ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2021-706 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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-2021-29580', 'GHSA-x8h6-xgqx-jqgp'} | 2021-12-09T06:35:28.532911Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp'} | null |
PyPI | GHSA-f58w-649r-qjr9 | Moderate severity vulnerability that affects splunk-sdk | Splunk-SDK-Python before 1.6.6 does not properly verify untrusted TLS server certificates, which could result in man-in-the-middle attacks. | {'CVE-2019-5729'} | 2022-03-03T05:14:07.996539Z | 2019-03-25T16:18:04Z | HIGH | null | {'CWE-295'} | {'https://github.com/advisories/GHSA-f58w-649r-qjr9', 'https://www.splunk.com/view/SP-CAAAQAD', 'https://nvd.nist.gov/vuln/detail/CVE-2019-5729'} | null |
PyPI | PYSEC-2020-213 | null | Tornado before 3.2.2 sends arbitrary responses that contain a fixed CSRF token and may be sent with HTTP compression, which makes it easier for remote attackers to conduct a BREACH attack and determine this token via a series of crafted requests. | {'CVE-2014-9720'} | 2021-07-05T00:01:27.333585Z | 2020-01-24T18:15:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=1222816', 'http://openwall.com/lists/oss-security/2015/05/19/4', 'https://bugzilla.novell.com/show_bug.cgi?id=930362', 'https://github.com/tornadoweb/tornado/commit/1c36307463b1e8affae100bf9386948e6c1b2308', 'http://www.tornadoweb.org/en/stable/releases/v3.2.2.html'} | null |
PyPI | PYSEC-2017-94 | null | Heap-based buffer overflow in the ALGnew function in block_templace.c in Python Cryptography Toolkit (aka pycrypto) allows remote attackers to execute arbitrary code as demonstrated by a crafted iv parameter to cryptmsg.py. | {'GHSA-cq27-v7xp-c356', 'CVE-2013-7459'} | 2021-08-27T03:22:16.665546Z | 2017-02-15T15:59:00Z | null | null | null | {'https://github.com/dlitz/pycrypto/issues/176', 'https://github.com/dlitz/pycrypto/commit/8dbe0dc3eea5c689d4f76b37b93fe216cf1f00d4', 'http://www.securityfocus.com/bid/95122', 'https://bugzilla.redhat.com/show_bug.cgi?id=1409754', 'https://pony7.fr/ctf:public:32c3:cryptmsg', 'https://security.gentoo.org/glsa/201702-14', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/C6BWNADPLKDBBQBUT3P75W7HAJCE7M3B/', 'https://github.com/advisories/GHSA-cq27-v7xp-c356', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/RJ37R2YLX56YZABFNAOWV4VTHTGYREAE/', 'http://www.openwall.com/lists/oss-security/2016/12/27/8'} | null |
PyPI | PYSEC-2010-5 | null | ftpserver.py in pyftpdlib before 0.5.0 does not delay its response after receiving an invalid login attempt, which makes it easier for remote attackers to obtain access via a brute-force attack. | {'CVE-2008-7263'} | 2021-07-05T00:01:24.685476Z | 2010-10-19T20:00:00Z | null | null | null | {'http://code.google.com/p/pyftpdlib/source/detail?r=348', 'http://code.google.com/p/pyftpdlib/issues/detail?id=73', 'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY', 'http://code.google.com/p/pyftpdlib/source/diff?spec=svn348&r=348&format=side&path=/trunk/pyftpdlib/ftpserver.py'} | null |
PyPI | PYSEC-2021-213 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values. 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-7cqx-92hp-x6wh', 'CVE-2021-29576'} | 2021-08-27T03:22:34.891385Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7cqx-92hp-x6wh', 'https://github.com/tensorflow/tensorflow/commit/63c6a29d0f2d692b247f7bf81f8732d6442fad09'} | null |
PyPI | GHSA-7vrm-3jc8-5wwm | Incorrect Comparison in Vyper | ### Impact
bytestrings can have dirty bytes in them, resulting in the word-for-word comparison to give incorrect results, e.g.
```vyper
b1: Bytes[32] = b"abcdef"
b1 = slice(b1, 0, 1)
b2: Bytes[32] = b"abcdef"
t: bool = b1 == b2 # incorrectly evaluates to True
```
even without dirty nonzero bytes, because there is no comparison of the length, two bytestrings can compare to equal if one ends with `"\x00"`.
```vyper
b1: Bytes[32] = b"abc\0"
b2: Bytes[32] = b"abc"
t: bool = b1 == b2 # incorrectly evaluates to True
```
### Patches
fixed in https://github.com/vyperlang/vyper/commit/2c73f8352635c0a433423a5b94740de1a118e508 | null | 2022-04-06T17:50:40.651520Z | 2022-04-04T21:40:45Z | HIGH | null | {'CWE-697'} | {'https://github.com/vyperlang/vyper/security/advisories/GHSA-7vrm-3jc8-5wwm', 'https://github.com/vyperlang/vyper/commit/2c73f8352635c0a433423a5b94740de1a118e508', 'https://github.com/vyperlang/vyper'} | null |
PyPI | GHSA-j8qh-3xrq-c825 | Division by zero in TFLite's implementation of `OneHot` | ### Impact
The implementation of the `OneHot` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72):
```cc
int prefix_dim_size = 1;
for (int i = 0; i < op_context.axis; ++i) {
prefix_dim_size *= op_context.indices->dims->data[i];
}
const int suffix_dim_size = NumElements(op_context.indices) / prefix_dim_size;
```
An attacker can craft a model such that at least one of the dimensions of `indices` would be 0. In turn, the `prefix_dim_size` value would become 0.
### Patches
We have patched the issue in GitHub commit [3ebedd7e345453d68e279cfc3e4072648e5e12e5](https://github.com/tensorflow/tensorflow/commit/3ebedd7e345453d68e279cfc3e4072648e5e12e5).
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-2021-29600'} | 2022-03-03T05:13:17.583435Z | 2021-05-21T14:28:04Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/3ebedd7e345453d68e279cfc3e4072648e5e12e5', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8qh-3xrq-c825', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29600'} | null |
PyPI | PYSEC-2019-6 | null | Buildbot before 1.8.2 and 2.x before 2.3.1 accepts a user-submitted authorization token from OAuth and uses it to authenticate a user. If an attacker has a token allowing them to read the user details of a victim, they can login as the victim. | {'GHSA-g86p-hgx5-2pfh', 'CVE-2019-12300'} | 2019-06-07T18:29:00Z | 2019-05-23T15:30:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7GXKO7OYLKBTXXXKF4VPHWT7GVYWFVYA/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4XLOM2K4M4723BCLHZJEX52KJXZSEVRL/', 'https://github.com/advisories/GHSA-g86p-hgx5-2pfh', 'https://github.com/buildbot/buildbot/wiki/OAuth-vulnerability-in-using-submitted-authorization-token-for-authentication'} | null |
PyPI | PYSEC-2021-643 | null | TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in `Conv3D` implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input. Thus, when `filter` has a 0 as the fifth element, this results in a division by 0. Additionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program 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-772p-x54p-hjrv', 'CVE-2021-29517'} | 2021-12-09T06:35:17.852782Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772p-x54p-hjrv'} | null |
PyPI | GHSA-hx7c-qpfq-xcrp | Cross-site Scripting in django-cms | Django CMS 3.7.3 does not validate the plugin_type parameter while generating error messages for an invalid plugin type, resulting in a Cross Site Scripting (XSS) vulnerability. The vulnerability allows an attacker to execute arbitrary JavaScript code in the web browser of the affected user. | {'CVE-2021-44649'} | 2022-03-03T05:13:17.378805Z | 2022-01-13T20:10:53Z | MODERATE | null | {'CWE-79'} | {'https://github.com/divio/django-cms/', 'https://sahildhar.github.io/blogpost/Django-CMS-Reflected-XSS-Vulnerability/', 'https://www.django-cms.org/en/blog/2020/07/22/django-cms-security-updates-1/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-44649'} | null |
PyPI | PYSEC-2018-48 | null | pysaml2 version 4.4.0 and older accept any password when run with python optimizations enabled. This allows attackers to log in as any user without knowing their password. | {'CVE-2017-1000433', 'GHSA-924m-4pmx-c67h'} | 2021-07-05T00:01:25.224283Z | 2018-01-02T23:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-924m-4pmx-c67h', 'https://security.gentoo.org/glsa/201801-11', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00000.html', 'https://lists.debian.org/debian-lts-announce/2021/02/msg00038.html', 'https://github.com/rohe/pysaml2/issues/451'} | null |
PyPI | PYSEC-2019-193 | null | In a default Red Hat Openstack Platform Director installation, openstack-octavia before versions openstack-octavia 2.0.2-5 and openstack-octavia-3.0.1-0.20181009115732 creates log files that are readable by all users. Sensitive information such as private keys can appear in these log files allowing for information exposure. | {'CVE-2018-16856'} | 2021-08-27T03:22:09.768851Z | 2019-03-26T18:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-16856'} | null |
