ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2021-375 | null | Cobbler before 3.3.0 allows authorization bypass for modification of settings. | {'GHSA-cr3f-r24j-3chw', 'CVE-2021-40325'} | 2021-10-19T21:47:31.769581Z | 2021-10-04T06:15:00Z | null | null | null | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://github.com/advisories/GHSA-cr3f-r24j-3chw', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0'} | null |
PyPI | PYSEC-2021-725 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `Split` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e2752089ef7ce9bcf3db0ec618ebd23ea119d0c7/tensorflow/lite/kernels/split.cc#L63-L65). An attacker can craft a model such that `num_splits` would be 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29599', 'GHSA-97wf-p777-86jq'} | 2021-12-09T06:35:31.883346Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-97wf-p777-86jq', 'https://github.com/tensorflow/tensorflow/commit/b22786e7e9b7bdb6a56936ff29cc7e9968d7bc1d'} | null |
PyPI | PYSEC-2021-230 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `BatchToSpaceNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/b5ed552fe55895aee8bd8b191f744a069957d18d/tensorflow/lite/kernels/batch_to_space_nd.cc#L81-L82). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-cfx7-2xpc-8w4h', 'CVE-2021-29593'} | 2021-08-27T03:22:37.941172Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/2c74674348a4708ced58ad6eb1b23354df8ee044', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfx7-2xpc-8w4h'} | null |
PyPI | GHSA-p45v-v4pw-77jr | Division by 0 in `QuantizedBatchNormWithGlobalNormalization` | ### Impact
An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:
```python
import tensorflow as tf
t = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
t_min = tf.constant(-10.0, dtype=tf.float32)
t_max = tf.constant(-10.0, dtype=tf.float32)
m = tf.constant([], shape=[0], dtype=tf.quint8)
m_min = tf.constant(-10.0, dtype=tf.float32)
m_max = tf.constant(-10.0, dtype=tf.float32)
v = tf.constant([], shape=[0], dtype=tf.quint8)
v_min = tf.constant(-10.0, dtype=tf.float32)
v_max = tf.constant(-10.0, dtype=tf.float32)
beta = tf.constant([], shape=[0], dtype=tf.quint8)
beta_min = tf.constant(-10.0, dtype=tf.float32)
beta_max = tf.constant(-10.0, dtype=tf.float32)
gamma = tf.constant([], shape=[0], dtype=tf.quint8)
gamma_min = tf.constant(-10.0, dtype=tf.float32)
gamma_max = tf.constant(-10.0, dtype=tf.float32)
tf.raw_ops.QuantizedBatchNormWithGlobalNormalization(
t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max,
v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min,
beta_max=beta_max, gamma=gamma, gamma_min=gamma_min,
gamma_max=gamma_max, out_type=tf.qint32,
variance_epsilon=0.1, scale_after_normalization=True)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the [op's contract](https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization).
### Patches
We have patched the issue in GitHub commit [d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b](https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team | {'CVE-2021-29548'} | 2022-03-03T05:14:08.985186Z | 2021-05-21T14:23:34Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29548', 'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr'} | null |
PyPI | GHSA-c94w-c95p-phf8 | Integer overflow in Tensorflow | ### Impact
The [implementation of `OpLevelCostEstimator::CalculateTensorSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558) is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:
```cc
int64_t OpLevelCostEstimator::CalculateTensorSize(
const OpInfo::TensorProperties& tensor, bool* found_unknown_shapes) {
int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);
int size = DataTypeSize(BaseType(tensor.dtype()));
VLOG(2) << "Count: " << count << " DataTypeSize: " << size;
return count * size;
}
```
Here, `count` and `size` can be large enough to cause `count * size` to overflow.
### Patches
We have patched the issue in GitHub commit [fcd18ce3101f245b083b30655c27b239dc72221e](https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23575'} | 2022-03-03T05:13:34.318775Z | 2022-02-10T00:32:59Z | MODERATE | null | {'CWE-190'} | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8', 'https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23575', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-660 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29534', 'GHSA-6j9c-grc6-5m6g'} | 2021-12-09T06:35:20.598497Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6j9c-grc6-5m6g'} | null |
PyPI | GHSA-cmgw-8vpc-rc59 | Segfault on strings tensors with mistmatched dimensions, due to Go code | ### Impact
Under certain conditions, Go code can trigger a segfault in string deallocation.
For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions).
To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written.
### Patches
We have patched the issue in GitHub commit [8721ba96e5760c229217b594f6d2ba332beedf22](https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22) (merging [#50508](https://github.com/tensorflow/tensorflow/pull/50508)).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version.
### 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 externally via a [fixing PR](https://github.com/tensorflow/tensorflow/pull/50508). | {'CVE-2021-37692'} | 2022-03-03T05:09:55.555709Z | 2021-08-25T14:38:57Z | MODERATE | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22', 'https://github.com/tensorflow/tensorflow/pull/50508', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cmgw-8vpc-rc59', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37692'} | null |
PyPI | PYSEC-2020-230 | null | In Django User Sessions (django-user-sessions) before 1.7.1, the views provided allow users to terminate specific sessions. The session key is used to identify sessions, and thus included in the rendered HTML. In itself this is not a problem. However if the website has an XSS vulnerability, the session key could be extracted by the attacker and a session takeover could happen. | {'GHSA-5fq8-3q2f-4m5g', 'CVE-2020-5224'} | 2021-08-27T03:21:57.616152Z | 2020-01-24T20:15:00Z | null | null | null | {'https://github.com/Bouke/django-user-sessions/security/advisories/GHSA-5fq8-3q2f-4m5g', 'https://github.com/jazzband/django-user-sessions/commit/f0c4077e7d1436ba6d721af85cee89222ca5d2d9'} | null |
PyPI | GHSA-qx3f-p745-w4hr | Integer overflow in Tensorflow | ### Impact
The implementation of `Range` suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations.
### Patches
We have patched the issue in GitHub commit [f0147751fd5d2ff23251149ebad9af9f03010732](https://github.com/tensorflow/tensorflow/commit/f0147751fd5d2ff23251149ebad9af9f03010732) (merging [#51733](https://github.com/tensorflow/tensorflow/pull/51733)).
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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/52676). | {'CVE-2022-23562'} | 2022-03-03T05:14:16.853671Z | 2022-02-09T23:54:07Z | HIGH | null | {'CWE-190'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23562', 'https://github.com/tensorflow/tensorflow/commit/f0147751fd5d2ff23251149ebad9af9f03010732', 'https://github.com/tensorflow/tensorflow/pull/51733', 'https://github.com/tensorflow/tensorflow/issues/52676', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qx3f-p745-w4hr', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-vxp9-wv2f-wqmw | High severity vulnerability that affects superset | Versions of Superset prior to 0.23 used an unsafe load method from the pickle library to deserialize data leading to possible remote code execution. Note Superset 0.23 was released prior to any Superset release under the Apache Software Foundation. | {'CVE-2018-8021'} | 2022-03-23T22:15:05.776608Z | 2018-11-09T17:40:56Z | CRITICAL | null | {'CWE-502'} | {'https://github.com/apache/superset/commit/2c72a7ae4fc0a8bac1f037a79efa90e1c5549710', 'https://github.com/apache/superset/pull/4243', 'https://github.com/apache/superset', 'https://nvd.nist.gov/vuln/detail/CVE-2018-8021', 'https://www.exploit-db.com/exploits/45933/'} | null |
PyPI | GHSA-m85c-9mf8-m2m6 | Critical severity vulnerability that affects confire | An exploitable vulnerability exists in the YAML parsing functionality in config.py in Confire 0.2.0. Due to the user-specific configuration being loaded from "~/.confire.yaml" using the yaml.load function, a YAML parser can execute arbitrary Python commands resulting in command execution. An attacker can insert Python into loaded YAML to trigger this vulnerability. | {'CVE-2017-16763'} | 2022-03-03T05:13:26.050847Z | 2018-07-18T18:28:26Z | CRITICAL | null | null | {'https://github.com/advisories/GHSA-m85c-9mf8-m2m6', 'https://github.com/bbengfort/confire', 'https://github.com/bbengfort/confire/issues/24', 'https://joel-malwarebenchmark.github.io/blog/2017/11/12/cve-2017-16763-configure-loaded-through-confire/', 'https://nvd.nist.gov/vuln/detail/CVE-2017-16763', 'https://github.com/bbengfort/confire/commit/8cc86a5ec2327e070f1d576d61bbaadf861597ea'} | null |
PyPI | GHSA-cpf4-wx82-gxp6 | Segfault due to negative splits in `SplitV` | ### Impact
The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/split_v_op.cc#L49-L205) of `SplitV` can trigger a segfault is an attacker supplies negative arguments:
```python
import tensorflow as tf
tf.raw_ops.SplitV(
value=tf.constant([]),
size_splits=[-1, -2]
,axis=0,
num_split=2)
```
This occurs whenever `size_splits` contains more than one value and at least one value is negative.
