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 | GHSA-xcp8-hh74-f6mc | Moderate severity vulnerability that affects oslo.middleware | python-oslo-middleware before versions 3.8.1, 3.19.1, 3.23.1 is vulnerable to an information disclosure. Software using the CatchError class could include sensitive values in a traceback's error message. System users could exploit this flaw to obtain sensitive information from OpenStack component error logs (for example, keystone tokens). | {'CVE-2017-2592'} | 2022-03-03T05:13:24.998175Z | 2018-07-13T15:16:45Z | MODERATE | null | {'CWE-532'} | {'https://github.com/advisories/GHSA-xcp8-hh74-f6mc', 'https://nvd.nist.gov/vuln/detail/CVE-2017-2592'} | null |
PyPI | GHSA-4ppp-gpcr-7qf6 | HTTP Request Smuggling: Content-Length Sent Twice in Waitress | ### Impact
Waitress would header fold a double `Content-Length` header and due to being unable to cast the now comma separated value to an integer would set the `Content-Length` to 0 internally.
So a request with:
```
Content-Length: 10
Content-Length: 10
```
would get transformed to:
```
Content-Length: 10, 10
```
Which would Waitress would then internally set to `Content-Lenght: 0`.
Waitress would then treat the request as having no body, thereby treating the body of the request as a new request in HTTP pipelining.
### Patches
This issue is fixed in Waitress 1.4.0. This brings a range of changes to harden Waitress against potential HTTP request confusions, and may change the behaviour of Waitress behind non-conformist proxies.
The Pylons Project recommends upgrading as soon as possible, while validating that the changes in Waitress don't cause any changes in behavior.
### Workarounds
Various reverse proxies may have protections against sending potentially bad HTTP requests to the backend, and or hardening against potential issues like this. If the reverse proxy doesn't use HTTP/1.1 for connecting to the backend issues are also somewhat mitigated, as HTTP pipelining does not exist in HTTP/1.0 and Waitress will close the connection after every single request (unless the Keep Alive header is explicitly sent... so this is not a fool proof security method).
### Issues/more security issues:
* open an issue at https://github.com/Pylons/waitress/issues (if not sensitive or security related)
* email the Pylons Security mailing list: pylons-project-security@googlegroups.com (if security related) | null | 2022-03-24T18:01:51.171462Z | 2019-12-20T23:04:35Z | CRITICAL | null | {'CWE-444'} | {'https://github.com/Pylons/waitress', 'https://github.com/Pylons/waitress/security/advisories/GHSA-4ppp-gpcr-7qf6', 'https://github.com/Pylons/waitress/commit/575994cd42e83fd772a5f7ec98b2c56751bd3f65'} | null |
PyPI | GHSA-h4pc-gx2w-f2xv | Heap OOB read in TFLite | ### Impact
A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of [`Split_V`](https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99):
```cc
const int input_size = SizeOfDimension(input, axis_value);
```
If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the [`SizeOfDimension` function](https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape array:
```cc
inline int SizeOfDimension(const TfLiteTensor* t, int dim) {
return t->dims->data[dim];
}
```
### Patches
We have patched the issue in GitHub commit [ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412](https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29606'} | 2022-03-03T05:13:05.178287Z | 2021-05-21T14:28:24Z | HIGH | null | {'CWE-125'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29606', 'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h4pc-gx2w-f2xv'} | null |
PyPI | PYSEC-2020-26 | null | Synopsys hub-rest-api-python (aka blackduck on PyPI) version 0.0.25 - 0.0.52 does not validate SSL certificates in certain cases. | {'GHSA-f248-v4qh-x2r6', 'CVE-2020-27589'} | 2021-09-01T06:49:41.380049Z | 2020-11-06T14:15:00Z | null | null | null | {'https://www.optiv.com/explore-optiv-insights/source-zero/certificate-validation-disabled-black-duck-api-wrapper', 'https://github.com/blackducksoftware/hub-rest-api-python/pull/113/commits/273b27d0de1004389dd8cf43c40b1197c787e7cd', 'https://community.synopsys.com/s/question/0D52H00005JCZAXSA5/announcement-black-duck-defect-identified', 'https://pypi.org/project/blackduck/', 'https://github.com/blackducksoftware/hub-rest-api-python', 'https://github.com/advisories/GHSA-f248-v4qh-x2r6'} | null |
PyPI | PYSEC-2021-428 | null | nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. | {'CVE-2021-41134', 'GHSA-p6rw-44q7-3fw4'} | 2021-11-16T21:20:29.137127Z | 2021-11-03T18:15:00Z | null | null | null | {'https://github.com/jupyter/nbdime/security/advisories/GHSA-p6rw-44q7-3fw4', 'https://github.com/jupyter/nbdime/commit/e44a5cc7677f24b45ebafc756db49058c2f750ea'} | null |
PyPI | GHSA-4cfr-gjfx-fj3x | Cobbler before 3.3.0 allows arbitrary file write operations via upload_log_data. | Cobbler before 3.3.0 allows arbitrary file write operations via upload_log_data. | {'CVE-2021-40324'} | 2022-03-03T05:14:01.052844Z | 2021-10-05T17:53:11Z | HIGH | null | {'CWE-434'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-40324', 'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://github.com/cobbler/cobbler', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0'} | null |
PyPI | PYSEC-2014-83 | null | The (1) extract_keys_from_pdf and (2) fill_pdf functions in pdf_ext.py in logilab-commons before 0.61.0 allows local users to overwrite arbitrary files and possibly have other unspecified impact via a symlink attack on /tmp/toto.fdf. | {'CVE-2014-1838'} | 2021-08-27T03:22:06.075755Z | 2014-03-11T19:37:00Z | null | null | null | {'http://comments.gmane.org/gmane.comp.security.oss.general/11986', 'http://www.logilab.org/ticket/207561', 'http://lists.opensuse.org/opensuse-updates/2014-02/msg00085.html', 'http://secunia.com/advisories/57209', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737051'} | null |
PyPI | PYSEC-2021-582 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vmjw-c2vp-p33c', 'CVE-2021-37669'} | 2021-12-09T06:35:04.885089Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d'} | null |
PyPI | PYSEC-2022-134 | null | Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a `DCHECK`. However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range. | {'CVE-2022-23570', 'GHSA-9p77-mmrw-69c7'} | 2022-03-09T00:18:26.999978Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L104-L106', 'https://github.com/tensorflow/tensorflow/commit/8a513cec4bec15961fbfdedcaa5376522980455c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9p77-mmrw-69c7'} | null |
PyPI | GHSA-7xwj-5r4v-429p | NPE in TFLite | ### Impact
The implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313):
```cc
TfLiteTensor* state = GetVariableInput(context, node, kStateTensor);
// ...
GetTensorData<float>(state)
```
The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor.
```cc
TfLiteTensor* GetVariableInput(TfLiteContext* context, const TfLiteNode* node,
int index) {
TfLiteTensor* tensor = GetMutableInput(context, node, index);
return tensor->is_variable ? tensor : nullptr;
}
```
Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception.
### Patches
We have patched the issue in GitHub commit [5b048e87e4e55990dae6b547add4dae59f4e1c76](https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76).
