discovered via variant analysis on other instances. | {'CVE-2022-23563'} | 2022-03-03T05:13:05.274265Z | 2022-02-09T23:54:51Z | HIGH | null | {'CWE-668', 'CWE-367'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23563', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wc4g-r73w-x8mm'} | null |
PyPI | PYSEC-2021-12 | null | Eventlet is a concurrent networking library for Python. A websocket peer may exhaust memory on Eventlet side by sending very large websocket frames. Malicious peer may exhaust memory on Eventlet side by sending highly compressed data frame. A patch in version 0.31.0 restricts websocket frame to reasonable limits. As a workaround, restricting memory usage via OS limits would help against overall machine exhaustion, but there is no workaround to protect Eventlet process. | {'GHSA-9p9m-jm8w-94p2', 'CVE-2021-21419'} | 2021-05-14T17:02:00Z | 2021-05-07T15:15:00Z | null | null | null | {'https://github.com/eventlet/eventlet/security/advisories/GHSA-9p9m-jm8w-94p2'} | null |
PyPI | PYSEC-2021-348 | null | Command Injection in Simiki v1.6.2.1 and prior allows remote attackers to execute arbitrary system commands via line 64 of the component 'simiki/blob/master/simiki/config.py'. | {'CVE-2020-19001', 'GHSA-w873-xcqq-x922'} | 2021-09-26T23:33:04.328365Z | 2021-08-27T19:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-w873-xcqq-x922', 'https://github.com/tankywoo/simiki/issues/123'} | null |
PyPI | GHSA-mr6r-mvw4-736g | Vyper interfaces returning integer types less than 256 bits can be manipulated if uint256 is used | # VVE-2020-0001
Earlier today, we received a responsible disclosure of a potential issue from @montyly (security researcher at @trailofbits) for Vyper users who make assumptions about what values certain interface types can return.
### Impact
We determined the issue to be mild and unlikely to be exploited, with an easy workaround while the correct resolution is in process. The issue stems from a number of things, which we will detail here.
(1) The ABI Specification is under-defined such that function return type is not always reflected in how you use it
This means that a function which returns `uint8` under the hood actually returns a 32 byte integer, making it identical to a function that returns `uint256`. This allows users to read an interface that returns a `uint8` value to be stored into a `uint256` variable without any explicit casting or input validation.
(2) Vyper doesn't have `uint8` types
When Vyper was originally created, it only had one numeric type, but we added just enough types to be able to work with the majority of ERC interfaces that exist.
Unfortunately, we never added `uint8`, because it's only majority usage was for `ERC20.decimals()` as the return type, which isn't reflected in the method ID. Because of (1), it didn't matter that we didn't have these types implemented because you could capture the return value as `uint256` and use it just fine.
(3) `ERC20.decimals()` returns `uint8`
`ERC20.decimal()` (which is an optional function) returns a `uint8` type. While it was never intentioned to be used directly within a smart contract (hence being optional), someone could easily make the decision to rely on it to perform important functionality within their Vyper smart contract. This might lead to a scenario where an unexpectedly large value (> 255) returned by calling this function (which a malicious contract writer might write) would allow an attacker to manipulate or bypass certain logic depending on this value.
In summary, because of (1), it isn't necessary to have to cast the return value of a function that returns `uint8` to `uint256`, and because of (2) it isn't possible to have the type system protect against this type of error. This could lead to scenarios like (3) where this behavior can be exploited.
### Patches
We are currently refactoring our typing system so we can implement all ABI-compliant integer types, but no currently patched version is available that gives users access to the `uint8` type.
### Workarounds
There is an easy workaround where you should check that the value returned by an interface which specifies `uint8` should be checked to be within the bounds of a `uint8` integer. As an example:
```python
...
# returns uint8, but we implicitly cast to uint256 without checking
decimals: uint256 = ERC20(_token).decimal()
# FIX: Insert this line
assert decimals < 256
...
```
Depending on how you use this value, it may not be necessary to insert this check.
### References
* [ABI Specification](https://solidity.readthedocs.io/en/latest/abi-spec.html)
### For more information
If you have any questions or comments about this advisory:
* Chat with us in [our gitter ](https://gitter.im/vyperlang/community)
* Open an issue in [https://github.com/vyperlang/vyper](https://github.com/vyperlang/vyper)
* Email us at [security@vyperlang.org](mailto:security@vyperlang.org) | null | 2022-03-03T05:13:42.761969Z | 2020-03-25T18:20:19Z | LOW | null | null | {'https://github.com/vyperlang/vyper/security/advisories/GHSA-mr6r-mvw4-736g'} | null |
PyPI | PYSEC-2021-718 | null | TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29592', 'GHSA-jjr8-m8g8-p6wv'} | 2021-12-09T06:35:30.746202Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jjr8-m8g8-p6wv', 'https://github.com/tensorflow/tensorflow/commit/f8378920345f4f4604202d4ab15ef64b2aceaa16'} | null |
PyPI | PYSEC-2013-26 | null | The default configuration for salt-ssh in Salt (aka SaltStack) 0.17.0 does not validate the SSH host key of requests, which allows remote attackers to have unspecified impact via a man-in-the-middle (MITM) attack. | {'CVE-2013-4436'} | 2021-07-25T23:34:53.687508Z | 2013-11-05T18:55:00Z | null | null | null | {'http://docs.saltstack.com/topics/releases/0.17.1.html', 'http://www.openwall.com/lists/oss-security/2013/10/18/3'} | null |
