TQRG/raw-osv-data huggingface dataset:
Vulnerability: GHSA-4p4p-www8-8fv9
Summary: Reference binding to null in `ParameterizedTruncatedNormal`
Aliases: CVE-2021-29568
Severity: LOW
CWE: CWE-824
Published: 2021-05-21T14:25:19Z

### Impact
An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`:

```python
import tensorflow as tf
    
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
  
tf.raw_ops.ParameterizedTruncatedNormal(
  shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)
```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`:

```cc
int32 num_batches = shape_tensor.flat<int32>()(0);
``` 

If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array.

### Patches
We have patched the issue in GitHub commit [5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8](https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

### For more information 
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
Vulnerability: PYSEC-2020-202
Aliases: CVE-2014-4660
Published: 2020-02-20T03:15:00Z

Ansible before 1.5.5 constructs filenames containing user and password fields on the basis of deb lines in sources.list, which might allow local users to obtain sensitive credential information in opportunistic circumstances by leveraging existence of a file that uses the "deb http://user:pass@server:port/" format.
Vulnerability: PYSEC-2021-652
Aliases: GHSA-4vf2-4xcg-65cx, CVE-2021-29526
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2021-202
Aliases: GHSA-r6pg-pjwc-j585, CVE-2021-29565
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2016-10
Aliases: CVE-2016-1494
Published: 2016-01-13T15:59:00Z

The verify function in the RSA package for Python (Python-RSA) before 3.3 allows attackers to spoof signatures with a small public exponent via crafted signature padding, aka a BERserk attack.
Vulnerability: GHSA-2ww3-fxvq-293j
Summary: Inefficient Regular Expression in nltk
Aliases: CVE-2021-3828
Severity: HIGH
CWE: CWE-697, CWE-1333
Published: 2021-09-29T17:14:53Z

nltk is contains an Inefficient Regular Expression and is vulnerable to regular expression denial of service attacks.
Vulnerability: PYSEC-2021-486
Aliases: GHSA-mqh2-9wrp-vx84, CVE-2021-29558
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: GHSA-m34j-p8rj-wjxq
Summary: Division by 0 in `QuantizedBiasAdd`
Aliases: CVE-2021-29546
Severity: LOW
CWE: CWE-369
Published: 2021-05-21T14:23:28Z

### Impact
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:

```python
import tensorflow as tf

input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
bias = tf.constant([], shape=[0], dtype=tf.quint8)
min_input = tf.constant(-10.0, dtype=tf.float32)
max_input = tf.constant(-10.0, dtype=tf.float32)
min_bias = tf.constant(-10.0, dtype=tf.float32)
max_bias = tf.constant(-10.0, dtype=tf.float32)

tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input,
                            max_input=max_input, min_bias=min_bias,
                            max_bias=max_bias, out_type=tf.qint32)
```

This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero:

```cc
template <typename T1, typename T2, typename T3>
void QuantizedAddUsingEigen(const Eigen::ThreadPoolDevice& device,
                            const Tensor& input, float input_min,
                            float input_max, const Tensor& smaller_input,
                            float smaller_input_min, float smaller_input_max,
                            Tensor* output, float* output_min,
                            float* output_max) {
  ...
  const int64 input_element_count = input.NumElements();
  const int64 smaller_input_element_count = smaller_input.NumElements();
  ...
  bcast[0] = input_element_count / smaller_input_element_count;
  ...
}
```

This integral division by 0 is undefined behavior.

### Patches
We have patched the issue in GitHub commit [67784700869470d65d5f2ef20aeb5e97c31673cb](https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.
Vulnerability: PYSEC-2020-88
Aliases: CVE-2020-7939
Published: 2020-01-23T21:15:00Z

SQL Injection in DTML or in connection objects in Plone 4.0 through 5.2.1 allows users to perform unwanted SQL queries. (This is a problem in Zope.)
Vulnerability: GHSA-fh37-cx83-q542
Summary: Improper Authentication in Apache Airflow
Aliases: CVE-2021-26697
Severity: MODERATE
CWE: CWE-287, CWE-269
Published: 2021-06-18T18:30:11Z

The lineage endpoint of the deprecated Experimental API was not protected by authentication in Airflow 2.0.0. This allowed unauthenticated users to hit that endpoint. This is low-severity issue as the attacker needs to be aware of certain parameters to pass to that endpoint and even after can just get some metadata about a DAG and a Task. This issue only affects Apache Airflow 2.0.0.
Vulnerability: PYSEC-2020-67
Aliases: CVE-2020-25074, GHSA-52q8-877j-gghq
Published: 2020-11-10T17:15:00Z