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-2021-37681'} | 2021-08-24T16:30:14Z | 2021-08-25T14:40:35Z | HIGH | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37681', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7xwj-5r4v-429p'} | null |
PyPI | PYSEC-2021-351 | null | ESPHome is a system to control the ESP8266/ESP32. Anyone with web_server enabled and HTTP basic auth configured on version 2021.9.1 or older is vulnerable to an issue in which `web_server` allows over-the-air (OTA) updates without checking user defined basic auth username & password. This issue is patched in version 2021.9.2. As a workaround, one may disable or remove `web_server`. | {'CVE-2021-41104', 'GHSA-48mj-p7x2-5jfm'} | 2021-09-30T23:26:26.067991Z | 2021-09-28T16:15:00Z | null | null | null | {'https://github.com/esphome/esphome/security/advisories/GHSA-48mj-p7x2-5jfm', 'https://github.com/esphome/esphome/releases/tag/2021.9.2', 'https://github.com/esphome/esphome/commit/2234f6aacf8cc653307fed80f3750317a82c4f83', 'https://github.com/esphome/esphome/pull/2409/commits/207cde1667d8c799a197b78ca8a5a14de8d5ca1e'} | null |
PyPI | PYSEC-2021-701 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. 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-6qgm-fv6v-rfpv', 'CVE-2021-29575'} | 2021-12-09T06:35:27.716876Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv'} | null |
PyPI | GHSA-7534-mm45-c74v | Buffer Overflow in Pillow | Pillow through 8.2.0 and PIL (aka Python Imaging Library) through 1.1.7 allow an attacker to pass controlled parameters directly into a convert function to trigger a buffer overflow in Convert.c. | {'CVE-2021-34552'} | 2022-03-22T22:32:03.249088Z | 2021-10-05T20:24:41Z | CRITICAL | null | {'CWE-120'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/index.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7V6LCG525ARIX6LX5QRYNAWVDD2MD2SV/', 'https://github.com/python-pillow/Pillow/pull/5567', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/VUGBBT63VL7G4JNOEIPDJIOC34ZFBKNJ/', 'https://lists.debian.org/debian-lts-announce/2021/07/msg00018.html', 'https://nvd.nist.gov/vuln/detail/CVE-2021-34552', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.3.0.html#buffer-overflow', 'https://github.com/python-pillow/Pillow'} | null |
PyPI | PYSEC-2021-214 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-v6r6-84gr-92rm', 'CVE-2021-29577'} | 2021-08-27T03:22:35.059356Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6r6-84gr-92rm'} | null |
PyPI | GHSA-3gh2-xw74-jmcw | SQL injection in Django | Django 1.11 before 1.11.29, 2.2 before 2.2.11, and 3.0 before 3.0.4 allows SQL Injection if untrusted data is used as a tolerance parameter in GIS functions and aggregates on Oracle. By passing a suitably crafted tolerance to GIS functions and aggregates on Oracle, it was possible to break escaping and inject malicious SQL. | {'CVE-2020-9402'} | 2022-03-03T05:13:24.577485Z | 2020-06-05T14:52:07Z | HIGH | null | {'CWE-89'} | {'https://github.com/django/django', 'https://security.netapp.com/advisory/ntap-20200327-0004/', 'https://www.djangoproject.com/weblog/2020/mar/04/security-releases/', 'https://security.gentoo.org/glsa/202004-17', 'https://docs.djangoproject.com/en/3.0/releases/security/', 'https://groups.google.com/forum/#!topic/django-announce/fLUh_pOaKrY', 'https://www.debian.org/security/2020/dsa-4705', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4A2AP4T7RKPBCLTI2NNQG3T6MINDUUMZ/', 'https://usn.ubuntu.com/4296-1/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-9402'} | null |
PyPI | PYSEC-2019-1 | null | aioxmpp version 0.10.2 and earlier contains a Improper Handling of Structural Elements vulnerability in Stanza Parser, rollback during error processing, aioxmpp.xso.model.guard function that can result in Denial of Service, Other. This attack appears to be exploitable via Remote. A crafted stanza can be sent to an application which uses the vulnerable components to either inject data in a different context or cause the application to reconnect (potentially losing data). This vulnerability appears to have been fixed in 0.10.3. | {'GHSA-6m9g-jr8c-cqw3', 'CVE-2019-1000007'} | 2019-02-15T15:00:00Z | 2019-02-04T21:29:00Z | null | null | null | {'https://github.com/horazont/aioxmpp/pull/268', 'https://github.com/advisories/GHSA-6m9g-jr8c-cqw3'} | null |
PyPI | PYSEC-2021-644 | null | TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior. 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-62gx-355r-9fhg', 'CVE-2021-29518'} | 2021-12-09T06:35:18.016615Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg', 'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | null |
PyPI | GHSA-wrp6-9w7f-3wxg | calibre-web is vulnerable to Cross-site Scripting | calibre-web is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') | {'CVE-2021-4170'} | 2022-03-03T05:14:13.530442Z | 2022-01-21T23:55:34Z | HIGH | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-4170', 'https://github.com/janeczku/calibre-web/', 'https://huntr.dev/bounties/ff395101-e392-401d-ab4f-579c63fbf6a0', 'https://github.com/janeczku/calibre-web/commit/7ad419dc8c12180e842a82118f4866ac3d074bc5'} | null |
PyPI | PYSEC-2020-214 | null | Twisted before 16.3.1 does not attempt to address RFC 3875 section 4.1.18 namespace conflicts and therefore does not protect CGI applications from the presence of untrusted client data in the HTTP_PROXY environment variable, which might allow remote attackers to redirect a CGI application's outbound HTTP traffic to an arbitrary proxy server via a crafted Proxy header in an HTTP request, aka an "httpoxy" issue. | {'GHSA-3gqj-cmxr-p4x2', 'CVE-2016-1000111'} | 2021-07-05T00:01:28.092827Z | 2020-03-11T20:15:00Z | null | null | null | {'https://twistedmatrix.com/trac/ticket/8623', 'https://github.com/advisories/GHSA-3gqj-cmxr-p4x2', 'http://www.oracle.com/technetwork/topics/security/linuxbulletinoct2016-3090545.html', 'https://twistedmatrix.com/pipermail/twisted-web/2016-August/005268.html', 'https://www.openwall.com/lists/oss-security/2016/07/18/6'} | null |
PyPI | GHSA-cw7p-q79f-m2v7 | incomplete JupyterHub logout with simultaneous JupyterLab sessions | ### Impact
Users of JupyterLab with JupyterHub who have multiple JupyterLab tabs open in the same browser session, may see incomplete logout from the single-user server, as fresh credentials (for the single-user server only, not the Hub) reinstated after logout, if another active JupyterLab session is open while the logout takes place.
### Patches
Upgrade to JupyterHub 1.5. For distributed deployments, it is jupyterhub in the _user_ environment that needs patching. There are no patches necessary in the Hub environment.
### Workarounds
The only workaround is to make sure that only one JupyterLab tab is open when you log out. | {'CVE-2021-41247'} | 2022-03-03T05:13:51.884212Z | 2021-11-08T18:02:37Z | LOW | null | {'CWE-613'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41247', 'https://github.com/jupyterhub/jupyterhub/commit/5ac9e7f73a6e1020ffddc40321fc53336829fe27', 'https://github.com/jupyterhub/jupyterhub/security/advisories/GHSA-cw7p-q79f-m2v7', 'https://github.com/jupyterhub/jupyterhub'} | null |
PyPI | GHSA-77pw-c3j2-5fc8 | Plaintext password leak in Apache Superset | In the course of work on the open source project it was discovered that authenticated users running queries against Hive and Presto database engines could access information via a number of templated fields including the contents of query description metadata database, the hashed version of the authenticated users’ password, and access to connection information including the plaintext password for the current connection. It would also be possible to run arbitrary methods on the database connection object for the Presto or Hive connection, allowing the user to bypass security controls internal to Superset. This vulnerability is present in every Apache Superset version < 0.37.2. | {'CVE-2020-13952'} | 2022-03-03T05:14:06.520524Z | 2021-04-30T17:34:03Z | HIGH | null | {'CWE-200'} | {'https://lists.apache.org/thread.html/rf1faa368f580d2cb691576bee1277855f769667f3114d5df1dacbea6%40%3Cdev.superset.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2020-13952'} | null |
PyPI | GHSA-42fp-4hm3-j8r7 | Moderate severity vulnerability that affects moin | Cross-site scripting (XSS) vulnerability in the link dialogue in GUI editor in MoinMoin before 1.9.10 allows remote attackers to inject arbitrary web script or HTML via unspecified vectors. | {'CVE-2017-5934'} | 2022-03-03T05:13:32.296666Z | 2019-01-04T17:46:08Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2017-5934', 'https://lists.debian.org/debian-lts-announce/2018/10/msg00007.html', 'https://github.com/advisories/GHSA-42fp-4hm3-j8r7', 'http://moinmo.in/SecurityFixes', 'https://www.debian.org/security/2018/dsa-4318', 'https://usn.ubuntu.com/3794-1/', 'https://github.com/moinwiki/moin-1.9/commit/70955a8eae091cc88fd9a6e510177e70289ec024', 'http://lists.opensuse.org/opensuse-security-announce/2018-10/msg00024.html', 'https://github.com/moinwiki/moin-1.9'} | null |