PyPI | PYSEC-2017-65 | null | protobuf allows remote authenticated attackers to cause a heap-based buffer overflow. | {'CVE-2015-5237'} | 2021-07-25T23:34:50.202612Z | 2017-09-25T17:29:00Z | null | null | null | {'https://lists.apache.org/thread.html/r320dc858da88846ba00bb077bcca2cdf75b7dde0f6eb3a3d60dba6a1@%3Ccommits.pulsar.apache.org%3E', 'https://bugzilla.redhat.com/show_bug.cgi?id=1256426', 'http://www.openwall.com/lists/oss-security/2015/08/27/2', 'https://lists.apache.org/thread.html/r42ef6acfb0d86a2df0c2390702ecbe97d2104a331560f2790d17ca69@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r42e47994734cd1980ef3e204a40555336e10cc80096927aca2f37d90@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/rb71dac1d9dd4e8a8ae3dbc033aeae514eda9be1263c1df3b42a530a2@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r17dc6f394429f6bffb5e4c66555d93c2e9923cbbdc5a93db9a56c1c7@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/519eb0fd45642dcecd9ff74cb3e71c20a4753f7d82e2f07864b5108f@%3Cdev.drill.apache.org%3E', 'https://github.com/google/protobuf/issues/760', 'https://lists.apache.org/thread.html/rf7539287c90be979bac94af9aaba34118fbf968864944b4871af48dd@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r1d274d647b3c2060df9be21eade4ce56d3a59998cf19ac72662dd994@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/re6d04a214424a97ea59c62190d79316edf311a0a6346524dfef3b940@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/b0656d359c7d40ec9f39c8cc61bca66802ef9a2a12ee199f5b0c1442@%3Cdev.drill.apache.org%3E', 'https://lists.apache.org/thread.html/ra28fed69eef3a71e5fe5daea001d0456b05b102044237330ec5c7c82@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r85c9a764b573c786224688cc906c27e28343e18f5b33387f94cae90f@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r02e39d7beb32eebcdbb4b516e95f67d71c90d5d462b26f4078d21eeb@%3Cuser.flink.apache.org%3E', 'https://lists.apache.org/thread.html/r02e39d7beb32eebcdbb4b516e95f67d71c90d5d462b26f4078d21eeb@%3Cdev.flink.apache.org%3E', 'https://lists.apache.org/thread.html/r5e52caf41dc49df55b4ee80758356fe1ff2a88179ff24c685de7c28d@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/r1263fa5b51e4ec3cb8f09ff40e4747428c71198e9bee93349ec96a3c@%3Ccommits.pulsar.apache.org%3E', 'https://lists.apache.org/thread.html/f9bc3e55f4e28d1dcd1a69aae6d53e609a758e34d2869b4d798e13cc@%3Cissues.drill.apache.org%3E'} | null |
PyPI | GHSA-fr28-569j-53c4 | Incorrect Default Permissions | An issue was discovered in Django 2.2 before 2.2.16, 3.0 before 3.0.10, and 3.1 before 3.1.1 (when Python 3.7+ is used). The intermediate-level directories of the filesystem cache had the system's standard umask rather than 0o077. | {'CVE-2020-24584'} | 2022-03-03T05:12:56.107855Z | 2021-03-18T20:30:01Z | HIGH | null | {'CWE-276'} | {'https://groups.google.com/forum/#!topic/django-announce/zFCMdgUnutU', 'https://usn.ubuntu.com/4479-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZCRPQCBTV3RZHKVZ6K6QOAANPRZQD3GI/', 'https://www.openwall.com/lists/oss-security/2020/09/01/2', 'https://www.djangoproject.com/weblog/2020/sep/01/security-releases/', 'https://github.com/django/django/commit/1853724acaf17ed7414d54c7d2b5563a25025a71', 'https://groups.google.com/forum/#!topic/django-announce/Gdqn58RqIDM', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/F2ZHO3GZCJMP3DDTXCNVFV6ED3W64NAU/', 'https://docs.djangoproject.com/en/dev/releases/security/', 'https://www.oracle.com/security-alerts/cpujan2021.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OLGFFLMF3X6USMJD7V5F5P4K2WVUTO3T/', 'https://security.netapp.com/advisory/ntap-20200918-0004/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-24584'} | null |
PyPI | PYSEC-2021-431 | null | django-helpdesk is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') | {'GHSA-vfrc-ggmc-5jwv', 'CVE-2021-3950'} | 2021-11-23T19:22:08.078180Z | 2021-11-19T12:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-vfrc-ggmc-5jwv', 'https://github.com/django-helpdesk/django-helpdesk/commit/04483bdac3b5196737516398b5ce0383875a5c60', 'https://huntr.dev/bounties/4d7a5fdd-b2de-467a-ade0-3f2fb386638e'} | null |
PyPI | PYSEC-2019-162 | null | aubio v0.4.0 to v0.4.8 has a Buffer Overflow in new_aubio_tempo. | {'GHSA-grmf-4fq6-2r79', 'CVE-2018-19800'} | 2021-08-25T04:29:55.885441Z | 2019-06-07T17:29:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/IYIKPYXZIWYWWNNORSKWRCFFCP6AFMRZ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OHIRMWW4JQ6UHJK4AVBJLFRLE2TPKC2W/', 'https://github.com/aubio/aubio/blob/0.4.9/ChangeLog', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00063.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00067.html', 'https://github.com/advisories/GHSA-grmf-4fq6-2r79'} | null |
PyPI | PYSEC-2018-56 | null | mitmweb in mitmproxy v4.0.3 allows DNS Rebinding attacks, related to tools/web/app.py. | {'GHSA-6m53-c78q-7qmg', 'CVE-2018-14505'} | 2021-07-15T02:22:15.843004Z | 2018-07-22T18:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-6m53-c78q-7qmg', 'https://github.com/mitmproxy/mitmproxy/pull/3243', 'https://github.com/mitmproxy/mitmproxy/issues/3234'} | null |
PyPI | PYSEC-2020-124 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15201', 'GHSA-p5f8-gfw5-33w4'} | 2021-09-01T08:19:33.344299Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4'} | null |
PyPI | GHSA-v899-28g4-qmh8 | XML External Entity vulnerability in Easy-XML | The parseXML function in Easy-XML 0.5.0 was discovered to have a XML External Entity (XXE) vulnerability which allows for an attacker to expose sensitive data or perform a denial of service (DOS) via a crafted external entity entered into the XML content as input. | {'CVE-2020-26705'} | 2022-03-21T22:31:58.289526Z | 2021-11-01T19:19:54Z | CRITICAL | null | {'CWE-611'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-26705', 'https://github.com/darkfoxprime/python-easy_xml/issues/1', 'https://github.com/darkfoxprime/python-easy_xml'} | null |
