ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2019-215 | null | A number of HTTP endpoints in the Airflow webserver (both RBAC and classic) did not have adequate protection and were vulnerable to cross-site request forgery attacks. | {'CVE-2019-0229', 'GHSA-w6j4-3gh2-9f5j'} | 2021-11-16T03:58:43.176949Z | 2019-04-10T20:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-w6j4-3gh2-9f5j', 'https://lists.apache.org/thread.html/2de387213d45bc626d27554a1bde7b8c67d08720901f82a50b6f4231@%3Cdev.airflow.apache.org%3E', 'http://www.securityfocus.com/bid/107869', 'http://www.openwall.com/lists/oss-security/2019/04/10/6'} | null |
PyPI | GHSA-fpwp-69xv-c67f | Moderate severity vulnerability that affects aiohttp-session | The pypi package aiohttp-session before 2.4.0 contained a Session Fixation vulnerability in load_session function for RedisStorage that can result in Session Hijacking. This attack appear to be exploitable via Any method that allows setting session cookies (?session=<>, or meta tags or script tags with Set-Cookie). | {'CVE-2018-1000519'} | 2022-03-03T05:13:40.535531Z | 2018-09-13T15:46:40Z | MODERATE | null | {'CWE-384'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-1000519', 'https://github.com/aio-libs/aiohttp-session/blob/master/aiohttp_session/redis_storage.py#L60', 'https://github.com/advisories/GHSA-fpwp-69xv-c67f', 'https://github.com/aio-libs/aiohttp-session/issues/272', 'https://github.com/aio-libs/aiohttp-session'} | null |
PyPI | PYSEC-2017-104 | null | An incorrect implementation of "XEP-0280: Message Carbons" in multiple XMPP clients allows a remote attacker to impersonate any user, including contacts, in the vulnerable application's display. This allows for various kinds of social engineering attacks. This CVE is for SleekXMPP up to 1.3.1 and Slixmpp all versions up to 1.2.3, as bundled in poezio (0.8 - 0.10) and other products. | {'CVE-2017-5591'} | 2021-12-14T08:19:29.481755Z | 2017-02-09T20:59:00Z | null | null | null | {'https://rt-solutions.de/wp-content/uploads/2017/02/CVE-2017-5589_xmpp_carbons.pdf', 'http://openwall.com/lists/oss-security/2017/02/09/29', 'https://nvd.nist.gov/vuln/detail/CVE-2017-5591', 'https://pypi.org/project/slixmpp', 'https://rt-solutions.de/en/2017/02/CVE-2017-5589_xmpp_carbons/', 'https://github.com/poezio/slixmpp/commit/22664ee7b86c8e010f312b66d12590fb47160ad8', 'http://www.securityfocus.com/bid/96166'} | null |
PyPI | GHSA-7mx5-x372-xh87 | Incorrect Session Validation in Apache Airflow | Incorrect Session Validation in Apache Airflow Webserver versions prior to 1.10.14 with default config allows a malicious airflow user on site A where they log in normally, to access unauthorized Airflow Webserver on Site B through the session from Site A. This does not affect users who have changed the default value for `[webserver] secret_key` config. | {'CVE-2020-17526'} | 2022-03-03T05:13:46.330427Z | 2021-04-20T16:40:27Z | HIGH | null | {'CWE-269'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-17526', 'https://lists.apache.org/thread.html/rbeeb73a6c741f2f9200d83b9c2220610da314810c4e8c9cf881d47ef%40%3Cusers.airflow.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2020/12/21/1', 'https://lists.apache.org/thread.html/r466759f377651f0a690475d5a52564d0e786e82c08d5a5730a4f8352@%3Cannounce.apache.org%3E'} | null |
PyPI | PYSEC-2020-253 | null | TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decoder in core/kernels/decode_bmp_op.cc. | {'CVE-2018-21233', 'GHSA-h98h-8mxr-m8gx'} | 2021-08-27T03:22:22.195752Z | 2020-05-04T15:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/49f73c55d56edffebde4bca4a407ad69c1cae433', 'https://github.com/advisories/GHSA-h98h-8mxr-m8gx', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-001.md'} | null |
PyPI | GHSA-cr3f-r24j-3chw | Cobbler before 3.3.0 allows authorization bypass for modification of settings. | Cobbler before 3.3.0 allows authorization bypass for modification of settings. | {'CVE-2021-40325'} | 2022-03-03T05:12:47.833092Z | 2021-10-05T17:53:29Z | MODERATE | null | {'CWE-863'} | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://github.com/cobbler/cobbler', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0', 'https://nvd.nist.gov/vuln/detail/CVE-2021-40325'} | null |
PyPI | PYSEC-2021-253 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of TrySimplify(https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc#L390-L401) has undefined behavior due to dereferencing a null pointer in corner cases that result in optimizing a node with no inputs. 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-4hvv-7x94-7vq8', 'CVE-2021-29616'} | 2021-08-27T03:22:42.041590Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hvv-7x94-7vq8', 'https://github.com/tensorflow/tensorflow/commit/e6340f0665d53716ef3197ada88936c2a5f7a2d3'} | null |
PyPI | PYSEC-2021-603 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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-2021-37690', 'GHSA-3hxh-8cp2-g4hg'} | 2021-12-09T06:35:06.680335Z | 2021-08-13T00:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg', 'https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1'} | null |
PyPI | PYSEC-2021-552 | null | TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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-gh6x-4whr-2qv4', 'CVE-2021-37639'} | 2021-12-09T06:35:02.331501Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/9e82dce6e6bd1f36a57e08fa85af213e2b2f2622', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh6x-4whr-2qv4'} | null |
PyPI | PYSEC-2014-53 | null | Multiple unspecified vulnerabilities in (1) dataitems.py, (2) get.py, and (3) traverseName.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allow remote authenticated users with administrator access to a subtree to access nodes above the subtree via unknown vectors. | {'CVE-2013-4189'} | 2021-07-25T23:34:45.892869Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'https://bugzilla.redhat.com/show_bug.cgi?id=978450', 'http://seclists.org/oss-sec/2013/q3/261', 'http://plone.org/products/plone/security/advisories/20130618-announcement'} | null |
PyPI | PYSEC-2021-102 | null | A Cross-site scripting (XSS) vulnerability exists in StackLift LocalStack 0.12.6. | {'CVE-2021-32091', 'GHSA-37m5-42qp-4qpr'} | 2021-06-22T04:54:56.108960Z | 2021-05-07T05:15:00Z | null | null | null | {'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://github.com/advisories/GHSA-37m5-42qp-4qpr'} | null |
PyPI | PYSEC-2018-70 | null | When you visit a page where you need to login, Plone 2.5-5.1rc1 sends you to the login form with a 'came_from' parameter set to the previous url. After you login, you get redirected to the page you tried to view before. An attacker might try to abuse this by letting you click on a specially crafted link. You would login, and get redirected to the site of the attacker, letting you think that you are still on the original Plone site. Or some javascript of the attacker could be executed. Most of these types of attacks are already blocked by Plone, using the `isURLInPortal` check to make sure we only redirect to a page on the same Plone site. But a few more ways of tricking Plone into accepting a malicious link were discovered, and fixed with this hotfix. | {'CVE-2017-1000481'} | 2021-08-25T04:30:16.749835Z | 2018-01-03T18:29:00Z | null | null | null | {'https://plone.org/security/hotfix/20171128/open-redirection-on-login-form'} | null |
PyPI | GHSA-8wwf-2644-f8x4 | Path traversal | The thefuck (aka The Fuck) package before 3.31 for Python allows Path Traversal that leads to arbitrary file deletion via the `undo archive operation` feature. | {'CVE-2021-34363'} | 2022-03-29T22:31:59.709279Z | 2021-06-15T15:49:01Z | CRITICAL | null | {'CWE-22'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4MEDDLBFVRUQHPYIBJ4MFM3M4NUJUXL5/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-34363', 'https://github.com/nvbn/thefuck/commit/e343c577cd7da4d304b837d4a07ab4df1e023092', 'https://vuln.ryotak.me/advisories/48', 'https://github.com/nvbn/thefuck/releases/tag/3.31', 'https://github.com/nvbn/thefuck', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YA6UNQSOY6M3NJDZLS6YJXTS4WGDMEEJ/'} | null |
PyPI | GHSA-99p8-9p2c-49j4 | 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-009
- Vulnerability type: Improper Access Control
- Threat level: Low
## Description:
Authenticated users (or unauthenticated in public mode) can send messages without being visible in the list of chat participants.
## Technical description:
Prerequisites:
- Existing chatroom
- Access to the chatroom (Public or known Private Key)
- Either a modified frontend client or manual requests from burp/curl
If a user opens the chatroom without emitting the join message he will not be present in session.users[x] list. Therefore there is no listing in the frontend and no chat participant knows another party joined the chat. It is still possible to send messages in the chatroom.
If a user decides to abuse OTF-003 (page 22) he can impersonate messages from existing users; others would not be able to distinguish original and faked messages. This is also a prerequisite for OTF-004 (page 19).
## Impact:
An adversary with access to the chat environment can send messages to the chat without being visible in the list of chat participants.
## Recommendation:
- Allow chat access only after emission of the join event.