PyPI | PYSEC-2010-2 | null | MoinMoin before 1.8.7 and 1.9.x before 1.9.2 does not properly sanitize user profiles, which has unspecified impact and attack vectors. | {'CVE-2010-0669'} | 2021-07-05T00:01:22.841909Z | 2010-02-26T19:30:00Z | null | null | null | {'http://moinmo.in/MoinMoinRelease1.8', 'http://hg.moinmo.in/moin/1.8/raw-file/1.8.7/docs/CHANGES', 'http://moinmo.in/SecurityFixes', 'http://www.openwall.com/lists/oss-security/2010/02/15/2', 'http://www.debian.org/security/2010/dsa-2014', 'http://secunia.com/advisories/38444', 'http://www.securityfocus.com/bid/38023', 'http://www.openwall.com/lists/oss-security/2010/02/15/4', 'http://www.vupen.com/english/advisories/2010/0600', 'http://secunia.com/advisories/38903', 'http://www.openwall.com/lists/oss-security/2010/02/21/2'} | null |
PyPI | PYSEC-2017-93 | null | A HTTP/2 implementation built using any version of the Python priority library prior to version 1.2.0 could be targeted by a malicious peer by having that peer assign priority information for every possible HTTP/2 stream ID. The priority tree would happily continue to store the priority information for each stream, and would therefore allocate unbounded amounts of memory. Attempting to actually use a tree like this would also cause extremely high CPU usage to maintain the tree. | {'CVE-2016-6580'} | 2021-08-27T03:22:16.246169Z | 2017-01-10T15:59:00Z | null | null | null | {'http://www.securityfocus.com/bid/92311', 'https://python-hyper.org/priority/en/latest/security/CVE-2016-6580.html'} | null |
PyPI | PYSEC-2021-828 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain 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. | {'CVE-2021-41221', 'GHSA-cqv6-3phm-hcwx'} | 2021-12-09T06:35:44.302427Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx'} | null |
PyPI | GHSA-rv95-4wxj-6fqq | Low severity vulnerability that affects colander | In Pylons Colander through 1.6, the URL validator allows an attacker to potentially cause an infinite loop thereby causing a denial of service via an unclosed parenthesis. | {'CVE-2017-18361'} | 2022-03-03T05:11:39.422665Z | 2019-02-07T18:18:22Z | HIGH | null | {'CWE-835'} | {'https://nvd.nist.gov/vuln/detail/CVE-2017-18361', 'https://github.com/Pylons/colander/issues/290', 'https://github.com/Pylons/colander/pull/323', 'https://github.com/Pylons/colander', 'https://github.com/advisories/GHSA-rv95-4wxj-6fqq'} | null |
PyPI | PYSEC-2018-59 | null | The safe_eval function in trytond in Tryton before 2.4.15, 2.6.x before 2.6.14, 2.8.x before 2.8.11, 3.0.x before 3.0.7, and 3.2.x before 3.2.3 allows remote authenticated users to execute arbitrary commands via shell metacharacters in (1) the collection.domain in the webdav module or (2) the formula field in the price_list module. | {'CVE-2014-6633'} | 2021-10-12T02:55:35.904690Z | 2018-04-12T15:29:00Z | null | null | null | {'https://bugs.tryton.org/issue4155', 'http://www.tryton.org/posts/security-release-for-issue4155.html'} | null |
PyPI | GHSA-r28v-mw67-m5p9 | Moderate severity vulnerability that affects django | An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. The django.utils.html.urlize() function was extremely slow to evaluate certain inputs due to catastrophic backtracking vulnerabilities in two regular expressions (only one regular expression for Django 1.8.x). The urlize() function is used to implement the urlize and urlizetrunc template filters, which were thus vulnerable. | {'CVE-2018-7536'} | 2022-03-03T05:12:49.634534Z | 2019-01-04T17:50:07Z | MODERATE | null | {'CWE-185'} | {'https://github.com/django/django', 'https://www.djangoproject.com/weblog/2018/mar/06/security-releases/', 'https://access.redhat.com/errata/RHSA-2019:0051', 'http://www.securityfocus.com/bid/103361', 'https://access.redhat.com/errata/RHSA-2018:2927', 'https://www.debian.org/security/2018/dsa-4161', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7536', 'https://lists.debian.org/debian-lts-announce/2018/03/msg00006.html', 'https://github.com/advisories/GHSA-r28v-mw67-m5p9', 'https://access.redhat.com/errata/RHSA-2019:0265', 'https://access.redhat.com/errata/RHSA-2019:0082', 'https://usn.ubuntu.com/3591-1/'} | null |
PyPI | PYSEC-2019-182 | null | Python keyring has insecure permissions on new databases allowing world-readable files to be created | {'GHSA-8867-vpm3-g98g', 'CVE-2012-5578'} | 2021-08-27T03:22:05.663844Z | 2019-11-25T13:15:00Z | null | null | null | {'https://security-tracker.debian.org/tracker/CVE-2012-5578', 'https://access.redhat.com/security/cve/cve-2012-5578', 'https://bugs.launchpad.net/ubuntu/+source/python-keyring/+bug/1031465', 'http://www.openwall.com/lists/oss-security/2012/11/27/4', 'https://github.com/advisories/GHSA-8867-vpm3-g98g', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2012-5578', 'https://bugzilla.suse.com/show_bug.cgi?id=CVE-2012-5578'} | null |
PyPI | GHSA-p69g-f978-xxv9 | Moderate severity vulnerability that affects luigi | Luigi version prior to version 2.8.0; after commit 53b52e12745075a8acc016d33945d9d6a7a6aaeb; after GitHub PR spotify/luigi/pull/1870 contains a Cross ite Request Forgery (CSRF) vulnerability in API endpoint: /api/<method> that can result in Task metadata such as task name, id, parameter, etc. will be leaked to unauthorized users. This attack appear to be exploitable via The victim must visit a specially crafted webpage from the network where their Luigi server is accessible.. This vulnerability appears to have been fixed in 2.8.0 and later. | {'CVE-2018-1000843'} | 2022-03-03T05:13:17.325236Z | 2018-12-20T22:01:39Z | HIGH | null | {'CWE-352'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-1000843', 'https://github.com/spotify/luigi/pull/1870', 'https://groups.google.com/forum/#!topic/luigi-user/ZgfRTpBsVUY', 'https://github.com/advisories/GHSA-p69g-f978-xxv9', 'https://github.com/spotify/luigi', 'https://github.com/spotify/luigi/blob/2.7.9/luigi/server.py#L67'} | null |
PyPI | PYSEC-2022-122 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in `TfLiteIntArrayCreate`. The `TfLiteIntArrayGetSizeInBytes` returns an `int` instead of a `size_t. An attacker can control model inputs such that `computed_size` overflows the size of `int` datatype. 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-2022-23558', 'GHSA-9gwq-6cwj-47h3'} | 2022-03-09T00:18:25.380350Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L24-L33', 'https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9gwq-6cwj-47h3', 'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L53-L60'} | null |
PyPI | GHSA-2wmv-37vq-52g5 | FPE in `tf.raw_ops.UnravelIndex` | ### Impact
An attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0:
```python
import tensorflow as tf
tf.raw_ops.UnravelIndex(indices=-1, dims=[1,0,2])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0.
### Patches
We have patched the issue in GitHub commit [a776040a5e7ebf76eeb7eb923bf1ae417dd4d233](https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233).
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-2021-37668'} | 2022-03-03T05:14:06.445606Z | 2021-08-25T14:42:06Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2wmv-37vq-52g5', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37668'} | null |
PyPI | PYSEC-2021-594 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. 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-2021-37681', 'GHSA-7xwj-5r4v-429p'} | 2021-12-09T06:35:05.896757Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7xwj-5r4v-429p'} | null |
PyPI | PYSEC-2020-4 | null | A flaw was found in the Ansible Engine when using module_args. Tasks executed with check mode (--check-mode) do not properly neutralize sensitive data exposed in the event data. This flaw allows unauthorized users to read this data. The highest threat from this vulnerability is to confidentiality. | {'CVE-2020-14332', 'GHSA-j667-c2hm-f2wp'} | 2020-09-21T12:33:00Z | 2020-09-11T18:15:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-14332', 'https://github.com/advisories/GHSA-j667-c2hm-f2wp', 'https://github.com/ansible/ansible/pull/71033'} | null |
PyPI | PYSEC-2014-95 | null | Race condition in the xdg.BaseDirectory.get_runtime_dir function in python-xdg 0.25 allows local users to overwrite arbitrary files by pre-creating /tmp/pyxdg-runtime-dir-fallback-victim to point to a victim-owned location, then replacing it with a symlink to an attacker-controlled location once the get_runtime_dir function is called. | {'CVE-2014-1624'} | 2021-08-27T03:22:18.849828Z | 2014-01-28T00:55:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/90618', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=736247', 'http://www.securityfocus.com/bid/65042', 'http://www.openwall.com/lists/oss-security/2014/01/21/3', 'http://www.openwall.com/lists/oss-security/2014/01/21/4'} | null |
PyPI | PYSEC-2020-30 | null | A buffer overflow in the patching routine of bsdiff4 before 1.2.0 allows an attacker to write to heap memory (beyond allocated bounds) via a crafted patch file. | {'CVE-2020-15904'} | 2020-07-31T16:15:00Z | 2020-07-22T23:15:00Z | null | null | null | {'https://github.com/ilanschnell/bsdiff4/commit/49a4cee2feef7deaf9d89e5e793a8824930284d7', 'https://github.com/ilanschnell/bsdiff4/blob/master/CHANGELOG.txt'} | null |