PyPI | PYSEC-2021-827 | null | TensorFlow is an open source platform for machine learning. In affected versions the async implementation of `CollectiveReduceV2` suffers from a memory leak and a use after free. This occurs due to the asynchronous computation and the fact that objects that have been `std::move()`d from are still accessed. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. | {'GHSA-gpfh-jvf9-7wg5', 'CVE-2021-41220'} | 2021-12-09T06:35:44.147623Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gpfh-jvf9-7wg5', 'https://github.com/tensorflow/tensorflow/commit/ca38dab9d3ee66c5de06f11af9a4b1200da5ef75'} | null |
PyPI | PYSEC-2014-75 | null | AccessControl/AuthEncoding.py in Zope before 2.13.19, as used in Plone before 4.2.3 and 4.3 before beta 1, allows remote attackers to obtain passwords via vectors involving timing discrepancies in password validation. | {'CVE-2012-5507', 'GHSA-3qpr-7rmg-73v8'} | 2021-07-25T23:34:58.957854Z | 2014-09-30T14:55:00Z | null | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://plone.org/products/plone/security/advisories/20121106/23', 'https://bugs.launchpad.net/zope2/+bug/1071067', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://github.com/advisories/GHSA-3qpr-7rmg-73v8'} | null |
PyPI | GHSA-mr7p-25v2-35wr | Path Traversal in nltk | NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during extraction. | {'CVE-2019-14751'} | 2022-03-03T05:13:40.004453Z | 2019-08-23T21:53:51Z | HIGH | null | {'CWE-22'} | {'http://lists.opensuse.org/opensuse-security-announce/2020-03/msg00054.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZGZSSEJH7RHH3RBUEVWWYT75QU67J7SE/', 'https://github.com/nltk/nltk/commit/f59d7ed8df2e0e957f7f247fe218032abdbe9a10', 'https://salvatoresecurity.com/zip-slip-in-nltk-cve-2019-14751/', 'https://github.com/nltk/nltk/blob/3.4.5/ChangeLog', 'https://nvd.nist.gov/vuln/detail/CVE-2019-14751', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00001.html', 'https://github.com/mssalvatore/CVE-2019-14751_PoC', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QI4IJGLZQ5S7C5LNRNROHAO2P526XE3D/'} | null |
PyPI | PYSEC-2021-574 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37661', 'GHSA-gf88-j2mg-cc82'} | 2021-12-09T06:35:04.173783Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82', 'https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992'} | null |
PyPI | GHSA-6m8p-x4qw-gh5j | Insufficient Session Expiration in OpenStack Keystone | An issue was discovered in OpenStack Keystone before 15.0.1, and 16.0.0. The list of roles provided for an OAuth1 access token is silently ignored. Thus, when an access token is used to request a keystone token, the keystone token contains every role assignment the creator had for the project. This results in the provided keystone token having more role assignments than the creator intended, possibly giving unintended escalated access. | {'CVE-2020-12690'} | 2022-03-03T05:14:14.575744Z | 2021-06-09T17:34:09Z | HIGH | null | {'CWE-613'} | {'https://lists.apache.org/thread.html/re4ffc55cd2f1b55a26e07c83b3c22c3fe4bae6054d000a57fb48d8c2@%3Ccommits.druid.apache.org%3E', 'https://www.openwall.com/lists/oss-security/2020/05/06/6', 'http://www.openwall.com/lists/oss-security/2020/05/07/3', 'https://nvd.nist.gov/vuln/detail/CVE-2020-12690', 'https://usn.ubuntu.com/4480-1/', 'https://bugs.launchpad.net/keystone/+bug/1873290', 'https://security.openstack.org/ossa/OSSA-2020-005.html'} | null |
PyPI | PYSEC-2021-124 | null | A flaw was found in ansible. Credentials, such as secrets, are being disclosed in console log by default and not protected by no_log feature when using those modules. An attacker can take advantage of this information to steal those credentials. The highest threat from this vulnerability is to data confidentiality. Versions before ansible 2.9.18 are affected. | {'CVE-2021-20191', 'GHSA-8f4m-hccc-8qph'} | 2021-08-27T03:21:53.214122Z | 2021-05-26T21:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-8f4m-hccc-8qph', 'https://bugzilla.redhat.com/show_bug.cgi?id=1916813'} | null |
PyPI | PYSEC-2021-45 | null | Products.PluggableAuthService is a pluggable Zope authentication and authorization framework. In Products.PluggableAuthService before version 2.6.0 there is an open redirect vulnerability. A maliciously crafted link to the login form and login functionality could redirect the browser to a different website. The problem has been fixed in version 2.6.1. Depending on how you have installed Products.PluggableAuthService, you should change the buildout version pin to `2.6.1` and re-run the buildout, or if you used `pip` simply do `pip install "Products.PluggableAuthService>=2.6.1". | {'CVE-2021-21337', 'GHSA-p44j-xrqg-4xrr'} | 2021-03-12T13:48:00Z | 2021-03-08T21:15:00Z | null | null | null | {'https://pypi.org/project/Products.PluggableAuthService/', 'https://github.com/zopefoundation/Products.PluggableAuthService/commit/7eead067898852ebd3e0f143bc51295928528dfa', 'https://github.com/zopefoundation/Products.PluggableAuthService/security/advisories/GHSA-p44j-xrqg-4xrr'} | null |