PyPI | PYSEC-2021-839 | null | Aim is an open-source, self-hosted machine learning experiment tracking tool. Versions of Aim prior to 3.1.0 are vulnerable to a path traversal attack. By manipulating variables that reference files with “dot-dot-slash (../)� sequences and its variations or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system including application source code or configuration and critical system files. The vulnerability issue is resolved in Aim v3.1.0. | {'GHSA-8phj-f9w2-cjcc', 'CVE-2021-43775'} | 2021-12-13T06:35:02.857370Z | 2021-11-23T21:15:00Z | null | null | null | {'https://github.com/aimhubio/aim/issues/999', 'https://github.com/aimhubio/aim/pull/1003/commits/f01266a1a479ef11d7d6c539e7dd89e9d5639738', 'https://github.com/aimhubio/aim/blob/0b99c6ca08e0ba7e7011453a2f68033e9b1d1bce/aim/web/api/views.py#L9-L16', 'https://github.com/aimhubio/aim/pull/1003', 'https://github.com/aimhubio/aim/security/advisories/GHSA-8phj-f9w2-cjcc'} | null |
PyPI | PYSEC-2010-28 | null | Cross-site scripting (XSS) vulnerability in action/Despam.py in the Despam action module in MoinMoin 1.8.7 and 1.9.2 allows remote authenticated users to inject arbitrary web script or HTML by creating a page with a crafted URI. | {'CVE-2010-0828'} | 2021-08-27T03:22:07.708069Z | 2010-04-05T15:30:00Z | null | null | null | {'http://lists.fedoraproject.org/pipermail/package-announce/2010-April/038490.html', 'http://www.debian.org/security/2010/dsa-2024', 'http://secunia.com/advisories/39188', 'http://www.vupen.com/english/advisories/2010/0767', 'http://www.vupen.com/english/advisories/2010/0834', 'http://www.ubuntu.com/usn/USN-925-1', 'https://bugzilla.redhat.com/show_bug.cgi?id=578801', 'http://secunia.com/advisories/39190', 'https://bugs.launchpad.net/ubuntu/+source/moin/+bug/538022', 'http://hg.moinmo.in/moin/1.9/rev/6e603e5411ca', 'http://secunia.com/advisories/39284', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/57435', 'http://secunia.com/advisories/39267', 'http://lists.fedoraproject.org/pipermail/package-announce/2010-April/038574.html', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=575995', 'http://www.vupen.com/english/advisories/2010/0831', 'http://lists.fedoraproject.org/pipermail/package-announce/2010-April/038706.html', 'http://www.securityfocus.com/bid/39110'} | null |
PyPI | PYSEC-2012-15 | null | Paste Script 1.7.5 and earlier does not properly set group memberships during execution with root privileges, which might allow remote attackers to bypass intended file-access restrictions by leveraging a web application that uses the local filesystem. | {'CVE-2012-0878'} | 2021-08-27T03:22:10.166915Z | 2012-05-01T19:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2012/02/23/4', 'https://bugzilla.redhat.com/show_bug.cgi?id=796790', 'https://bitbucket.org/ianb/pastescript/changeset/a19e462769b4', 'https://bitbucket.org/ianb/pastescript/pull-request/3/fix-group-permissions-for-pastescriptserve', 'http://rhn.redhat.com/errata/RHSA-2012-1206.html', 'http://www.openwall.com/lists/oss-security/2012/02/23/1', 'http://secunia.com/advisories/50410', 'http://groups.google.com/group/paste-users/browse_thread/thread/2aa651ba331c2471', 'http://secunia.com/advisories/48812'} | null |
PyPI | GHSA-2xpj-f5g2-8p7m | Access of Uninitialized Pointer | asyncpg before 0.21.0 allows a malicious PostgreSQL server to trigger a crash or execute arbitrary code (on a database client) via a crafted server response, because of access to an uninitialized pointer in the array data decoder. | {'CVE-2020-17446'} | 2022-03-03T05:12:57.647477Z | 2021-04-20T16:30:51Z | HIGH | null | {'CWE-824'} | {'https://lists.debian.org/debian-lts-announce/2020/09/msg00002.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-17446', 'https://github.com/MagicStack/asyncpg/releases/tag/v0.21.0'} | null |
PyPI | PYSEC-2021-585 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-5hj3-vjjf-f5m7', 'CVE-2021-37672'} | 2021-12-09T06:35:05.144273Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a4e138660270e7599793fa438cd7b2fc2ce215a6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hj3-vjjf-f5m7'} | null |
PyPI | PYSEC-2022-133 | null | Tensorflow is an Open Source Machine Learning Framework. Multiple operations in TensorFlow can be used to trigger a denial of service via `CHECK`-fails (i.e., assertion failures). This is similar to TFSA-2021-198 and has similar fixes. We have patched the reported issues in multiple GitHub commits. It is possible that other similar instances exist in TensorFlow, we will issue fixes as these are discovered. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-qj5r-f9mv-rffh', 'CVE-2022-23569'} | 2022-03-09T00:18:26.852426Z | 2022-02-03T13:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qj5r-f9mv-rffh'} | null |
PyPI | PYSEC-2014-84 | null | The Execute class in shellutils in logilab-commons before 0.61.0 uses tempfile.mktemp, which allows local users to have an unspecified impact by pre-creating the temporary file. | {'CVE-2014-1839'} | 2021-08-27T03:22:06.108554Z | 2014-03-11T19:37:00Z | null | null | null | {'http://comments.gmane.org/gmane.comp.security.oss.general/11986', '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', 'http://www.logilab.org/ticket/207562'} | null |
PyPI | GHSA-9ccv-p7fg-m73x | XML Injection in python-libnmap | python-libnmap is affected by: XML Injection. The impact is: Denial of service (DoS) by consuming resources. The component is: XML Parsing. The attack vector is: Specially crafted XML payload. | {'CVE-2019-1010017'} | 2022-03-03T05:14:15.963423Z | 2019-07-18T15:38:41Z | HIGH | null | {'CWE-91'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-1010017', 'https://github.com/savon-noir/python-libnmap/issues/87'} | null |
PyPI | GHSA-pfwg-rxf4-97c3 | Open Redirect in Apache Superset | Apache Superset up to and including 1.0.1 allowed for the creation of an external URL that could be malicious. By not checking user input for open redirects the URL shortener functionality would allow for a malicious user to create a short URL for a dashboard that could convince the user to click the link. | {'CVE-2021-28125'} | 2022-03-03T05:13:20.366441Z | 2021-10-06T17:47:53Z | MODERATE | null | {'CWE-601'} | {'https://github.com/apache/superset', 'https://lists.apache.org/thread.html/r89b5d0dd35c1adc9624b48d6247729c73b2641b32754226661368434@%3Cdev.superset.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2021-28125', 'http://www.openwall.com/lists/oss-security/2021/04/27/2', 'https://lists.apache.org/thread.html/r89b5d0dd35c1adc9624b48d6247729c73b2641b32754226661368434%40%3Cdev.superset.apache.org%3E'} | null |
PyPI | PYSEC-2020-21 | null | The "origin" parameter passed to some of the endpoints like '/trigger' was vulnerable to XSS exploit. This issue affects Apache Airflow versions prior to 1.10.13. This is same as CVE-2020-13944 but the implemented fix in Airflow 1.10.13 did not fix the issue completely. | {'CVE-2020-17515', 'GHSA-86vp-x3pr-79rx'} | 2021-05-04T00:15:00Z | 2020-12-11T14:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2021/05/01/2', 'https://lists.apache.org/thread.html/r4656959c8ed06c1f6202d89aa4e67b35ad7bdba5a666caff3fea888e%40%3Cusers.airflow.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2020/12/11/2', 'https://lists.apache.org/thread.html/r2892ef594dbbf54d0939b808626f52f7c2d1584f8aa1d81570847d2a@%3Cdev.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/r2892ef594dbbf54d0939b808626f52f7c2d1584f8aa1d81570847d2a@%3Cannounce.apache.org%3E', 'https://lists.apache.org/thread.html/r2892ef594dbbf54d0939b808626f52f7c2d1584f8aa1d81570847d2a@%3Cusers.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/r4656959c8ed06c1f6202d89aa4e67b35ad7bdba5a666caff3fea888e@%3Cusers.airflow.apache.org%3E', 'https://github.com/advisories/GHSA-86vp-x3pr-79rx', 'https://lists.apache.org/thread.html/ra8ce70088ba291f358e077cafdb14d174b7a1ce9a9d86d1b332d6367@%3Cusers.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/rc005f4de9d9b0ba943ceb8ff5a21a5c6ff8a9df52632476698d99432@%3Cannounce.apache.org%3E'} | null |
PyPI | GHSA-4xfp-4pfp-89wg | Reference binding to nullptr in `RaggedTensorToSparse` | ### Impact
An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToSparse`:
```python
import tensorflow as tf
tf.raw_ops.RaggedTensorToSparse(
rt_nested_splits=[[0, 38, 0]],
rt_dense_values=[])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order.
### Patches
We have patched the issue in GitHub commit [1071f554dbd09f7e101324d366eec5f4fe5a3ece](https://github.com/tensorflow/tensorflow/commit/1071f554dbd09f7e101324d366eec5f4fe5a3ece).