### Patches
We have patched the issue in GitHub commit [25d622ffc432acc736b14ca3904177579e733cc6](https://github.com/tensorflow/tensorflow/commit/25d622ffc432acc736b14ca3904177579e733cc6).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41222'} | 2022-03-03T05:13:07.507477Z | 2021-11-10T18:48:15Z | MODERATE | null | {'CWE-682'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41222', 'https://github.com/tensorflow/tensorflow/commit/25d622ffc432acc736b14ca3904177579e733cc6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cpf4-wx82-gxp6'} | null |
PyPI | PYSEC-2017-8 | null | HKDF in cryptography before 1.5.2 returns an empty byte-string if used with a length less than algorithm.digest_size. | {'CVE-2016-9243'} | 2021-07-05T00:01:17.464237Z | 2017-03-27T17:59:00Z | null | null | null | {'https://github.com/pyca/cryptography/issues/3211', 'http://www.securityfocus.com/bid/94216', 'https://github.com/pyca/cryptography/commit/b924696b2e8731f39696584d12cceeb3aeb2d874', 'http://www.ubuntu.com/usn/USN-3138-1', 'https://cryptography.io/en/latest/changelog', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/5R2ZOBMPWDFFHUZ6QOZZY36A6H5CGJXL/', 'http://www.openwall.com/lists/oss-security/2016/11/09/2', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/U23KDR2M2N7W2ZSREG63BVW7D4VC6CIZ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQ5G7KHKZC4SI23JE7277KZXM57GEQKT/'} | null |
PyPI | PYSEC-2022-87 | null | Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. 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-8r7c-3cm2-3h8f', 'CVE-2022-23578'} | 2022-03-09T00:17:34.646320Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8r7c-3cm2-3h8f', 'https://github.com/tensorflow/tensorflow/commit/c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/common_runtime/immutable_executor_state.cc#L84-L262'} | null |
PyPI | PYSEC-2016-22 | null | OpenStack Murano before 1.0.3 (liberty) and 2.x before 2.0.1 (mitaka), Murano-dashboard before 1.0.3 (liberty) and 2.x before 2.0.1 (mitaka), and python-muranoclient before 0.7.3 (liberty) and 0.8.x before 0.8.5 (mitaka) improperly use loaders inherited from yaml.Loader when parsing MuranoPL and UI files, which allows remote attackers to create arbitrary Python objects and execute arbitrary code via crafted extended YAML tags in UI definitions in packages. | {'CVE-2016-4972'} | 2021-07-25T23:34:52.302342Z | 2016-09-26T16:59:00Z | null | null | null | {'https://bugs.launchpad.net/murano/+bug/1586079', 'https://bugs.launchpad.net/python-muranoclient/+bug/1586078', 'http://www.openwall.com/lists/oss-security/2016/06/23/8'} | null |
PyPI | GHSA-7rp2-fm2h-wchj | Cross-site Scripting in Django | An issue was discovered in Django 1.11 before 1.11.21, 2.1 before 2.1.9, and 2.2 before 2.2.2. The clickable Current URL value displayed by the AdminURLFieldWidget displays the provided value without validating it as a safe URL. Thus, an unvalidated value stored in the database, or a value provided as a URL query parameter payload, could result in an clickable JavaScript link. | {'CVE-2019-12308'} | 2022-03-03T05:13:25.188172Z | 2019-06-10T18:43:25Z | MODERATE | null | {'CWE-79'} | {'http://www.openwall.com/lists/oss-security/2019/06/03/2', 'https://nvd.nist.gov/vuln/detail/CVE-2019-12308', 'https://www.djangoproject.com/weblog/2019/jun/03/security-releases/', 'https://docs.djangoproject.com/en/dev/releases/2.2.2/', 'https://groups.google.com/forum/#!topic/django-announce/GEbHU7YoVz8', 'https://docs.djangoproject.com/en/dev/releases/1.11.21/', 'https://docs.djangoproject.com/en/dev/releases/2.1.9/', 'https://docs.djangoproject.com/en/dev/releases/security/'} | null |
PyPI | PYSEC-2022-147 | null | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23583', 'GHSA-gjqc-q9g6-q2j3'} | 2022-03-09T00:18:28.843331Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gjqc-q9g6-q2j3', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/cwise_ops_common.h#L88-L137', 'https://github.com/tensorflow/tensorflow/commit/a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9'} | null |
PyPI | PYSEC-2018-108 | null | The SSH server implementation of AsyncSSH before 1.12.1 does not properly check whether authentication is completed before processing other requests. A customized SSH client can simply skip the authentication step. | {'CVE-2018-7749'} | 2021-12-13T06:35:08.979709Z | 2018-03-12T19:29:00Z | null | null | null | {'https://github.com/ronf/asyncssh/commit/c161e26cdc0d41b745b63d9f17b437f073bf7ba4', 'https://groups.google.com/forum/#!msg/asyncssh-announce/57_5O7kiHSA/8BXZ_hxHAQAJ'} | null |
PyPI | GHSA-grfj-wjv9-4f9v | Open redirect in Jupyter Server | ### 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 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 originated in jupyter/notebook: https://github.com/jupyter/notebook/security/advisories/GHSA-c7vm-f5p4-8fqh
### Patches
_Has the problem been patched? What versions should users upgrade to?_
jupyter_server 1.0.6
### 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: zhuonan li of Alibaba Application Security Team | {'CVE-2020-26232'} | 2022-03-03T05:13:24.890200Z | 2020-11-24T21:20:52Z | MODERATE | null | {'CWE-601'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-26232', 'https://github.com/jupyter-server/jupyter_server/commit/3d83e49090289c431da253e2bdb8dc479cbcb157', 'https://github.com/jupyter-server/jupyter_server/blob/master/CHANGELOG.md#106---2020-11-18', 'https://github.com/jupyter/jupyter_server/security/advisories/GHSA-grfj-wjv9-4f9v'} | null |
PyPI | GHSA-w74j-v8xh-3w5h | Reference binding to nullptr in unicode encoding | ### Impact
An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`:
```python
import tensorflow as tf
from tensorflow.python.ops import gen_string_ops
gen_string_ops.unicode_encode(
input_values=[],
input_splits=[],
output_encoding='UTF-8',
errors='ignore',
replacement_char='a')
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty:
```cc
const Tensor& input_splits = context->input(1);
const auto input_splits_flat = input_splits.flat<SPLITS_TYPE>();
TensorShape output_shape({input_splits.dim_size(0) - 1});
```
### Patches
We have patched the issue in GitHub commit [2e0ee46f1a47675152d3d865797a18358881d7a6](https://github.com/tensorflow/tensorflow/commit/2e0ee46f1a47675152d3d865797a18358881d7a6).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37667'} | 2022-03-03T05:13:33.464306Z | 2021-08-25T14:42:09Z | HIGH | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w74j-v8xh-3w5h', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37667', 'https://github.com/tensorflow/tensorflow/commit/2e0ee46f1a47675152d3d865797a18358881d7a6'} | null |
PyPI | PYSEC-2019-108 | null | ** DISPUTED ** An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. | {'CVE-2019-6446'} | 2019-10-01T00:15:00Z | 2019-01-16T05:29:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00092.html', 'https://access.redhat.com/errata/RHSA-2019:3704', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4/', 'http://www.securityfocus.com/bid/106670', 'https://bugzilla.suse.com/show_bug.cgi?id=1122208', 'http://lists.opensuse.org/opensuse-security-announce/2019-10/msg00015.html', 'https://github.com/numpy/numpy/issues/12759', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00091.html', 'https://access.redhat.com/errata/RHSA-2019:3335'} | null |
PyPI | PYSEC-2020-55 | null | An issue was discovered in OpenStack Keystone before 15.0.1, and 16.0.0. Any authenticated user can create an EC2 credential for themselves for a project that they have a specified role on, and then perform an update to the credential user and project, allowing them to masquerade as another user. This potentially allows a malicious user to act as the admin on a project another user has the admin role on, which can effectively grant that user global admin privileges. | {'CVE-2020-12691'} | 2020-09-02T16:15:00Z | 2020-05-07T00:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/re4ffc55cd2f1b55a26e07c83b3c22c3fe4bae6054d000a57fb48d8c2@%3Ccommits.druid.apache.org%3E', 'https://security.openstack.org/ossa/OSSA-2020-004.html', 'https://usn.ubuntu.com/4480-1/', 'https://bugs.launchpad.net/keystone/+bug/1872733', 'https://www.openwall.com/lists/oss-security/2020/05/06/5', 'http://www.openwall.com/lists/oss-security/2020/05/07/2'} | null |
PyPI | PYSEC-2022-68 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both `embedding_size` and `lookup_size` are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version. | {'GHSA-98p5-x8x4-c9m5', 'CVE-2022-23559'} | 2022-03-09T00:17:32.298949Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/embedding_lookup_sparse.cc#L179-L189', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98p5-x8x4-c9m5', 'https://github.com/tensorflow/tensorflow/commit/a4e401da71458d253b05e41f28637b65baf64be4', 'https://github.com/tensorflow/tensorflow/commit/1de49725a5fc4e48f1a3b902ec3599ee99283043', 'https://github.com/tensorflow/tensorflow/commit/f19be71717c497723ba0cea0379e84f061a75e01'} | null |
PyPI | GHSA-8c5j-9r9f-c6w8 | Information disclosure in Django | An issue was discovered in Django 2.2 before 2.2.26, 3.2 before 3.2.11, and 4.0 before 4.0.1. Due to leveraging the Django Template Language's variable resolution logic, the dictsort template filter was potentially vulnerable to information disclosure, or an unintended method call, if passed a suitably crafted key. | {'CVE-2021-45116'} | 2022-03-03T05:13:50.494336Z | 2022-01-12T19:21:10Z | HIGH | null | {'CWE-668'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://www.djangoproject.com/weblog/2022/jan/04/security-releases/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/B4SQG2EAF4WCI2SLRL6XRDJ3RPK3ZRDV/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-45116', 'https://security.netapp.com/advisory/ntap-20220121-0005/', 'https://docs.djangoproject.com/en/4.0/releases/security/'} | null |
PyPI | PYSEC-2021-772 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37661', 'GHSA-gf88-j2mg-cc82'} | 2021-12-09T06:35:37.616060Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82', 'https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992'} | null |
PyPI | PYSEC-2021-288 | 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.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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-2021-37666', 'GHSA-w4xf-2pqw-5mq7'} | 2021-08-27T03:22:45.481654Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/be7a4de6adfbd303ce08be4332554dff70362612', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w4xf-2pqw-5mq7'} | null |