PyPI | GHSA-m6vm-8g8v-xfjh | Out-of-bounds Write in OpenCV | An exploitable heap buffer overflow vulnerability exists in the data structure persistence functionality of OpenCV 4.1.0 (corresponds with OpenCV-Python 4.1.0.25). A specially crafted XML file can cause a buffer overflow, resulting in multiple heap corruptions and potential code execution. An attacker can provide a specially crafted file to trigger this vulnerability. | {'CVE-2019-5063'} | 2022-04-20T19:30:11.845812Z | 2021-10-12T22:23:13Z | HIGH | null | {'CWE-787'} | {'https://github.com/opencv/opencv-python/releases/tag/25', 'https://talosintelligence.com/vulnerability_reports/TALOS-2019-0852', 'https://nvd.nist.gov/vuln/detail/CVE-2019-5063', 'https://github.com/opencv/opencv/issues/16951', 'https://www.oracle.com/security-alerts/cpuApr2021.html', 'https://www.oracle.com//security-alerts/cpujul2021.html', 'https://github.com/opencv/opencv-python'} | null |
PyPI | GHSA-656c-6cxf-hvcv | Deserialization of Untrusted Data in Flask-Caching | Flask-Cache adds easy cache support to Flask. The Flask-Caching extension through 1.10.1 for Flask relies on Pickle for serialization, which may lead to remote code execution or local privilege escalation. If an attacker gains access to cache storage (e.g., filesystem, Memcached, Redis, etc.), they can construct a crafted payload, poison the cache, and execute Python code. | {'CVE-2021-33026'} | 2022-05-05T16:17:29.700740Z | 2021-06-18T18:33:40Z | CRITICAL | null | {'CWE-502', 'CWE-269'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-33026', 'https://github.com/sh4nks/flask-caching', 'https://github.com/sh4nks/flask-caching/pull/209'} | null |
PyPI | GHSA-xmq7-7fxm-rr79 | Denial of Service in Tensorflow | ### Impact
By controlling the `fill` argument of [`tf.strings.as_string`](https://www.tensorflow.org/api_docs/python/tf/strings/as_string), a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/as_string_op.cc#L68-L74
This can result in unexpected output:
```python
In [1]: tf.strings.as_string(input=[1234], width=6, fill='-')
Out[1]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['1234 '], dtype=object)>
In [2]: tf.strings.as_string(input=[1234], width=6, fill='+')
Out[2]: <tf.Tensor: shape=(1,), dtype=string, numpy=array([' +1234'], dtype=object)>
In [3]: tf.strings.as_string(input=[1234], width=6, fill="h")
Out[3]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['%6d'], dtype=object)>
In [4]: tf.strings.as_string(input=[1234], width=6, fill="d")
Out[4]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['12346d'], dtype=object)>
In [5]: tf.strings.as_string(input=[1234], width=6, fill="o")
Out[5]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['23226d'], dtype=object)>
In [6]: tf.strings.as_string(input=[1234], width=6, fill="x")
Out[6]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['4d26d'], dtype=object)>
In [7]: tf.strings.as_string(input=[1234], width=6, fill="g")
Out[7]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['8.67458e-3116d'], dtype=object)>
In [8]: tf.strings.as_string(input=[1234], width=6, fill="a")
Out[8]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x0.00ff7eebb4d4p-10226d'], dtype=object)>
In [9]: tf.strings.as_string(input=[1234], width=6, fill="c")
Out[9]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['\xd26d'], dtype=object)>
In [10]: tf.strings.as_string(input=[1234], width=6, fill="p")
Out[10]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x4d26d'], dtype=object)>
In [11]: tf.strings.as_string(input=[1234], width=6, fill='m')
Out[11]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['Success6d'], dtype=object)>
```
However, passing in `n` or `s` results in segmentation fault.
### Patches
We have patched the issue in 33be22c65d86256e6826666662e40dbdfe70ee83 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-2020-15203'} | 2022-03-03T05:14:01.043032Z | 2020-09-25T18:28:37Z | HIGH | null | {'CWE-20', 'CWE-134'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-15203', 'https://github.com/tensorflow/tensorflow/commit/33be22c65d86256e6826666662e40dbdfe70ee83', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xmq7-7fxm-rr79', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2011-9 | null | The password reset functionality in django.contrib.auth in Django before 1.1.3, 1.2.x before 1.2.4, and 1.3.x before 1.3 beta 1 does not validate the length of a string representing a base36 timestamp, which allows remote attackers to cause a denial of service (resource consumption) via a URL that specifies a large base36 integer. | {'GHSA-7wph-fc4w-wqp2', 'CVE-2010-4535'} | 2021-07-15T02:22:08.187235Z | 2011-01-10T20:00:00Z | null | null | null | {'http://www.vupen.com/english/advisories/2011/0098', 'http://secunia.com/advisories/42913', 'http://www.vupen.com/english/advisories/2011/0048', 'http://secunia.com/advisories/42827', 'http://www.securityfocus.com/bid/45563', 'https://github.com/advisories/GHSA-7wph-fc4w-wqp2', 'http://www.openwall.com/lists/oss-security/2011/01/03/5', 'http://www.ubuntu.com/usn/USN-1040-1', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-January/053072.html', 'http://www.djangoproject.com/weblog/2010/dec/22/security/', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-January/053041.html', 'http://code.djangoproject.com/changeset/15032', 'http://www.openwall.com/lists/oss-security/2010/12/23/4', 'https://bugzilla.redhat.com/show_bug.cgi?id=665373', 'http://secunia.com/advisories/42715'} | null |
PyPI | PYSEC-2017-32 | null | The state.sls function in Salt before 2015.8.3 uses weak permissions on the cache data, which allows local users to obtain sensitive information by reading the file. | {'CVE-2015-8034'} | 2021-07-05T00:01:26.287704Z | 2017-01-30T22:59:00Z | null | null | null | {'http://www.securityfocus.com/bid/96390', 'https://docs.saltstack.com/en/latest/topics/releases/2015.8.3.html'} | null |
PyPI | GHSA-hh7m-rx4f-4vpv | CSRF can expose users authentication token | ### Issue
The /login and /change endpoints can return the authenticated user's authentication token in response to a GET request. Since GET requests aren't protected with a CSRF token, this could lead to a malicious 3rd party site acquiring the authentication token.