The cache action in action/cache.py in MoinMoin through 1.9.10 allows directory traversal through a crafted HTTP request. An attacker who can upload attachments to the wiki can use this to achieve remote code execution.
Vulnerability: PYSEC-2021-469
Aliases: CVE-2021-29541, GHSA-xqfj-35wv-m3cr
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in `ngrams_data`(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size. Later writes to the output tensor would then cause a null pointer dereference. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2021-193
Aliases: GHSA-fxqh-cfjm-fp93, CVE-2021-29556
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: GHSA-xqfj-35wv-m3cr
Summary: Null pointer dereference in `StringNGrams`
Aliases: CVE-2021-29541
Severity: LOW
CWE: CWE-476
Published: 2021-05-21T14:23:12Z

### Impact
An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`:

```python
import tensorflow as tf

data=tf.constant([''] * 11, shape=[11], dtype=tf.string)

splits = [0]*115
splits.append(3)
data_splits=tf.constant(splits, shape=[116], dtype=tf.int64)

tf.raw_ops.StringNGrams(data=data, data_splits=data_splits, separator=b'Ss',
                        ngram_widths=[7,6,11],
                        left_pad='ABCDE', right_pad=b'ZYXWVU',
                        pad_width=50, preserve_short_sequences=True)
```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in [`ngrams_data`](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size.

Later writes to the output tensor would then cause a null pointer dereference.

### Patches
We have patched the issue in GitHub commit [ba424dd8f16f7110eea526a8086f1a155f14f22b](https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b).
    
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

### For more information 
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
  
### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.
Vulnerability: PYSEC-2022-175
Aliases: CVE-2022-0315, GHSA-47wv-vhj2-g66m
Published: 2022-03-24T09:15:00Z

Insecure Temporary File in GitHub repository horovod/horovod prior to 0.24.0.
Vulnerability: PYSEC-2019-213
Aliases: GHSA-27p5-7cw6-m45h, CVE-2019-17400
Published: 2019-10-21T23:15:00Z

The unoconv package before 0.9 mishandles untrusted pathnames, leading to SSRF and local file inclusion.
Vulnerability: GHSA-63rq-p8fp-524q
Summary: Potential API key leak
Severity: MODERATE
CWE: CWE-200
Published: 2021-04-13T15:12:06Z

If a user is actively blackholing the location or weather APIs, or those APIs become otherwise unavailable, it is possible for the API keys to get leaked to the active IRC channel.

This is patched in v1.2.4
Vulnerability: PYSEC-2020-310
Aliases: GHSA-63xm-rx5p-xvqr, CVE-2020-15195
Published: 2020-09-25T19:15:00Z

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Vulnerability: PYSEC-2011-6
Aliases: CVE-2011-1058
Published: 2011-02-22T18:00:00Z

Cross-site scripting (XSS) vulnerability in the reStructuredText (rst) parser in parser/text_rst.py in MoinMoin before 1.9.3, when docutils is installed or when "format rst" is set, allows remote attackers to inject arbitrary web script or HTML via a javascript: URL in the refuri attribute.  NOTE: some of these details are obtained from third party information.
Vulnerability: PYSEC-2019-23
Aliases: GHSA-xjjg-vmw6-c2p9, CVE-2019-10751, SNYK-PYTHON-HTTPIE-460107
Published: 2019-08-23T17:15:00Z

All versions of the HTTPie package prior to version 1.0.3 are vulnerable to Open Redirect that allows an attacker to write an arbitrary file with supplied filename and content to the current directory, by redirecting a request from HTTP to a crafted URL pointing to a server in his or hers control.
Vulnerability: PYSEC-2021-310
Aliases: GHSA-vcjj-9vg7-vf68, CVE-2021-37688
Published: 2021-08-12T22:15:00Z

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.
Vulnerability: PYSEC-2018-5
Aliases: CVE-2018-7536, GHSA-r28v-mw67-m5p9
Published: 2018-03-09T20:29:00Z

An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. The django.utils.html.urlize() function was extremely slow to evaluate certain inputs due to catastrophic backtracking vulnerabilities in two regular expressions (only one regular expression for Django 1.8.x). The urlize() function is used to implement the urlize and urlizetrunc template filters, which were thus vulnerable.
Vulnerability: PYSEC-2021-740
Aliases: GHSA-8pmx-p244-g88h, CVE-2021-29614
Published: 2021-05-14T20:15:00Z

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.
Vulnerability: GHSA-374m-jm66-3vj8
Summary: Heap OOB in `SparseBinCount`
Aliases: CVE-2021-41226
Severity: HIGH
CWE: CWE-125
Published: 2021-11-10T18:41:47Z

### Impact
The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/bincount_op.cc#L353-L417) of `SparseBinCount` is vulnerable to a heap OOB:

```python
import tensorflow as tf
  
  
tf.raw_ops.SparseBincount(
  indices=[[0],[1],[2]]
  values=[0,-10000000]
  dense_shape=[1,1]
  size=[1]
  weights=[3,2,1]
  binary_output=False)
```