PyPI | PYSEC-2021-97 | null | 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. | {'GHSA-8wwf-2644-f8x4', 'CVE-2021-34363'} | 2021-06-16T00:03:24.982635Z | 2021-06-10T11:15:00Z | null | null | null | {'https://github.com/nvbn/thefuck/commit/e343c577cd7da4d304b837d4a07ab4df1e023092', 'https://github.com/nvbn/thefuck/releases/tag/3.31', 'https://vuln.ryotak.me/advisories/48', 'https://github.com/advisories/GHSA-8wwf-2644-f8x4'} | null |
PyPI | PYSEC-2021-322 | null | Wasmtime is an open source runtime for WebAssembly & WASI. Wasmtime before version 0.30.0 is affected by a type confusion vulnerability. As a Rust library the `wasmtime` crate clearly marks which functions are safe and which are `unsafe`, guaranteeing that if consumers never use `unsafe` then it should not be possible to have memory unsafety issues in their embeddings of Wasmtime. An issue was discovered in the safe API of `Linker::func_*` APIs. These APIs were previously not sound when one `Engine` was used to create the `Linker` and then a different `Engine` was used to create a `Store` and then the `Linker` was used to instantiate a module into that `Store`. Cross-`Engine` usage of functions is not supported in Wasmtime and this can result in type confusion of function pointers, resulting in being able to safely call a function with the wrong type. Triggering this bug requires using at least two `Engine` values in an embedding and then additionally using two different values with a `Linker` (one at the creation time of the `Linker` and another when instantiating a module with the `Linker`). It's expected that usage of more-than-one `Engine` in an embedding is relatively rare since an `Engine` is intended to be a globally shared resource, so the expectation is that the impact of this issue is relatively small. The fix implemented is to change this behavior to `panic!()` in Rust instead of silently allowing it. Using different `Engine` instances with a `Linker` is a programmer bug that `wasmtime` catches at runtime. This bug has been patched and users should upgrade to Wasmtime version 0.30.0. If you cannot upgrade Wasmtime and are using more than one `Engine` in your embedding it's recommended to instead use only one `Engine` for the entire program if possible. An `Engine` is designed to be a globally shared resource that is suitable to have only one for the lifetime of an entire process. If using multiple `Engine`s is required then code should be audited to ensure that `Linker` is only used with one `Engine`. | {'CVE-2021-39219', 'GHSA-q879-9g95-56mx'} | 2021-09-17T22:30:49.947373Z | 2021-09-17T20:15:00Z | null | null | null | {'https://crates.io/crates/wasmtime', 'https://github.com/bytecodealliance/wasmtime/commit/b39f087414f27ae40c44449ed5d1154e03449bff', 'https://github.com/bytecodealliance/wasmtime/security/advisories/GHSA-q879-9g95-56mx'} | null |
PyPI | PYSEC-2019-11 | null | 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. If django.utils.text.Truncator's chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable. | {'CVE-2019-14232', 'GHSA-c4qh-4vgv-qc6g'} | 2020-08-24T17:37:00Z | 2019-08-02T15:15:00Z | null | null | null | {'https://seclists.org/bugtraq/2019/Aug/15', 'https://groups.google.com/forum/#!topic/django-announce/jIoju2-KLDs', 'https://www.debian.org/security/2019/dsa-4498', 'https://security.netapp.com/advisory/ntap-20190828-0002/', 'https://security.gentoo.org/glsa/202004-17', 'https://github.com/advisories/GHSA-c4qh-4vgv-qc6g', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00006.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00025.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/STVX7X7IDWAH5SKE6MBMY3TEI6ZODBTK/', 'https://docs.djangoproject.com/en/dev/releases/security/', 'https://www.djangoproject.com/weblog/2019/aug/01/security-releases/'} | null |
PyPI | GHSA-ghjx-3jg5-h6r2 | High severity vulnerability that affects mercurial | In Mercurial before 4.1.3, "hg serve --stdio" allows remote authenticated users to launch the Python debugger, and consequently execute arbitrary code, by using --debugger as a repository name. | {'CVE-2017-9462'} | 2022-03-03T05:14:19.878917Z | 2018-07-13T15:17:10Z | HIGH | null | {'CWE-732'} | {'https://nvd.nist.gov/vuln/detail/CVE-2017-9462', 'http://www.securityfocus.com/bid/99123', 'https://github.com/advisories/GHSA-ghjx-3jg5-h6r2', 'https://bugs.debian.org/861243', 'https://www.mercurial-scm.org/repo/hg/rev/77eaf9539499', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_4.1.3_.282017-4-18.29', 'http://www.debian.org/security/2017/dsa-3963', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00005.html', 'https://security.gentoo.org/glsa/201709-18', 'https://access.redhat.com/errata/RHSA-2017:1576'} | null |
PyPI | PYSEC-2020-288 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'GHSA-mxjj-953w-2c2v', 'CVE-2020-15208'} | 2021-12-09T06:34:43.041754Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2019-221 | null | Home Assistant before 0.67.0 was vulnerable to an information disclosure that allowed an unauthenticated attacker to read the application's error log via components/api.py. | {'CVE-2018-21019'} | 2021-11-24T22:47:02.221265Z | 2019-09-23T16:15:00Z | null | null | null | {'https://github.com/home-assistant/home-assistant/pull/13836', 'https://github.com/home-assistant/home-assistant/releases/tag/0.67.0'} | null |
PyPI | PYSEC-2015-32 | 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'} | 2021-07-25T23:34:53.419876Z | 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 | PYSEC-2020-322 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15207', 'GHSA-q4qf-3fc6-8x34'} | 2021-12-09T06:35:14.570909Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34', 'https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2020-267 | null | Red Discord Bot before version 3.4.1 has an unauthorized privilege escalation exploit in the Mod module. This exploit allows Discord users with a high privilege level within the guild to bypass hierarchy checks when the application is in a specific condition that is beyond that user's control. By abusing this exploit, it is possible to perform destructive actions within the guild the user has high privileges in. This exploit has been fixed in version 3.4.1. As a workaround, unloading the Mod module with unload mod or, disabling the massban command with command disable global massban can render this exploit not accessible. We still highly recommend updating to 3.4.1 to completely patch this issue. | {'CVE-2020-15278', 'GHSA-mp9m-g7qj-6vqr'} | 2021-11-16T03:58:45.518170Z | 2020-10-28T17:15:00Z | null | null | null | {'https://github.com/Cog-Creators/Red-DiscordBot/releases/tag/3.4.1', 'https://github.com/Cog-Creators/Red-DiscordBot/security/advisories/GHSA-mp9m-g7qj-6vqr', 'https://github.com/Cog-Creators/Red-DiscordBot/commit/726bfd38adfdfaef760412a68e01447b470f438b'} | null |
PyPI | PYSEC-2021-78 | null | Plone CMS until version 5.2.4 has a stored Cross-Site Scripting (XSS) vulnerability in the user fullname property and the file upload functionality. The user's input data is not properly encoded when being echoed back to the user. This data can be interpreted as executable code by the browser and allows an attacker to execute JavaScript in the context of the victim's browser if the victim opens a vulnerable page containing an XSS payload. | {'CVE-2021-3313'} | 2021-06-09T05:00:50.662546Z | 2021-05-20T16:15:00Z | null | null | null | {'https://plone.org/security/hotfix/20210518', 'http://www.openwall.com/lists/oss-security/2021/05/22/1', 'https://www.compass-security.com/fileadmin/Research/Advisories/2021-07_CSNC-2021-013_XSS_in_Plone_CMS.txt', 'https://plone.org/download/releases/5.2.3'} | null |
PyPI | PYSEC-2021-637 | null | TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. 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-3rcw-9p9x-582v', 'CVE-2021-41228'} | 2021-12-09T06:35:11.562556Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3rcw-9p9x-582v', 'https://github.com/tensorflow/tensorflow/commit/8b202f08d52e8206af2bdb2112a62fafbc546ec7'} | null |
PyPI | PYSEC-2021-267 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. | {'CVE-2021-37645', 'GHSA-9w2p-5mgw-p94c'} | 2021-08-27T03:22:43.539250Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c', 'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1'} | null |
PyPI | PYSEC-2021-508 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29580', 'GHSA-x8h6-xgqx-jqgp'} | 2021-12-09T06:34:55.778346Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp'} | null |
PyPI | PYSEC-2016-34 | null | The TripleO Heat templates (tripleo-heat-templates) do not properly order the Identity Service (keystone) before the OpenStack Object Storage (Swift) staticweb middleware in the swiftproxy pipeline when the staticweb middleware is enabled, which might allow remote attackers to obtain sensitive information from private containers via unspecified vectors. | {'CVE-2015-5271'} | 2021-08-27T03:22:48.421612Z | 2016-04-15T17:59:00Z | null | null | null | {'https://bugs.launchpad.net/tripleo/+bug/1494896', 'https://launchpadlibrarian.net/217268516/CVE-2015-5271_puppet-swift.patch', 'https://bugzilla.redhat.com/show_bug.cgi?id=1261697', 'https://access.redhat.com/errata/RHSA-2015:1862'} | null |
PyPI | PYSEC-2021-158 | null | TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. 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. | {'CVE-2021-29521', 'GHSA-hr84-fqvp-48mm'} | 2021-08-27T03:22:25.027733Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm', 'https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5'} | null |
PyPI | PYSEC-2022-91 | null | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23582', 'GHSA-4j82-5ccr-4r8v'} | 2022-03-09T00:17:35.169396Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50'} | null |
PyPI | GHSA-968f-66r5-5v74 | HTTP Request Smuggling in Waitress: Invalid whitespace characters in headers (Follow-up) | ### Impact
The patches introduced to fix https://github.com/Pylons/waitress/security/advisories/GHSA-m5ff-3wj3-8ph4 were not complete and still would allow an attacker to smuggle requests/split a HTTP request with invalid data.