### Patches
Version 3.4.5 and soon to be released 4.0.0 are patched.
### Workarounds
If you aren't using authentication tokens - you can set the SECURITY_TOKEN_MAX_AGE to "0" (seconds) which should make the token unusable.
### References
None | {'CVE-2021-21241'} | 2022-03-03T05:13:30.663886Z | 2021-01-11T20:38:28Z | HIGH | null | {'CWE-352'} | {'https://github.com/Flask-Middleware/flask-security/commit/6d50ee9169acf813257c37b75babe9c28e83542a', 'https://github.com/Flask-Middleware/flask-security/security/advisories/GHSA-hh7m-rx4f-4vpv', 'https://pypi.org/project/Flask-Security-Too', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21241', 'https://github.com/Flask-Middleware/flask-security/commit/61d313150b5f620d0b800896c4f2199005e84b1f', 'https://github.com/Flask-Middleware/flask-security/pull/422', 'https://github.com/Flask-Middleware/flask-security/releases/tag/3.4.5'} | null |
PyPI | PYSEC-2022-55 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. 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-2022-21731', 'GHSA-m4hf-j54p-p353'} | 2022-03-09T00:17:30.689879Z | 2022-02-03T12:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059'} | null |
PyPI | PYSEC-2020-68 | null | OAuthenticator is an OAuth login mechanism for JupyterHub. In oauthenticator from version 0.12.0 and before 0.12.2, the deprecated (in jupyterhub 1.2) configuration `Authenticator.whitelist`, which should be transparently mapped to `Authenticator.allowed_users` with a warning, is instead ignored by OAuthenticator classes, resulting in the same behavior as if this configuration has not been set. If this is the only mechanism of authorization restriction (i.e. no group or team restrictions in configuration) then all authenticated users will be allowed. Provider-based restrictions, including deprecated values such as `GitHubOAuthenticator.org_whitelist` are **not** affected. All users of OAuthenticator 0.12.0 and 0.12.1 with JupyterHub 1.2 (JupyterHub Helm chart 0.10.0-0.10.5) who use the `admin.whitelist.users` configuration in the jupyterhub helm chart or the `c.Authenticator.whitelist` configuration directly. Users of other deprecated configuration, e.g. `c.GitHubOAuthenticator.team_whitelist` are **not** affected. If you see a log line like this and expect a specific list of allowed usernames: "[I 2020-11-27 16:51:54.528 JupyterHub app:1717] Not using allowed_users. Any authenticated user will be allowed." you are likely affected. Updating oauthenticator to 0.12.2 is recommended. A workaround is to replace the deprecated `c.Authenticator.whitelist = ...` with `c.Authenticator.allowed_users = ...`. If any users have been authorized during this time who should not have been, they must be deleted via the API or admin interface, per the referenced documentation. | {'CVE-2020-26250', 'GHSA-384w-5v3f-q499'} | 2020-12-08T17:50:00Z | 2020-12-01T21:15:00Z | null | null | null | {'https://github.com/jupyterhub/oauthenticator/commit/a4aac191c16cf6281f3d346615aefa75702b02d7', 'https://github.com/jupyterhub/oauthenticator/security/advisories/GHSA-384w-5v3f-q499', 'https://github.com/jupyterhub/oauthenticator/blob/master/docs/source/changelog.md#0122---2020-11-30', 'https://jupyterhub.readthedocs.io/en/1.2.2/getting-started/authenticators-users-basics.html#add-or-remove-users-from-the-hub'} | null |
PyPI | PYSEC-2019-135 | null | When using wagtail-2fa before 1.3.0, if someone gains access to someone's Wagtail login credentials, they can log into the CMS and bypass the 2FA check by changing the URL. They can then add a new device and gain full access to the CMS. This problem has been patched in version 1.3.0. | {'GHSA-89px-ww3j-g2mm', 'CVE-2019-16766'} | 2020-10-09T13:27:00Z | 2019-11-29T17:15:00Z | null | null | null | {'https://github.com/labd/wagtail-2fa/commit/a6711b29711729005770ff481b22675b35ff5c81', 'https://github.com/LabD/wagtail-2fa/security/advisories/GHSA-89px-ww3j-g2mm', 'https://github.com/labd/wagtail-2fa/commit/13b12995d35b566df08a17257a23863ab6efb0ca'} | null |
PyPI | GHSA-r6h7-5pq2-j77h | Insufficiently random values in Ansible | 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'} | 2022-03-03T05:13:41.670114Z | 2021-06-15T16:10:11Z | MODERATE | null | {'CWE-330'} | {'https://github.com/ansible/ansible/issues/34144', 'https://github.com/ansible/ansible/pull/67429/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10729', 'https://bugzilla.redhat.com/show_bug.cgi?id=1831089', 'https://github.com/ansible/ansible', 'https://github.com/ansible/ansible/blob/v2.9.6/changelogs/CHANGELOG-v2.9.rst', 'https://www.debian.org/security/2021/dsa-4950'} | null |
PyPI | PYSEC-2021-466 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a division by zero to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L513-L522) computes a divisor based on user provided data (i.e., the shape of the tensors given as arguments). If all shapes are empty then `work_unit_size` is 0. Since there is no check for this case before division, this results in a runtime exception, with potential to be abused for a denial of service. 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-j8qc-5fqr-52fp', 'CVE-2021-29538'} | 2021-12-09T06:34:49.257791Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8qc-5fqr-52fp'} | null |
PyPI | PYSEC-2021-173 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29536', 'GHSA-2gfx-95x2-5v3x'} | 2021-08-27T03:22:27.845923Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2gfx-95x2-5v3x', 'https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933e'} | null |
PyPI | PYSEC-2021-489 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29561', 'GHSA-gvm4-h8j3-rjrq'} | 2021-12-09T06:34:52.832408Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq', 'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} | null |
PyPI | GHSA-27qf-jwm8-g7f3 | FPE in LSH in TFLite | ### Impact
An attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118).