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-2021-37656'} | 2022-03-03T05:12:55.872845Z | 2021-08-25T14:42:55Z | HIGH | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/1071f554dbd09f7e101324d366eec5f4fe5a3ece', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4xfp-4pfp-89wg', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37656'} | null |
PyPI | PYSEC-2019-202 | null | python-rply before 0.7.4 insecurely creates temporary files. | {'CVE-2014-1938', 'GHSA-m8qc-mf6p-pfq9'} | 2021-08-27T03:22:19.853413Z | 2019-11-21T15:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-m8qc-mf6p-pfq9', 'https://security-tracker.debian.org/tracker/CVE-2014-1938', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737627', 'http://www.openwall.com/lists/oss-security/2014/02/11/1'} | null |
PyPI | PYSEC-2020-301 | null | In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. 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-2020-26270', 'GHSA-m648-33qf-v3gp'} | 2021-12-09T06:34:44.825248Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp'} | null |
PyPI | GHSA-j9m2-6hq2-4r3c | Cross-site Scripting in invenio-previewer | ## Cross-Site Scripting (XSS) vulnerability in JSON, Markdown and iPython Notebook previewers
### Impact
Several Cross-Site Scripting (XSS) vulnerabilities have been found in the JSON, Markdown and iPython Notebook previewers. The vulnerabilities would allow a malicous user to upload a JSON, Markdown or Notebook file with embedded scripts that would be executed by a victims browser.
### Patches
Invenio-Previewer v1.0.0a12 fixes the issue.
### Workarounds
You can remediate the vulnerability without upgrading by disabling the affected previewers. You do this by adding the following to your configuration:
```python
PREVIEWER_PREFERENCE = [
'csv_dthreejs',
'simple_image',
# 'json_prismjs',
'xml_prismjs',
# 'mistune',
'pdfjs',
# 'ipynb',
'zip',
]
```
Afterwards, you should not be able to preview JSON, Markdown or iPython Notebook files.
### For more information
If you have any questions or comments about this advisory:
* Email us at [info@inveniosoftware.org](mailto:info@inveniosoftware.org) | {'CVE-2019-1020019'} | 2022-03-03T05:13:12.651598Z | 2019-07-16T00:52:22Z | MODERATE | null | {'CWE-79'} | {'https://github.com/inveniosoftware/invenio-previewer/security/advisories/GHSA-j9m2-6hq2-4r3c', 'https://nvd.nist.gov/vuln/detail/CVE-2019-1020019', 'https://github.com/advisories/GHSA-j9m2-6hq2-4r3c'} | null |
PyPI | PYSEC-2015-11 | null | The get_format function in utils/formats.py in Django before 1.7.x before 1.7.11, 1.8.x before 1.8.7, and 1.9.x before 1.9rc2 might allow remote attackers to obtain sensitive application secrets via a settings key in place of a date/time format setting, as demonstrated by SECRET_KEY. | {'CVE-2015-8213'} | 2021-09-01T08:35:41.190803Z | 2015-12-07T20:59:00Z | null | null | null | {'http://rhn.redhat.com/errata/RHSA-2016-0157.html', 'http://rhn.redhat.com/errata/RHSA-2016-0158.html', 'http://lists.opensuse.org/opensuse-updates/2015-12/msg00014.html', 'https://github.com/django/django/commit/316bc3fc9437c5960c24baceb93c73f1939711e4', 'http://www.securityfocus.com/bid/77750', 'http://rhn.redhat.com/errata/RHSA-2016-0129.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-December/173375.html', 'http://www.securitytracker.com/id/1034237', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-December/174770.html', 'http://lists.opensuse.org/opensuse-updates/2015-12/msg00017.html', 'http://www.debian.org/security/2015/dsa-3404', 'http://rhn.redhat.com/errata/RHSA-2016-0156.html', 'https://www.djangoproject.com/weblog/2015/nov/24/security-releases-issued/', 'http://www.ubuntu.com/usn/USN-2816-1'} | null |
PyPI | PYSEC-2021-751 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements. The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. We have patched the issue in GitHub commit 4923de56ec94fff7770df259ab7f2288a74feb41. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1 as this is the other affected version. | {'GHSA-95xm-g58g-3p88', 'CVE-2021-37640'} | 2021-12-09T06:35:35.756075Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-95xm-g58g-3p88', 'https://github.com/tensorflow/tensorflow/commit/4923de56ec94fff7770df259ab7f2288a74feb41'} | null |
PyPI | PYSEC-2021-301 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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-2021-37679', 'GHSA-g8wg-cjwc-xhhp'} | 2021-08-27T03:22:46.691143Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g8wg-cjwc-xhhp', 'https://github.com/tensorflow/tensorflow/commit/4e2565483d0ffcadc719bd44893fb7f609bb5f12'} | null |
PyPI | GHSA-p5wr-vp8g-q5p4 | Moderate severity vulnerability that affects Plone | Plone 4.x through 4.3.11 and 5.x through 5.0.6 allow remote attackers to bypass a sandbox protection mechanism and obtain sensitive information by leveraging the Python string format method. | {'CVE-2017-5524'} | 2022-03-03T05:14:12.183484Z | 2018-07-12T14:45:15Z | MODERATE | null | {'CWE-134'} | {'http://www.securityfocus.com/bid/95679', 'https://github.com/advisories/GHSA-p5wr-vp8g-q5p4', 'http://www.openwall.com/lists/oss-security/2017/01/18/6', 'https://nvd.nist.gov/vuln/detail/CVE-2017-5524', 'https://plone.org/security/hotfix/20170117/sandbox-escape'} | null |
PyPI | PYSEC-2021-614 | null | TensorFlow is an open source platform for machine learning. In affected versions during TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change. 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-786j-5qwq-r36x', 'CVE-2021-41204'} | 2021-12-09T06:35:08.218423Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-786j-5qwq-r36x', 'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} | null |
PyPI | PYSEC-2021-244 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-gv26-jpj9-c8gq', 'CVE-2021-29607'} | 2021-08-27T03:22:40.417025Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq', 'https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2'} | null |
PyPI | GHSA-qcx9-j53g-ccgf | Remote Code Execution via unsafe classes in otherwise permitted modules | ### Impact
The module `AccessControl` defines security policies for Python code used in restricted code within Zope applications. Restricted code is any code that resides in Zope's object database, such as the contents of `Script (Python)` objects.
The policies defined in `AccessControl` severely restrict access to Python modules and only exempt a few that are deemed safe, such as Python's `string` module. However, full access to the `string` module also allows access to the class `Formatter`, which can be overridden and extended within `Script (Python)` in a way that provides access to other unsafe Python libraries. Those unsafe Python libraries can be used for remote code execution.
By default, you need to have the admin-level Zope "Manager" role to add or edit `Script (Python)` objects through the web. Only sites that allow untrusted users to add/edit these scripts through the web - which would be a very unusual configuration to begin with - are at risk.
### Patches
The problem has been fixed in AccessControl 4.3 and 5.2.
Only AccessControl versions 4 and 5 are vulnerable, and only on Python 3, not Python 2.7.