- Implement proper session handling. | {'CVE-2022-21695'} | 2022-03-03T05:13:17.699341Z | 2022-01-21T23:20:16Z | MODERATE | null | {'CWE-287'} | {'https://github.com/onionshare/onionshare', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21695', 'https://github.com/onionshare/onionshare/releases/tag/v2.5', 'https://github.com/onionshare/onionshare/security/advisories/GHSA-99p8-9p2c-49j4'} | null |
PyPI | PYSEC-2010-10 | null | Memory leak in the on_dtp_close function in ftpserver.py in pyftpdlib before 0.5.2 allows remote authenticated users to cause a denial of service (memory consumption) by sending a QUIT command during a data transfer. | {'CVE-2009-5013'} | 2021-07-05T00:01:24.847543Z | 2010-10-19T20:00:00Z | null | null | null | {'http://code.google.com/p/pyftpdlib/issues/detail?id=119', 'http://code.google.com/p/pyftpdlib/source/detail?r=615', 'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY', 'http://code.google.com/p/pyftpdlib/source/diff?spec=svn615&r=615&format=side&path=/trunk/pyftpdlib/ftpserver.py'} | null |
PyPI | PYSEC-2021-801 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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-2021-37690', 'GHSA-3hxh-8cp2-g4hg'} | 2021-12-09T06:35:40.227651Z | 2021-08-13T00:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg', 'https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1'} | null |
PyPI | PYSEC-2020-102 | null | An issue was discovered in SaltStack Salt before 2019.2.4 and 3000 before 3000.2. The salt-master process ClearFuncs class does not properly validate method calls. This allows a remote user to access some methods without authentication. These methods can be used to retrieve user tokens from the salt master and/or run arbitrary commands on salt minions. | {'CVE-2020-11651'} | 2020-08-20T01:17:00Z | 2020-04-30T17:15:00Z | null | null | null | {'http://packetstormsecurity.com/files/157678/SaltStack-Salt-Master-Minion-Unauthenticated-Remote-Code-Execution.html', 'http://packetstormsecurity.com/files/157560/Saltstack-3000.1-Remote-Code-Execution.html', 'https://lists.debian.org/debian-lts-announce/2020/05/msg00027.html', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00047.html', 'https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-salt-2vx545AG', 'http://www.vmware.com/security/advisories/VMSA-2020-0009.html', 'https://docs.saltstack.com/en/latest/topics/releases/2019.2.4.html', 'https://usn.ubuntu.com/4459-1/', 'http://lists.opensuse.org/opensuse-security-announce/2020-07/msg00070.html', 'https://www.debian.org/security/2020/dsa-4676', 'https://github.com/saltstack/salt/blob/v3000.2_docs/doc/topics/releases/3000.2.rst'} | null |
PyPI | PYSEC-2022-24 | null | Flask-AppBuilder is an application development framework, built on top of the Flask web framework. In affected versions there exists a user enumeration vulnerability. This vulnerability allows for a non authenticated user to enumerate existing accounts by timing the response time from the server when you are logging in. Users are advised to upgrade to version 3.4.4 as soon as possible. There are no known workarounds for this issue. | {'CVE-2022-21659', 'GHSA-wfjw-w6pv-8p7f'} | 2022-02-07T21:26:59.516513Z | 2022-01-31T21:15:00Z | null | null | null | {'https://github.com/dpgaspar/Flask-AppBuilder/security/advisories/GHSA-wfjw-w6pv-8p7f', 'https://github.com/dpgaspar/Flask-AppBuilder/pull/1775'} | null |
PyPI | PYSEC-2020-19 | null | In Apache Airflow < 1.10.12, the "origin" parameter passed to some of the endpoints like '/trigger' was vulnerable to XSS exploit. | {'GHSA-4pwq-fj89-6rjc', 'CVE-2020-13944'} | 2021-05-04T00:15:00Z | 2020-09-17T14:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2021/05/01/2', 'http://www.openwall.com/lists/oss-security/2020/12/11/2', 'https://lists.apache.org/thread.html/r97e1b60ca508a86be58c43f405c0c8ff00ba467ba0bee68704ae7e3e%40%3Cdev.airflow.apache.org%3E', '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-4pwq-fj89-6rjc', '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-23c7-6444-399m | Improper Input Validation in sopel-plugins.channelmgnt | ### Impact
On some IRC servers, restrictions around the removal of the bot using the kick/kickban command could be bypassed when kicking multiple users at once.
We also believe it may have been possible to remove users from other channels but due to the wonder that is IRC and following RfCs, We have no POC for that.
Freenode is not affected.
### Patches
Upgrade to 2.0.1 or higher
### Workarounds
Do not use this plugin on networks where TARGMAX > 1.
### For more information
If you have any questions or comments about this advisory:
* Open an issue on [phab](https://phab.mirahezebots.org/maniphest/task/edit/form/1/).
* Email us at [staff(at)mirahezebots(dot)org](mailto:staff@mirahezebots.org) | {'CVE-2021-21431'} | 2022-03-03T05:13:40.160944Z | 2021-04-09T15:42:40Z | HIGH | null | {'CWE-20', 'CWE-284'} | {'https://github.com/MirahezeBots/sopel-channelmgnt/commit/7c96d400358221e59135f0a0be0744f3fad73856', 'https://github.com/MirahezeBots/sopel-channelmgnt/commit/643388365f28c5cc682254ab913c401f0e53260a', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21431', 'https://pypi.org/project/sopel-plugins.channelmgnt/', 'https://github.com/MirahezeBots/sopel-channelmgnt/security/advisories/GHSA-23c7-6444-399m'} | null |
PyPI | PYSEC-2019-144 | null | An issue was discovered in the arrayfire crate before 3.6.0 for Rust. Addition of the repr() attribute to an enum is mishandled, leading to memory corruption. | {'CVE-2018-20998'} | 2021-06-10T06:51:33.535067Z | 2019-08-26T18:15:00Z | null | null | null | {'https://rustsec.org/advisories/RUSTSEC-2018-0011.html'} | null |
PyPI | PYSEC-2016-1 | null | The create_script function in the lxc_container module in Ansible before 1.9.6-1 and 2.x before 2.0.2.0 allows local users to write to arbitrary files or gain privileges via a symlink attack on (1) /opt/.lxc-attach-script, (2) the archived container in the archive_path directory, or the (3) lxc-attach-script.log or (4) lxc-attach-script.err files in the temporary directory. | {'GHSA-rh6x-qvg7-rrmj', 'CVE-2016-3096'} | 2021-07-02T02:41:33.519196Z | 2016-06-03T14:59:00Z | null | null | null | {'https://github.com/ansible/ansible/blob/v2.0.2.0-1/CHANGELOG.md#202-over-the-hills-and-far-away', 'https://groups.google.com/forum/#!topic/ansible-announce/tqiZbcWxYig', 'https://security.gentoo.org/glsa/201607-14', 'https://github.com/ansible/ansible-modules-extras/pull/1941', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/183132.html', 'https://groups.google.com/forum/#!topic/ansible-announce/E80HLZilTU0', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/183274.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-May/184175.html', 'https://github.com/ansible/ansible/blob/v1.9.6-1/CHANGELOG.md#196-dancing-in-the-street---tbd', 'https://bugzilla.redhat.com/show_bug.cgi?id=1322925', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/183103.html', 'https://github.com/ansible/ansible-modules-extras/pull/1941/commits/8c6fe646ee79f5e55361b885b7efed5bec72d4a4', 'https://github.com/advisories/GHSA-rh6x-qvg7-rrmj', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/183252.html'} | null |
PyPI | PYSEC-2021-417 | null | TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's Grappler optimizer has a use of unitialized variable. If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized. 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-2021-41225', 'GHSA-7r94-xv9v-63jw'} | 2021-11-13T06:52:45.918636Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/68867bf01239d9e1048f98cbad185bf4761bedd3', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7r94-xv9v-63jw'} | null |
PyPI | GHSA-47qg-q58v-7vrp | UNEDITABLE_SCHEMAS and UNEDITABLE_TABLE_DESCRIPTION_MATCH_RULES not respected by frontend service backend | ### Impact
Any install that has `UNEDITABLE_SCHEMAS` and/or `UNEDITABLE_TABLE_DESCRIPTION_MATCH_RULES` set in the front-end, is being impacted. The value of these properties is ignored if set, allowing any user to modify table and column descriptions, even though the properties imply they shouldn't be.
### Patches
There is an attached PR that applies this restriction on the back-end.
### Workarounds
N/A
### References
N/A
### For more information
If you have any questions or comments about this advisory:
* Email us at [amundsen-security@lists.lfaidata.foundation](mailto:amundsen-security@lists.lfaidata.foundation)
### More details
Summary: I believe that UNEDITABLE_SCHEMAS and
UNEDITABLE_TABLE_DESCRIPTION_MATCH_RULES are only being applied on the
front-end, not on the frontend service back-end, allowing any user to
modify table and column descriptions even if this configuration parameter
is set.
Repro steps:
1. docker-compose -f docker-amundsen.yml up neo4j elasticsearch
amundsensearch amundsenmetadata
2. python example/scripts/sample_data_loader.py
3. FRONTEND_SVC_CONFIG_MODULE_CLASS=amundsen_application.config.TestConfig
PYTHONPATH=. python3 amundsen_application/wsgi.py
4. Attempt a modification to a table description:
curl '<http://localhost:5000/api/metadata/v0/put_table_description>' \\\\
-X 'PUT' \\\\
-H 'Content-Type: application/json;charset=UTF-8' \\\\
--data-binary '{"description":"2t test table","key":"hive://gold.test_schema/test_table1","source":"user"}'
{"msg":"Success"}
5. This correctly succeeds, which can be validated by GETing the info:
curl '<http://localhost:5000/api/metadata/v0/get_table_description?key=hive://gold.test_schema/test_table1>'
{"description":"1st test table","msg":"Success"}
At this point, modify TestConfig inside config.py to add this line: UNEDITABLE_SCHEMAS
= set(['test_schema'])
You can now re-run step 4, and step 5 with different data, and confirm
that the modification has persisted. If you build and run the UI, you can
see that on the page
<http://localhost:5000/table_detail/gold/hive/test_schema/test_table1>
http://localhost:5000/table_detail/gold/hive/test_schema/test_table1, the
inline editor is correctly disabled.
Looking at
amundsenfrontendlibrary/amundsen_application/api/metadata/v0.py:268
put_table_description, you can see there's no reference to
UNEDITABLE_SCHEMAS or UNEDITABLE_TABLE_DESCRIPTION_MATCH_RULES.