PyPI | PYSEC-2013-29 | null | The Crypto.Random.atfork function in PyCrypto before 2.6.1 does not properly reseed the pseudo-random number generator (PRNG) before allowing a child process to access it, which makes it easier for context-dependent attackers to obtain sensitive information by leveraging a race condition in which a child process is created and accesses the PRNG within the same rate-limit period as another process. | {'CVE-2013-1445'} | 2021-08-27T03:22:16.634811Z | 2013-10-26T17:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2013/10/17/3', 'https://github.com/dlitz/pycrypto/commit/19dcf7b15d61b7dc1a125a367151de40df6ef175', 'http://www.debian.org/security/2013/dsa-2781'} | null |
PyPI | PYSEC-2011-14 | null | Cross-site scripting (XSS) vulnerability in Plone 4.1 and earlier allows remote attackers to inject arbitrary web script or HTML via a crafted URL. | {'CVE-2011-1948'} | 2021-07-25T23:34:43.114497Z | 2011-06-06T19:55:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/67693', 'http://secunia.com/advisories/44776', 'http://plone.org/products/plone/security/advisories/CVE-2011-1948', 'http://secunia.com/advisories/44775', 'http://osvdb.org/72727', 'http://securityreason.com/securityalert/8269', 'http://www.securityfocus.com/archive/1/518155/100/0/threaded', 'http://www.securityfocus.com/bid/48005'} | null |
PyPI | GHSA-hhx9-p69v-cx2j | Authentication bypass in Apache Airflow | "The previous default setting for Airflow's Experimental API was to allow all API requests without authentication, but this poses security risks to users who miss this fact. From Airflow 1.10.11 the default has been changed to deny all requests by default and is documented at https://airflow.apache.org/docs/1.10.11/security.html#api-authentication. Note this change fixes it for new installs but existing users need to change their config to default `[api]auth_backend = airflow.api.auth.backend.deny_all` as mentioned in the Updating Guide: https://github.com/apache/airflow/blob/1.10.11/UPDATING.md#experimental-api-will-deny-all-request-by-default" | {'CVE-2020-13927'} | 2022-03-03T05:13:29.653716Z | 2021-04-30T17:34:13Z | CRITICAL | null | {'CWE-287'} | {'http://packetstormsecurity.com/files/162908/Apache-Airflow-1.10.10-Remote-Code-Execution.html', 'https://github.com/apache/airflow/pull/9611/commits/c8053e166d45ad519c0a1cd4480e025a759c176e', 'https://nvd.nist.gov/vuln/detail/CVE-2020-13927', 'https://airflow.apache.org/docs/apache-airflow/1.10.11/security.html#api-authentication', 'https://lists.apache.org/thread.html/r23a81b247aa346ff193670be565b2b8ea4b17ddbc7a35fc099c1aadd%40%3Cdev.airflow.apache.org%3E', 'https://github.com/apache/airflow/releases/tag/1.10.11'} | null |
PyPI | PYSEC-2021-717 | null | TensorFlow is an end-to-end open source platform for machine learning. TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls. For example, the `While` implementation(https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space. 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. Please consult our security guide(https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2021-29591', 'GHSA-cwv3-863g-39vx'} | 2021-12-09T06:35:30.563708Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4', 'https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx'} | null |
PyPI | PYSEC-2021-347 | null | Cross Site Scripting (XSS) in Simiki v1.6.2.1 and prior allows remote attackers to execute arbitrary code via line 54 of the component 'simiki/blob/master/simiki/generators.py'. | {'GHSA-fqr5-qphf-vfr8', 'CVE-2020-19000'} | 2021-09-26T23:33:04.295133Z | 2021-08-27T19:15:00Z | null | null | null | {'https://github.com/tankywoo/simiki/issues/123', 'https://github.com/advisories/GHSA-fqr5-qphf-vfr8'} | null |
PyPI | PYSEC-2015-1 | null | Ansible before 1.9.2 does not verify that the server hostname matches a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate, which allows man-in-the-middle attackers to spoof SSL servers via an arbitrary valid certificate. | {'CVE-2015-3908', 'GHSA-w64c-pxjj-h866'} | 2021-07-02T02:41:33.423322Z | 2015-08-12T14:59:00Z | null | null | null | {'http://www.ansible.com/security', 'http://lists.opensuse.org/opensuse-updates/2015-08/msg00029.html', 'http://www.openwall.com/lists/oss-security/2015/07/14/4', 'http://lists.opensuse.org/opensuse-updates/2015-07/msg00051.html', 'https://lists.debian.org/debian-lts-announce/2019/09/msg00016.html', 'https://github.com/advisories/GHSA-w64c-pxjj-h866'} | null |
PyPI | PYSEC-2017-85 | null | txAWS (all current versions) fail to perform complete certificate verification resulting in vulnerability to MitM attacks and information disclosure. | {'CVE-2017-1000007'} | 2021-08-25T04:30:35.998894Z | 2017-07-17T13:18:00Z | null | null | null | {'https://github.com/twisted/txaws/issues/24'} | null |
PyPI | GHSA-8w54-22w9-3g8f | Cross-site Scripting and Open Redirect in Products.CMFPlone | ### Impact
Plone is vulnerable to reflected cross site scripting and open redirect when an attacker can get a compromised version of the image_view_fullscreen page in a cache, for example in Varnish.
The technique is known as cache poisoning.
Any later visitor can get redirected when clicking on a link on this page.
Usually only anonymous users are affected, but this depends on your cache settings.
### Patches
No patch is available for the Products.CMFPlone 4 series.
Versions 5.0 and higher are not affected, but two other packages used by these versions are affected.
`plone.app.contenttypes` has the same problem in all versions, see [advisory](https://github.com/plone/plone.app.contenttypes/security/advisories/GHSA-f7qw-5fgj-247x).
In Plone 5.0-5.2, the default Products.ATContentTypes version has the same problem. See [advisory](https://github.com/plone/Products.ATContentTypes/security/advisories/GHSA-g4c2-ghfg-g5rh).
Plone 5.2.7 and 6.0.0a3 will be released today and will include these fixes.
For all unpatched versions of the three packages, you can use the following workaround.
### Workaround
Make sure the image_view_fullscreen page is not stored in the cache.
In Plone:
* Login as Manager and go to Site Setup.
* Go to the 'Caching' control panel. If this does not exist, or 'Enable caching' is not checked, you should normally not be vulnerable.
* Click on the tab 'Caching operations'.
* Under 'Legacy template mappings' locate the ruleset 'Content item view'.
* From the last column ('Templates') remove 'image_view_fullscreen'.
* Click on Save.
### Reporter
This vulnerability was responsibly disclosed to the Plone Security Team by Gustav Hansen, F-Secure Consulting. Thank you!
### For more information
If you have any questions or comments about this advisory, email us at [security@plone.org](mailto:security@plone.org)
This is also the correct address to use when you want to report a possible vulnerability.
See [our security report policy](https://plone.org/security/report). | null | 2022-03-03T05:11:31.068352Z | 2022-01-28T23:10:40Z | MODERATE | null | {'CWE-79'} | {'https://github.com/plone/Products.CMFPlone/security/advisories/GHSA-8w54-22w9-3g8f', 'https://github.com/plone/Products.CMFPlone'} | null |
PyPI | GHSA-mpvw-25mg-59vx | Server-side Request Forgery (SSRF) via img tags in reportlab | All versions of package reportlab at time of writing are vulnerable to Server-side Request Forgery (SSRF) via img tags. In order to reduce risk, use trustedSchemes & trustedHosts (see in Reportlab's documentation) Steps to reproduce by Karan Bamal: 1. Download and install the latest package of reportlab 2. Go to demos -> odyssey -> dodyssey 3. In the text file odyssey.txt that needs to be converted to pdf inject <img src="http://127.0.0.1:5000" valign="top"/> 4. Create a nc listener nc -lp 5000 5. Run python3 dodyssey.py 6. You will get a hit on your nc showing we have successfully proceded to send a server side request 7. dodyssey.py will show error since there is no img file on the url, but we are able to do SSRF | {'CVE-2020-28463'} | 2022-03-03T05:13:54.876123Z | 2021-03-29T16:32:27Z | MODERATE | null | {'CWE-918'} | {'https://hg.reportlab.com/hg-public/reportlab', 'https://www.reportlab.com/docs/reportlab-userguide.pdf', 'https://hg.reportlab.com/hg-public/reportlab/rev/7f2231703dc7', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YZQSFCID67K6BTC655EQY6MNOF35QI44/', 'https://bugzilla.redhat.com/show_bug.cgi?id=1930417', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HMUJA5GZTPQ5WRYUCCK2GEZM4W43N7HH/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-28463', 'https://snyk.io/vuln/SNYK-PYTHON-REPORTLAB-1022145', 'https://hg.reportlab.com/hg-public/reportlab/file/f094d273903a/CHANGES.md#l71'} | null |
PyPI | GHSA-4p4p-www8-8fv9 | Reference binding to null in `ParameterizedTruncatedNormal` | ### Impact
An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`:
```python
import tensorflow as tf
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
tf.raw_ops.ParameterizedTruncatedNormal(
shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`:
```cc
int32 num_batches = shape_tensor.flat<int32>()(0);
```
If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array.
### Patches
We have patched the issue in GitHub commit [5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8](https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8).