### Workarounds
A site administrator can restrict adding/editing `Script (Python)` objects through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing these scripts through the web should be restricted to trusted users only. This is the default configuration in Zope.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [AccessControl issue tracker](https://github.com/zopefoundation/AccessControl/issues)
* Email us at [security@plone.org](mailto:security@plone.org)
| {'CVE-2021-32807'} | 2022-03-03T05:13:17.404739Z | 2021-08-05T17:01:30Z | MODERATE | null | {'CWE-915'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-32807', 'https://github.com/zopefoundation/AccessControl', 'https://github.com/zopefoundation/AccessControl/blob/master/CHANGES.rst#51-2021-07-30', 'https://github.com/zopefoundation/AccessControl/commit/b42dd4badf803bb9fb71ac34cd9cb0c249262f2c', 'https://github.com/zopefoundation/AccessControl/security/advisories/GHSA-qcx9-j53g-ccgf'} | null |
PyPI | PYSEC-2020-244 | null | OMERO.web before 5.6.3 optionally allows sensitive data elements (e.g., a session key) to be passed as URL query parameters. If an attacker tricks a user into clicking a malicious link in OMERO.web, the information in the query parameters may be exposed in the Referer header seen by the target. Information in the URL path such as object IDs may also be exposed. | {'CVE-2020-7932'} | 2021-08-27T03:22:09.833484Z | 2020-06-17T17:15:00Z | null | null | null | {'https://www.openmicroscopy.org/security/advisories/2019-SV4/'} | null |
PyPI | PYSEC-2014-2 | null | The caching framework in Django before 1.4.11, 1.5.x before 1.5.6, 1.6.x before 1.6.3, and 1.7.x before 1.7 beta 2 reuses a cached CSRF token for all anonymous users, which allows remote attackers to bypass CSRF protections by reading the CSRF cookie for anonymous users. | {'CVE-2014-0473'} | 2021-07-05T00:01:18.594368Z | 2014-04-23T15:55:00Z | null | null | null | {'http://www.ubuntu.com/usn/USN-2169-1', 'https://www.djangoproject.com/weblog/2014/apr/21/security/', 'http://rhn.redhat.com/errata/RHSA-2014-0456.html', 'http://lists.opensuse.org/opensuse-updates/2014-09/msg00023.html', 'http://secunia.com/advisories/61281', 'http://rhn.redhat.com/errata/RHSA-2014-0457.html', 'http://www.debian.org/security/2014/dsa-2934'} | null |
PyPI | PYSEC-2021-497 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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-2021-29569', 'GHSA-3h8m-483j-7xxm'} | 2021-12-09T06:34:54.064557Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm'} | null |
PyPI | PYSEC-2021-7 | null | In Django 2.2 before 2.2.21, 3.1 before 3.1.9, and 3.2 before 3.2.1, MultiPartParser, UploadedFile, and FieldFile allowed directory traversal via uploaded files with suitably crafted file names. | {'GHSA-rxjp-mfm9-w4wr', 'CVE-2021-31542'} | 2021-05-13T13:41:00Z | 2021-05-05T15:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00005.html', 'https://github.com/advisories/GHSA-rxjp-mfm9-w4wr', 'http://www.openwall.com/lists/oss-security/2021/05/04/3', 'https://www.djangoproject.com/weblog/2021/may/04/security-releases/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZVKYPHR3TKR2ESWXBPOJEKRO2OSJRZUE/'} | null |
PyPI | GHSA-fpjm-rp2g-3r4c | Django Rest Framework jwt allows obtaining new token from notionally invalidated token | An issue was discovered in drf-jwt 1.15.x before 1.15.1. It allows attackers with access to a notionally invalidated token to obtain a new, working token via the refresh endpoint, because the blacklist protection mechanism is incompatible with the token-refresh feature. NOTE: drf-jwt is a fork of jpadilla/django-rest-framework-jwt, which is unmaintained. | {'CVE-2020-10594'} | 2022-03-21T22:31:58.234107Z | 2020-06-05T16:09:34Z | CRITICAL | null | {'CWE-287'} | {'https://github.com/Styria-Digital/django-rest-framework-jwt/issues/36', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10594', 'https://github.com/Styria-Digital/django-rest-framework-jwt', 'https://github.com/jpadilla/django-rest-framework-jwt/issues/484', 'https://pypi.org/project/drf-jwt/1.15.1/#history', 'https://github.com/Styria-Digital/django-rest-framework-jwt/commit/868b5c22ddad59772b447080183e7c7101bb18e0'} | null |
PyPI | PYSEC-2020-99 | null | Python-RSA before 4.1 ignores leading '\0' bytes during decryption of ciphertext. This could conceivably have a security-relevant impact, e.g., by helping an attacker to infer that an application uses Python-RSA, or if the length of accepted ciphertext affects application behavior (such as by causing excessive memory allocation). | {'GHSA-537h-rv9q-vvph', 'CVE-2020-13757'} | 2020-09-02T16:15:00Z | 2020-06-01T19:15:00Z | null | null | null | {'https://github.com/sybrenstuvel/python-rsa/issues/146#issuecomment-641845667', 'https://github.com/advisories/GHSA-537h-rv9q-vvph', 'https://github.com/sybrenstuvel/python-rsa/issues/146', 'https://usn.ubuntu.com/4478-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZYB65VNILRBTXL6EITQTH2PZPK7I23MW/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2KILTHBHNSDUCYV22ODLOKTICJJ7JQIQ/'} | null |
PyPI | PYSEC-2020-76 | null | Pillow before 7.1.0 has multiple out-of-bounds reads in libImaging/FliDecode.c. | {'GHSA-cqhg-xjhh-p8hf', 'CVE-2020-10177'} | 2020-08-08T20:15:00Z | 2020-06-25T19:15:00Z | null | null | null | {'https://github.com/python-pillow/Pillow/commits/master/src/libImaging', 'https://github.com/python-pillow/Pillow/pull/4538', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOKHNWV2VS5GESY7IBD237E7C6T3I427/', 'https://usn.ubuntu.com/4430-1/', 'https://github.com/python-pillow/Pillow/pull/4503', 'https://github.com/advisories/GHSA-cqhg-xjhh-p8hf', 'https://lists.debian.org/debian-lts-announce/2020/08/msg00012.html', 'https://usn.ubuntu.com/4430-2/', 'https://pillow.readthedocs.io/en/stable/releasenotes/7.1.0.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BEBCPE4F2VHTIT6EZA2YZQZLPVDEBJGD/'} | null |
PyPI | PYSEC-2021-478 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-f78g-q7r4-9wcv', 'CVE-2021-29550'} | 2021-12-09T06:34:51.099370Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv'} | null |
PyPI | PYSEC-2021-182 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in converting sparse tensors to CSR Sparse matrices. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/800346f2c03a27e182dd4fba48295f65e7790739/tensorflow/core/kernels/sparse/kernels.cc#L66) does a double redirection to access an element of an array allocated on the heap. If the value at `indices(i, 0)` is such that `indices(i, 0) + 1` is outside the bounds of `csr_row_ptr`, this results in writing outside of bounds of heap allocated data. 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-2021-29545', 'GHSA-hmg3-c7xj-6qwm'} | 2021-08-27T03:22:29.446413Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/1e922ccdf6bf46a3a52641f99fd47d54c1decd13', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hmg3-c7xj-6qwm'} | null |
PyPI | GHSA-q263-fvxm-m5mw | Heap out of bounds access in MakeEdge in TensorFlow | ### Impact
Under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The [`MakeEdge` function](https://github.com/tensorflow/tensorflow/blob/3616708cb866365301d8e67b43b32b46d94b08a0/tensorflow/core/common_runtime/graph_constructor.cc#L1426-L1438) creates an edge between one output tensor of the `src` node (given by `output_index`) and the input slot of the `dst` node (given by `input_index`). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding `DataType` values and comparing these for equality:
```cc
DataType src_out = src->output_type(output_index);
DataType dst_in = dst->input_type(input_index);
//...
```
However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays.
In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library.
### Patches
We have patched the issue in GitHub commit [0cc38aaa4064fd9e79101994ce9872c6d91f816b](https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.
### 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-2020-26271'} | 2022-03-03T05:14:08.830315Z | 2020-12-10T19:07:34Z | LOW | null | {'CWE-125', 'CWE-908'} | {'https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26271', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw'} | null |
PyPI | PYSEC-2021-20 | null | markdown2 >=1.0.1.18, fixed in 2.4.0, is affected by a regular expression denial of service vulnerability. If an attacker provides a malicious string, it can make markdown2 processing difficult or delayed for an extended period of time. | {'GHSA-jr9p-r423-9m2r', 'CVE-2021-26813'} | 2021-05-10T03:15:00Z | 2021-03-03T16:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-jr9p-r423-9m2r', 'https://github.com/trentm/python-markdown2/pull/387', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BRP5RN35JZTSJ3JT4722F447ZDK7LZS5/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JTIX5UXRDJZJ57DO4V33ZNJTNKWGBQLY/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/J752422YELXLMLZJPVJVKD2KKHHQRVEH/'} | null |
PyPI | GHSA-4m72-rmm9-2qjr | Moderate severity vulnerability that affects feedparser | Cross-site scripting (XSS) vulnerability in feedparser.py in Universal Feed Parser (aka feedparser or python-feedparser) 5.x before 5.0.1 allows remote attackers to inject arbitrary web script or HTML via an unexpected URI scheme, as demonstrated by a javascript: URI. | {'CVE-2011-1158'} | 2022-03-03T05:13:47.985036Z | 2018-07-23T19:51:43Z | MODERATE | null | {'CWE-79'} | {'http://lists.opensuse.org/opensuse-updates/2011-04/msg00026.html', 'http://secunia.com/advisories/44074', 'http://support.novell.com/security/cve/CVE-2011-1158.html', 'http://www.mandriva.com/security/advisories?name=MDVSA-2011:082', 'https://bugzilla.novell.com/show_bug.cgi?id=680074', 'https://nvd.nist.gov/vuln/detail/CVE-2011-1158', 'http://openwall.com/lists/oss-security/2011/03/15/11', 'http://openwall.com/lists/oss-security/2011/03/14/18', 'http://secunia.com/advisories/43730', 'https://bugzilla.redhat.com/show_bug.cgi?id=684877', 'http://www.securityfocus.com/bid/46867', 'https://github.com/advisories/GHSA-4m72-rmm9-2qjr', 'https://code.google.com/p/feedparser/issues/detail?id=255'} | null |