This updates the existing CVE with ID: CVE-2019-16789
### Patches
Waitress version 1.4.2 has been updated to now validate HTTP headers better to avoid the issue, completely fixing all known issues with whitespace.
### Workarounds
There are no work-arounds, upgrading to Waitress 1.4.2 is highly recommended.
### References
See https://github.com/Pylons/waitress/security/advisories/GHSA-m5ff-3wj3-8ph4 for more information on the security issue.
### For more information
If you have any questions or comments about this advisory:
* open an issue at https://github.com/Pylons/waitress/issues (if not sensitive or security related)
* email the Pylons Security mailing list: pylons-project-security@googlegroups.com (if security related) | {'CVE-2019-16789'} | 2022-04-25T23:16:55.739172Z | 2020-01-06T18:44:21Z | HIGH | null | {'CWE-444'} | {'https://github.com/github/advisory-review/pull/14604', 'https://docs.pylonsproject.org/projects/waitress/en/latest/#security-fixes', 'https://github.com/Pylons/waitress/commit/11d9e138125ad46e951027184b13242a3c1de017', 'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16789', 'https://github.com/Pylons/waitress/security/advisories/GHSA-968f-66r5-5v74', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYEOTGWJZVKPRXX2HBNVIYWCX73QYPM5/', 'https://access.redhat.com/errata/RHSA-2020:0720', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GVDHR2DNKCNQ7YQXISJ45NT4IQDX3LJ7/'} | null |
PyPI | PYSEC-2020-158 | null | In xmpp-http-upload before version 0.4.0, when the GET method is attacked, attackers can read files which have a `.data` suffix and which are accompanied by a JSON file with the `.meta` suffix. This can lead to Information Disclosure and in some shared-hosting scenarios also to circumvention of authentication or other limitations on the outbound (GET) traffic. For example, in a scenario where a single server has multiple instances of the application running (with separate DATA_ROOT settings), an attacker who has knowledge about the directory structure is able to read files from any other instance to which the process has read access. If instances have individual authentication (for example, HTTP authentication via a reverse proxy, source IP based filtering) or other restrictions (such as quotas), attackers may circumvent those limits in such a scenario by using the Directory Traversal to retrieve data from the other instances. If the associated XMPP server (or anyone knowing the SECRET_KEY) is malicious, they can write files outside the DATA_ROOT. The files which are written are constrained to have the `.meta` and the `.data` suffixes; the `.meta` file will contain the JSON with the Content-Type of the original request and the `.data` file will contain the payload. The issue is patched in version 0.4.0. | {'GHSA-hwv5-w8gm-fq9f', 'CVE-2020-15239'} | 2020-10-23T03:09:00Z | 2020-10-06T19:15:00Z | null | null | null | {'https://github.com/horazont/xmpp-http-upload/pull/12', 'https://github.com/horazont/xmpp-http-upload/security/advisories/GHSA-hwv5-w8gm-fq9f', 'https://github.com/horazont/xmpp-http-upload/commit/82056540191e89f0cd697c81f57714c00962ed75', 'https://pypi.org/project/xmpp-http-upload/#history'} | null |
PyPI | PYSEC-2020-43 | null | An issue was discovered in Flask-CORS (aka CORS Middleware for Flask) before 3.0.9. It allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. | {'GHSA-xc3p-ff3m-f46v', 'CVE-2020-25032'} | 2020-10-21T12:15:00Z | 2020-08-31T04:15:00Z | null | null | null | {'https://github.com/corydolphin/flask-cors/releases/tag/3.0.9', 'http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00048.html', 'https://github.com/advisories/GHSA-xc3p-ff3m-f46v', 'http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00032.html', 'http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00028.html', 'https://www.debian.org/security/2020/dsa-4775', 'http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00039.html'} | null |
PyPI | GHSA-vf94-36g5-69v8 | Division by zero in TFLite's implementation of `DepthToSpace` | ### Impact
The implementation of the `DepthToSpace` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depth_to_space.cc#L63-L69):
```cc
const int block_size = params->block_size;
...
const int input_channels = input->dims->data[3];
...
int output_channels = input_channels / block_size / block_size;
```
An attacker can craft a model such that `params->block_size` is 0.
### Patches
We have patched the issue in GitHub commit [106d8f4fb89335a2c52d7c895b7a7485465ca8d9](https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29595'} | 2022-03-03T05:14:04.139271Z | 2021-05-21T14:27:49Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vf94-36g5-69v8', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29595', 'https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9'} | null |
PyPI | GHSA-h6gw-r52c-724r | NULL Pointer Dereference and Access of Uninitialized Pointer in TensorFlow | ### Impact
The [code for boosted trees in TensorFlow](https://github.com/tensorflow/tensorflow/blob/e0b6e58c328059829c3eb968136f17aa72b6c876/tensorflow/core/kernels/boosted_trees/stats_ops.cc) is still missing validation. This allows malicious users to read and write outside of bounds of heap allocated data as well as trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures).
This follows after CVE-2021-41208 where these APIs were still vulnerable to multiple security issues.
**Note**: Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. Instead, please use the downstream [TensorFlow Decision Forests](https://github.com/tensorflow/decision-forests) project which is newer and supports more features.
These APIs are now deprecated in TensorFlow 2.8. We will remove TensorFlow's boosted trees APIs in subsequent releases.
### Patches
We have patched the known issues in multiple GitHub commits.
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.
This should allow users to use existing boosted trees APIs for a while until they migrate to [TensorFlow Decision Forests](https://github.com/tensorflow/decision-forests), while guaranteeing that known vulnerabilities are fixed.
### 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
These vulnerabilities have been reported by Yu Tian of Qihoo 360 AIVul Team and Faysal Hossain Shezan from University of Virginia. Some of the issues have been discovered internally after a careful audit of the APIs. | null | 2022-03-23T23:00:06.750157Z | 2022-02-09T23:38:36Z | CRITICAL | null | {'CWE-476', 'CWE-824'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-57wx-m983-2f88', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6gw-r52c-724r', 'https://github.com/tensorflow/tensorflow/blob/e0b6e58c328059829c3eb968136f17aa72b6c876/tensorflow/core/kernels/boosted_trees/stats_ops.cc'} | null |
PyPI | PYSEC-2022-151 | null | Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23587', 'GHSA-8jj7-5vxc-pg2q'} | 2022-03-09T00:18:29.453433Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8jj7-5vxc-pg2q', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L2621-L2689', 'https://github.com/tensorflow/tensorflow/commit/0aaaae6eca5a7175a193696383f582f53adab23f'} | null |
PyPI | GHSA-jgm9-xpfj-4fq6 | Path traversal 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-013
- Vulnerability type: Improper Hardening
- Threat level: Low
## Description:
The filesystem restriction could be hardened and should only allow for pre-defined subfolders.
## Technical description:
The Flatpak and Snap configurations allow for read-only access on the whole home folder. The relevant lines in the configuration files are `onionshare/snap/snapcraft.yaml#L20` and `onionshare/flatpak/org.onionshare.OnionShare.yaml#L19` , respectively.
The encapsulation of filesystem access via these mechanisms should be restricted to pre-defined folders and not allow for access to (configuration) files outside the Onionshare-specific folders.
Sadly Snap does not allow for further restriction to specific folders and therefore cannot be further hardened. By default both frameworks disallow access to hidden folders and therefore reduce the potential impact.
## Impact:
An adversary with a primitive that allows for filesystem access from the context of the Onionshare process can access sensitive files in the entire user home folder. This could lead to the leaking of sensitive data. Due to the automatic exclusion of hidden folders, the impact is reduced.