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-2021-29568'} | 2022-03-03T05:12:41.657056Z | 2021-05-21T14:25:19Z | LOW | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4p4p-www8-8fv9', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29568', 'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} | null |
PyPI | PYSEC-2020-202 | null | Ansible before 1.5.5 constructs filenames containing user and password fields on the basis of deb lines in sources.list, which might allow local users to obtain sensitive credential information in opportunistic circumstances by leveraging existence of a file that uses the "deb http://user:pass@server:port/" format. | {'CVE-2014-4660'} | 2021-07-02T02:41:33.239912Z | 2020-02-20T03:15:00Z | null | null | null | {'https://github.com/ansible/ansible/commit/c4b5e46054c74176b2446c82d4df1a2610eddc08', 'https://security-tracker.debian.org/tracker/CVE-2014-4660', 'https://github.com/ansible/ansible/blob/release1.5.5/CHANGELOG.md', 'https://www.securityfocus.com/bid/68231', 'https://www.openwall.com/lists/oss-security/2014/06/26/19'} | null |
PyPI | PYSEC-2021-652 | 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.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-4vf2-4xcg-65cx', 'CVE-2021-29526'} | 2021-12-09T06:35:19.249421Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4vf2-4xcg-65cx', 'https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b'} | null |
PyPI | PYSEC-2021-202 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. 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-r6pg-pjwc-j585', 'CVE-2021-29565'} | 2021-08-27T03:22:32.984830Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6pg-pjwc-j585', 'https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f'} | null |
PyPI | PYSEC-2016-10 | null | The verify function in the RSA package for Python (Python-RSA) before 3.3 allows attackers to spoof signatures with a small public exponent via crafted signature padding, aka a BERserk attack. | {'CVE-2016-1494'} | 2021-07-05T00:01:25.929299Z | 2016-01-13T15:59:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2016/01/05/3', 'http://www.securityfocus.com/bid/79829', 'http://www.openwall.com/lists/oss-security/2016/01/05/1', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-January/175897.html', 'https://blog.filippo.io/bleichenbacher-06-signature-forgery-in-python-rsa/', 'https://bitbucket.org/sybren/python-rsa/pull-requests/14/security-fix-bb06-attack-in-verify-by/diff', 'http://lists.opensuse.org/opensuse-updates/2016-01/msg00032.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-January/175942.html'} | null |
PyPI | GHSA-2ww3-fxvq-293j | Inefficient Regular Expression in nltk | nltk is contains an Inefficient Regular Expression and is vulnerable to regular expression denial of service attacks. | {'CVE-2021-3828'} | 2022-04-26T18:17:15.373864Z | 2021-09-29T17:14:53Z | HIGH | null | {'CWE-697', 'CWE-1333'} | {'https://github.com/nltk/nltk/commit/277711ab1dec729e626b27aab6fa35ea5efbd7e6', 'https://nvd.nist.gov/vuln/detail/CVE-2021-3828', 'https://github.com/nltk/nltk/pull/2816', 'https://huntr.dev/bounties/d19aed43-75bc-4a03-91a0-4d0bb516bc32', 'https://github.com/nltk/nltk'} | null |
PyPI | PYSEC-2021-486 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. 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-mqh2-9wrp-vx84', 'CVE-2021-29558'} | 2021-12-09T06:34:52.373382Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84', 'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} | null |
PyPI | GHSA-m34j-p8rj-wjxq | Division by 0 in `QuantizedBiasAdd` | ### Impact
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
bias = tf.constant([], shape=[0], dtype=tf.quint8)
min_input = tf.constant(-10.0, dtype=tf.float32)
max_input = tf.constant(-10.0, dtype=tf.float32)
min_bias = tf.constant(-10.0, dtype=tf.float32)
max_bias = tf.constant(-10.0, dtype=tf.float32)
tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input,
max_input=max_input, min_bias=min_bias,
max_bias=max_bias, out_type=tf.qint32)
```
This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero:
```cc
template <typename T1, typename T2, typename T3>
void QuantizedAddUsingEigen(const Eigen::ThreadPoolDevice& device,
const Tensor& input, float input_min,
float input_max, const Tensor& smaller_input,
float smaller_input_min, float smaller_input_max,
Tensor* output, float* output_min,
float* output_max) {
...
const int64 input_element_count = input.NumElements();
const int64 smaller_input_element_count = smaller_input.NumElements();
...
bcast[0] = input_element_count / smaller_input_element_count;
...
}
```
This integral division by 0 is undefined behavior.
### Patches
We have patched the issue in GitHub commit [67784700869470d65d5f2ef20aeb5e97c31673cb](https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb).
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-2021-29546'} | 2022-03-03T05:13:15.068960Z | 2021-05-21T14:23:28Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29546', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq', 'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | null |
PyPI | PYSEC-2020-88 | null | SQL Injection in DTML or in connection objects in Plone 4.0 through 5.2.1 allows users to perform unwanted SQL queries. (This is a problem in Zope.) | {'CVE-2020-7939'} | 2020-01-24T23:00:00Z | 2020-01-23T21:15:00Z | null | null | null | {'https://plone.org/security/hotfix/20200121', 'https://www.openwall.com/lists/oss-security/2020/01/22/1', 'http://www.openwall.com/lists/oss-security/2020/01/24/1', 'https://plone.org/security/hotfix/20200121/sql-injection-in-dtml-or-in-connection-objects'} | null |
PyPI | GHSA-fh37-cx83-q542 | Improper Authentication in Apache Airflow | The lineage endpoint of the deprecated Experimental API was not protected by authentication in Airflow 2.0.0. This allowed unauthenticated users to hit that endpoint. This is low-severity issue as the attacker needs to be aware of certain parameters to pass to that endpoint and even after can just get some metadata about a DAG and a Task. This issue only affects Apache Airflow 2.0.0. | {'CVE-2021-26697'} | 2022-03-03T05:12:19.674223Z | 2021-06-18T18:30:11Z | MODERATE | null | {'CWE-287', 'CWE-269'} | {'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cdev.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519%40%3Cusers.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/r36111262a59219a3e2704c71e97cf84937dae5ba7a1da99499e5d8f9@%3Cannounce.apache.org%3E', 'https://github.com/apache/airflow/commit/21cedff205e7d62675949fda2aa4616d77232b76', 'https://nvd.nist.gov/vuln/detail/CVE-2021-26697', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cusers.airflow.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2021/02/17/2'} | null |
PyPI | PYSEC-2020-67 | null | The cache action in action/cache.py in MoinMoin through 1.9.10 allows directory traversal through a crafted HTTP request. An attacker who can upload attachments to the wiki can use this to achieve remote code execution. | {'CVE-2020-25074', 'GHSA-52q8-877j-gghq'} | 2020-11-24T17:20:00Z | 2020-11-10T17:15:00Z | null | null | null | {'https://github.com/moinwiki/moin-1.9/security/advisories/GHSA-52q8-877j-gghq', 'http://moinmo.in/SecurityFixes', 'https://lists.debian.org/debian-lts-announce/2020/11/msg00020.html', 'https://www.debian.org/security/2020/dsa-4787'} | null |
PyPI | PYSEC-2021-469 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in `ngrams_data`(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size. Later writes to the output tensor would then cause a null pointer dereference. 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-2021-29541', 'GHSA-xqfj-35wv-m3cr'} | 2021-12-09T06:34:49.747683Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-35wv-m3cr'} | null |
PyPI | PYSEC-2021-193 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-fxqh-cfjm-fp93', 'CVE-2021-29556'} | 2021-08-27T03:22:31.368222Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxqh-cfjm-fp93', 'https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1'} | null |
PyPI | GHSA-xqfj-35wv-m3cr | Null pointer dereference in `StringNGrams` | ### Impact
An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`:
```python
import tensorflow as tf
data=tf.constant([''] * 11, shape=[11], dtype=tf.string)
splits = [0]*115
splits.append(3)
data_splits=tf.constant(splits, shape=[116], dtype=tf.int64)
tf.raw_ops.StringNGrams(data=data, data_splits=data_splits, separator=b'Ss',
ngram_widths=[7,6,11],
left_pad='ABCDE', right_pad=b'ZYXWVU',
pad_width=50, preserve_short_sequences=True)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in [`ngrams_data`](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size.
Later writes to the output tensor would then cause a null pointer dereference.
### Patches
We have patched the issue in GitHub commit [ba424dd8f16f7110eea526a8086f1a155f14f22b](https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b).
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-2021-29541'} | 2022-03-03T05:13:08.273193Z | 2021-05-21T14:23:12Z | LOW | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-35wv-m3cr', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29541'} | null |
PyPI | PYSEC-2022-175 | null | Insecure Temporary File in GitHub repository horovod/horovod prior to 0.24.0. | {'CVE-2022-0315', 'GHSA-47wv-vhj2-g66m'} | 2022-03-31T20:31:44.168006Z | 2022-03-24T09:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-47wv-vhj2-g66m', 'https://huntr.dev/bounties/7e50397b-dd63-4bb5-b56d-704094a7da45', 'https://github.com/horovod/horovod/commit/b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41'} | null |
PyPI | PYSEC-2019-213 | null | The unoconv package before 0.9 mishandles untrusted pathnames, leading to SSRF and local file inclusion. | {'GHSA-27p5-7cw6-m45h', 'CVE-2019-17400'} | 2021-08-27T03:22:49.773623Z | 2019-10-21T23:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-27p5-7cw6-m45h', 'https://buer.haus/2019/10/18/a-tale-of-exploitation-in-spreadsheet-file-conversions/', 'https://github.com/unoconv/unoconv/pull/510'} | null |
PyPI | GHSA-63rq-p8fp-524q | Potential API key leak | If a user is actively blackholing the location or weather APIs, or those APIs become otherwise unavailable, it is possible for the API keys to get leaked to the active IRC channel.