PyPI | PYSEC-2021-395 | null | TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41202', 'GHSA-xrqm-fpgr-6hhx'} | 2021-11-13T06:52:42.645758Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xrqm-fpgr-6hhx', 'https://github.com/tensorflow/tensorflow/commit/1b0e0ec27e7895b9985076eab32445026ae5ca94', 'https://github.com/tensorflow/tensorflow/issues/46912', 'https://github.com/tensorflow/tensorflow/commit/6d94002a09711d297dbba90390d5482b76113899', 'https://github.com/tensorflow/tensorflow/issues/46889'} | null |
PyPI | GHSA-33c7-2mpw-hg34 | Log injection in uvicorn | This affects all versions of package uvicorn. The request logger provided by the package is vulnerable to ASNI escape sequence injection. Whenever any HTTP request is received, the default behaviour of uvicorn is to log its details to either the console or a log file. When attackers request crafted URLs with percent-encoded escape sequences, the logging component will log the URL after it's been processed with urllib.parse.unquote, therefore converting any percent-encoded characters into their single-character equivalent, which can have special meaning in terminal emulators. By requesting URLs with crafted paths, attackers can: * Pollute uvicorn's access logs, therefore jeopardising the integrity of such files. * Use ANSI sequence codes to attempt to interact with the terminal emulator that's displaying the logs (either in real time or from a file). | {'CVE-2020-7694'} | 2022-03-03T05:12:40.727569Z | 2020-07-29T18:07:16Z | HIGH | null | {'CWE-94', 'CWE-116'} | {'https://github.com/encode/uvicorn', 'https://snyk.io/vuln/SNYK-PYTHON-UVICORN-575560', 'https://nvd.nist.gov/vuln/detail/CVE-2020-7694'} | null |
PyPI | GHSA-48mj-p7x2-5jfm | Basic auth bypass in esphome | ### Impact
Anyone with web_server enabled and HTTP basic auth configured on 2021.9.1 or older
`web_server` allows OTA update without checking user defined basic auth username & password
### Patches
Patch released in 2021.9.2
### Workarounds
Disable/remove `web_server`
| {'CVE-2021-41104'} | 2022-03-03T05:13:27.379334Z | 2021-09-29T17:09:14Z | HIGH | null | {'CWE-306'} | {'https://github.com/esphome/esphome/commit/be965a60eba6bb769e2a5afdbc8eed132f077a59', 'https://github.com/esphome/esphome/pull/2409/commits/207cde1667d8c799a197b78ca8a5a14de8d5ca1e', 'https://github.com/esphome/esphome', 'https://github.com/esphome/esphome/security/advisories/GHSA-48mj-p7x2-5jfm', 'https://github.com/esphome/esphome/releases/tag/2021.9.2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41104'} | null |
PyPI | PYSEC-2017-57 | null | Chameleon (five.pt) in Plone 5.0rc1 through 5.1a1 allows remote authenticated users to bypass Restricted Python by leveraging permissions to create or edit templates. | {'CVE-2016-4043'} | 2021-07-25T23:34:48.662249Z | 2017-02-24T20:59:00Z | null | null | null | {'https://plone.org/security/hotfix/20160419/bypass-restricted-python', 'http://www.openwall.com/lists/oss-security/2016/04/20/3'} | null |
PyPI | PYSEC-2013-14 | null | Salt (aka SaltStack) before 0.15.0 through 0.17.0 allows remote authenticated minions to impersonate arbitrary minions via a crafted minion with a valid key. | {'CVE-2013-4439'} | 2021-07-05T00:01:26.068729Z | 2013-11-05T18:55:00Z | null | null | null | {'https://github.com/saltstack/salt/pull/7356', 'http://docs.saltstack.com/topics/releases/0.17.1.html', 'http://www.openwall.com/lists/oss-security/2013/10/18/3'} | null |
PyPI | GHSA-r838-q6jp-58xx | Improper Restriction of Excessive Authentication Attempts in py-bcrypt | The py-bcrypt module before 0.3 for Python does not properly handle concurrent memory access, which allows attackers to bypass authentication via multiple authentication requests, which trigger the password hash to be overwritten. | {'CVE-2013-1895'} | 2022-03-03T05:13:43.087514Z | 2021-10-12T16:31:22Z | HIGH | null | {'CWE-307'} | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/83039', 'http://www.openwall.com/lists/oss-security/2013/03/26/2', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-April/101387.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-April/101382.html', 'https://nvd.nist.gov/vuln/detail/CVE-2013-1895', 'http://www.securityfocus.com/bid/58702'} | null |
PyPI | GHSA-jh82-c5jw-pxpc | Denial of Service in Onionshare | Between September 26, 2021 and October 8, 2021, [Radically Open Security](https://www.radicallyopensecurity.com/) conducted a penetration test of OnionShare 2.4, funded by the Open Technology Fund's [Red Team lab](https://www.opentech.fund/labs/red-team-lab/).
- Vulnerability ID: OTF-012
- Vulnerability type: Denial of Service
- Threat level: Moderate
## Description:
The receive mode limits concurrent uploads to 100 per second and blocks other uploads in the same second, which can be triggered by a simple script.
## Technical description:
The following script uses GNU parallel and curl with around 6000 requests in parallel to send 10000 requests. A change in the `ulimit -n` configuration is required for it to work. This is sufficient to block file upload on a (public) receive instance.
```
seq 10000 | parallel --max-args 0 --jobs 6000 "curl -i -s -x socks5h://localhost:9150 -k -X $'POST' -H $'Host: csqrp3qciewvj5axph4o62jnr6aevhmpxfkydmi3256bprhbusr2ltid.onion' -H $'Accept-Encoding: gzip, deflate' -H $'Content-Type: multipart/form-data; boundary=---------------------------19182376703918074873375387042' -H $'Content-Length: 329' -H $'Connection: close' --data-binary $'-----------------------------19182376703918074873375387042\x0d\x0aContent-Disposition: form-data; name=\"file[]\"; filename=\"poc.txt\"\x0d\x0aContent-Type: text/plain\x0d\x0a\x0d\x0aA\x0d\x0a-----------------------------19182376703918074873375387042\x0d\x0aContent-Disposition: form-data; name=\"text\"\x0d\x0a\x0d\x0a\x0d\x0a-----------------------------19182376703918074873375387042--\x0d\x0a' $'http://csqrp3qciewvj5axph4o62jnr6aevhmpxfkydmi3256bprhbusr2ltid.onion/upload-ajax'"
```
Attack duration was around 80 seconds.
Cases where over 99 requests were sent per second:
```
Every 0.1s: ls | grep... onionvm: Tue Oct 5 12:17:00 2021
78
```
Cases where files were successfully written to disk:
```
Every 0.1s: ls | wc -w onionvm: Tue Oct 5 12:17:00 2021
8399
```
This means that during the attack time 1601 requests of 10000 were dropped. We tried to upload multiple files in the web interface during the attack and were not successful.
The failsafe is used to prevent creating more than 100 directories per second:
https://github.com/onionshare/onionshare/blob/d08d5f0f32f755f504494d80794886f346fbafdb/cli/onionshare_cli/web/receive_mode.py#L386-L427
The limit of 100 requests/second is significantly lower than the possible network bandwidth and greatly reduces the attack complexity for denial of service. Our test was conducted over the tor network, which showed no limitation for the required bandwidth.
## Impact:
An adversary with access to the receive mode can block file upload for others. There is no way to block this attack in public mode due to the anonymity properties of the tor network.
## Recommendation:
- Remove this limitation, or
- Derive directory name from milliseconds
| {'CVE-2022-21689'} | 2022-03-03T05:13:21.617588Z | 2022-01-21T23:20:27Z | HIGH | null | {'CWE-400'} | {'https://github.com/onionshare/onionshare/', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21689', 'https://github.com/onionshare/onionshare/security/advisories/GHSA-jh82-c5jw-pxpc', 'https://github.com/onionshare/onionshare/releases/tag/v2.5'} | null |
PyPI | GHSA-fxpg-gg9g-76gj | Moderate severity vulnerability that affects django | Cross-site scripting (XSS) vulnerability in Django 1.2.x before 1.2.2 allows remote attackers to inject arbitrary web script or HTML via a csrfmiddlewaretoken (aka csrf_token) cookie. | {'CVE-2010-3082'} | 2022-03-03T05:13:05.080531Z | 2018-07-23T19:52:42Z | MODERATE | null | {'CWE-79'} | {'https://github.com/django/django', 'http://www.ubuntu.com/usn/USN-1004-1', 'http://www.djangoproject.com/weblog/2010/sep/08/security-release/', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/61729', 'https://bugzilla.redhat.com/show_bug.cgi?id=632239', 'https://github.com/advisories/GHSA-fxpg-gg9g-76gj', 'http://marc.info/?l=oss-security&m=128403961700444&w=2', 'http://www.securityfocus.com/bid/43116', 'https://nvd.nist.gov/vuln/detail/CVE-2010-3082'} | null |
PyPI | PYSEC-2021-680 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected. | {'GHSA-qg48-85hg-mqc5', 'CVE-2021-29554'} | 2021-12-09T06:35:24.121504Z | 2021-05-14T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5'} | null |
PyPI | PYSEC-2019-150 | null | Bodhi 2.9.0 and lower is vulnerable to cross-site scripting resulting in code injection caused by incorrect validation of bug titles. | {'CVE-2017-1002152'} | 2021-07-05T00:01:17.244288Z | 2019-01-10T21:29:00Z | null | null | null | {'https://github.com/fedora-infra/bodhi/issues/1740'} | null |
PyPI | GHSA-rrfp-j2mp-hq9c | Segfault in `tf.quantization.quantize_and_dequantize` | ### Impact
An attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`:
```python
tf.quantization.quantize_and_dequantize(
input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10)
```
This results in accessing [a dimension outside the rank of the input tensor](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74) in the C++ kernel implementation:
```
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
```
However, [`dim_size` only does a `DCHECK`](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/framework/tensor_shape.cc#L292-L307) to validate the argument and then uses it to access the corresponding element of an array:
```
int64 TensorShapeBase<Shape>::dim_size(int d) const {
DCHECK_GE(d, 0);
DCHECK_LT(d, dims());
DoStuffWith(dims_[d]);
}
```
Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array.