## Recommendation:
- Reduce read access in Flatpak configuration. | {'CVE-2022-21693'} | 2022-03-03T05:13:35.332599Z | 2022-01-21T23:20:19Z | MODERATE | null | {'CWE-22'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-21693', 'https://github.com/onionshare/onionshare/security/advisories/GHSA-jgm9-xpfj-4fq6', 'https://github.com/onionshare/onionshare/releases/tag/v2.5', 'https://github.com/onionshare/onionshare'} | null |
PyPI | PYSEC-2020-334 | null | In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area. If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault. This is because the allocator used to return the buffer data is not marked as returning an opaque handle since the needed virtual method is not overridden. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0. | {'CVE-2020-26268', 'GHSA-hhvc-g5hv-48c6'} | 2021-12-09T06:35:16.406292Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6'} | null |
PyPI | PYSEC-2017-19 | null | An exploitable vulnerability exists in the YAML parsing functionality in the parse_yaml_query method in parser.py in MLAlchemy before 0.2.2. When processing YAML-Based queries for data, a YAML parser 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-2017-16615', 'GHSA-xpm8-98mx-h4c5'} | 2021-07-05T00:01:22.762966Z | 2017-11-08T03:29:00Z | null | null | null | {'https://github.com/thanethomson/MLAlchemy/issues/1', 'https://github.com/advisories/GHSA-xpm8-98mx-h4c5', 'https://github.com/thanethomson/MLAlchemy/commit/bc795757febdcce430d89f9d08f75c32d6989d3c', 'https://joel-malwarebenchmark.github.io/blog/2017/11/08/cve-2017-16615-critical-restful-web-applications-vulnerability/'} | null |
PyPI | PYSEC-2015-24 | null | Cross-site scripting (XSS) vulnerability in the file browser in notebook/notebookapp.py in IPython Notebook before 3.2.2 and Jupyter Notebook 4.0.x before 4.0.5 allows remote attackers to inject arbitrary web script or HTML via a folder name. NOTE: this was originally reported as a cross-site request forgery (CSRF) vulnerability, but this may be inaccurate. | {'CVE-2015-6938'} | 2021-07-15T02:22:14.906376Z | 2015-09-21T19:59:00Z | null | null | null | {'http://lists.fedoraproject.org/pipermail/package-announce/2015-September/167670.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-September/166471.html', 'https://github.com/jupyter/notebook/commit/dd9876381f0ef09873d8c5f6f2063269172331e3', 'http://seclists.org/oss-sec/2015/q3/474', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-September/166460.html', 'http://seclists.org/oss-sec/2015/q3/544', 'http://lists.opensuse.org/opensuse-updates/2015-10/msg00016.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=1259405', 'https://github.com/jupyter/notebook/commit/35f32dd2da804d108a3a3585b69ec3295b2677ed', 'https://github.com/ipython/ipython/commit/3ab41641cf6fce3860c73d5cf4645aa12e1e5892'} | null |
PyPI | PYSEC-2019-237 | null | An issue was discovered in py-lmdb 0.97. For certain values of mp_flags, mdb_page_touch does not properly set up mc->mc_pg[mc->top], leading to an invalid write operation. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker. | {'CVE-2019-16225'} | 2021-12-14T08:17:08.271573Z | 2019-09-11T15:15:00Z | null | null | null | {'https://pypi.org/project/lmdb', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16225', 'https://github.com/TeamSeri0us/pocs/tree/master/lmdb/lmdb%20write%20to%20illegal%20address'} | null |
PyPI | GHSA-p62g-jhg6-v3rq | Code Injection, Race Condition, and Execution with Unnecessary Privileges in Ansible | A flaw was found in Ansible Engine, all versions 2.7.x, 2.8.x and 2.9.x prior to 2.7.17, 2.8.9 and 2.9.6 respectively, when using ansible_facts as a subkey of itself and promoting it to a variable when inject is enabled, overwriting the ansible_facts after the clean. An attacker could take advantage of this by altering the ansible_facts, such as ansible_hosts, users and any other key data which would lead into privilege escalation or code injection. | {'CVE-2020-10684'} | 2022-03-03T05:14:17.619649Z | 2021-04-07T20:37:06Z | LOW | null | {'CWE-362', 'CWE-862', 'CWE-94', 'CWE-250'} | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-10684', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQVOQD4VAIXXTVQAJKTN7NUGTJFE2PCB/', 'https://www.debian.org/security/2021/dsa-4950', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MRRYUU5ZBLPBXCYG6CFP35D64NP2UB2S/', 'https://github.com/ansible/ansible', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DKPA4KC3OJSUFASUYMG66HKJE7ADNGFW/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10684', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2021-334 | null | parlai is a framework for training and evaluating AI models on a variety of openly available dialogue datasets. In affected versions the package is vulnerable to YAML deserialization attack caused by unsafe loading which leads to Arbitary code execution. This security bug is patched by avoiding unsafe loader users should update to version above v1.1.0. If upgrading is not possible then users can change the Loader used to SafeLoader as a workaround. See commit 507d066ef432ea27d3e201da08009872a2f37725 for details. | {'CVE-2021-39207', 'GHSA-m87f-9fvv-2mgg'} | 2021-09-23T16:57:40.954858Z | 2021-09-10T23:15:00Z | null | null | null | {'https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725', 'https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879', 'https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg'} | null |
PyPI | PYSEC-2021-81 | null | Plone through 5.2.4 allows remote authenticated managers to perform disk I/O via crafted keyword arguments to the ReStructuredText transform in a Python script. | {'CVE-2021-33509', 'GHSA-hm2p-fhwx-9285'} | 2021-06-02T03:48:09.722168Z | 2021-05-21T22:15:00Z | null | null | null | {'https://plone.org/security/hotfix/20210518/writing-arbitrary-files-via-docutils-and-python-script', 'http://www.openwall.com/lists/oss-security/2021/05/22/1', 'https://github.com/advisories/GHSA-hm2p-fhwx-9285'} | null |
PyPI | PYSEC-2021-764 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-qjj8-32p7-h289', 'CVE-2021-37653'} | 2021-12-09T06:35:36.903192Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qjj8-32p7-h289', 'https://github.com/tensorflow/tensorflow/commit/ac117ee8a8ea57b73d34665cdf00ef3303bc0b11'} | null |
PyPI | GHSA-xpfp-f569-q3p2 | SQL Injection in Django | Django 3.1.x before 3.1.13 and 3.2.x before 3.2.5 allows QuerySet.order_by SQL injection if order_by is untrusted input from a client of a web application. | {'CVE-2021-35042'} | 2022-03-07T20:46:57.413338Z | 2021-09-22T17:34:49Z | CRITICAL | null | {'CWE-89'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://www.openwall.com/lists/oss-security/2021/07/02/2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-35042', 'https://security.netapp.com/advisory/ntap-20210805-0008/', 'https://www.djangoproject.com/weblog/2021/jul/01/security-releases/', 'https://github.com/django/django/commit/0bd57a879a0d54920bb9038a732645fb917040e9', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/SS6NJTBYWOX6J7G4U3LUOILARJKWPQ5Y/'} | null |
PyPI | GHSA-5hmm-x8q8-w5jh | LDAP authentication bypass with empty password | ### Impact
Users may be able to bypass LDAP authentication if they provide an empty password when Alerta server is configure to use LDAP as the authorization provider.
Only deployments where LDAP servers are configured to allow unauthenticated binds (eg. default on Active Directory) are affected.
### Patches
A fix has been implemented that returns HTTP 401 Unauthorized response for any authentication attempts where the password field is empty. See https://github.com/alerta/alerta/pull/1345
### Workarounds
LDAP administrators can disallow unauthenticated bind requests by clients.
### References
https://tools.ietf.org/html/rfc4513#section-5.1.2
https://pypi.org/project/alerta-server/8.1.0/
### For more information
If you have any questions or comments about this advisory:
* Add a comment to the issue [#1277](https://github.com/alerta/alerta/issues/1277)
* Email us at [admin@alerta.dev](mailto:admin@alerta.dev) | {'CVE-2020-26214'} | 2022-03-03T05:13:21.868248Z | 2020-11-06T17:35:49Z | HIGH | null | {'CWE-287'} | {'https://github.com/alerta/alerta/pull/1345', 'https://pypi.org/project/alerta-server/8.1.0/', 'https://github.com/alerta/alerta/issues/1277', 'https://github.com/alerta/alerta/commit/2bfa31779a4c9df2fa68fa4d0c5c909698c5ef65', 'https://tools.ietf.org/html/rfc4513#section-5.1.2', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26214', 'https://github.com/alerta/alerta/security/advisories/GHSA-5hmm-x8q8-w5jh'} | null |
PyPI | PYSEC-2021-271 | null | TensorFlow is an end-to-end open source platform for machine learning. The code for `tf.raw_ops.UncompressElement` can be made to trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/compression_ops.cc#L50-L53) obtains a pointer to a `CompressedElement` from a `Variant` tensor and then proceeds to dereference it for decompressing. There is no check that the `Variant` tensor contained a `CompressedElement`, so the pointer is actually `nullptr`. We have patched the issue in GitHub commit 7bdf50bb4f5c54a4997c379092888546c97c3ebd. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37649', 'GHSA-6gv8-p3vj-pxvr'} | 2021-08-27T03:22:43.879548Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gv8-p3vj-pxvr', 'https://github.com/tensorflow/tensorflow/commit/7bdf50bb4f5c54a4997c379092888546c97c3ebd'} | null |
PyPI | GHSA-fr77-rrx3-cp7g | Heap OOB read in `tf.ragged.cross` | ### Impact
The [shape inference code for `tf.ragged.cross`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/ragged_array_ops.cc#L64) can trigger a read outside of bounds of heap allocated array:
```python
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.RaggedCross(ragged_values=[],
ragged_row_splits=[],
sparse_indices=[[5]],
sparse_values=[],
sparse_shape=[5],
dense_inputs=[['a']],
input_order='RD',
hashed_output=False,
num_buckets=5,
hash_key=2,
out_values_type=tf.string,
out_row_splits_type=tf.int64)
return y
test()
```
### Patches
We have patched the issue in GitHub commit [fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8](https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41212'} | 2022-03-03T05:13:40.961532Z | 2021-11-10T19:00:31Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fr77-rrx3-cp7g', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41212'} | null |
PyPI | PYSEC-2021-621 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` 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-fr77-rrx3-cp7g', 'CVE-2021-41212'} | 2021-12-09T06:35:09.206142Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fr77-rrx3-cp7g'} | null |
PyPI | GHSA-w9fg-xffh-p362 | Denial of service (via resource exhaustion) due to improper input validation on third-party identifier endpoints | ### Impact
Missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion.
### Patches
The issue is fixed by #9321.
### Workarounds
Depending on the needs and configuration of the homeserver a few options are available:
1. Using email as third-party identifiers be disabled by not configuring the `email` setting.
2. Using phone numbers as third-party identifiers can be disabled by ensuring that `account_threepid_delegates.msisdn` is not configured.