The only place I can find these referenced is in
amundsenfrontendlibrary/amundsen_application/api/utils/metadata_utils.py:marshall_table_full,
which would explain why the UI is correctly respecting this setting.
If this is correct, put_column_description would also be similarly
affected.
I believe the correct fix for all of these methods is to load the table,
run it through marshall_dashboard_partial to fully evaluate what's
editable or not (to reuse the same code path for FE and back-end), and
reject the response if it's not editable. I'll implement a fix along these
lines once someone confirms this.
History: This functionality was introduced in
<https://github.com/amundsen-io/amundsenfrontendlibrary/pull/497/files>
https://github.com/amundsen-io/amundsenfrontendlibrary/pull/497 on July
9, corresponding to the 2.3.0 release of amundsenfrontend. That release was
introduced into the main repo dockerfile on October 28 in
<https://github.com/amundsen-io/amundsen/pull/785>
https://github.com/amundsen-io/amundsen/pull/785 | null | 2022-03-03T05:12:41.098968Z | 2020-12-02T18:28:10Z | LOW | null | {'CWE-602'} | {'https://github.com/amundsen-io/amundsenfrontendlibrary/security/advisories/GHSA-47qg-q58v-7vrp', 'https://github.com/amundsen-io/amundsenfrontendlibrary/commit/0b47694ea74cbbef34e03eb45f29643b16a1332a'} | null |
PyPI | PYSEC-2017-43 | null | Cross-site scripting (XSS) vulnerability in the render_full function in debug/tbtools.py in the debugger in Pallets Werkzeug before 0.11.11 (as used in Pallets Flask and other products) allows remote attackers to inject arbitrary web script or HTML via a field that contains an exception message. | {'CVE-2016-10516'} | 2021-07-05T00:01:28.359311Z | 2017-10-23T16:29:00Z | null | null | null | {'http://blog.neargle.com/2016/09/21/flask-src-review-get-a-xss-from-debuger/', 'https://lists.debian.org/debian-lts-announce/2017/11/msg00037.html', 'https://github.com/pallets/werkzeug/pull/1001'} | null |
PyPI | GHSA-p9wf-3xpg-c9g5 | XML External Entity Injection in PyWPS | An XML external entity (XXE) injection in PyWPS before 4.5.0 allows an attacker to view files on the application server filesystem by assigning a path to the entity. OWSLib 0.24.1 may also be affected. | {'CVE-2021-39371'} | 2022-03-03T05:13:37.293430Z | 2021-09-02T17:11:13Z | HIGH | null | {'CWE-91', 'CWE-611'} | {'https://lists.debian.org/debian-lts-announce/2021/09/msg00001.html', 'https://github.com/geopython/pywps/pull/616', 'https://github.com/geopython/pywps', 'https://github.com/geopython/OWSLib/issues/790', 'https://nvd.nist.gov/vuln/detail/CVE-2021-39371'} | null |
PyPI | PYSEC-2021-694 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`. If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array. 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-4p4p-www8-8fv9', 'CVE-2021-29568'} | 2021-12-09T06:35:26.499647Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4p4p-www8-8fv9', 'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} | null |
PyPI | GHSA-3mw4-6rj6-74g5 | Null pointer dereference in TensorFlow | ### Impact
The [implementation of `QuantizedMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130) has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer.
```python
import tensorflow as tf
tf.raw_ops.QuantizedMaxPool(
input = tf.constant([[[[4]]]], dtype=tf.quint8),
min_input = [],
max_input = [1],
ksize = [1, 1, 1, 1],
strides = [1, 1, 1, 1],
padding = "SAME", name=None
)
```
### Patches
We have patched the issue in GitHub commit [53b0dd6dc5957652f35964af16b892ec9af4a559](https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia. | {'CVE-2022-21739'} | 2022-03-03T05:13:37.611501Z | 2022-02-09T23:46:46Z | MODERATE | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21739'} | null |
PyPI | GHSA-r35g-4525-29fq | Division by 0 in `FusedBatchNorm` | ### Impact
An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`:
```python
import tensorflow as tf
x = tf.constant([], shape=[1, 1, 1, 0], dtype=tf.float32)
scale = tf.constant([], shape=[0], dtype=tf.float32)
offset = tf.constant([], shape=[0], dtype=tf.float32)
mean = tf.constant([], shape=[0], dtype=tf.float32)
variance = tf.constant([], shape=[0], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False
tf.raw_ops.FusedBatchNorm(
x=x, scale=scale, offset=offset, mean=mean,
variance=variance, epsilon=epsilon,
exponential_avg_factor=exponential_avg_factor,
data_format=data_format, is_training=is_training)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor:
```cc
const int depth = x.dimension(3);
const int rest_size = size / depth;
```
Since this is controlled by the user, an attacker can trigger a denial of service.
### Patches
We have patched the issue in GitHub commit [1a2a87229d1d61e23a39373777c056161eb4084d](https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29555'} | 2022-03-03T05:10:28.715091Z | 2021-05-21T14:23:58Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r35g-4525-29fq', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29555'} | null |
PyPI | PYSEC-2021-34 | null | models/metadata.py in the pikepdf package 1.3.0 through 2.9.2 for Python allows XXE when parsing XMP metadata entries. | {'CVE-2021-29421', 'GHSA-ccgm-3xw4-h5p8'} | 2021-04-09T19:15:00Z | 2021-04-01T20:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-ccgm-3xw4-h5p8', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/36P4HTLBJPO524WMQWW57N3QRF4RFSJG/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3QFLBBYGEDNXJ7FS6PIWTVI4T4BUPGEQ/', 'https://github.com/pikepdf/pikepdf/commit/3f38f73218e5e782fe411ccbb3b44a793c0b343a'} | null |
PyPI | PYSEC-2021-381 | null | Rasa is an open source machine learning framework to automate text-and voice-based conversations. In affected versions a vulnerability exists in the functionality that loads a trained model `tar.gz` file which allows a malicious actor to craft a `model.tar.gz` file which can overwrite or replace bot files in the bot directory. The vulnerability is fixed in Rasa 2.8.10. For users unable to update ensure that users do not upload untrusted model files, and restrict CLI or API endpoint access where a malicious actor could target a deployed Rasa instance. | {'GHSA-4365-fhm5-qcrx', 'CVE-2021-41127'} | 2021-10-24T23:24:39.410729Z | 2021-10-21T21:15:00Z | null | null | null | {'https://github.com/RasaHQ/rasa/commit/1b6b502f52d73b4f8cd1959ce724b8ad0eb33989', 'https://github.com/RasaHQ/rasa/security/advisories/GHSA-4365-fhm5-qcrx'} | null |
PyPI | PYSEC-2020-155 | null | Waitress version 1.4.2 allows a DOS attack When waitress receives a header that contains invalid characters. When a header like "Bad-header: xxxxxxxxxxxxxxx\x10" is received, it will cause the regular expression engine to catastrophically backtrack causing the process to use 100% CPU time and blocking any other interactions. This allows an attacker to send a single request with an invalid header and take the service offline. This issue was introduced in version 1.4.2 when the regular expression was updated to attempt to match the behaviour required by errata associated with RFC7230. The regular expression that is used to validate incoming headers has been updated in version 1.4.3, it is recommended that people upgrade to the new version of Waitress as soon as possible. | {'CVE-2020-5236', 'GHSA-73m2-3pwg-5fgc'} | 2020-02-06T18:46:00Z | 2020-02-04T03:15:00Z | null | null | null | {'https://github.com/Pylons/waitress/security/advisories/GHSA-73m2-3pwg-5fgc', 'https://github.com/Pylons/waitress/commit/6e46f9e3f014d64dd7d1e258eaf626e39870ee1f'} | null |
PyPI | PYSEC-2021-856 | null | Null Pointer Dereference vulnerability exists in numpy.sort in NumPy < and 1.19 in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. | {'CVE-2021-41495'} | 2021-12-22T21:28:25.939120Z | 2021-12-17T20:15:00Z | null | null | null | {'https://github.com/numpy/numpy/issues/19038'} | null |
PyPI | PYSEC-2008-1 | null | Cross-site scripting (XSS) vulnerability in the login form in the administration application in Django 0.91 before 0.91.2, 0.95 before 0.95.3, and 0.96 before 0.96.2 allows remote attackers to inject arbitrary web script or HTML via the URI of a certain previous request. | {'CVE-2008-2302'} | 2021-07-15T02:22:07.778598Z | 2008-05-23T15:32:00Z | null | null | null | {'http://secunia.com/advisories/30250', 'http://www.vupen.com/english/advisories/2008/1618', 'http://www.djangoproject.com/weblog/2008/may/14/security/', 'http://www.securityfocus.com/bid/29209', 'http://secunia.com/advisories/30291', 'http://securitytracker.com/id?1020028', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/42396'} | null |
PyPI | PYSEC-2018-27 | null | qutebrowser before version 1.4.1 is vulnerable to a cross-site request forgery flaw that allows websites to access 'qute://*' URLs. A malicious website could exploit this to load a 'qute://settings/set' URL, which then sets 'editor.command' to a bash script, resulting in arbitrary code execution. | {'CVE-2018-10895', 'GHSA-wgmx-52ph-qqcw'} | 2021-06-10T06:51:37.378319Z | 2018-07-12T12:29:00Z | null | null | null | {'https://github.com/qutebrowser/qutebrowser/commit/43e58ac865ff862c2008c510fc5f7627e10b4660', 'http://www.openwall.com/lists/oss-security/2018/07/11/7', 'https://github.com/advisories/GHSA-wgmx-52ph-qqcw', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10895'} | null |
PyPI | GHSA-3c67-gc48-983w | Path Traversal in Ansible | An archive traversal flaw was found in all ansible-engine versions 2.9.x prior to 2.9.7, when running ansible-galaxy collection install. When extracting a collection .tar.gz file, the directory is created without sanitizing the filename. An attacker could take advantage to overwrite any file within the system. | {'CVE-2020-10691'} | 2022-03-03T05:13:28.998694Z | 2021-04-20T16:44:37Z | MODERATE | null | {'CWE-22'} | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-10691', 'https://github.com/ansible/ansible/pull/68596', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10691'} | null |
PyPI | PYSEC-2021-155 | null | TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-62gx-355r-9fhg', 'CVE-2021-29518'} | 2021-08-27T03:22:24.585448Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg', 'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | null |
PyPI | GHSA-q3m9-9fj2-mfwr | URL Redirection to Untrusted Site ('Open Redirect') in Products.isurlinportal | ### Impact
Various parts of Plone use the 'is url in portal' check for security, mostly to see if it is safe to redirect to a url. A url like `https://example.org` is not in the portal.