This is patched in v1.2.4 | null | 2022-03-03T05:11:58.131675Z | 2021-04-13T15:12:06Z | MODERATE | null | {'CWE-200'} | {'https://github.com/sopel-irc/sopel-weather/security/advisories/GHSA-63rq-p8fp-524q'} | null |
PyPI | PYSEC-2020-310 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. 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. | {'GHSA-63xm-rx5p-xvqr', 'CVE-2020-15195'} | 2021-12-09T06:35:12.907152Z | 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-63xm-rx5p-xvqr'} | null |
PyPI | PYSEC-2011-6 | null | Cross-site scripting (XSS) vulnerability in the reStructuredText (rst) parser in parser/text_rst.py in MoinMoin before 1.9.3, when docutils is installed or when "format rst" is set, allows remote attackers to inject arbitrary web script or HTML via a javascript: URL in the refuri attribute. NOTE: some of these details are obtained from third party information. | {'CVE-2011-1058'} | 2021-07-05T00:01:22.907058Z | 2011-02-22T18:00:00Z | null | null | null | {'http://www.debian.org/security/2011/dsa-2321', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-March/055116.html', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/65545', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-March/054544.html', 'http://www.vupen.com/english/advisories/2011/0455', 'http://secunia.com/advisories/43413', 'http://www.vupen.com/english/advisories/2011/0588', 'http://www.vupen.com/english/advisories/2011/0571', 'http://secunia.com/advisories/50885', 'http://moinmo.in/SecurityFixes', 'http://www.securityfocus.com/bid/46476', 'http://www.ubuntu.com/usn/USN-1604-1', 'http://lists.fedoraproject.org/pipermail/package-announce/2011-March/055124.html', 'http://secunia.com/advisories/43665'} | null |
PyPI | PYSEC-2019-23 | null | All versions of the HTTPie package prior to version 1.0.3 are vulnerable to Open Redirect that allows an attacker to write an arbitrary file with supplied filename and content to the current directory, by redirecting a request from HTTP to a crafted URL pointing to a server in his or hers control. | {'GHSA-xjjg-vmw6-c2p9', 'CVE-2019-10751', 'SNYK-PYTHON-HTTPIE-460107'} | 2019-09-02T18:15:00Z | 2019-08-23T17:15:00Z | null | null | null | {'https://snyk.io/vuln/SNYK-PYTHON-HTTPIE-460107', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00003.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00022.html', 'https://github.com/advisories/GHSA-xjjg-vmw6-c2p9', 'https://github.com/jakubroztocil/httpie/releases/tag/1.0.3', 'https://lists.debian.org/debian-lts-announce/2019/09/msg00031.html'} | null |
PyPI | PYSEC-2021-310 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vcjj-9vg7-vf68', 'CVE-2021-37688'} | 2021-08-27T03:22:47.519318Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vcjj-9vg7-vf68'} | null |
PyPI | PYSEC-2018-5 | null | An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. The django.utils.html.urlize() function was extremely slow to evaluate certain inputs due to catastrophic backtracking vulnerabilities in two regular expressions (only one regular expression for Django 1.8.x). The urlize() function is used to implement the urlize and urlizetrunc template filters, which were thus vulnerable. | {'CVE-2018-7536', 'GHSA-r28v-mw67-m5p9'} | 2021-06-16T00:03:23.200365Z | 2018-03-09T20:29:00Z | null | null | null | {'https://www.djangoproject.com/weblog/2018/mar/06/security-releases/', 'http://www.securityfocus.com/bid/103361', 'https://access.redhat.com/errata/RHSA-2019:0051', 'https://access.redhat.com/errata/RHSA-2018:2927', 'https://www.debian.org/security/2018/dsa-4161', 'https://lists.debian.org/debian-lts-announce/2018/03/msg00006.html', 'https://access.redhat.com/errata/RHSA-2019:0265', 'https://github.com/advisories/GHSA-r28v-mw67-m5p9', 'https://access.redhat.com/errata/RHSA-2019:0082', 'https://usn.ubuntu.com/3591-1/'} | null |
PyPI | PYSEC-2021-740 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. 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-8pmx-p244-g88h', 'CVE-2021-29614'} | 2021-12-09T06:35:34.396130Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h', 'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d'} | null |
PyPI | GHSA-374m-jm66-3vj8 | Heap OOB in `SparseBinCount` | ### Impact
The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/bincount_op.cc#L353-L417) of `SparseBinCount` is vulnerable to a heap OOB:
```python
import tensorflow as tf
tf.raw_ops.SparseBincount(
indices=[[0],[1],[2]]
values=[0,-10000000]
dense_shape=[1,1]
size=[1]
weights=[3,2,1]
binary_output=False)
```
This is because of missing validation between the elements of the `values` argument and the shape of the sparse output:
```cc
for (int64_t i = 0; i < indices_mat.dimension(0); ++i) {
const int64_t batch = indices_mat(i, 0);
const Tidx bin = values(i);
...
out(batch, bin) = ...;
}
```
### Patches
We have patched the issue in GitHub commit [f410212e373eb2aec4c9e60bf3702eba99a38aba](https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41226'} | 2022-03-03T05:14:12.215771Z | 2021-11-10T18:41:47Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41226', 'https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-374m-jm66-3vj8'} | null |
PyPI | GHSA-gfp2-w5jm-955q | OMERO.web exposes some unnecessary session information in the page | ### Background
OMERO.web loads various information about the current user such as their id, name and the groups they are in, and these are available on the main webclient pages. Some additional information being loaded is not used by the webclient and is being removed in this release.
### Impact
OMERO.web before 5.9.0
### Patches
5.9.0
### Workarounds
No workaround
### References
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [omero-web](https://github.com/ome/omero-web)
* Email us at [security](mailto:security@openmicroscopy.org.uk) | {'CVE-2021-21376'} | 2022-03-03T05:13:29.883008Z | 2021-03-23T15:26:34Z | MODERATE | null | {'CWE-200'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-21376', 'https://github.com/ome/omero-web/commit/952f8e5d28532fbb14fb665982211329d137908c', 'https://pypi.org/project/omero-web/', 'https://github.com/ome/omero-web/security/advisories/GHSA-gfp2-w5jm-955q', 'https://www.openmicroscopy.org/security/advisories/2021-SV1/', 'https://github.com/ome/omero-web/blob/master/CHANGELOG.md#590-march-2021'} | null |
PyPI | PYSEC-2021-255 | null | TensorFlow is an end-to-end open source platform for machine learning. Passing a complex argument to `tf.transpose` at the same time as passing `conjugate=True` argument results in a crash. 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-xqfj-cr6q-pc8w', 'CVE-2021-29618'} | 2021-08-27T03:22:42.358462Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/issues/46973', 'https://github.com/tensorflow/issues/42105', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-cr6q-pc8w', 'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88'} | null |
PyPI | GHSA-9crf-c6qr-r273 | Integer division by 0 in `tf.raw_ops.AllToAll` | ### Impact
The [shape inference code for `AllToAll`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/tpu_cross_replica_ops.cc#L25-L74) can be made to execute a division by 0:
```python
import tensorflow as tf
@tf.function
def func():
return tf.raw_ops.AllToAll(
input=[0.0, 0.1652, 0.6543],
group_assignment=[1, -1],
concat_dimension=0,
split_dimension=0,
split_count=0)
func()
```
This occurs whenever the `split_count` argument is 0:
```cc
TF_RETURN_IF_ERROR(c->GetAttr("split_count", &split_count));
...
for (int32_t i = 0; i < rank; ++i) {
...
dims[i] = c->MakeDim(c->Value(dims[i]) / split_count);
...
}
```
### Patches
We have patched the issue in GitHub commit [a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc](https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41218'} | 2022-03-03T05:13:16.433441Z | 2021-11-10T18:52:24Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41218'} | null |
PyPI | PYSEC-2021-605 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version. | {'CVE-2021-37692', 'GHSA-cmgw-8vpc-rc59'} | 2021-12-09T06:35:06.839358Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cmgw-8vpc-rc59', 'https://github.com/tensorflow/tensorflow/pull/50508'} | null |
PyPI | PYSEC-2020-255 | null | In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area. If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault. This is because the allocator used to return the buffer data is not marked as returning an opaque handle since the needed virtual method is not overridden. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0. | {'CVE-2020-26268', 'GHSA-hhvc-g5hv-48c6'} | 2021-08-27T03:22:22.907995Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6'} | null |
PyPI | PYSEC-2017-102 | null | Radicale before 1.1.2 and 2.x before 2.0.0rc2 is prone to timing oracles and simple brute-force attacks when using the htpasswd authentication method. | {'CVE-2017-8342'} | 2021-12-14T08:18:58.722697Z | 2017-04-30T15:59:00Z | null | null | null | {'https://github.com/Kozea/Radicale/blob/1.1.2/NEWS.rst', 'https://github.com/Kozea/Radicale/commit/190b1dd795f0c552a4992445a231da760211183b', 'https://lists.debian.org/debian-lts-announce/2020/04/msg00019.html', 'https://pypi.org/project/radicale', 'https://nvd.nist.gov/vuln/detail/CVE-2017-8342', 'https://bugs.debian.org/861514', 'https://github.com/Kozea/Radicale/commit/059ba8dec1f22ccbeab837e288b3833a099cee2d'} | null |
PyPI | GHSA-v542-8q9x-cffc | Exposure of Sensitive Information to an Unauthorized Actor | Django Channels 3.x before 3.0.3 allows remote attackers to obtain sensitive information from a different request scope. The legacy channels.http.AsgiHandler class, used for handling HTTP type requests in an ASGI environment prior to Django 3.0, did not correctly separate request scopes in Channels 3.0. In many cases this would result in a crash but, with correct timing, responses could be sent to the wrong client, resulting in potential leakage of session identifiers and other sensitive data. Note that this affects only the legacy Channels provided class, and not Django's similar ASGIHandler, available from Django 3.0. | {'CVE-2020-35681'} | 2022-03-03T05:13:58.617865Z | 2021-03-19T21:29:02Z | HIGH | null | {'CWE-200'} | {'https://github.com/django/channels/commit/e85874d9630474986a6937430eac52db79a2a022', 'https://nvd.nist.gov/vuln/detail/CVE-2020-35681', 'https://github.com/django/channels/releases', 'https://channels.readthedocs.io/en/stable/releases/3.0.3.html', 'https://channels.readthedocs.io/en/stable/releases/index.html'} | null |
PyPI | GHSA-9px9-73fg-3fqp | Null pointer dereference in Grappler's `IsConstant` | ### Impact
Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place):
First, during [constant folding](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L3466-L3497), the `GraphDef` might not have the required nodes for the binary operation:
```cc
NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
// One child must be constant, and the second must be Conv op.