3. Additionally, the affected endpoint patterns can be blocked at a reverse proxy:
* `^/_matrix/client/(r0|unstable)/register/email`
* `^/_matrix/client/(r0|unstable)/register/msisdn`
* `^/_matrix/client/(r0|unstable)/account/password`
* `^/_matrix/client/(r0|unstable)/account/3pid` | {'CVE-2021-21394'} | 2022-03-03T05:13:45.656189Z | 2021-04-13T15:12:51Z | MODERATE | null | {'CWE-20'} | {'https://github.com/matrix-org/synapse/pull/9393', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21394', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-w9fg-xffh-p362', 'https://github.com/matrix-org/synapse/pull/9321', 'https://github.com/matrix-org/synapse', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TNNAJOZNMVMXM6AS7RFFKB4QLUJ4IFEY/', 'https://pypi.org/project/matrix-synapse/'} | null |
PyPI | PYSEC-2020-271 | 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'} | 2021-12-09T06:34:40.816458Z | 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 | GHSA-77hv-8796-8ccp | Moderate severity vulnerability that affects Plone and Zope2 | ZPublisher.HTTPRequest._scrubHeader in Zope 2 before 2.13.19, as used in Plone before 4.3 beta 1, allows remote attackers to inject arbitrary HTTP headers via a linefeed (LF) character. | {'CVE-2012-5486'} | 2022-03-03T05:14:05.475059Z | 2018-07-23T19:51:50Z | MODERATE | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://bugs.launchpad.net/zope2/+bug/930812', 'https://github.com/advisories/GHSA-77hv-8796-8ccp', 'https://nvd.nist.gov/vuln/detail/CVE-2012-5486', 'https://plone.org/products/plone/security/advisories/20121106/02', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'http://rhn.redhat.com/errata/RHSA-2014-1194.html'} | null |
PyPI | PYSEC-2022-106 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-21727', 'GHSA-c6fh-56w7-fvjw'} | 2022-03-09T00:18:23.259781Z | 2022-02-03T11:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c6fh-56w7-fvjw', 'https://github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034'} | null |
PyPI | GHSA-8p5c-f328-9fvv | Diffoscope may write to arbitrary locations due to an untrusted archive | diffoscope before 76 writes to arbitrary locations on disk based on the contents of an untrusted archive. | {'CVE-2017-0359'} | 2022-04-26T18:33:06.821118Z | 2018-07-13T16:01:21Z | CRITICAL | null | {'CWE-22'} | {'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=854723', 'https://github.com/anthraxx/diffoscope/commit/632a40828a54b399787c25e7fa243f732aef7e05', 'https://nvd.nist.gov/vuln/detail/CVE-2017-0359', 'https://security-tracker.debian.org/tracker/CVE-2017-0359', 'https://github.com/anthraxx/diffoscope'} | null |
PyPI | PYSEC-2019-149 | null | In Apache Airflow 1.8.2 and earlier, an experimental Airflow feature displayed authenticated cookies, as well as passwords to databases used by Airflow. An attacker who has limited access to airflow, whether it be via XSS or by leaving a machine unlocked can exfiltrate all credentials from the system. | {'CVE-2017-17836', 'GHSA-9gqg-3fxr-9hv7'} | 2021-07-05T00:01:17.060541Z | 2019-01-23T17:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-9gqg-3fxr-9hv7', 'https://lists.apache.org/thread.html/ade4d54ebf614f68dc81a08891755e60ea58ba88e0209233eeea5f57@%3Cdev.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2018-92 | null | A flaw was found in openstack-mistral. By manipulating the SSH private key filename, the std.ssh action can be used to disclose the presence of arbitrary files within the filesystem of the executor running the action. Since std.ssh private_key_filename can take an absolute path, it can be used to assess whether or not a file exists on the executor's filesystem. | {'CVE-2018-16849'} | 2021-08-27T03:22:07.552723Z | 2018-11-02T21:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-16849', 'https://bugs.launchpad.net/mistral/+bug/1783708'} | null |
PyPI | PYSEC-2022-29 | null | It was discovered that the "Trigger DAG with config" screen was susceptible to XSS attacks via the `origin` query argument. This issue affects Apache Airflow versions 2.2.3 and below. | {'CVE-2021-45229', 'GHSA-65xw-pcqw-hjrh'} | 2022-03-04T21:27:14.014874Z | 2022-02-25T09:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-65xw-pcqw-hjrh', 'https://lists.apache.org/thread/phx76cgtmhwwdy780rvwhobx8qoy4bnk'} | null |
PyPI | PYSEC-2020-14 | null | An issue was found in Apache Airflow versions 1.10.10 and below. A remote code/command injection vulnerability was discovered in one of the example DAGs shipped with Airflow which would allow any authenticated user to run arbitrary commands as the user running airflow worker/scheduler (depending on the executor in use). If you already have examples disabled by setting load_examples=False in the config then you are not vulnerable. | {'CVE-2020-11978', 'GHSA-rvmq-4x66-q7j3'} | 2020-07-22T17:15:00Z | 2020-07-17T00:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-rvmq-4x66-q7j3', 'https://lists.apache.org/thread.html/r7255cf0be3566f23a768e2a04b40fb09e52fcd1872695428ba9afe91%40%3Cusers.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2021-733 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-gv26-jpj9-c8gq', 'CVE-2021-29607'} | 2021-12-09T06:35:33.208696Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq', 'https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2'} | null |
PyPI | GHSA-q799-q27x-vp7w | Out-of-bounds Write in OpenCV | An exploitable heap buffer overflow vulnerability exists in the data structure persistence functionality of OpenCV, version 4.1.0 (corresponds with OpenCV-Python version 4.1.2.30). A specially crafted JSON file can cause a buffer overflow, resulting in multiple heap corruptions and potentially code execution. An attacker can provide a specially crafted file to trigger this vulnerability. | {'CVE-2019-5064'} | 2022-04-20T19:16:58.547140Z | 2021-10-12T22:23:21Z | HIGH | null | {'CWE-120', 'CWE-787'} | {'https://github.com/opencv/opencv/releases/tag/4.2.0', 'https://talosintelligence.com/vulnerability_reports/TALOS-2019-0853', 'https://www.oracle.com/security-alerts/cpuApr2021.html', 'https://github.com/opencv/opencv/issues/15857', 'https://github.com/opencv/opencv-python/releases/tag/32', 'https://nvd.nist.gov/vuln/detail/CVE-2019-5064', 'https://www.oracle.com//security-alerts/cpujul2021.html', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2021-363 | null | Scrapy is a high-level web crawling and scraping framework for Python. If you use `HttpAuthMiddleware` (i.e. the `http_user` and `http_pass` spider attributes) for HTTP authentication, all requests will expose your credentials to the request target. This includes requests generated by Scrapy components, such as `robots.txt` requests sent by Scrapy when the `ROBOTSTXT_OBEY` setting is set to `True`, or as requests reached through redirects. Upgrade to Scrapy 2.5.1 and use the new `http_auth_domain` spider attribute to control which domains are allowed to receive the configured HTTP authentication credentials. If you are using Scrapy 1.8 or a lower version, and upgrading to Scrapy 2.5.1 is not an option, you may upgrade to Scrapy 1.8.1 instead. If you cannot upgrade, set your HTTP authentication credentials on a per-request basis, using for example the `w3lib.http.basic_auth_header` function to convert your credentials into a value that you can assign to the `Authorization` header of your request, instead of defining your credentials globally using `HttpAuthMiddleware`. | {'GHSA-jwqp-28gf-p498', 'CVE-2021-41125'} | 2021-10-11T01:16:42.905582Z | 2021-10-06T18:15:00Z | null | null | null | {'https://github.com/scrapy/scrapy/commit/b01d69a1bf48060daec8f751368622352d8b85a6', 'https://github.com/scrapy/scrapy/security/advisories/GHSA-jwqp-28gf-p498', 'https://w3lib.readthedocs.io/en/latest/w3lib.html#w3lib.http.basic_auth_header', 'http://doc.scrapy.org/en/latest/topics/downloader-middleware.html#module-scrapy.downloadermiddlewares.httpauth'} | null |
PyPI | PYSEC-2021-699 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` is vulnerable to a division by 0. The implementation(https://github.com/tensorflow/tensorflow/blob/279bab6efa22752a2827621b7edb56a730233bd8/tensorflow/core/kernels/maxpooling_op.cc#L1033-L1034) fails to validate that the batch dimension of the tensor is non-zero, before dividing by this quantity. 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-9vpm-rcf4-9wqw', 'CVE-2021-29573'} | 2021-12-09T06:35:27.365628Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9vpm-rcf4-9wqw', 'https://github.com/tensorflow/tensorflow/commit/376c352a37ce5a68b721406dc7e77ac4b6cf483d'} | null |
PyPI | GHSA-3x4c-pq33-4w3q | Improper authorisation of members discloses room membership to non-members | ### Impact
Unauthorised users can access the membership (list of members, with their display names) of a room if they know the ID of the room. The vulnerability is limited to rooms with `shared` history visibility. Furthermore, the unauthorised user must be using an account on a vulnerable homeserver that is in the room.
### Patches
Server administrators should upgrade to 1.41.1 or later.