But the url `https:example.org` without slashes tricks our code and it _is_ considered to be in the portal.
When redirecting, some browsers go to `https://example.org`, others give an error.
Attackers may use this to redirect you to their site, especially as part of a phishing attack.
### Patches
The problem has been patched in `Products.isurlinportal` 1.2.0.
This is a recommended upgrade for all users of Plone 4.3 and 5, on Python 2.7 or higher.
It has not been tested on earlier Plone or Python versions.
Upcoming Plone 5.2.5 and higher will include the new version.
### Discovered
This vulnerability was discovered and reported by Yuji Tounai of Mitsui Bussan Secure Directions, Inc. Thank you!
### For more information
If you have any questions or comments about this advisory:
* Email the Plone Security Team at [security@plone.org](mailto:security@plone.org), especially when you think you have discovered a security problem or when you are not sure.
* Open an issue in [the tracker](https://github.com/plone/Products.isurlinportal/issues) if your question or comment can be public.
| {'CVE-2021-32806'} | 2022-03-03T05:12:39.025583Z | 2021-08-05T17:02:12Z | MODERATE | null | {'CWE-601'} | {'https://github.com/plone/Products.isurlinportal/commit/d4fd34990d18adf05a10dc5e2bb4b066798280ba', 'https://github.com/plone/Products.isurlinportal', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32806', 'https://github.com/plone/Products.isurlinportal/security/advisories/GHSA-q3m9-9fj2-mfwr', 'http://jvn.jp/en/jp/JVN50804280/index.html'} | null |
PyPI | PYSEC-2021-505 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-v6r6-84gr-92rm', 'CVE-2021-29577'} | 2021-12-09T06:34:55.310052Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6r6-84gr-92rm'} | null |
PyPI | PYSEC-2018-113 | null | Ajenti version 2 contains an Information Disclosure vulnerability in Line 176 of the code source that can result in user and system enumeration as well as data from the /etc/ajenti/config.yml file. This attack appears to be exploitable via network connectivity to the web application. | {'CVE-2018-1000126'} | 2022-02-17T09:17:11.143263Z | 2018-03-13T21:29:00Z | null | null | null | {'https://pypi.org/project/ajenti-panel', 'https://medium.com/stolabs/security-issues-on-ajenti-d2b7526eaeee', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000126'} | null |
PyPI | GHSA-4q2r-qxp6-h5j6 | Improper Restriction of XML External Entity Reference in Quokka | XML External Entities (XXE) in Quokka v0.4.0 allows remote attackers to execute arbitrary code via the component 'quokka/core/content/views.py'. | {'CVE-2020-18705'} | 2022-03-23T20:30:10.785209Z | 2021-08-30T16:25:18Z | CRITICAL | null | {'CWE-611'} | {'https://github.com/quokkaproject/quokka/pull/679', 'https://nvd.nist.gov/vuln/detail/CVE-2020-18705', 'https://github.com/rochacbruno/quokka/issues/676', 'https://github.com/rochacbruno/quokka'} | null |
PyPI | GHSA-893h-35v4-mxqx | Path Traversal in Ansible | A flaw was found in Ansible 2.7.17 and prior, 2.8.9 and prior, and 2.9.6 and prior when using the Extract-Zip function from the win_unzip module as the extracted file(s) are not checked if they belong to the destination folder. An attacker could take advantage of this flaw by crafting an archive anywhere in the file system, using a path traversal. This issue is fixed in 2.10. | {'CVE-2020-1737'} | 2022-03-03T05:13:15.897590Z | 2021-04-20T16:43:33Z | MODERATE | null | {'CWE-22'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/U3IMV3XEIUXL6S4KPLYYM4TVJQ2VNEP2/', 'https://github.com/ansible/ansible/issues/67795', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1737', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FWDK3QUVBULS3Q3PQTGEKUQYPSNOU5M3/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QT27K5ZRGDPCH7GT3DRI3LO4IVDVQUB7/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1737', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2021-440 | 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'} | 2021-12-09T06:34:45.216617Z | 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 | GHSA-87v6-crgm-2gfj | Division by zero in Tensorflow | ### Impact
The [implementation of `FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192) can be made to crash a TensorFlow process via a division by 0:
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.FractionalMaxPool(
value=tf.constant(value=[[[[1, 4, 2, 3]]]], dtype=tf.int64),
pooling_ratio=[1.0, 1.44, 1.73, 1.0],
pseudo_random=False,
overlapping=False,
deterministic=False,
seed=0,
seed2=0,
name=None)
```
### Patches
We have patched the issue in GitHub commit [ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb](https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia. | {'CVE-2022-21735'} | 2022-03-03T05:13:41.296850Z | 2022-02-10T00:21:32Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-87v6-crgm-2gfj', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192', 'https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21735'} | null |
PyPI | PYSEC-2019-113 | null | CRLF Injection in pypiserver 1.2.5 and below allows attackers to set arbitrary HTTP headers and possibly conduct XSS attacks via a %0d%0a in a URI. | {'CVE-2019-6802', 'GHSA-mh24-7wvg-v88g'} | 2019-01-25T19:42:00Z | 2019-01-25T04:29:00Z | null | null | null | {'https://github.com/pypiserver/pypiserver/issues/237', 'https://github.com/advisories/GHSA-mh24-7wvg-v88g'} | null |
PyPI | PYSEC-2022-73 | null | Tensorflow is an Open Source Machine Learning Framework. When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes. 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-8rcj-c8pj-v3m3', 'CVE-2022-23564'} | 2022-03-09T00:17:32.923545Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/14fea662350e7c26eb5fe1be2ac31704e5682ee6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8rcj-c8pj-v3m3'} | null |
PyPI | PYSEC-2012-6 | null | model/modelstorage.py in the Tryton application framework (trytond) before 2.4.0 for Python does not properly restrict access to the Many2Many field in the relation model, which allows remote authenticated users to modify the privileges of arbitrary users via a (1) create, (2) write, (3) delete, or (4) copy rpc call. | {'CVE-2012-0215'} | 2021-07-05T00:01:27.407587Z | 2012-07-12T20:55:00Z | null | null | null | {'http://www.debian.org/security/2012/dsa-2444', 'https://bugs.tryton.org/issue2476', 'http://hg.tryton.org/trytond/rev/8e64d52ecea4', 'http://news.tryton.org/2012/03/security-releases-for-all-supported.html'} | null |
PyPI | PYSEC-2021-769 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b. 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-2021-37658', 'GHSA-6p5r-g9mq-ggh2'} | 2021-12-09T06:35:37.342418Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2'} | null |
PyPI | GHSA-rhrq-64mq-hf9h | FPE in TFLite division operations | ### Impact
The implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc)
There is no check that the divisor tensor does not contain zero elements.
### Patches
We have patched the issue in GitHub commit [1e206baedf8bef0334cca3eb92bab134ef525a28](https://github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37683'} | 2021-08-24T17:06:32Z | 2021-08-25T14:40:16Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37683', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rhrq-64mq-hf9h', 'https://github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28'} | null |
PyPI | PYSEC-2021-293 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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-2021-37671', 'GHSA-qr82-2c78-4m8h'} | 2021-08-27T03:22:45.925209Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qr82-2c78-4m8h', 'https://github.com/tensorflow/tensorflow/commit/532f5c5a547126c634fefd43bbad1dc6417678ac'} | null |
PyPI | PYSEC-2021-339 | null | Improper Authentication in Lin-CMS-Flask v0.1.1 allows remote attackers to launch brute force login attempts without restriction via the 'login' function in the component 'app/api/cms/user.py'. | {'CVE-2020-18698'} | 2022-03-16T02:19:49.985623Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/TaleLin/lin-cms-flask/issues/27'} | null |
PyPI | PYSEC-2020-293 | null | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. | {'CVE-2020-15213', 'GHSA-hjmq-236j-8m87'} | 2021-12-09T06:34:43.849481Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a'} | null |
PyPI | GHSA-qc9x-gjcv-465w | Pipenv's requirements.txt parsing allows malicious index url in comments | ## Issue Summary
Due to a flaw in pipenv's parsing of requirements files, an attacker can insert a specially crafted string inside a comment anywhere within a requirements.txt file, which will cause victims who use pipenv to install the requirements file (e.g. with "`pipenv install -r requirements.txt`") to download dependencies from a package index server controlled by the attacker. By embedding malicious code in packages served from their malicious index server, the attacker can trigger arbitrary remote code execution (RCE) on the victims' systems.
### Impact
The impact of successful exploitation is **severe/critical**.
If an attacker is able to hide a malicious `--index-url` option in a requirements file that a victim installs with pipenv, the attacker can embed arbitrary malicious code in packages served from their malicious index server that will be executed on the victim's host during installation (remote code execution/RCE). Exploitation using this technique would be relatively simple to achieve for an attacker with basic knowledge of Python, as the attacker can simply build a source distribution for any of the packages specified in the requirements file, and embed arbitrary malicious code in the setup.py file. When pip installs from a source distribution, any code in the setup.py is executed by the install process.