### Patches
We have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
### 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 in #42105 | {'CVE-2020-15265'} | 2022-03-03T05:13:37.229593Z | 2020-11-13T17:13:04Z | LOW | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/issues/42105', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15265', 'https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808', 'https://github.com/tensorflow/tensorflow'} | null |
PyPI | PYSEC-2009-7 | null | Multiple unspecified vulnerabilities in Trac before 0.11.6 have unknown impact and attack vectors, possibly related to (1) "policy checks in report results when using alternate formats" or (2) a "check for the 'raw' role that is missing in docutils < 0.6." | {'CVE-2009-4405'} | 2021-07-16T01:31:34.738485Z | 2009-12-23T21:30:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=542394', 'http://www.vupen.com/english/advisories/2009/3615', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/54983', 'http://secunia.com/advisories/37807', 'http://trac.edgewall.org/browser/tags/trac-0.11.6/RELEASE', 'http://secunia.com/advisories/37901', 'https://www.redhat.com/archives/fedora-package-announce/2009-December/msg01169.html'} | null |
PyPI | PYSEC-2022-30 | null | In Apache Airflow, prior to version 2.2.4, some example DAGs did not properly sanitize user-provided params, making them susceptible to OS Command Injection from the web UI. | {'GHSA-3v7g-4pg3-7r6j', 'CVE-2022-24288'} | 2022-03-04T21:27:14.083744Z | 2022-02-25T09:15:00Z | null | null | null | {'https://lists.apache.org/thread/dbw5ozcmr0h0lhs0yjph7xdc64oht23t', 'https://github.com/advisories/GHSA-3v7g-4pg3-7r6j'} | null |
PyPI | GHSA-c545-c4f9-rf6v | Heap OOB in TFLite | ### Impact
TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data:
```cc
if (axis < 0) {
axis = input_dims.size + 1 + axis;
}
TF_LITE_ENSURE(context, axis <= input_dims.size);
TfLiteIntArray* output_dims = TfLiteIntArrayCreate(input_dims.size + 1);
for (int i = 0; i < output_dims->size; ++i) {
if (i < axis) {
output_dims->data[i] = input_dims.data[i];
} else if (i == axis) {
output_dims->data[i] = 1;
} else {
output_dims->data[i] = input_dims.data[i - 1];
}
}
```
If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`).
### Patches
We have patched the issue in GitHub commit [d94ffe08a65400f898241c0374e9edc6fa8ed257](https://github.com/tensorflow/tensorflow/commit/d94ffe08a65400f898241c0374e9edc6fa8ed257).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security. | {'CVE-2021-37685'} | 2021-08-24T17:15:34Z | 2021-08-25T14:40:09Z | MODERATE | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/d94ffe08a65400f898241c0374e9edc6fa8ed257', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c545-c4f9-rf6v', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37685'} | null |
PyPI | PYSEC-2021-403 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. | {'CVE-2021-41211', 'GHSA-cvgx-3v3q-m36c'} | 2021-11-13T06:52:43.843277Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c', 'https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244'} | null |
PyPI | GHSA-gwp7-vqr5-h33h | Open Redirect in autobahn | Autobahn|Python before 20.12.3 allows redirect header injection. | {'CVE-2020-35678'} | 2022-03-03T05:12:21.771321Z | 2021-04-20T16:13:45Z | MODERATE | null | {'CWE-601'} | {'https://github.com/crossbario/autobahn-python/compare/v20.12.2...v20.12.3', 'https://autobahn.readthedocs.io/en/latest/changelog.html', 'https://github.com/crossbario/autobahn-python/pull/1439', 'https://nvd.nist.gov/vuln/detail/CVE-2020-35678', 'https://github.com/crossbario/autobahn-python', 'https://pypi.org/project/autobahn/20.12.3/'} | null |
PyPI | GHSA-gjj5-998g-v36v | Improper Access Control in Onionshare | Between September 26, 2021 and October 8, 2021, [Radically Open Security](https://www.radicallyopensecurity.com/) conducted a penetration test of OnionShare 2.4, funded by the Open Technology Fund's [Red Team lab](https://www.opentech.fund/labs/red-team-lab/). This is an issue from that penetration test.
- Vulnerability ID: OTF-003
- Vulnerability type: Improper Access Control
- Threat level: Moderate
## Description:
Anyone with access to the chat environment can write messages disguised as another chat participant.
## Technical description:
Prerequisites:
- Alice and Bob are legitimate users
- A third user has access to the chat environment
This screenshot shows Alice (`glimpse-depress`) and Bob (`blinker-doorpost`) joined a chatroom and are the only participants in the chatroom. Then the non-listed user squad-nursing writes a message in the chatroom without being visible in the list of users. The sending of the message itself is not required but was done here to show the initial access. The non-listed participant now renames himself to Bob and writes another message, seemingly coming from Bob.
This can be reproduced by slightly modifying the client-side JavaScript. The `joined` emit needs to be removed from the `socket.on(connect) `event handler. Therefore a client is not listed in the userlist and has no active session.
https://github.com/onionshare/onionshare/blob/d08d5f0f32f755f504494d80794886f346fbafdb/cli/onionshare_cli/resources/static/js/chat.js#L16-L18
This can be done either via a crafted client or runtime modification of the `chat.js` script in the browser's internal debugger.
It is still possible to call the text method and send text to the chat via websocket.
https://github.com/onionshare/onionshare/blob/d08d5f0f32f755f504494d80794886f346fbafdb/cli/onionshare_cli/web/chat_mode.py#L131-L139
It is also possible to call the `update_username` function and choose an existing username from the chat.
https://github.com/onionshare/onionshare/blob/d08d5f0f32f755f504494d80794886f346fbafdb/cli/onionshare_cli/web/chat_mode.py#L141-L162
Afterwards the hidden user can send messages that are displayed as coming from the impersonated user. There is no way to distinguish between the fake and original message.
## Impact:
An adversary with access to the chat environment can impersonate existing chat participants and write messages but not read the conversation. The similar exploit described in OTF-004 (page 19) has only slightly more requirements but also allows for reading.
## Recommendation:
- Implement proper session handling | {'CVE-2022-21692'} | 2022-03-03T05:13:03.563038Z | 2022-01-21T23:20:21Z | MODERATE | null | {'CWE-287'} | {'https://github.com/onionshare/onionshare', 'https://github.com/onionshare/onionshare/security/advisories/GHSA-gjj5-998g-v36v', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21692', 'https://github.com/onionshare/onionshare/releases/tag/v2.5'} | null |
PyPI | GHSA-9c84-4hx6-xmm4 | Integer overflow in TFLite concatentation | ### Impact
The TFLite implementation of concatenation is [vulnerable to an integer overflow issue](https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76):
```cc
for (int d = 0; d < t0->dims->size; ++d) {
if (d == axis) {
sum_axis += t->dims->data[axis];
} else {
TF_LITE_ENSURE_EQ(context, t->dims->data[d], t0->dims->data[d]);
}
}
```
An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format.
### Patches
We have patched the issue in GitHub commit [4253f96a58486ffe84b61c0415bb234a4632ee73](https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73).