const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
const bool right_child_is_constant = IsReallyConstant(*mul_right_child);
```
If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect.
We have a similar issue during [`IsIdentityConsumingSwitch`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/mutable_graph_view.cc#L59-L74):
```cc
NodeDef* input_node = graph.GetNode(tensor_id.node());
return IsSwitch(*input_node);
```
### Patches
We have patched the issue in GitHub commits [0a365c029e437be0349c31f8d4c9926b69fa3fa1](https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1) and [045deec1cbdebb27d817008ad5df94d96a08b1bf](https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23589'} | 2022-03-03T05:13:46.368917Z | 2022-02-09T23:29:14Z | MODERATE | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L3466-L3497', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/mutable_graph_view.cc#L59-L74', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23589', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9px9-73fg-3fqp', 'https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1', 'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf'} | null |
PyPI | GHSA-qw5h-7f53-xrp6 | Stack overflow in `ParseAttrValue` with nested tensors | ### Impact
The implementation of [`ParseAttrValue`](https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/framework/attr_value_util.cc#L397-L453) can be tricked into stack overflow due to recursion by giving in a specially crafted input.
### Patches
We have patched the issue in GitHub commit [e07e1c3d26492c06f078c7e5bf2d138043e199c1](https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1).
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. | {'CVE-2021-29615'} | 2022-03-03T05:13:40.155128Z | 2021-05-21T14:28:45Z | LOW | null | {'CWE-674'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qw5h-7f53-xrp6', 'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29615'} | null |
PyPI | PYSEC-2020-222 | null | While investigating a bug report on Apache Superset, it was determined that an authenticated user could craft requests via a number of templated text fields in the product that would allow arbitrary access to Python’s `os` package in the web application process in versions < 0.37.1. It was thus possible for an authenticated user to list and access files, environment variables, and process information. Additionally it was possible to set environment variables for the current process, create and update files in folders writable by the web process, and execute arbitrary programs accessible by the web process. All other operations available to the `os` package in Python were also available, even if not explicitly enumerated in this CVE. | {'CVE-2020-13948'} | 2021-08-27T03:21:55.635305Z | 2020-09-17T13:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/r0e35c7c5672a6146b962840be5c1a7b7461c05a71cd7ecc62774d155@%3Cnotifications.superset.apache.org%3E', 'https://lists.apache.org/thread.html/r4fc7115f6e63ac255c48fc68c0da592df55fe4be47cae6378d39ac22@%3Cnotifications.superset.apache.org%3E', 'https://lists.apache.org/thread.html/rdeee068ac1e0c43bd5b69830240f30598df15a2ef9f7998c7b29131e%40%3Cdev.superset.apache.org%3E'} | null |
PyPI | GHSA-6g87-ff9q-v847 | High severity vulnerability that affects websockets | The Python websockets library version 4 contains a CWE-409: Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Servers and clients, unless configured with compression=None that can result in Denial of Service by memory exhaustion. This attack appears to be exploitable via sending a specially crafted frame on an established connection. This vulnerability appears to have been fixed in version 5.0 | {'CVE-2018-1000518'} | 2022-03-07T20:47:15.392818Z | 2018-09-17T20:46:52Z | HIGH | null | {'CWE-400'} | {'https://github.com/aaugustin/websockets/pull/407', 'https://github.com/aaugustin/websockets', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000518', 'https://github.com/advisories/GHSA-6g87-ff9q-v847'} | null |
PyPI | PYSEC-2021-672 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29546', 'GHSA-m34j-p8rj-wjxq'} | 2021-12-09T06:35:22.808181Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq', 'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | null |
PyPI | PYSEC-2021-388 | null | 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', 'GHSA-v899-28g4-qmh8'} | 2021-11-11T13:06:47.875432Z | 2021-10-31T20:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-v899-28g4-qmh8', 'https://github.com/darkfoxprime/python-easy_xml/issues/1'} | null |
PyPI | PYSEC-2021-222 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mv78-g7wq-mhp4', 'CVE-2021-29585'} | 2021-08-27T03:22:36.517027Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mv78-g7wq-mhp4', 'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948'} | null |
PyPI | PYSEC-2021-737 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. The implementation(https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments specify a valid sparse tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions. | {'GHSA-9rpc-5v9q-5r7f', 'CVE-2021-29611'} | 2021-12-09T06:35:33.881511Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9rpc-5v9q-5r7f'} | null |
PyPI | PYSEC-2022-102 | null | Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version. | {'GHSA-gwcx-jrx4-92w2', 'CVE-2022-23593'} | 2022-03-09T00:17:36.413722Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a', 'https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gwcx-jrx4-92w2'} | null |
PyPI | PYSEC-2020-10 | null | A flaw was found in Ansible Engine when the module package or service is used and the parameter 'use' is not specified. If a previous task is executed with a malicious user, the module sent can be selected by the attacker using the ansible facts file. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1738', 'GHSA-f85h-23mf-2fwh'} | 2020-06-13T04:15:00Z | 2020-03-16T16:15:00Z | null | null | null | {'https://github.com/ansible/ansible/issues/67796', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1738', 'https://github.com/advisories/GHSA-f85h-23mf-2fwh', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2018-96 | null | Py-EVM v0.2.0-alpha.33 allows attackers to make a vm.execute_bytecode call that triggers computation._stack.values with '"stack": [100, 100, 0]' where b'\x' was expected, resulting in an execution failure because of an invalid opcode. This is reportedly related to "smart contracts can be executed indefinitely without gas being paid." | {'GHSA-vqgp-4jgj-5j64', 'CVE-2018-18920'} | 2021-08-27T03:22:16.474976Z | 2018-11-12T02:29:00Z | null | null | null | {'https://www.reddit.com/r/ethereum/comments/9vkk2g/netta_labs_claim_to_have_found_a_vulnerability_in/e9d3wyx/', 'https://github.com/advisories/GHSA-vqgp-4jgj-5j64', 'https://twitter.com/NettaLab/status/1060889400102383617', 'https://twitter.com/AlexanderFisher/status/1060923428641878019', 'https://github.com/ethereum/py-evm/issues/1448'} | null |
PyPI | PYSEC-2016-8 | null | Pillow before 3.3.2 allows context-dependent attackers to obtain sensitive information by using the "crafted image file" approach, related to an "Integer Overflow" issue affecting the Image.core.map_buffer in map.c component. | {'GHSA-rwr3-c2q8-gm56', 'CVE-2016-9189'} | 2021-07-05T00:01:24.104078Z | 2016-11-04T10:59:00Z | null | null | null | {'https://github.com/python-pillow/Pillow/issues/2105', 'http://www.securityfocus.com/bid/94234', 'http://pillow.readthedocs.io/en/3.4.x/releasenotes/3.3.2.html', 'https://github.com/advisories/GHSA-rwr3-c2q8-gm56', 'https://security.gentoo.org/glsa/201612-52', 'http://www.debian.org/security/2016/dsa-3710', 'https://github.com/python-pillow/Pillow/pull/2146/commits/c50ebe6459a131a1ea8ca531f10da616d3ceaa0f'} | null |
PyPI | GHSA-x95h-979x-cf3j | Policies not properly enforced in bluemonday | The bluemonday sanitizer before 1.0.16 for Go, and before 0.0.8 for Python (in pybluemonday), does not properly enforce policies associated with the SELECT, STYLE, and OPTION elements. | {'CVE-2021-42576'} | 2022-03-03T05:14:13.158012Z | 2021-10-19T20:15:30Z | MODERATE | null | {'CWE-20'} | {'https://docs.google.com/document/d/11SoX296sMS0XoQiQbpxc5pNxSdbJKDJkm5BDv0zrX50/', 'https://github.com/microcosm-cc/bluemonday', 'https://nvd.nist.gov/vuln/detail/CVE-2021-42576'} | null |
PyPI | PYSEC-2021-808 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.summary.create_file_writer` is called with non-scalar arguments code crashes due to a `CHECK`-fail. 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-gh8h-7j2j-qv4f', 'CVE-2021-41200'} | 2021-12-09T06:35:41.245758Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh8h-7j2j-qv4f', 'https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e', 'https://github.com/tensorflow/tensorflow/issues/46909'} | null |
PyPI | PYSEC-2010-19 | null | Cross-site scripting (XSS) vulnerability in PortalTransforms in Plone 2.1 through 3.3.4 before hotfix 20100612 allows remote attackers to inject arbitrary web script or HTML via the safe_html transform. | {'CVE-2010-2422'} | 2021-07-16T01:31:27.252837Z | 2010-06-24T12:17:00Z | null | null | null | {'http://www.securityfocus.com/bid/40999', 'http://secunia.com/advisories/40270', 'http://plone.org/products/plone/security/advisories/cve-2010-unassigned-html-injection-in-safe_html'} | null |
PyPI | PYSEC-2018-79 | null | aaugustin websockets version 4 contains a CWE-409: Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Servers and clients, unless configured with compression=None that can result in Denial of Service by memory exhaustion. This attack appear to be exploitable via Sending a specially crafted frame on an established connection. This vulnerability appears to have been fixed in 5. | {'GHSA-6g87-ff9q-v847', 'CVE-2018-1000518'} | 2021-08-25T04:30:36.925398Z | 2018-06-26T16:29:00Z | null | null | null | {'https://github.com/aaugustin/websockets/pull/407', 'https://github.com/advisories/GHSA-6g87-ff9q-v847'} | null |
PyPI | GHSA-x5h4-9gqw-942j | Improper Verification of Cryptographic Signature in aws-encryption-sdk | ### Impact
This advisory addresses several LOW severity issues with streaming signed messages and restricting processing of certain types of invalid messages.