```cc
int RunningSignBit(const TfLiteTensor* input, const TfLiteTensor* weight,
float seed) {
int input_item_bytes = input->bytes / SizeOfDimension(input, 0);
// ...
}
```
There is no check that the first dimension of the input is non zero.
### Patches
We have patched the issue in GitHub commit [0575b640091680cfb70f4dd93e70658de43b94f9](https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security. | {'CVE-2021-37691'} | 2022-03-03T05:13:33.257862Z | 2021-08-25T14:39:17Z | MODERATE | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-37691', 'https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-27qf-jwm8-g7f3', 'https://github.com/tensorflow/tensorflow'} | null |
PyPI | PYSEC-2021-523 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `DepthToSpace` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depth_to_space.cc#L63-L69). An attacker can craft a model such that `params->block_size` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29595', 'GHSA-vf94-36g5-69v8'} | 2021-12-09T06:34:58.107477Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vf94-36g5-69v8', 'https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9'} | null |
PyPI | PYSEC-2014-22 | null | The (1) load_djpeg function in JpegImagePlugin.py, (2) Ghostscript function in EpsImagePlugin.py, (3) load function in IptcImagePlugin.py, and (4) _copy function in Image.py in Python Image Library (PIL) 1.1.7 and earlier and Pillow before 2.3.1 do not properly create temporary files, which allow local users to overwrite arbitrary files and obtain sensitive information via a symlink attack on the temporary file. | {'CVE-2014-1932'} | 2021-07-15T02:22:16.928376Z | 2014-04-17T14:55:00Z | null | null | null | {'https://security.gentoo.org/glsa/201612-52', 'http://www.securityfocus.com/bid/65511', 'https://github.com/python-imaging/Pillow/commit/4e9f367dfd3f04c8f5d23f7f759ec12782e10ee7', 'http://www.ubuntu.com/usn/USN-2168-1', 'http://lists.opensuse.org/opensuse-updates/2014-05/msg00002.html', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737059', 'http://www.openwall.com/lists/oss-security/2014/02/11/1'} | null |
PyPI | GHSA-5hg3-6c2f-f3wr | Moderate severity vulnerability that affects django | django.middleware.common.CommonMiddleware in Django 1.11.x before 1.11.15 and 2.0.x before 2.0.8 has an Open Redirect. | {'CVE-2018-14574'} | 2022-03-03T05:13:38.840967Z | 2018-10-04T21:58:46Z | MODERATE | null | {'CWE-601'} | {'http://www.securityfocus.com/bid/104970', 'https://github.com/advisories/GHSA-5hg3-6c2f-f3wr', 'https://nvd.nist.gov/vuln/detail/CVE-2018-14574', 'https://www.debian.org/security/2018/dsa-4264', 'https://www.djangoproject.com/weblog/2018/aug/01/security-releases/', 'http://www.securitytracker.com/id/1041403', 'https://access.redhat.com/errata/RHSA-2019:0265', 'https://usn.ubuntu.com/3726-1/'} | null |
PyPI | PYSEC-2021-870 | null | Incomplete string comparison vulnerability exits in cvxopt.org cvxop <= 1.2.6 in APIs (cvxopt.cholmod.diag, cvxopt.cholmod.getfactor, cvxopt.cholmod.solve, cvxopt.cholmod.spsolve), which allows attackers to conduct Denial of Service attacks by construct fake Capsule objects. | {'CVE-2021-41500', 'GHSA-8rh6-h94m-vj54'} | 2022-03-09T00:15:59.735428Z | 2021-12-17T21:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-8rh6-h94m-vj54', 'https://github.com/cvxopt/cvxopt/issues/193', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/CXTPM3DGVYTYQ54OFCMXZVWVOMR7JM2D/'} | null |
PyPI | PYSEC-2020-173 | null | The pip package before 19.2 for Python allows Directory Traversal when a URL is given in an install command, because a Content-Disposition header can have ../ in a filename, as demonstrated by overwriting the /root/.ssh/authorized_keys file. This occurs in _download_http_url in _internal/download.py. | {'CVE-2019-20916', 'GHSA-gpvv-69j7-gwj8'} | 2021-03-15T16:18:00Z | 2020-09-04T20:15:00Z | null | null | null | {'https://lists.debian.org/debian-lts-announce/2020/09/msg00010.html', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00010.html', 'https://github.com/pypa/pip/compare/19.1.1...19.2', 'https://github.com/pypa/pip/issues/6413', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00005.html', 'https://github.com/gzpan123/pip/commit/a4c735b14a62f9cb864533808ac63936704f2ace', 'https://github.com/advisories/GHSA-gpvv-69j7-gwj8'} | null |
PyPI | PYSEC-2020-87 | null | plone.restapi in Plone 5.2.0 through 5.2.1 allows users with a certain privilege level to escalate their privileges up to the highest level. | {'CVE-2020-7938'} | 2020-01-24T23:03:00Z | 2020-01-23T21:15:00Z | null | null | null | {'https://plone.org/security/hotfix/20200121', 'https://plone.org/security/hotfix/20200121/privilege-escalation-when-plone-restapi-is-installed', 'https://www.openwall.com/lists/oss-security/2020/01/22/1', 'http://www.openwall.com/lists/oss-security/2020/01/24/1'} | null |
PyPI | GHSA-x7rp-74x2-mjf3 | Segfault in Tensorflow | ### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265
) sets up conditions to cause a heap buffer overflow:
```cc
auto per_batch_counts = BatchedMap<W>(num_batches);
int batch_idx = 0;
for (int idx = 0; idx < num_values; ++idx) {
while (idx >= splits_values(batch_idx)) {
batch_idx++;
}
const auto& value = values_values(idx);
if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {
per_batch_counts[batch_idx - 1][value] = 1;
}
}
```