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-2021-29601'} | 2022-03-03T05:13:56.316972Z | 2021-05-21T14:28:08Z | MODERATE | null | {'CWE-190'} | {'https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29601', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c84-4hx6-xmm4'} | null |
PyPI | PYSEC-2021-116 | null | This affects the package bikeshed before 3.0.0. This can occur when an untrusted source file containing Inline Tag Command metadata is processed. When an arbitrary OS command is executed, the command output would be included in the HTML output. | {'CVE-2021-23422', 'SNYK-PYTHON-BIKESHED-1537646', 'GHSA-87cj-px37-rc3x'} | 2021-08-16T10:33:00.121184Z | 2021-08-16T08:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-87cj-px37-rc3x', 'https://github.com/tabatkins/bikeshed/commit/b2f668fca204260b1cad28d5078e93471cb6b2dd', 'https://snyk.io/vuln/SNYK-PYTHON-BIKESHED-1537646'} | null |
PyPI | GHSA-qx2v-j445-g354 | Improper Input Validation in Google TensorFlow | Memcpy parameter overlap in Google Snappy library 1.1.4, as used in Google TensorFlow before 1.7.1, could result in a crash or read from other parts of process memory. | {'CVE-2018-7577'} | 2022-03-03T05:12:42.927093Z | 2019-04-30T15:37:34Z | HIGH | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-005.md', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7577'} | null |
PyPI | PYSEC-2014-47 | null | atat.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to read private data structures via a request for a view without a name. | {'CVE-2012-5505'} | 2021-09-01T08:44:30.978910Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone-hotfix/releases/20121106', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone/security/advisories/20121106/21'} | null |
PyPI | GHSA-37m5-42qp-4qpr | Cross-site scripting in LocalStack | A Cross-site scripting (XSS) vulnerability exists in StackLift LocalStack. | {'CVE-2021-32091'} | 2022-03-03T05:13:09.523188Z | 2021-06-18T18:38:09Z | MODERATE | null | {'CWE-79'} | {'https://portswigger.net/daily-swig/localstack-zero-day-vulnerabilities-chained-to-achieve-remote-takeover-of-local-instances', 'https://blog.sonarsource.com/hack-the-stack-with-localstack', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32091'} | null |
PyPI | PYSEC-2021-546 | 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'} | 2021-12-09T06:35:01.733982Z | 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 | PYSEC-2020-116 | null | In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | {'CVE-2020-15193', 'GHSA-rjjg-hgv6-h69v'} | 2021-09-01T08:19:32.562362Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2021-815 | null | TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures) as well as abuse undefined behavior (binding references to `nullptr`s). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. 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-57wx-m983-2f88', 'CVE-2021-41208'} | 2021-12-09T06:35:42.346240Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-57wx-m983-2f88', 'https://github.com/tensorflow/tensorflow/commit/5c8c9a8bfe750f9743d0c859bae112060b216f5c'} | null |
PyPI | GHSA-fcf9-3qw3-gxmj | High severity vulnerability that affects cryptography | A flaw was found in python-cryptography versions between >=1.9.0 and <2.3. The finalize_with_tag API did not enforce a minimum tag length. If a user did not validate the input length prior to passing it to finalize_with_tag an attacker could craft an invalid payload with a shortened tag (e.g. 1 byte) such that they would have a 1 in 256 chance of passing the MAC check. GCM tag forgeries can cause key leakage. | {'CVE-2018-10903'} | 2022-03-07T20:47:10.911751Z | 2018-07-31T18:28:09Z | HIGH | null | {'CWE-20'} | {'https://github.com/advisories/GHSA-fcf9-3qw3-gxmj', 'https://nvd.nist.gov/vuln/detail/CVE-2018-10903', 'https://github.com/pyca/cryptography/pull/4342/commits/688e0f673bfbf43fa898994326c6877f00ab19ef', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10903'} | null |
PyPI | PYSEC-2018-64 | null | In conference-scheduler-cli, a pickle.load call on imported data allows remote attackers to execute arbitrary code via a crafted .pickle file, as demonstrated by Python code that contains an os.system call. | {'GHSA-cf3c-fffp-34qh', 'CVE-2018-14572'} | 2021-08-25T04:29:57.468517Z | 2018-08-28T19:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-cf3c-fffp-34qh', 'https://joel-malwarebenchmark.github.io/blog/2020/04/25/cve-2018-14572-conference-scheduler-cli/', 'https://github.com/PyconUK/ConferenceScheduler-cli/issues/19'} | null |
PyPI | GHSA-mhhc-q96p-mfm9 | Infinite loop in TFLite | ### Impact
The strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122):
```cc
for (int i = 0; i < effective_dims;) {
if ((1 << i) & op_context->params->ellipsis_mask) {
// ...
int ellipsis_end_idx =
std::min(i + 1 + num_add_axis + op_context->input_dims - begin_count,
effective_dims);
// ...
for (; i < ellipsis_end_idx; ++i) {
// ...
}
continue;
}
// ...
++i;
}
```
An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop.
### Patches
We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695).
The fix will be included in TensorFlow 2.6.0. This is the only affected version.
### 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-2021-37686'} | 2022-03-03T05:13:58.855686Z | 2021-08-25T14:39:58Z | MODERATE | null | {'CWE-835'} | {'https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.4', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mhhc-q96p-mfm9', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.5.1', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37686', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.4.3', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.6.0'} | null |
PyPI | PYSEC-2020-268 | null | In EasyBuild before version 4.1.2, the GitHub Personal Access Token (PAT) used by EasyBuild for the GitHub integration features (like `--new-pr`, `--fro,-pr`, etc.) is shown in plain text in EasyBuild debug log files. This issue is fixed in EasyBuild v4.1.2, and in the `master`+ `develop` branches of the `easybuild-framework` repository. | {'CVE-2020-5262', 'GHSA-2wx6-wc87-rmjm'} | 2021-11-24T22:46:59.562632Z | 2020-03-19T17:15:00Z | null | null | null | {'https://github.com/easybuilders/easybuild-framework/security/advisories/GHSA-2wx6-wc87-rmjm', 'https://github.com/easybuilders/easybuild-framework/pull/3248', 'https://github.com/easybuilders/easybuild-framework/pull/3249'} | null |
PyPI | GHSA-q5hq-fp76-qmrc | Uncontrolled Resource Consumption in Pillow | An issue was discovered in Pillow before 8.2.0. For EPS data, the readline implementation used in EPSImageFile has to deal with any combination of \r and \n as line endings. It used an accidentally quadratic method of accumulating lines while looking for a line ending. A malicious EPS file could use this to perform a DoS of Pillow in the open phase, before an image was accepted for opening. | {'CVE-2021-28677'} | 2022-03-03T05:13:14.100305Z | 2021-06-08T18:49:36Z | HIGH | null | {'CWE-400'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.2.0.html#cve-2021-28677-fix-eps-dos-on-open', 'https://nvd.nist.gov/vuln/detail/CVE-2021-28677', 'https://lists.debian.org/debian-lts-announce/2021/07/msg00018.html', 'https://security.gentoo.org/glsa/202107-33', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MQHA5HAIBOYI3R6HDWCLAGFTIQP767FL/', 'https://github.com/python-pillow/Pillow', 'https://github.com/python-pillow/Pillow/pull/5377'} | null |
PyPI | GHSA-5m69-3chg-6f8m | Cross Site Scripting (XSS) in Quokka | Cross Site Scripting (XSS) in Quokka v0.4.0 allows remote attackers to execute arbitrary code via the 'Username' parameter in the component 'quokka/admin/actions.py'. | {'CVE-2020-18702'} | 2022-03-03T05:13:08.358979Z | 2021-08-30T16:23:26Z | MODERATE | null | {'CWE-79'} | {'https://github.com/rochacbruno/quokka/issues/675', 'https://nvd.nist.gov/vuln/detail/CVE-2020-18702', 'https://github.com/rochacbruno/quokka'} | null |
PyPI | PYSEC-2022-2 | null | An issue was discovered in Django 2.2 before 2.2.26, 3.2 before 3.2.11, and 4.0 before 4.0.1. Due to leveraging the Django Template Language's variable resolution logic, the dictsort template filter was potentially vulnerable to information disclosure, or an unintended method call, if passed a suitably crafted key. | {'CVE-2021-45116', 'GHSA-8c5j-9r9f-c6w8'} | 2022-01-05T02:16:15.490683Z | 2022-01-05T00:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://www.djangoproject.com/weblog/2022/jan/04/security-releases/', 'https://github.com/advisories/GHSA-8c5j-9r9f-c6w8', 'https://docs.djangoproject.com/en/4.0/releases/security/'} | null |
PyPI | PYSEC-2021-268 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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-2021-37646', 'GHSA-h6jh-7gv5-28vg'} | 2021-08-27T03:22:43.623027Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6jh-7gv5-28vg'} | null |
PyPI | PYSEC-2021-792 | 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'} | 2021-12-09T06:35:39.432731Z | 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-2021-638 | null | TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected. | {'GHSA-4278-2v5v-65r4', 'CVE-2021-29512'} | 2021-12-09T06:35:17.036607Z | 2021-05-14T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4278-2v5v-65r4', 'https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5'} | null |
PyPI | PYSEC-2021-77 | null | An issue was discovered in management/commands/hyperkitty_import.py in HyperKitty through 1.3.4. When importing a private mailing list's archives, these archives are publicly visible for the duration of the import. For example, sensitive information might be available on the web for an hour during a large migration from Mailman 2 to Mailman 3. | {'GHSA-h39g-q63v-4h9p', 'CVE-2021-33038'} | 2021-06-09T05:01:08.351404Z | 2021-05-26T14:15:00Z | null | null | null | {'https://www.debian.org/security/2021/dsa-4922', 'https://gitlab.com/mailman/hyperkitty/-/commit/9025324597d60b2dff740e49b70b15589d6804fa', 'https://github.com/advisories/GHSA-h39g-q63v-4h9p', 'https://gitlab.com/mailman/hyperkitty/-/issues/380'} | null |
PyPI | PYSEC-2021-98 | null | Django before 2.2.24, 3.x before 3.1.12, and 3.2.x before 3.2.4 has a potential directory traversal via django.contrib.admindocs. Staff members could use the TemplateDetailView view to check the existence of arbitrary files. Additionally, if (and only if) the default admindocs templates have been customized by application developers to also show file contents, then not only the existence but also the file contents would have been exposed. In other words, there is directory traversal outside of the template root directories. | {'CVE-2021-33203', 'GHSA-68w8-qjq3-2gfm'} | 2021-06-22T04:54:55.381670Z | 2021-06-08T18:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://github.com/advisories/GHSA-68w8-qjq3-2gfm', 'https://www.djangoproject.com/weblog/2021/jun/02/security-releases/'} | null |
PyPI | GHSA-37hp-765x-j95x | Moderate severity vulnerability that affects django | Django 1.10 before 1.10.7, 1.9 before 1.9.13, and 1.8 before 1.8.18 relies on user input in some cases to redirect the user to an "on success" URL. The security check for these redirects (namely ``django.utils.http.is_safe_url()``) considered some numeric URLs "safe" when they shouldn't be, aka an open redirect vulnerability. Also, if a developer relies on ``is_safe_url()`` to provide safe redirect targets and puts such a URL into a link, they could suffer from an XSS attack. | {'CVE-2017-7233'} | 2022-03-03T05:13:07.767106Z | 2019-01-04T17:50:26Z | MODERATE | null | {'CWE-601'} | {'http://www.securitytracker.com/id/1038177', 'https://access.redhat.com/errata/RHSA-2017:1596', 'https://github.com/advisories/GHSA-37hp-765x-j95x', 'http://www.debian.org/security/2017/dsa-3835', 'https://access.redhat.com/errata/RHSA-2017:1470', 'https://access.redhat.com/errata/RHSA-2018:2927', 'https://access.redhat.com/errata/RHSA-2017:1451', 'https://nvd.nist.gov/vuln/detail/CVE-2017-7233', 'https://access.redhat.com/errata/RHSA-2017:1462', 'http://www.securityfocus.com/bid/97406', 'https://access.redhat.com/errata/RHSA-2017:3093', 'https://www.djangoproject.com/weblog/2017/apr/04/security-releases/', 'https://access.redhat.com/errata/RHSA-2017:1445'} | null |
PyPI | GHSA-4f7p-27jc-3c36 | HTTP Request Smuggling in waitress | ### Impact
When using Waitress behind a proxy that does not properly validate the incoming HTTP request matches the RFC7230 standard, Waitress and the frontend proxy may disagree on where one request starts and where it ends.