Basic attacks might use the initial RCE triggered when a victim installs the attacker's malicious package to steal credentials from the victim's host, leach the host's resources to mine cryptocurrency, or install exploit kits or other malware. More sophisticated attackers may use more advanced techniques to persist access to the victim's host, hide or remove evidence of their attack by deleting references to the malicious index server in the Pipfile and Pipfile.lock generated by pipenv or other potential indicators of compromise. Highly sophisticated attackers could attempt to pivot to additional targets from the initial compromised host, and might leverage any exposed credentials in the compromised host environment or implicit authorization granted to the host to gain privileged access to other systems or resources, such as source repositories or package registries.
### Likelihood
The overall likelihood of exploitation is **low to moderate** depending on a range of factors.
The primary hurdle to successful exploitation of this vulnerability depends on an attacker's ability to surreptitiously insert a specially crafted string into a requirements.txt file which will be installed by a victim (or victims). Unfortunately, because the attacker can insert this string into a comment, the attacker's ability to evade suspicion is greatly increased, and they may even be able to hide the initial payload in plain sight if a victim assumes that comments will be ignored by pipenv as expected.
In many common usage contexts — for example in environments where a requirements file is used to lock or "freeze" dependency versions for reproducible builds — requirements files can often become quite large, particularly when leveraging pip's integrity checking, which requires every dependency specified in the requirements file to includes hashes for all of its distribution files. In such cases, a malicious actor might mask an exploitation attempt by opening a pull request ostensibly to update or "bump" the project's dependencies to their latest versions, but surreptitiously insert a malicious `—index-url` option amidst the many other changes associated with updating the dependencies in a lock file. As these dependency updates often result in hundreds or even thousands of changes spread across the requirements file and are not easy to review manually, such an attack could be difficult to identify or prevent without tools or other mitigating controls.
Moreover, because the `argparse` module is used to parse the `--index-url`, `--extra-index-url`, and `--trusted-host` options, an attacker's ability to obfuscate their payload and hide their malicious intent is even more greatly enhanced, as the attacker may use abbreviated option names, which are supported by default with `argparse`. For example, an attacker can insert the string, "`--t pypi.org`" into a comment anywhere in the requirements file, which will automatically be expanded to "`--trusted-host pypi.org`" during processing by pipenv. This "`--trusted-host pypi.org`" option will disable SSL/TLS validation when pipenv attempts to connect to the default/official package index server (https://pypi.org/simple), and could allow a malicious index server to pose as the pipi.org index server in a man-in-the-middle attack.
Setting up the malicious index server to serve compromised package versions is relatively simple, even for a non-sophisticated attacker. As `pip` uses a simple directory format for serving packages, the malicious packages simply need to be placed in the correct folder structure and served using an HTTP server with autoindex enabled (e.g. `python3 -m http.server`).
Packaging up the exploit code into the malicious package versions would also be trivial for an attacker with basic knowledge of Python development, as the attacker can simply clone the source code for any of the packages specified in the requirements file, embed their malicious exploit code in the cloned package's setup.py file, and then build a source distribution of the package. When pip installs a package from a source distribution, any code in the setup.py is executed by the install process.
### Additional Context & Details
According to the requirements file format specification (https://pip.pypa.io/en/stable/reference/requirements-file-format/#comments), any lines which begin with a "#" character, and/or any text in a line following a whitespace and a "#" character, should be interpreted as a comment which will be removed/ignored during processing of the requirements file.
However, due to a flaw in pipenv's parsing of requirements files, an attacker can insert a specially crafted string inside a comment anywhere within a requirements.txt file, which will cause victims who use pipenv to install the requirements file (e.g. with "`pipenv install -r requirements.txt`") to download dependencies from a package index server controlled by the attacker. By embedding malicious code in packages served from their malicious index server, the attacker is then able to gain arbitrary remote code execution on the victims' systems.
The vulnerable requirements file parsing code is in the parse_indexes(str: line) function of the pipenv.utils module:
https://github.com/pypa/pipenv/blob/cdde3f7bcee6bacba89538f73aba9401337be10c/pipenv/utils.py#L2061-L2078
This function is called iteratively on each line of a requirements file, and uses the argparse module to find and process `--index-url`, `--extra-index-url`, and `--trusted-host` options (and variations thereof). However, it does not ignore these options when they appear in comments, or validate that these options appear on their own lines as required by the requirements file specification (see: https://pip.pypa.io/en/stable/reference/requirements-file-format/#global-options). The options can also be abbreviated due to default behavior provided by the `argparse.ArgumentParser` object used to parse these options in the requirements file, so that `--trusted-host` and `--t` will be treated as equivalent by pipenv, for example.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [https://github.com/pypa/pipenv/](https://github.com/pypa/pipenv/)
* Contact the pipenv maintainers:
* [Dan Ryan](https://github.com/techalchemy)
* [Tzu-ping Chung](https://github.com/uranusjr)
* [Nate Prewitt](https://github.com/nateprewitt)
* Contact the contributor who discovered the issue and authored this report:
* [Chris Passarello](https://github.com/milo-minderbinder) | {'CVE-2022-21668'} | 2022-03-30T16:46:59.674900Z | 2022-01-12T22:29:41Z | HIGH | null | {'CWE-20', 'CWE-77'} | {'https://github.com/pypa/pipenv/releases/tag/v2022.1.8', 'https://github.com/pypa/pipenv/security/advisories/GHSA-qc9x-gjcv-465w', 'https://github.com/pypa/pipenv', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/KCROBYHUS6DKQPCXBRPCZ5CDBNQTYAWT/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QHQRIWKDP3SVJABAPEXBIQPKDI6UP7G4/', 'https://github.com/pypa/pipenv/commit/439782a8ae36c4762c88e43d5f0d8e563371b46f', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21668', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/56HBA3EOSLEDNCCBJVHE6DO34P56EOUM/'} | null |
PyPI | PYSEC-2020-339 | null | XML external entity (XXE) vulnerability in PyAMF before 0.8.0 allows remote attackers to cause a denial of service or read arbitrary files via a crafted Action Message Format (AMF) payload. | {'CVE-2015-8549'} | 2021-12-14T08:18:22.975601Z | 2020-01-15T15:15:00Z | null | null | null | {'https://github.com/hydralabs/pyamf/releases/tag/v0.8.0', 'https://nvd.nist.gov/vuln/detail/CVE-2015-8549', 'http://www.ocert.org/advisories/ocert-2015-011.html', 'http://www.securityfocus.com/archive/1/archive/1/537151/100/0/threaded', 'https://pypi.org/project/pyamf', 'https://github.com/hydralabs/pyamf/pull/58'} | null |
PyPI | PYSEC-2017-14 | null | The serializer in html5lib before 0.99999999 might allow remote attackers to conduct cross-site scripting (XSS) attacks by leveraging mishandling of the < (less than) character in attribute values. | {'CVE-2016-9909'} | 2021-07-05T00:01:21.837127Z | 2017-02-22T16:59:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2016/12/08/8', 'https://html5lib.readthedocs.io/en/latest/changes.html#b9', 'http://www.securityfocus.com/bid/95132', 'https://github.com/html5lib/html5lib-python/issues/12', 'https://github.com/html5lib/html5lib-python/issues/11', 'http://www.openwall.com/lists/oss-security/2016/12/06/5', 'https://github.com/html5lib/html5lib-python/commit/9b8d8eb5afbc066b7fac9390f5ec75e5e8a7cab7'} | null |
PyPI | PYSEC-2015-29 | null | RhodeCode before 2.2.7 and Kallithea 0.1 allows remote authenticated users to obtain API keys and other sensitive information via the get_repo API method. | {'CVE-2015-0260'} | 2021-07-25T23:49:37.203310Z | 2015-02-16T15:59:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/100888', 'https://kallithea-scm.org/security/cve-2015-0260.html', 'http://seclists.org/oss-sec/2015/q1/505', 'https://rhodecode.com/blog/rhodecode-enterprise-security-release/', 'http://www.securityfocus.com/bid/72573'} | null |
PyPI | GHSA-8fg4-j562-mjrc | Low severity vulnerability that affects apache-airflow | In Apache Airflow 1.8.2 and earlier, an authenticated user can execute code remotely on the Airflow webserver by creating a special object. | {'CVE-2017-15720'} | 2022-03-03T05:13:23.157394Z | 2019-01-25T16:19:01Z | HIGH | null | {'CWE-20'} | {'https://github.com/advisories/GHSA-8fg4-j562-mjrc', 'https://nvd.nist.gov/vuln/detail/CVE-2017-15720', 'https://lists.apache.org/thread.html/ade4d54ebf614f68dc81a08891755e60ea58ba88e0209233eeea5f57@%3Cdev.airflow.apache.org%3E'} | null |