This ESDK supports a streaming mode where callers may stream the plaintext of signed messages before the ECDSA signature is validated. In addition to these signatures, the ESDK uses AES-GCM encryption and all plaintext is verified before being released to a caller. There is no impact on the integrity of the ciphertext or decrypted plaintext, however some callers may rely on the the ECDSA signature for non-repudiation. Without validating the ECDSA signature, an actor with trusted KMS permissions to decrypt a message may also be able to encrypt messages. This update introduces a new API for callers who wish to stream only unsigned messages.
For customers who process ESDK messages from untrusted sources, this update also introduces a new configuration to limit the number of Encrypted Data Keys (EDKs) that the ESDK will attempt to process per message. This configuration provides customers with a way to limit the number of AWS KMS Decrypt API calls that the ESDK will make per message. This setting will reject messages with more EDKs than the configured limit.
Finally, this update adds early rejection of invalid messages with certain invalid combinations of algorithm suite and header data.
### Patches
Fixed in versions 1.9 and 2.2. We recommend that all users upgrade to address these issues.
Customers leveraging the ESDK’s streaming features have several options to protect signature validation. One is to ensure that client code reads to the end of the stream before using released plaintext. With this release, using the new API for streaming and falling back to the non-streaming decrypt API for signed messages prevents using any plaintext from signed data before the signature is validated. See https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x
Users processing ESDK messages from untrusted sources should use the new maximum encrypted data keys parameter. See https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x
### Workarounds
None
### For more information
https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/concepts.html#digital-sigs
https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x
| null | 2022-03-03T05:13:46.667926Z | 2021-06-01T21:17:53Z | MODERATE | null | {'CWE-347'} | {'https://github.com/aws/aws-encryption-sdk-python/security/advisories/GHSA-x5h4-9gqw-942j'} | null |
PyPI | PYSEC-2021-275 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-qjj8-32p7-h289', 'CVE-2021-37653'} | 2021-08-27T03:22:44.260808Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qjj8-32p7-h289', 'https://github.com/tensorflow/tensorflow/commit/ac117ee8a8ea57b73d34665cdf00ef3303bc0b11'} | null |
PyPI | GHSA-gf2j-f278-xh4v | Division by zero in TFLite | ### Impact
An attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75):
```cc
inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
const float* bias_data, int array_size,
float* array_data) {
// ...
TFLITE_DCHECK_EQ((array_size % bias_size), 0);
// ...
}
```
There is no check that the `bias_size` is non zero.
### Patches
We have patched the issue in GitHub commit [8c6f391a2282684a25cbfec7687bd5d35261a209](https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team. | {'CVE-2022-23557'} | 2022-03-03T05:13:58.557534Z | 2022-02-09T23:47:57Z | MODERATE | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23557', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75', 'https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-2j58-pwwv-x666 | Cross-Site Request Forgery in sqlite-web | This affects all versions of package sqlite-web. The SQL dashboard area allows sensitive actions to be performed without validating that the request originated from the application. This could enable an attacker to trick a user into performing these actions unknowingly through a Cross Site Request Forgery (CSRF) attack. | {'CVE-2021-23404'} | 2022-03-03T05:14:09.911233Z | 2021-09-09T17:10:35Z | HIGH | null | {'CWE-352'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-23404', 'https://github.com/coleifer/sqlite-web/blob/2e7c85da3d37f80074ed3ae39b5851069b4f301c/sqlite_web/__main__.py%23L1', 'https://github.com/coleifer/sqlite-web', 'https://snyk.io/vuln/SNYK-PYTHON-SQLITEWEB-1316324'} | null |
PyPI | GHSA-m4fw-77v7-924m | Moderate severity vulnerability that affects qutebrowser | qutebrowser version introduced in v0.11.0 (1179ee7a937fb31414d77d9970bac21095358449) contains a Cross Site Scripting (XSS) vulnerability in history command, qute://history page that can result in Via injected JavaScript code, a website can steal the user's browsing history. This attack appear to be exploitable via the victim must open a page with a specially crafted <title> attribute, and then open the qute://history site via the :history command. This vulnerability appears to have been fixed in fixed in v1.3.3 (4c9360237f186681b1e3f2a0f30c45161cf405c7, to be released today) and v1.4.0 (5a7869f2feaa346853d2a85413d6527c87ef0d9f, released later this week). | {'CVE-2018-1000559'} | 2022-03-03T05:14:14.678547Z | 2018-09-13T15:47:57Z | MODERATE | null | {'CWE-79'} | {'https://github.com/qutebrowser/qutebrowser', 'https://github.com/qutebrowser/qutebrowser/issues/4011', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000559', 'https://github.com/advisories/GHSA-m4fw-77v7-924m', 'https://github.com/qutebrowser/qutebrowser/commit/4c9360237f186681b1e3f2a0f30c45161cf405c7', 'https://github.com/qutebrowser/qutebrowser/commit/5a7869f2feaa346853d2a85413d6527c87ef0d9f'} | null |
PyPI | PYSEC-2021-625 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. 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-2021-41216', 'GHSA-3ff2-r28g-w7h9'} | 2021-12-09T06:35:09.827396Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3ff2-r28g-w7h9', 'https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14'} | null |
PyPI | GHSA-h4m5-qpfp-3mpv | Directory Traversal in Babel | Babel.Locale in Babel before 2.9.1 allows attackers to load arbitrary locale .dat files (containing serialized Python objects) via directory traversal, leading to code execution. | {'CVE-2021-42771'} | 2022-03-03T05:14:07.387626Z | 2021-10-21T17:49:59Z | HIGH | null | {'CWE-22'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-42771', 'https://www.debian.org/security/2021/dsa-5018', 'https://lists.debian.org/debian-lts/2021/10/msg00040.html', 'https://github.com/python-babel/babel/', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00018.html', 'https://www.tenable.com/security/research/tra-2021-14', 'https://github.com/python-babel/babel/pull/782'} | null |
PyPI | GHSA-pvhp-v9qp-xf5r | High severity vulnerability that affects django-piston and django-tastypie | emitters.py in Django Piston before 0.2.3 and 0.2.x before 0.2.2.1 does not properly deserialize YAML data, which allows remote attackers to execute arbitrary Python code via vectors related to the yaml.load method.
Django Tastypie has a very similar vulnerability. | {'CVE-2011-4103'} | 2022-03-03T05:13:25.942581Z | 2018-07-23T19:50:48Z | HIGH | null | {'CWE-20'} | {'http://www.openwall.com/lists/oss-security/2011/11/01/10', 'https://bitbucket.org/jespern/django-piston/commits/91bdaec89543/', 'https://bitbucket.org/jespern/django-piston', 'https://www.djangoproject.com/weblog/2011/nov/01/piston-and-tastypie-security-releases/', 'https://bugzilla.redhat.com/show_bug.cgi?id=750658', 'http://www.debian.org/security/2011/dsa-2344', 'https://nvd.nist.gov/vuln/detail/CVE-2011-4103', 'https://github.com/advisories/GHSA-pvhp-v9qp-xf5r'} | null |
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