This would allow requests to be smuggled via the front-end proxy to waitress and later behavior.
There are two classes of vulnerability that may lead to request smuggling that are addressed by this advisory:
- The use of Python's `int()` to parse strings into integers, leading to `+10` to be parsed as `10`, or `0x01` to be parsed as `1`, where as the standard specifies that the string should contain only digits or hex digits.
- Waitress does not support chunk extensions, however it was discarding them without validating that they did not contain illegal characters
### Patches
This has been fixed in Waitress 2.1.1
### Workarounds
When deploying a proxy in front of waitress, turning on any and all functionality to make sure that the request matches the RFC7230 standard. Certain proxy servers may not have this functionality though and users are encouraged to upgrade to the latest version of waitress instead.
### References
- https://portswigger.net/research/http-desync-attacks-request-smuggling-reborn
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [the Github issue tracker](https://github.com/Pylons/waitress/issues) (if not security related/sensitive)
* Email us at [pylons-project-security@googlegroups.com](mailto:pylons-project-security@googlegroups.com) (If security related or sensitive)
| {'CVE-2022-24761'} | 2022-03-18T19:18:30.184688Z | 2022-03-18T19:00:59Z | HIGH | null | {'CWE-444'} | {'https://github.com/Pylons/waitress/security/advisories/GHSA-4f7p-27jc-3c36', 'https://github.com/Pylons/waitress/releases/tag/v2.1.1', 'https://github.com/Pylons/waitress', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24761', 'https://github.com/Pylons/waitress/commit/9e0b8c801e4d505c2ffc91b891af4ba48af715e0'} | null |
PyPI | PYSEC-2021-287 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. 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-2021-37665', 'GHSA-v82p-hv3v-p6qp'} | 2021-08-27T03:22:45.390087Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp', 'https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69', 'https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9'} | null |
PyPI | PYSEC-2020-287 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15207', 'GHSA-q4qf-3fc6-8x34'} | 2021-12-09T06:34:42.836592Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34', 'https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2021-454 | 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'} | 2021-12-09T06:34:47.426864Z | 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-2018-107 | null | ajenticp (aka Ajenti Docker control panel) for Ajenti through v1.2.23.13 has XSS via a filename that is mishandled in File Manager. | {'CVE-2018-18548'} | 2021-12-13T06:35:03.125488Z | 2018-10-24T21:29:00Z | null | null | null | {'http://packetstormsecurity.com/files/149898/AjentiCP-1.2.23.13-Cross-Site-Scripting.html', 'https://www.exploit-db.com/exploits/45691/', 'https://numanozdemir.com/ajenti-xss.txt'} | null |
PyPI | PYSEC-2022-148 | null | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a use after free behavior when decoding PNG images. After `png::CommonFreeDecode(&decode)` gets called, the values of `decode.width` and `decode.height` are in an unspecified state. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-24x4-6qmh-88qg', 'CVE-2022-23584'} | 2022-03-09T00:18:28.987872Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L339-L346', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-24x4-6qmh-88qg', 'https://github.com/tensorflow/tensorflow/commit/e746adbfcfee15e9cfdb391ff746c765b99bdf9b'} | null |
PyPI | GHSA-w64c-pxjj-h866 | Moderate severity vulnerability that affects ansible | 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'} | 2022-03-03T05:14:13.240639Z | 2018-10-10T17:23:51Z | MODERATE | null | {'CWE-345'} | {'http://www.ansible.com/security', 'http://lists.opensuse.org/opensuse-updates/2015-08/msg00029.html', 'https://nvd.nist.gov/vuln/detail/CVE-2015-3908', '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-2022-67 | 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'} | 2022-03-09T00:17:32.167293Z | 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 | PYSEC-2019-107 | null | nbla/logger.cpp in libnnabla.a in Sony Neural Network Libraries (aka nnabla) through v1.0.14 relies on the HOME environment variable, which might be untrusted. | {'CVE-2019-10844'} | 2019-04-05T20:09:00Z | 2019-04-04T05:29:00Z | null | null | null | {'https://github.com/sony/nnabla/issues/209'} | null |
PyPI | PYSEC-2022-88 | null | Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that `SafeToRemoveIdentity` would trigger `CHECK` failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-5f2r-qp73-37mr', 'CVE-2022-23579'} | 2022-03-09T00:17:34.776924Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/92dba16749fae36c246bec3f9ba474d9ddeb7662', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5f2r-qp73-37mr', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/dependency_optimizer.cc#L59-L98'} | null |
PyPI | PYSEC-2018-33 | null | __init__.py in f2py in NumPy before 1.8.1 allows local users to write to arbitrary files via a symlink attack on a temporary file. | {'CVE-2014-1858'} | 2021-06-29T22:52:17.794688Z | 2018-01-08T19:29:00Z | null | null | null | {'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128358.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128781.html', 'https://github.com/numpy/numpy/blob/maintenance/1.8.x/doc/release/1.8.1-notes.rst', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737778', 'http://www.securityfocus.com/bid/65441', 'https://github.com/numpy/numpy/pull/4262', 'https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15', 'https://bugzilla.redhat.com/show_bug.cgi?id=1062009', 'http://www.openwall.com/lists/oss-security/2014/02/08/3', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/91318'} | null |
PyPI | PYSEC-2017-7 | null | An issue was discovered in cloudflare-scrape 1.6.6 through 1.7.1. A malicious website owner could craft a page that executes arbitrary Python code against any cfscrape user who scrapes that website. This is fixed in 1.8.0. | {'GHSA-5mc5-5j6c-qmf9', 'CVE-2017-7235'} | 2021-07-05T00:01:17.351047Z | 2017-03-23T04:59:00Z | null | null | null | {'https://github.com/advisories/GHSA-5mc5-5j6c-qmf9', 'https://github.com/Anorov/cloudflare-scrape/issues/97', 'http://www.securityfocus.com/bid/97191', 'https://github.com/Anorov/cloudflare-scrape/releases/tag/1.8.0'} | null |
PyPI | PYSEC-2021-842 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `tf.math.segment_*` operations results in a `CHECK`-fail related abort (and denial of service) if a segment id in `segment_ids` is large. This is similar to CVE-2021-29584 (and similar other reported vulnerabilities in TensorFlow, localized to specific APIs): the implementation (both on CPU and GPU) computes the output shape using `AddDim`. However, if the number of elements in the tensor overflows an `int64_t` value, `AddDim` results in a `CHECK` failure which provokes a `std::abort`. Instead, code should use `AddDimWithStatus`. 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-cq76-mxrc-vchh', 'CVE-2021-41195'} | 2021-12-13T06:21:24.676324Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/pull/51733', 'https://github.com/tensorflow/tensorflow/issues/46888', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cq76-mxrc-vchh', 'https://github.com/tensorflow/tensorflow/commit/e9c81c1e1a9cd8dd31f4e83676cab61b60658429'} | null |
PyPI | PYSEC-2020-141 | null | In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched. | {'GHSA-9jjw-hf72-3mxw', 'CVE-2020-26269'} | 2020-12-14T17:42:00Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9jjw-hf72-3mxw', 'https://github.com/tensorflow/tensorflow/commit/8b5b9dc96666a3a5d27fad7179ff215e3b74b67c'} | null |
PyPI | GHSA-2ghc-6v89-pw9j | Prototype Pollution in body-parser-xml | body-parser-xml is vulnerable to Improperly Controlled Modification of Object Prototype Attributes ('Prototype Pollution') | {'CVE-2021-3666'} | 2021-09-14T18:39:31Z | 2021-09-14T20:25:35Z | HIGH | null | {'CWE-1321', 'CWE-915'} | {'https://github.com/fiznool/body-parser-xml/commit/d46ca622560f7c9a033cd9321c61e92558150d63', 'https://huntr.dev/bounties/1-other-fiznool/body-parser-xml', 'https://nvd.nist.gov/vuln/detail/CVE-2021-3666', 'https://github.com/fiznool/body-parser-xml'} | null |
PyPI | PYSEC-2021-511 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow. If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the 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-9xh4-23q4-v6wr', 'CVE-2021-29583'} | 2021-12-09T06:34:56.228145Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9xh4-23q4-v6wr'} | null |
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