PyPI | GHSA-hvmf-r92r-27hr | Django allows unintended model editing | Django 2.1 before 2.1.15 and 2.2 before 2.2.8 allows unintended model editing. A Django model admin displaying inline related models, where the user has view-only permissions to a parent model but edit permissions to the inline model, would be presented with an editing UI, allowing POST requests, for updating the inline model. Directly editing the view-only parent model was not possible, but the parent model's save() method was called, triggering potential side effects, and causing pre and post-save signal handlers to be invoked. (To resolve this, the Django admin is adjusted to require edit permissions on the parent model in order for inline models to be editable.) | {'CVE-2019-19118'} | 2022-03-03T05:12:44.044245Z | 2019-12-04T21:26:28Z | MODERATE | null | {'CWE-276'} | {'https://github.com/django/django/commit/103ebe2b5ff1b2614b85a52c239f471904d26244', 'https://nvd.nist.gov/vuln/detail/CVE-2019-19118', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/6R4HD22PVEVQ45H2JA2NXH443AYJOPL5/', 'http://www.openwall.com/lists/oss-security/2019/12/02/1', 'https://security.gentoo.org/glsa/202004-17', 'https://security.netapp.com/advisory/ntap-20191217-0003/', 'https://www.djangoproject.com/weblog/2019/dec/02/security-releases/', 'https://groups.google.com/forum/#!topic/django-announce/GjGqDvtNmWQ', 'https://docs.djangoproject.com/en/dev/releases/security/', 'https://github.com/django/django/commit/36f580a17f0b3cb087deadf3b65eea024f479c21'} | null |
PyPI | PYSEC-2021-63 | null | In the cryptography package before 3.3.2 for Python, certain sequences of update calls to symmetrically encrypt multi-GB values could result in an integer overflow and buffer overflow, as demonstrated by the Fernet class. | {'GHSA-rhm9-p9w5-fwm7', 'CVE-2020-36242'} | 2021-02-19T17:23:00Z | 2021-02-07T20:15:00Z | null | null | null | {'https://github.com/pyca/cryptography/issues/5615', 'https://github.com/pyca/cryptography/compare/3.3.1...3.3.2', 'https://github.com/pyca/cryptography/blob/master/CHANGELOG.rst', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/L7RGQLK4J5ZQFRLKCHVVG6BKZTUQMG7E/', 'https://github.com/advisories/GHSA-rhm9-p9w5-fwm7'} | null |
PyPI | GHSA-ccmq-qvcp-5mrm | Critical severity vulnerability that affects owlmixin | An exploitable vulnerability exists in the YAML loading functionality of util.py in OwlMixin before 2.0.0a12. A "Load YAML" string or file (aka load_yaml or load_yamlf) can execute arbitrary Python commands resulting in command execution because load is used where safe_load should have been used. An attacker can insert Python into loaded YAML to trigger this vulnerability. | {'CVE-2017-16618'} | 2022-03-22T22:01:52.729397Z | 2018-07-13T16:01:12Z | CRITICAL | null | null | {'https://github.com/advisories/GHSA-ccmq-qvcp-5mrm', 'https://joel-malwarebenchmark.github.io/blog/2017/11/08/cve-2017-16618-convert-through-owlmixin/', 'https://nvd.nist.gov/vuln/detail/CVE-2017-16618', 'https://github.com/tadashi-aikawa/owlmixin', 'https://github.com/tadashi-aikawa/owlmixin/issues/12', 'https://github.com/tadashi-aikawa/owlmixin/commit/5d0575303f6df869a515ced4285f24ba721e0d4e'} | null |
PyPI | PYSEC-2021-786 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. 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-2021-37675', 'GHSA-9c8h-2mv3-49ww'} | 2021-12-09T06:35:38.896417Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww'} | null |
PyPI | PYSEC-2021-513 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mv78-g7wq-mhp4', 'CVE-2021-29585'} | 2021-12-09T06:34:56.553875Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mv78-g7wq-mhp4', 'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948'} | null |
PyPI | PYSEC-2014-12 | null | The OpenStack Python client library for Swift (python-swiftclient) 1.0 through 1.9.0 does not verify X.509 certificates from SSL servers, which allows man-in-the-middle attackers to spoof servers and obtain sensitive information via a crafted certificate. | {'CVE-2013-6396'} | 2021-07-05T00:01:25.452828Z | 2014-02-18T19:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2014/02/17/7', 'https://bugs.launchpad.net/python-swiftclient/+bug/1199783'} | null |
PyPI | PYSEC-2021-143 | null | 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'. | {'GHSA-5m69-3chg-6f8m', 'CVE-2020-18702'} | 2021-08-27T03:22:19.002010Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/rochacbruno/quokka/issues/675', 'https://github.com/advisories/GHSA-5m69-3chg-6f8m'} | null |
PyPI | GHSA-m3f9-w3p3-p669 | Heap buffer overflow in `QuantizedMul` | ### Impact
An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization:
```python
import tensorflow as tf
x = tf.constant([256, 328], shape=[1, 2], dtype=tf.quint8)
y = tf.constant([256, 328], shape=[1, 2], dtype=tf.quint8)
min_x = tf.constant([], dtype=tf.float32)
max_x = tf.constant([], dtype=tf.float32)
min_y = tf.constant([], dtype=tf.float32)
max_y = tf.constant([], dtype=tf.float32)
tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly:
```cc
const float min_x = context->input(2).flat<float>()(0);
const float max_x = context->input(3).flat<float>()(0);
const float min_y = context->input(4).flat<float>()(0);
const float max_y = context->input(5).flat<float>()(0);
```
However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow.
### Patches
We have patched the issue in GitHub commit [efea03b38fb8d3b81762237dc85e579cc5fc6e87](https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29535'} | 2022-03-03T05:13:58.080072Z | 2021-05-21T14:22:28Z | LOW | null | {'CWE-787', 'CWE-131'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29535', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669', 'https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87'} | null |
PyPI | PYSEC-2018-31 | null | tlslite-ng version 0.7.3 and earlier, since commit d7b288316bca7bcdd082e6ccff5491e241305233 contains a CWE-354: Improper Validation of Integrity Check Value vulnerability in TLS implementation, tlslite/utils/constanttime.py: ct_check_cbc_mac_and_pad(); line "end_pos = data_len - 1 - mac.digest_size" that can result in an attacker manipulating the TLS ciphertext which will not be detected by receiving tlslite-ng. This attack appears to be exploitable via man in the middle on a network connection. This vulnerability appears to have been fixed after commit 3674815d1b0f7484454995e2737a352e0a6a93d8. | {'GHSA-cwh5-3cw7-4286', 'CVE-2018-1000159'} | 2021-06-16T00:03:25.014006Z | 2018-04-18T19:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-cwh5-3cw7-4286', 'https://github.com/tomato42/tlslite-ng/pull/234'} | null |
PyPI | PYSEC-2021-840 | null | A dependency confusion vulnerability was reported in the Antilles open-source software prior to version 1.0.1 that could allow for remote code execution during installation due to a package listed in requirements.txt not existing in the public package index (PyPi). MITRE classifies this weakness as an Uncontrolled Search Path Element (CWE-427) in which a private package dependency may be replaced by an unauthorized package of the same name published to a well-known public repository such as PyPi. The configuration has been updated to only install components built by Antilles, removing all other public package indexes. Additionally, the antilles-tools dependency has been published to PyPi. | {'GHSA-hgc3-hp6x-wpgx', 'CVE-2021-3840'} | 2021-12-13T06:35:07.662600Z | 2021-11-12T22:15:00Z | null | null | null | {'https://github.com/lenovo/Antilles/security/advisories/GHSA-hgc3-hp6x-wpgx'} | null |
PyPI | PYSEC-2017-5 | null | An exploitable vulnerability exists in the yaml loading functionality of ansible-vault before 1.0.5. A specially crafted vault can execute arbitrary python commands resulting in command execution. An attacker can insert python into the vault to trigger this vulnerability. | {'CVE-2017-2809'} | 2021-07-05T00:01:14.915465Z | 2017-09-14T19:29:00Z | null | null | null | {'https://www.talosintelligence.com/vulnerability_reports/TALOS-2017-0305', 'https://github.com/tomoh1r/ansible-vault/issues/4', 'http://www.securityfocus.com/bid/100824', 'https://github.com/tomoh1r/ansible-vault/commit/3f8f659ef443ab870bb19f95d43543470168ae04', 'https://github.com/tomoh1r/ansible-vault/blob/v1.0.5/CHANGES.txt'} | null |
PyPI | PYSEC-2020-143 | null | tlslite-ng is an open source python library that implements SSL and TLS cryptographic protocols. In tlslite-ng before versions 0.7.6 and 0.8.0-alpha39, the code that performs decryption and padding check in RSA PKCS#1 v1.5 decryption is data dependant. In particular, the code has multiple ways in which it leaks information about the decrypted ciphertext. It aborts as soon as the plaintext doesn't start with 0x00, 0x02. All TLS servers that enable RSA key exchange as well as applications that use the RSA decryption API directly are vulnerable. This is patched in versions 0.7.6 and 0.8.0-alpha39. Note: the patches depend on Python processing the individual bytes in side-channel free manner, this is known to not the case (see reference). As such, users that require side-channel resistance are recommended to use different TLS implementations, as stated in the security policy of tlslite-ng. | {'CVE-2020-26263', 'GHSA-wvcv-832q-fjg7'} | 2020-12-23T16:09:00Z | 2020-12-21T17:15:00Z | null | null | null | {'https://github.com/tlsfuzzer/tlslite-ng/security/advisories/GHSA-wvcv-832q-fjg7', 'https://pypi.org/project/tlslite-ng/', 'https://github.com/tlsfuzzer/tlslite-ng/pull/438', 'https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/', 'https://github.com/tlsfuzzer/tlslite-ng/commit/c28d6d387bba59d8bd5cb3ba15edc42edf54b368', 'https://github.com/tlsfuzzer/tlslite-ng/pull/439'} | null |
PyPI | GHSA-qppg-v75c-r5ff | S3Scanner before 2.0.2 allows Directory Traversal | S3Scanner before 2.0.2 allows Directory Traversal via a crafted bucket, as demonstrated by a <Key>../ substring in a ListBucketResult element. | {'CVE-2021-32061'} | 2022-03-03T05:14:18.930054Z | 2021-11-30T22:21:36Z | MODERATE | null | {'CWE-22'} | {'https://github.com/sa7mon/S3Scanner/', 'https://github.com/sa7mon/S3Scanner/issues/122', 'https://github.com/sa7mon/S3Scanner/releases/tag/2.0.2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-32061', 'https://vuln.ryotak.me/advisories/62'} | null |