A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4) | {'CVE-2020-15200'} | 2021-08-26T15:13:38Z | 2020-09-25T18:28:32Z | MODERATE | null | {'CWE-20', 'CWE-787', 'CWE-122'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15200', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} | null |
PyPI | GHSA-hggx-3h72-49ww | Moderate severity vulnerability that affects Pillow | Buffer overflow in the ImagingLibTiffDecode function in libImaging/TiffDecode.c in Pillow before 3.1.1 allows remote attackers to overwrite memory via a crafted TIFF file. | {'CVE-2016-0740'} | 2022-03-03T05:13:15.863124Z | 2018-07-24T20:03:51Z | MODERATE | null | {'CWE-119'} | {'https://github.com/python-pillow/Pillow/blob/c3cb690fed5d4bf0c45576759de55d054916c165/CHANGES.rst', 'https://nvd.nist.gov/vuln/detail/CVE-2016-0740', 'https://security.gentoo.org/glsa/201612-52', 'https://github.com/python-pillow/Pillow/commit/6dcbf5bd96b717c58d7b642949da8d323099928e', 'https://github.com/python-pillow/Pillow', 'http://www.debian.org/security/2016/dsa-3499', 'https://github.com/advisories/GHSA-hggx-3h72-49ww'} | null |
PyPI | PYSEC-2018-76 | null | topydo contains a CWE-20: Improper Input Validation vulnerability in ListFormatParser::parse, file topydo/lib/ListFormat.py line 292 as of d4f843dac71308b2f29a7c2cdc76f055c3841523 that can result in Injection of arbitrary bytes to the terminal, including terminal escape code sequences. This attack appear to be exploitable via The victim must open a todo.txt with at least one specially crafted line.. | {'GHSA-h6h9-pphv-m266', 'CVE-2018-1000523'} | 2021-08-25T04:30:33.312157Z | 2018-06-26T16:29:00Z | null | null | null | {'https://github.com/bram85/topydo/blob/master/topydo/lib/ListFormat.py#L292', 'https://github.com/bram85/topydo/issues/240', 'https://github.com/advisories/GHSA-h6h9-pphv-m266'} | null |
PyPI | GHSA-hx2x-85gr-wrpq | Out of bounds access in tensorflow-lite | ### Impact
In TensorFlow Lite models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reference_ops.h#L2625-L2631
Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer.
This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits.
### Patches
We have patched the issue in 204945b and will release patch releases for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.
### Workarounds
A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, 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.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been discovered from a variant analysis of [GHSA-p2cq-cprg-frvm](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm). | {'CVE-2020-15212'} | 2021-08-26T15:20:18Z | 2020-09-25T18:29:00Z | HIGH | null | {'CWE-787'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-15212', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null |
PyPI | GHSA-xr2c-5w89-63pv | Untrusted Search Path in Poetry | Poetry prior to v1.1.9 was discovered to contain an untrusted search path which causes the application to behave in unexpected ways when users execute Poetry commands in a directory containing malicious content. This vulnerability occurs when the application is ran on Windows OS. | {'CVE-2022-26184'} | 2022-03-30T21:17:05.181660Z | 2022-03-23T00:00:24Z | CRITICAL | null | {'CWE-426'} | {'https://github.com/python-poetry/', 'https://github.com/python-poetry/poetry-core/pull/205/commits/fa9cb6f358ae840885c700f954317f34838caba7', 'https://github.com/python-poetry/poetry/releases/tag/1.1.9', 'https://nvd.nist.gov/vuln/detail/CVE-2022-26184'} | null |
PyPI | PYSEC-2020-104 | null | An issue was discovered in SaltStack Salt through 3002. Sending crafted web requests to the Salt API, with the SSH client enabled, can result in shell injection. | {'CVE-2020-16846'} | 2021-03-30T13:29:00Z | 2020-11-06T08:15:00Z | null | null | null | {'https://github.com/saltstack/salt/releases', 'https://www.saltstack.com/blog/on-november-3-2020-saltstack-publicly-disclosed-three-new-cves/', 'https://www.zerodayinitiative.com/advisories/ZDI-20-1379/', 'https://www.zerodayinitiative.com/advisories/ZDI-20-1383/', 'https://www.zerodayinitiative.com/advisories/ZDI-20-1382/', '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://www.zerodayinitiative.com/advisories/ZDI-20-1380/', 'https://www.zerodayinitiative.com/advisories/ZDI-20-1381/', 'http://packetstormsecurity.com/files/160039/SaltStack-Salt-REST-API-Arbitrary-Command-Execution.html', '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-2010-16 | null | Multiple cross-site scripting (XSS) vulnerabilities in MoinMoin 1.7.3 and earlier, 1.8.x before 1.8.8, and 1.9.x before 1.9.3 allow remote attackers to inject arbitrary web script or HTML via crafted content, related to (1) Page.py, (2) PageEditor.py, (3) PageGraphicalEditor.py, (4) action/CopyPage.py, (5) action/Load.py, (6) action/RenamePage.py, (7) action/backup.py, (8) action/login.py, (9) action/newaccount.py, and (10) action/recoverpass.py. | {'CVE-2010-2487'} | 2021-07-16T01:31:23.671563Z | 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://moinmo.in/MoinMoinRelease1.8', 'http://www.securityfocus.com/bid/40549', 'http://hg.moinmo.in/moin/1.9/rev/e50b087c4572', 'http://hg.moinmo.in/moin/1.9/rev/68ba3cc79513', 'http://hg.moinmo.in/moin/1.8/rev/4238b0c90871', 'http://marc.info/?l=oss-security&m=127799369406968&w=2', 'http://moinmo.in/SecurityFixes', 'http://moinmo.in/MoinMoinRelease1.9', 'http://hg.moinmo.in/moin/1.8/raw-file/1.8.8/docs/CHANGES', '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 | PYSEC-2021-807 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.image.resize` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41199', 'GHSA-5hx2-qx8j-qjqm'} | 2021-12-09T06:35:41.080668Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hx2-qx8j-qjqm', 'https://github.com/tensorflow/tensorflow/issues/46914'} | null |