### Workarounds
Administrators of servers that use a reverse proxy could, with potentially unacceptable loss of functionality, block the following endpoints:
* `/_matrix/client/r0/rooms/{room_id}/members` with `at` query parameter
* `/_matrix/client/unstable/rooms/{room_id}/members` with `at` query parameter
### References
n/a
### For more information
If you have any questions or comments about this advisory, e-mail us at security@matrix.org. | {'CVE-2021-39164'} | 2022-03-03T05:12:37.503297Z | 2021-09-01T18:25:27Z | LOW | null | {'CWE-200'} | {'https://github.com/matrix-org/synapse/releases/tag/v1.41.1', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-3x4c-pq33-4w3q', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2VHDEPCZ22GJFMZCWA2XZAGPOEV72POF/', 'https://nvd.nist.gov/vuln/detail/CVE-2021-39164', 'https://github.com/matrix-org/synapse', 'https://github.com/matrix-org/synapse/commit/cb35df940a', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PXT7ID7DNBRN2TVTETU3SYQHJKEG6PXN/'} | null |
PyPI | PYSEC-2020-226 | null | Cross Site Scripting (XSS) vulnerability in Arachnys Cabot 0.11.12 can be exploited via the Address column. | {'CVE-2020-25449'} | 2021-08-27T03:21:56.543783Z | 2020-12-04T20:15:00Z | null | null | null | {'https://packetstormsecurity.com/files/159070/Cabot-0.11.12-Cross-Site-Scripting.html', 'https://www.exploitalert.com/view-details.html?id=36106', 'https://www.exploit-db.com/exploits/48791', 'https://itsmeanonartist.tech/blogs/blog2.html'} | null |
PyPI | GHSA-mqh2-9wrp-vx84 | Heap buffer overflow in `SparseSplit` | ### Impact
An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`:
```python
import tensorflow as tf
shape_dims = tf.constant(0, dtype=tf.int64)
indices = tf.ones([1, 1], dtype=tf.int64)
values = tf.ones([1], dtype=tf.int64)
shape = tf.ones([1], dtype=tf.int64)
tf.raw_ops.SparseSplit(
split_dim=shape_dims, indices=indices, values=values,
shape=shape, num_split=1)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset:
```cc
const int dim = input_tensor.indices().matrix<int64>()(i, split_dim);
int slice_index = GetSliceIndex(dim, split_size, residual);
num_values[slice_index]++;
```
This results in overriding values on the heap.
### Patches
We have patched the issue in GitHub commit [8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31](https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31).
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-2021-29558'} | 2022-03-03T05:13:00.168493Z | 2021-05-21T14:24:51Z | LOW | null | {'CWE-787'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29558', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84', 'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} | null |
PyPI | GHSA-98p5-x8x4-c9m5 | Integer overflow in TFLite | ### Impact
An attacker can craft a TFLite model that would cause an integer overflow [in embedding lookup operations](https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/embedding_lookup_sparse.cc#L179-L189):
```cc
int embedding_size = 1;
int lookup_size = 1;
for (int i = 0; i < lookup_rank - 1; i++, k++) {
const int dim = dense_shape->data.i32[i];
lookup_size *= dim;
output_shape->data[k] = dim;
}
for (int i = 1; i < embedding_rank; i++, k++) {
const int dim = SizeOfDimension(value, i);
embedding_size *= dim;
output_shape->data[k] = dim;
}
```
Both `embedding_size` and `lookup_size` are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication.
In certain scenarios, this can then result in heap OOB read/write.
### Patches
We have patched the issue in GitHub commits [f19be71717c497723ba0cea0379e84f061a75e01](https://github.com/tensorflow/tensorflow/commit/f19be71717c497723ba0cea0379e84f061a75e01), [1de49725a5fc4e48f1a3b902ec3599ee99283043](https://github.com/tensorflow/tensorflow/commit/1de49725a5fc4e48f1a3b902ec3599ee99283043) and [a4e401da71458d253b05e41f28637b65baf64be4](https://github.com/tensorflow/tensorflow/commit/a4e401da71458d253b05e41f28637b65baf64be4).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team. | {'CVE-2022-23559'} | 2022-03-03T05:13:07.271919Z | 2022-02-09T23:52:51Z | HIGH | null | {'CWE-190'} | {'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/embedding_lookup_sparse.cc#L179-L189', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98p5-x8x4-c9m5', 'https://github.com/tensorflow/tensorflow/commit/a4e401da71458d253b05e41f28637b65baf64be4', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23559', 'https://github.com/tensorflow/tensorflow/commit/1de49725a5fc4e48f1a3b902ec3599ee99283043', 'https://github.com/tensorflow/tensorflow/commit/f19be71717c497723ba0cea0379e84f061a75e01', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-39 | null | An issue was discovered in Pillow before 8.1.1. There is an out-of-bounds read in SGIRleDecode.c. | {'GHSA-p43w-g3c5-g5mq', 'CVE-2021-25293'} | 2021-03-22T13:36:00Z | 2021-03-19T04:15:00Z | null | null | null | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://github.com/advisories/GHSA-p43w-g3c5-g5mq'} | null |
PyPI | PYSEC-2021-676 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-f78g-q7r4-9wcv', 'CVE-2021-29550'} | 2021-12-09T06:35:23.467562Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv'} | null |
PyPI | GHSA-g4h2-gqm3-c9wq | Segfault in tf.raw_ops.ImmutableConst | ### Impact
Calling [`tf.raw_ops.ImmutableConst`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars.
```python
>>> import tensorflow as tf
>>> tf.raw_ops.ImmutableConst(dtype=tf.resource, shape=[], memory_region_name="/tmp/test.txt")
...
Segmentation fault
```
### Patches
We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
### Workarounds
If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument.
### 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-2021-29539'} | 2022-03-03T05:13:39.768588Z | 2021-05-21T14:23:05Z | LOW | null | {'CWE-681'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g4h2-gqm3-c9wq', 'https://github.com/tensorflow/tensorflow/commit/4f663d4b8f0bec1b48da6fa091a7d29609980fa4', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29539'} | null |
PyPI | PYSEC-2021-226 | null | TensorFlow is an end-to-end open source platform for machine learning. The reference implementation of the `GatherNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966). An attacker can craft a model such that `params` input would be an empty tensor. In turn, `params_shape.Dims(.)` would be zero, in at least one dimension. 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-3w67-q784-6w7c', 'CVE-2021-29589'} | 2021-08-27T03:22:37.235055Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3w67-q784-6w7c'} | null |
PyPI | PYSEC-2021-251 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-8pmx-p244-g88h', 'CVE-2021-29614'} | 2021-08-27T03:22:41.712204Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h', 'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d'} | null |
PyPI | PYSEC-2021-601 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vcjj-9vg7-vf68', 'CVE-2021-37688'} | 2021-12-09T06:35:06.517637Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vcjj-9vg7-vf68'} | null |
PyPI | GHSA-mv78-g7wq-mhp4 | Division by zero in padding computation in TFLite | ### Impact
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.
```cc
inline int ComputeOutSize(TfLitePadding padding, int image_size,
int filter_size, int stride, int dilation_rate = 1) {
int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
switch (padding) {
case kTfLitePaddingSame:
return (image_size + stride - 1) / stride;
case kTfLitePaddingValid:
return (image_size + stride - effective_filter_size) / stride;
default:
return 0;
}
}
```
Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0.
### Patches
We have patched the issue in GitHub commit [49847ae69a4e1a97ae7f2db5e217c77721e37948](https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29585'} | 2022-03-03T05:12:56.224293Z | 2021-05-21T14:26:41Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mv78-g7wq-mhp4', 'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29585'} | null |
PyPI | PYSEC-2020-251 | null | The Scalyr Agent before 2.1.10 has Missing SSL Certificate Validation because, in some circumstances, the openssl binary is called without the -verify_hostname option. | {'CVE-2020-24714'} | 2021-08-27T03:22:21.123825Z | 2020-08-27T22:15:00Z | null | null | null | {'https://scalyr-static.s3.amazonaws.com/technical-details/index.html'} | null |
PyPI | GHSA-9vg3-cf92-h2h7 | Insufficient Verification of Data Authenticity in python-keystoneclient | python-keystoneclient version 0.2.3 to 0.2.5 has middleware memcache signing bypass | {'CVE-2013-2167'} | 2022-03-23T20:00:10.830873Z | 2020-03-10T20:39:05Z | CRITICAL | null | {'CWE-345'} | {'http://www.openwall.com/lists/oss-security/2013/06/19/5', 'https://github.com/openstack/python-keystoneclient/commits/0.3.0', 'https://bugs.gentoo.org/show_bug.cgi?id=CVE-2013-2167', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2013-2167', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/85492', 'https://nvd.nist.gov/vuln/detail/CVE-2013-2167', 'http://rhn.redhat.com/errata/RHSA-2013-0992.html', 'http://www.securityfocus.com/bid/60680', 'https://github.com/openstack/python-keystoneclient/commit/eeefb784f24c37d5f56a421e1ccc911cace9385e', 'https://security-tracker.debian.org/tracker/CVE-2013-2167', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-August/113944.html', 'https://access.redhat.com/security/cve/cve-2013-2167'} | null |