PyPI | GHSA-m956-frf4-m2wr | Ansible is vulnerable to an improper input validation in Ansible's handling of data sent from client systems | Ansible before versions 2.1.4, 2.2.1 is vulnerable to an improper input validation in Ansible's handling of data sent from client systems. An attacker with control over a client system being managed by Ansible and the ability to send facts back to the Ansible server could use this flaw to execute arbitrary code on the Ansible server using the Ansible server privileges. | {'CVE-2016-9587'} | 2022-04-26T18:47:54.824600Z | 2018-10-10T17:22:53Z | HIGH | null | {'CWE-20'} | {'http://rhn.redhat.com/errata/RHSA-2017-0195.html', 'https://security.gentoo.org/glsa/201701-77', 'http://rhn.redhat.com/errata/RHSA-2017-0260.html', 'https://access.redhat.com/errata/RHSA-2017:0448', 'https://access.redhat.com/errata/RHSA-2017:1685', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2016-9587', 'https://access.redhat.com/errata/RHSA-2017:0515', 'https://github.com/ansible/ansible', 'http://www.securityfocus.com/bid/95352', 'https://github.com/advisories/GHSA-m956-frf4-m2wr', 'https://www.exploit-db.com/exploits/41013/', 'https://nvd.nist.gov/vuln/detail/CVE-2016-9587'} | null |
PyPI | GHSA-fjq3-5pxw-4wj4 | Cross-Site Request Forgery in Webargs | flaskparser.py in Webargs 5.x through 5.5.2 doesn't check that the Content-Type header is application/json when receiving JSON input. If the request body is valid JSON, it will accept it even if the content type is application/x-www-form-urlencoded. This allows for JSON POST requests to be made across domains, leading to CSRF. | {'CVE-2020-7965'} | 2022-03-03T05:13:49.252451Z | 2021-04-07T21:06:30Z | MODERATE | null | {'CWE-352'} | {'https://webargs.readthedocs.io/en/latest/changelog.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-7965'} | null |
PyPI | PYSEC-2022-65 | null | Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-428x-9xc2-m8mj', 'CVE-2022-21741'} | 2022-03-09T00:17:31.924375Z | 2022-02-03T15:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e5b0eec199c2d03de54fd6a7fd9275692218e2bc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-428x-9xc2-m8mj', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/depthwise_conv.cc#L96'} | null |
PyPI | GHSA-fxjm-wvj9-9c39 | Information disclosure in Apache Superset | An information disclosure issue was found in Apache Superset 0.34.0, 0.34.1, 0.35.0, and 0.35.1. Authenticated Apache Superset users are able to retrieve other users' information, including hashed passwords, by accessing an unused and undocumented API endpoint on Apache Superset. | {'CVE-2020-1932'} | 2022-03-03T05:12:56.974737Z | 2020-02-26T19:54:57Z | MODERATE | null | {'CWE-200'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-1932', 'https://lists.apache.org/thread.html/r4e5323c3bc786005495311a6ff53ac6d990b2c7eb52941a1a13ce227%40%3Cdev.superset.apache.org%3E'} | null |
PyPI | PYSEC-2019-105 | null | The modoboa-dmarc plugin 1.1.0 for Modoboa is vulnerable to an XML External Entity Injection (XXE) attack when processing XML data. A remote attacker could exploit this to perform a denial of service against the DMARC reporting functionality, such as by referencing the /dev/random file within XML documents that are emailed to the address in the rua field of the DMARC records of a domain. | {'CVE-2019-19702'} | 2019-12-19T15:11:00Z | 2019-12-10T20:15:00Z | null | null | null | {'https://github.com/modoboa/modoboa-dmarc/issues/38'} | null |
PyPI | PYSEC-2021-456 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29528', 'GHSA-6f84-42vf-ppwp'} | 2021-12-09T06:34:47.721328Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f84-42vf-ppwp'} | null |
PyPI | PYSEC-2018-105 | null | Incorrect implementation of access controls allows remote users to override repository restrictions in Borg servers 1.1.x before 1.1.3. | {'CVE-2017-15914'} | 2021-11-24T22:46:40.919619Z | 2018-02-08T23:29:00Z | null | null | null | {'http://borgbackup.readthedocs.io/en/stable/changes.html#version-1-1-3-2017-11-27'} | null |
PyPI | GHSA-h582-2pch-3xv3 | High severity vulnerability that affects django | The session backends in Django before 1.4.21, 1.5.x through 1.6.x, 1.7.x before 1.7.9, and 1.8.x before 1.8.3 allows remote attackers to cause a denial of service (session store consumption) via multiple requests with unique session keys. | {'CVE-2015-5143'} | 2022-03-03T05:12:55.972342Z | 2019-07-05T21:10:39Z | HIGH | null | null | {'http://www.securityfocus.com/bid/75666', 'http://rhn.redhat.com/errata/RHSA-2015-1686.html', 'http://www.securitytracker.com/id/1032820', 'http://www.debian.org/security/2015/dsa-3305', 'https://github.com/advisories/GHSA-h582-2pch-3xv3', 'http://www.ubuntu.com/usn/USN-2671-1', 'http://www.oracle.com/technetwork/topics/security/bulletinoct2015-2511968.html', 'https://www.djangoproject.com/weblog/2015/jul/08/security-releases/', 'http://lists.opensuse.org/opensuse-updates/2015-10/msg00043.html', 'http://rhn.redhat.com/errata/RHSA-2015-1678.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-November/172084.html', 'https://security.gentoo.org/glsa/201510-06', 'https://nvd.nist.gov/vuln/detail/CVE-2015-5143', 'http://lists.opensuse.org/opensuse-updates/2015-10/msg00046.html'} | null |
PyPI | GHSA-xq58-69h2-765m | Cross Site Request Forgery in mailman | In GNU Mailman before 2.1.38, a list member or moderator can get a CSRF token and craft an admin request (using that token) to set a new admin password or make other changes. | {'CVE-2021-44227'} | 2022-03-03T05:12:39.915575Z | 2021-12-16T15:27:06Z | HIGH | null | {'CWE-352'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-44227', 'https://bugs.launchpad.net/mailman/+bug/1952384', 'https://gitlab.com/mailman/mailman'} | null |
PyPI | GHSA-879r-7f3w-8jj3 | Moderate severity vulnerability that affects Plone and Zope2 | The App.Undo.UndoSupport.get_request_var_or_attr function in Zope before 2.12.21 and 3.13.x before 2.13.11, as used in Plone before 4.2.3 and 4.3 before beta 1, allows remote authenticated users to gain access to restricted attributes via unspecified vectors. | {'CVE-2012-5489'} | 2022-03-03T05:14:04.543584Z | 2018-07-23T19:52:06Z | MODERATE | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://plone.org/products/plone/security/advisories/20121106/05', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://nvd.nist.gov/vuln/detail/CVE-2012-5489', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://bugs.launchpad.net/zope2/+bug/1079238', 'https://github.com/advisories/GHSA-879r-7f3w-8jj3'} | null |
PyPI | PYSEC-2020-285 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15205', 'GHSA-g7p5-5759-qv46'} | 2021-12-09T06:34:42.433318Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46', 'https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-95jp-77w6-qj52 | Cross-site Scripting in python-cjson | Python-cjson 1.0.5 does not properly handle a ['/'] argument to cjson.encode, which makes it easier for remote attackers to conduct certain cross-site scripting (XSS) attacks involving Firefox and the end tag of a SCRIPT element. | {'CVE-2009-4924'} | 2022-03-03T05:13:42.720950Z | 2021-12-06T18:17:45Z | MODERATE | null | {'CWE-79'} | {'http://pypi.python.org/pypi/python-cjson/', 'https://nvd.nist.gov/vuln/detail/CVE-2009-4924', 'http://t3.dotgnu.info/blog/insecurity/quotes-dont-help.html', 'https://github.com/pypa/advisory-db/tree/main/vulns/python-cjson/PYSEC-2010-26.yaml'} | null |
PyPI | GHSA-wvjw-p9f5-vq28 | Segfault in `tf.raw_ops.SparseCountSparseOutput` | ### Impact
Passing invalid arguments (e.g., discovered via fuzzing) to `tf.raw_ops.SparseCountSparseOutput` results in segfault.
### Patches
We have patched the issue in GitHub commit [82e6203221865de4008445b13c69b6826d2b28d9](https://github.com/tensorflow/tensorflow/commit/82e6203221865de4008445b13c69b6826d2b28d9).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2021-29619'} | 2022-03-03T05:13:41.308754Z | 2021-05-21T14:29:02Z | LOW | null | {'CWE-755'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29619', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wvjw-p9f5-vq28', 'https://github.com/tensorflow/tensorflow/commit/82e6203221865de4008445b13c69b6826d2b28d9'} | null |
PyPI | GHSA-ggmv-6q9p-9gm6 | Cross-site Scripting in django-unicorn | The Unicorn framework before 0.36.1 for Django allows XSS via a component. NOTE: this issue exists because of an incomplete fix for CVE-2021-42053. | {'CVE-2021-42134'} | 2022-03-03T05:13:20.261904Z | 2021-10-12T17:51:04Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-42134', 'https://github.com/adamghill/django-unicorn', 'https://github.com/adamghill/django-unicorn/commit/3a832a9e3f6455ddd3b87f646247269918ad10c6', 'https://github.com/adamghill/django-unicorn/compare/0.36.0...0.36.1'} | null |
PyPI | PYSEC-2021-285 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-g25h-jr74-qp5j', 'CVE-2021-37663'} | 2021-08-27T03:22:45.209094Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g25h-jr74-qp5j', 'https://github.com/tensorflow/tensorflow/commit/6da6620efad397c85493b8f8667b821403516708'} | null |
PyPI | GHSA-c7gp-2pch-qh2v | Out-of-bounds Write in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to OpenCV-Python and OpenCV-Contrib-Python 3.3.0.9) has an out-of-bounds write error in the FillUniColor function in utils.cpp when reading an image file by using cv::imread. | {'CVE-2017-12604'} | 2022-03-03T05:14:10.412261Z | 2021-10-12T22:01:55Z | HIGH | null | {'CWE-787'} | {'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12604', 'https://github.com/opencv/opencv/issues/9309', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://security.gentoo.org/glsa/201712-02', 'https://github.com/xiaoqx/pocs/blob/master/opencv.md', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2021-790 | 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'} | 2021-12-09T06:35:39.261433Z | 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 | PYSEC-2021-75 | null | In SaltStack Salt before 3002.5, when authenticating to services using certain modules, the SSL certificate is not always validated. | {'CVE-2020-35662'} | 2021-03-31T14:15:00Z | 2021-02-27T05:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YOGNT2XWPOYV7YT75DN7PS4GIYWFKOK5/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FUGLOJ6NXLCIFRD2JTXBYQEMAEF2B6XH/', 'https://saltproject.io/security_announcements/active-saltstack-cve-release-2021-feb-25/', 'https://security.gentoo.org/glsa/202103-01', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7GRVZ5WAEI3XFN2BDTL6DDXFS5HYSDVB/'} | null |
PyPI | GHSA-p2cq-cprg-frvm | Out of bounds write in tensorflow-lite | ### Impact
In TensorFlow Lite models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44
This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reference_ops.h#L2625-L2631
This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits.