PyPI | PYSEC-2014-55 | null | zip.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 does not properly enforce access restrictions when including content in a zip archive, which allows remote attackers to obtain sensitive information by reading a generated archive. | {'CVE-2013-4191'} | 2021-07-25T23:34:46.176817Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'http://seclists.org/oss-sec/2013/q3/261', 'http://plone.org/products/plone/security/advisories/20130618-announcement', 'https://bugzilla.redhat.com/show_bug.cgi?id=978453'} | null |
PyPI | GHSA-43fq-w8qq-v88h | Out-of-bounds read in Pillow | In libImaging/SgiRleDecode.c in Pillow through 7.0.0, a number of out-of-bounds reads exist in the parsing of SGI image files, a different issue than CVE-2020-5311. | {'CVE-2020-11538'} | 2022-03-03T05:13:46.477221Z | 2020-07-27T21:52:36Z | HIGH | null | {'CWE-125'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/index.html', 'https://github.com/python-pillow/Pillow/blob/master/docs/releasenotes/7.1.0.rst#security', 'https://github.com/python-pillow/Pillow/pull/4538', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BEBCPE4F2VHTIT6EZA2YZQZLPVDEBJGD/', 'https://usn.ubuntu.com/4430-2/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOKHNWV2VS5GESY7IBD237E7C6T3I427/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-11538', 'https://snyk.io/vuln/SNYK-PYTHON-PILLOW-574574', 'https://usn.ubuntu.com/4430-1/', 'https://github.com/python-pillow/Pillow', 'https://github.com/python-pillow/Pillow/pull/4504', 'https://pillow.readthedocs.io/en/stable/releasenotes/7.1.0.html', 'https://github.com/python-pillow/Pillow/commit/2ef59fdbaeb756bc512ab3f2ad15ac45665b303d'} | null |
PyPI | PYSEC-2021-554 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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-2021-37641', 'GHSA-9c8h-vvrj-w2p8'} | 2021-12-09T06:35:02.493921Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8'} | null |
PyPI | GHSA-mcgw-5fhw-3fq8 | Incorrect Authorization in saleor | Incorrect Authorization in saleor prior to 3.1.2. | {'CVE-2022-0932'} | 2022-03-25T19:31:58.123393Z | 2022-03-12T00:00:34Z | MODERATE | null | {'CWE-863'} | {'https://huntr.dev/bounties/88ae4cbc-c697-401b-8b04-7dc4e03ad8eb', 'https://github.com/saleor/saleor', 'https://nvd.nist.gov/vuln/detail/CVE-2022-0932', 'https://github.com/saleor/saleor/commit/521dfd6394f3926a77c60d8633c058e16d0f916d'} | null |
PyPI | GHSA-hj5v-574p-mj7c | Regular expression deinal of service in py | A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality. | {'CVE-2020-29651'} | 2022-03-03T05:13:39.087574Z | 2021-04-20T16:39:57Z | HIGH | null | {'CWE-400'} | {'https://github.com/pytest-dev/py/pull/257/commits/4a9017dc6199d2a564b6e4b0aa39d6d8870e4144', 'https://nvd.nist.gov/vuln/detail/CVE-2020-29651', 'https://github.com/pytest-dev/py/issues/256', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/CHDTINIBJZ67T3W74QTBIY5LPKAXEOGR/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/AYWNYEV3FGDHPIHX4DDUDMFZ6NLCQRC4/', 'https://github.com/pytest-dev/py/pull/257'} | null |
PyPI | PYSEC-2021-104 | null | Zope is an open-source web application server. This advisory extends the previous advisory at https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36 with additional cases of TAL expression traversal vulnerabilities. Most Python modules are not available for using in TAL expressions that you can add through-the-web, for example in Zope Page Templates. This restriction avoids file system access, for example via the 'os' module. But some of the untrusted modules are available indirectly through Python modules that are available for direct use. By default, you need to have the Manager role to add or edit Zope Page Templates through the web. Only sites that allow untrusted users to add/edit Zope Page Templates through the web are at risk. The problem has been fixed in Zope 5.21 and 4.6.1. The workaround is the same as for https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36: A site administrator can restrict adding/editing Zope Page Templates through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing Zope Page Templates through the web should be restricted to trusted users only. | {'GHSA-5pr9-v234-jw36', 'CVE-2021-32674', 'GHSA-rpcg-f9q6-2mq6', 'GHSA-5vq5-pg3r-9ph3'} | 2021-06-22T04:54:57.652841Z | 2021-06-08T18:15:00Z | null | null | null | {'https://github.com/zopefoundation/Zope/commit/1d897910139e2c0b11984fc9b78c1da1365bec21', 'https://pypi.org/project/Zope/', 'https://github.com/zopefoundation/Zope/security/advisories/GHSA-5pr9-v234-jw36', 'https://github.com/zopefoundation/Zope/security/advisories/GHSA-rpcg-f9q6-2mq6', 'https://github.com/advisories/GHSA-5vq5-pg3r-9ph3'} | null |
PyPI | PYSEC-2021-411 | null | TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41219', 'GHSA-4f99-p9c2-3j8x'} | 2021-11-13T06:52:45.099185Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4f99-p9c2-3j8x', 'https://github.com/tensorflow/tensorflow/commit/e6cf28c72ba2eb949ca950d834dd6d66bb01cfae'} | null |
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