PyPI | PYSEC-2020-314 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'GHSA-x5cp-9pcf-pp3h', 'CVE-2020-15199'} | 2021-12-09T06:35:13.149576Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x5cp-9pcf-pp3h'} | null |
PyPI | PYSEC-2017-39 | null | Salt-api in SaltStack Salt before 2015.8.13, 2016.3.x before 2016.3.5, and 2016.11.x before 2016.11.2 allows arbitrary command execution on a salt-master via Salt's ssh_client. | {'CVE-2017-5200'} | 2021-07-05T00:01:26.833704Z | 2017-09-26T14:29:00Z | null | null | null | {'https://docs.saltstack.com/en/2016.3/topics/releases/2015.8.13.html', 'https://docs.saltstack.com/en/latest/topics/releases/2016.11.2.html', 'https://docs.saltstack.com/en/2016.3/topics/releases/2016.3.5.html'} | null |
PyPI | GHSA-86vp-x3pr-79rx | Cross-site scripting in Apache airflow | The "origin" parameter passed to some of the endpoints like '/trigger' was vulnerable to XSS exploit. This issue affects Apache Airflow versions prior to 1.10.14. This is same as CVE-2020-13944 but the implemented fix in Airflow 1.10.13 did not fix the issue completely. | {'CVE-2020-17515'} | 2022-03-03T05:12:26.343329Z | 2021-04-20T16:40:14Z | MODERATE | null | {'CWE-79'} | {'http://www.openwall.com/lists/oss-security/2021/05/01/2', 'https://nvd.nist.gov/vuln/detail/CVE-2020-17515', 'https://pypi.org/project/apache-airflow', 'https://lists.apache.org/thread.html/r4656959c8ed06c1f6202d89aa4e67b35ad7bdba5a666caff3fea888e%40%3Cusers.airflow.apache.org%3E', 'https://github.com/apache/airflow/commit/409c249121bd9c8902fc2ba551b21873ab41f953', 'http://www.openwall.com/lists/oss-security/2020/12/11/2', 'https://github.com/apache/airflow/releases/tag/1.10.15', 'https://lists.apache.org/thread.html/r2892ef594dbbf54d0939b808626f52f7c2d1584f8aa1d81570847d2a@%3Cdev.airflow.apache.org%3E', 'https://github.com/apache/airflow/pull/14738', 'https://lists.apache.org/thread.html/r2892ef594dbbf54d0939b808626f52f7c2d1584f8aa1d81570847d2a@%3Cannounce.apache.org%3E', 'https://github.com/apache/airflow/releases/tag/2.0.2', '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://lists.apache.org/thread.html/ra8ce70088ba291f358e077cafdb14d174b7a1ce9a9d86d1b332d6367@%3Cusers.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/rc005f4de9d9b0ba943ceb8ff5a21a5c6ff8a9df52632476698d99432@%3Cannounce.apache.org%3E'} | null |
PyPI | PYSEC-2019-217 | null | In Pallets Jinja before 2.10.1, str.format_map allows a sandbox escape. | {'CVE-2019-10906', 'GHSA-462w-v97r-4m45'} | 2021-11-22T04:57:52.862665Z | 2019-04-07T00:29:00Z | null | null | null | {'https://lists.apache.org/thread.html/2b52b9c8b9d6366a4f1b407a8bde6af28d9fc73fdb3b37695fd0d9ac@%3Cdevnull.infra.apache.org%3E', 'https://github.com/advisories/GHSA-462w-v97r-4m45', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QCDYIS254EJMBNWOG4S5QY6AOTOR4TZU/', 'http://lists.opensuse.org/opensuse-security-announce/2019-05/msg00030.html', 'https://lists.apache.org/thread.html/57673a78c4d5c870d3f21465c7e2946b9f8285c7c57e54c2ae552f02@%3Ccommits.airflow.apache.org%3E', 'https://usn.ubuntu.com/4011-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TS7IVZAJBWOHNRDMFJDIZVFCMRP6YIUQ/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DSW3QZMFVVR7YE3UT4YRQA272TYAL5AF/', 'https://lists.apache.org/thread.html/b2380d147b508bbcb90d2cad443c159e63e12555966ab4f320ee22da@%3Ccommits.airflow.apache.org%3E', 'https://usn.ubuntu.com/4011-2/', 'https://palletsprojects.com/blog/jinja-2-10-1-released', 'https://lists.apache.org/thread.html/46c055e173b52d599c648a98199972dbd6a89d2b4c4647b0500f2284@%3Cdevnull.infra.apache.org%3E', 'https://access.redhat.com/errata/RHSA-2019:1329', 'https://lists.apache.org/thread.html/320441dccbd9a545320f5f07306d711d4bbd31ba43dc9eebcfc602df@%3Cdevnull.infra.apache.org%3E', 'https://access.redhat.com/errata/RHSA-2019:1237', 'https://lists.apache.org/thread.html/7f39f01392d320dfb48e4901db68daeece62fd60ef20955966739993@%3Ccommits.airflow.apache.org%3E', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00064.html', 'https://access.redhat.com/errata/RHSA-2019:1152', 'https://lists.apache.org/thread.html/f0c4a03418bcfe70c539c5dbaf99c04c98da13bfa1d3266f08564316@%3Ccommits.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/09fc842ff444cd43d9d4c510756fec625ef8eb1175f14fd21de2605f@%3Cdevnull.infra.apache.org%3E'} | null |
PyPI | GHSA-9c29-9h4m-wg5p | Users can view database names in Apache Superset | In Apache Incubator Superset before 0.32, a user can view database names that he has no access to on a dropdown list in SQLLab | {'CVE-2019-12414'} | 2021-08-19T19:25:35Z | 2020-02-26T19:55:14Z | MODERATE | null | {'CWE-200'} | {'https://lists.apache.org/thread.html/396034aabe08dd349ff44eb062c718aadcf1b4e86f6372c7d5e988c0%40%3Cdev.superset.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2019-12414'} | null |
PyPI | PYSEC-2011-2 | null | The verify_exists functionality in the URLField implementation in Django before 1.2.7 and 1.3.x before 1.3.1 relies on Python libraries that attempt access to an arbitrary URL with no timeout, which allows remote attackers to cause a denial of service (resource consumption) via a URL associated with (1) a slow response, (2) a completed TCP connection with no application data sent, or (3) a large amount of application data, a related issue to CVE-2011-1521. | {'CVE-2011-4137', 'GHSA-3jqw-crqj-w8qw'} | 2021-07-05T00:01:17.875375Z | 2011-10-19T10:55:00Z | null | null | null | {'https://www.djangoproject.com/weblog/2011/sep/09/', 'http://openwall.com/lists/oss-security/2011/09/13/2', 'http://www.debian.org/security/2011/dsa-2332', 'http://openwall.com/lists/oss-security/2011/09/15/5', 'https://hermes.opensuse.org/messages/14700881', 'https://github.com/advisories/GHSA-3jqw-crqj-w8qw', 'http://openwall.com/lists/oss-security/2011/09/11/1', 'https://bugzilla.redhat.com/show_bug.cgi?id=737366', 'http://secunia.com/advisories/46614', 'https://www.djangoproject.com/weblog/2011/sep/10/127/'} | null |
PyPI | GHSA-6m9g-jr8c-cqw3 | Depth counting error in guard() leading to multiple potential security issues in aioxmpp | ### Impact
Possible remote Denial of Service or Data Injection.
### Patches
Patches are available in https://github.com/horazont/aioxmpp/pull/268. They have been backported to the 0.10 release series and 0.10.3 is the first release to contain the fix.
### Workarounds
To make the bug exploitable, an error suppressing ``xso_error_handler`` is required. By not using ``xso_error_handlers`` or not using the suppression function, the vulnerability can be mitigated completely (to our knowledge).
### References
The pull request contains a detailed description: https://github.com/horazont/aioxmpp/pull/268
### For more information
If you have any questions or comments about this advisory:
* [Join our chat](xmpp:aioxmpp@conference.zombofant.net?join)
* Email the maintainer [Jonas Schäfer](mailto:jonas@wielicki.name) | {'CVE-2019-1000007'} | 2022-03-03T05:14:02.836006Z | 2020-04-29T17:12:39Z | HIGH | null | {'CWE-237'} | {'https://github.com/horazont/aioxmpp/commit/29ff0838a40f58efe30a4bbcea95aa8dab7da475', 'https://nvd.nist.gov/vuln/detail/CVE-2019-1000007', 'https://github.com/horazont/aioxmpp/commit/f151f920f439d97d4103fc11057ed6dc34fe98be', 'https://github.com/horazont/aioxmpp/pull/268', 'https://github.com/horazont/aioxmpp/security/advisories/GHSA-6m9g-jr8c-cqw3'} | null |
PyPI | PYSEC-2021-314 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version. | {'CVE-2021-37692', 'GHSA-cmgw-8vpc-rc59'} | 2021-08-27T03:22:47.865620Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cmgw-8vpc-rc59', 'https://github.com/tensorflow/tensorflow/pull/50508'} | null |
PyPI | PYSEC-2019-27 | null | invenio-records before 1.2.2 allows XSS. | {'CVE-2019-1020003', 'GHSA-vxh3-mvv7-265j'} | 2019-08-01T16:29:00Z | 2019-07-29T15:15:00Z | null | null | null | {'https://github.com/inveniosoftware/invenio-records/security/advisories/GHSA-vxh3-mvv7-265j'} | null |
PyPI | PYSEC-2021-744 | null | TensorFlow is an end-to-end open source platform for machine learning. Passing a complex argument to `tf.transpose` at the same time as passing `conjugate=True` argument results in a crash. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-xqfj-cr6q-pc8w', 'CVE-2021-29618'} | 2021-12-09T06:35:35.049527Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/issues/46973', 'https://github.com/tensorflow/issues/42105', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-cr6q-pc8w', 'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88'} | null |
PyPI | PYSEC-2018-1 | null | Unauthenticated access to cloudtoken daemon on Linux via network from version 0.1.1 before version 0.1.24 allows attackers on the same subnet to gain temporary AWS credentials for the users' roles. | {'CVE-2018-13390'} | 2021-06-10T06:50:35.324330Z | 2018-08-10T15:29:00Z | null | null | null | {'https://bitbucket.org/atlassian/cloudtoken/wiki/CVE-2018-13390%20-%20Exposed%20credentials%20in%20daemon%20mode%20on%20Linux'} | null |
PyPI | PYSEC-2020-63 | null | OpenStack Manila <7.4.1, >=8.0.0 <8.1.1, and >=9.0.0 <9.1.1 allows attackers to view, update, delete, or share resources that do not belong to them, because of a context-free lookup of a UUID. Attackers may also create resources, such as shared file systems and groups of shares on such share networks. | {'CVE-2020-9543'} | 2020-07-14T17:27:00Z | 2020-03-12T17:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2020/03/12/1', 'https://security.openstack.org/ossa/OSSA-2020-002.html', 'https://bugs.launchpad.net/manila/+bug/1861485'} | null |
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