### Patches
We have patched the issue in 204945b and will release patch releases for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.
### Workarounds
A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model.
A similar validation could be done if the segment ids are generated at runtime between inference steps.
If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15214'} | 2021-08-26T15:20:06Z | 2020-09-25T18:28:56Z | HIGH | null | {'CWE-787'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a', 'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15214', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null |
PyPI | GHSA-9f66-54xg-pc2c | Open redirect vulnerability | ### Impact
_What kind of vulnerability is it? Who is impacted?_
Open redirect vulnerability - a maliciously crafted link to a jupyter server could redirect the browser to a different website.
All jupyter servers running without a base_url prefix are technically affected, however, these maliciously crafted links can only be reasonably made for known jupyter server hosts. A link to your jupyter server may *appear* safe, but ultimately redirect to a spoofed server on the public internet. This same vulnerability was patched in upstream notebook v5.7.8.
### Patches
_Has the problem been patched? What versions should users upgrade to?_
Patched in jupyter_server 1.1.1. If upgrade is not available, a workaround can be to run your server on a url prefix:
```
jupyter server --ServerApp.base_url=/jupyter/
```
### References
[OWASP page on open redirects](https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html)
### For more information
If you have any questions or comments about this advisory, or vulnerabilities to report, please email our security list [security@ipython.org](mailto:security@ipython.org).
Credit: Yaniv Nizry from CxSCA group at Checkmarx | {'CVE-2020-26275'} | 2022-03-03T05:13:03.409856Z | 2020-12-21T18:01:41Z | LOW | null | {'CWE-601'} | {'https://advisory.checkmarx.net/advisory/CX-2020-4291', 'https://pypi.org/project/jupyter-server/', 'https://github.com/jupyter-server/jupyter_server/security/advisories/GHSA-9f66-54xg-pc2c', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26275', 'https://github.com/jupyter-server/jupyter_server/commit/85e4abccf6ea9321d29153f73b0bd72ccb3a6bca'} | null |
PyPI | GHSA-56wv-2wr9-3h9r | Improper Verification of Cryptographic Signature in fastecdsa | An issue was discovered in fastecdsa before 2.1.2. When using the NIST P-256 curve in the ECDSA implementation, the point at infinity is mishandled. This means that for an extreme value in k and s^-1, the signature verification fails even if the signature is correct. This behavior is not solely a usability problem. There are some threat models where an attacker can benefit by successfully guessing users for whom signature verification will fail. | {'CVE-2020-12607'} | 2022-03-03T05:13:42.856644Z | 2021-10-12T16:30:37Z | HIGH | null | {'CWE-347'} | {'https://github.com/AntonKueltz/fastecdsa', 'https://github.com/AntonKueltz/fastecdsa/commit/7b64e3efaa806b4daaf73bb5172af3581812f8de', 'https://github.com/AntonKueltz/fastecdsa/commit/e592f106edd5acf6dacedfab2ad16fe6c735c9d1', 'https://nvd.nist.gov/vuln/detail/CVE-2020-12607', 'https://github.com/AntonKueltz/fastecdsa/commit/4a16daeaf139be20654ef58a9fe4c79dc030458c', 'https://github.com/AntonKueltz/fastecdsa/issues/52'} | null |
PyPI | PYSEC-2020-114 | null | In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | {'GHSA-q8qj-fc9q-cphr', 'CVE-2020-15191'} | 2021-09-01T08:19:32.360913Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2021-817 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. 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-m342-ff57-4jcc', 'CVE-2021-41210'} | 2021-12-09T06:35:42.682170Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m342-ff57-4jcc', 'https://github.com/tensorflow/tensorflow/commit/701cfaca222a82afbeeb17496bd718baa65a67d2'} | null |
PyPI | PYSEC-2013-2 | null | lib/ansible/playbook/__init__.py in Ansible 1.2.x before 1.2.3, when playbook does not run due to an error, allows local users to overwrite arbitrary files via a symlink attack on a retry file with a predictable name in /var/tmp/ansible/. | {'CVE-2013-4260'} | 2021-07-02T02:41:32.973358Z | 2013-09-16T19:14:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=998227', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/86898', 'http://www.ansible.com/security', 'https://groups.google.com/forum/#!topic/ansible-project/UVDYW0HGcNg'} | null |
PyPI | PYSEC-2018-66 | null | The Pallets Project flask version Before 0.12.3 contains a CWE-20: Improper Input Validation vulnerability in flask that can result in Large amount of memory usage possibly leading to denial of service. This attack appear to be exploitable via Attacker provides JSON data in incorrect encoding. This vulnerability appears to have been fixed in 0.12.3. NOTE: this may overlap CVE-2019-1010083. | {'GHSA-562c-5r94-xh97', 'CVE-2018-1000656'} | 2021-08-25T04:30:09.712538Z | 2018-08-20T19:31:00Z | null | null | null | {'https://github.com/advisories/GHSA-562c-5r94-xh97', 'https://github.com/pallets/flask/pull/2691', 'https://github.com/pallets/flask/releases/tag/0.12.3', 'https://usn.ubuntu.com/4378-1/', 'https://lists.debian.org/debian-lts-announce/2019/08/msg00025.html', 'https://security.netapp.com/advisory/ntap-20190221-0001/'} | null |
PyPI | PYSEC-2021-114 | null | Wagtail is a Django content management system. In affected versions of Wagtail, when saving the contents of a rich text field in the admin interface, Wagtail does not apply server-side checks to ensure that link URLs use a valid protocol. A malicious user with access to the admin interface could thus craft a POST request to publish content with `javascript:` URLs containing arbitrary code. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin. See referenced GitHub advisory for additional details, including a workaround. Patched versions have been released as Wagtail 2.11.7 (for the LTS 2.11 branch) and Wagtail 2.12.4 (for the current 2.12 branch). | {'GHSA-wq5h-f9p5-q7fx', 'CVE-2021-29434'} | 2021-04-29T14:24:00Z | 2021-04-19T19:15:00Z | null | null | null | {'https://github.com/wagtail/wagtail/security/advisories/GHSA-wq5h-f9p5-q7fx', 'https://pypi.org/project/wagtail/'} | null |
PyPI | GHSA-6r97-cj55-9hrq | SQL Injection in Django | An issue was discovered in Django 1.11.x before 1.11.23, 2.1.x before 2.1.11, and 2.2.x before 2.2.4. Due to an error in shallow key transformation, key and index lookups for django.contrib.postgres.fields.JSONField, and key lookups for django.contrib.postgres.fields.HStoreField, were subject to SQL injection. This could, for example, be exploited via crafted use of "OR 1=1" in a key or index name to return all records, using a suitably crafted dictionary, with dictionary expansion, as the **kwargs passed to the QuerySet.filter() function. | {'CVE-2019-14234'} | 2022-03-21T21:16:55.353080Z | 2019-08-16T14:00:34Z | CRITICAL | null | {'CWE-89'} | {'https://github.com/django/django/commit/4f5b58f5cd3c57fee9972ab074f8dc6895d8f387', 'https://www.djangoproject.com/weblog/2019/aug/01/security-releases/', 'https://groups.google.com/forum/#!topic/django-announce/jIoju2-KLDs', 'https://nvd.nist.gov/vuln/detail/CVE-2019-14234'} | null |
PyPI | PYSEC-2014-45 | null | ftp.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to read hidden folder contents via unspecified vectors. | {'GHSA-prr5-pfr8-q9f3', 'CVE-2012-5503'} | 2021-09-01T08:44:30.766279Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/advisories/GHSA-prr5-pfr8-q9f3', 'https://plone.org/products/plone/security/advisories/20121106/19', 'https://plone.org/products/plone-hotfix/releases/20121106', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1'} | null |
PyPI | PYSEC-2021-544 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of TrySimplify(https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc#L390-L401) has undefined behavior due to dereferencing a null pointer in corner cases that result in optimizing a node with no inputs. 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-4hvv-7x94-7vq8', 'CVE-2021-29616'} | 2021-12-09T06:35:01.440204Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hvv-7x94-7vq8', 'https://github.com/tensorflow/tensorflow/commit/e6340f0665d53716ef3197ada88936c2a5f7a2d3'} | null |
PyPI | PYSEC-2021-401 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementations for convolution operators trigger a division by 0 if passed empty filter tensor arguments. 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-6hpv-v2rx-c5g6', 'CVE-2021-41209'} | 2021-11-13T06:52:43.607331Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f2c3931113eaafe9ef558faaddd48e00a6606235', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6hpv-v2rx-c5g6'} | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.