This is because of missing validation between the elements of the `values` argument and the shape of the sparse output:


```cc
for (int64_t i = 0; i < indices_mat.dimension(0); ++i) {
  const int64_t batch = indices_mat(i, 0);
  const Tidx bin = values(i);
  ...
  out(batch, bin) = ...;
}
```

### Patches
We have patched the issue in GitHub commit [f410212e373eb2aec4c9e60bf3702eba99a38aba](https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Vulnerability: GHSA-gfp2-w5jm-955q
Summary: OMERO.web exposes some unnecessary session information in the page
Aliases: CVE-2021-21376
Severity: MODERATE
CWE: CWE-200
Published: 2021-03-23T15:26:34Z

### Background
OMERO.web loads various information about the current user such as their id, name and the groups they are in, and these are available on the main webclient pages. Some additional information being loaded is not used by the webclient and is being removed in this release.

### Impact
OMERO.web before 5.9.0

### Patches
5.9.0

### Workarounds
No workaround

### References

### For more information
If you have any questions or comments about this advisory:
* Open an issue in [omero-web](https://github.com/ome/omero-web)
* Email us at [security](mailto:security@openmicroscopy.org.uk)
Vulnerability: PYSEC-2021-255
Aliases: GHSA-xqfj-cr6q-pc8w, CVE-2021-29618
Published: 2021-05-14T20:15:00Z

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.
Vulnerability: GHSA-9crf-c6qr-r273
Summary: Integer division by 0 in `tf.raw_ops.AllToAll`
Aliases: CVE-2021-41218
Severity: MODERATE
CWE: CWE-369
Published: 2021-11-10T18:52:24Z

### Impact
The [shape inference code for `AllToAll`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/tpu_cross_replica_ops.cc#L25-L74) can be made to execute a division by 0:

```python
import tensorflow as tf
  
@tf.function
def func():
  return tf.raw_ops.AllToAll(
    input=[0.0, 0.1652, 0.6543],
    group_assignment=[1, -1],
    concat_dimension=0,
    split_dimension=0,
    split_count=0)

func()
```

This occurs whenever the `split_count` argument is 0:
  
```cc
TF_RETURN_IF_ERROR(c->GetAttr("split_count", &split_count));
...                  
for (int32_t i = 0; i < rank; ++i) {      
  ...                                     
  dims[i] = c->MakeDim(c->Value(dims[i]) / split_count);
  ...                
}
```

### Patches
We have patched the issue in GitHub commit [a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc](https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Vulnerability: PYSEC-2021-605
Aliases: CVE-2021-37692, GHSA-cmgw-8vpc-rc59
Published: 2021-08-12T23:15:00Z

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.
Vulnerability: PYSEC-2020-255
Aliases: CVE-2020-26268, GHSA-hhvc-g5hv-48c6
Published: 2020-12-10T23:15:00Z

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.
Vulnerability: PYSEC-2017-102
Aliases: CVE-2017-8342
Published: 2017-04-30T15:59:00Z

Radicale before 1.1.2 and 2.x before 2.0.0rc2 is prone to timing oracles and simple brute-force attacks when using the htpasswd authentication method.
Vulnerability: GHSA-v542-8q9x-cffc
Summary: Exposure of Sensitive Information to an Unauthorized Actor
Aliases: CVE-2020-35681
Severity: HIGH
CWE: CWE-200
Published: 2021-03-19T21:29:02Z

Django Channels 3.x before 3.0.3 allows remote attackers to obtain sensitive information from a different request scope. The legacy channels.http.AsgiHandler class, used for handling HTTP type requests in an ASGI environment prior to Django 3.0, did not correctly separate request scopes in Channels 3.0. In many cases this would result in a crash but, with correct timing, responses could be sent to the wrong client, resulting in potential leakage of session identifiers and other sensitive data. Note that this affects only the legacy Channels provided class, and not Django's similar ASGIHandler, available from Django 3.0.
Vulnerability: GHSA-9px9-73fg-3fqp
Summary: Null pointer dereference in Grappler's `IsConstant`
Aliases: CVE-2022-23589
Severity: MODERATE
CWE: CWE-476
Published: 2022-02-09T23:29:14Z

### Impact
Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place):

First, during [constant folding](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L3466-L3497), the `GraphDef` might not have the required nodes for the binary operation:

```cc
  NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
  NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
  // One child must be constant, and the second must be Conv op.
  const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
  const bool right_child_is_constant = IsReallyConstant(*mul_right_child);
```

If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect.

We have a similar issue during [`IsIdentityConsumingSwitch`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/mutable_graph_view.cc#L59-L74):

```cc
  NodeDef* input_node = graph.GetNode(tensor_id.node());
  return IsSwitch(*input_node);
```

### Patches
We have patched the issue in GitHub commits [0a365c029e437be0349c31f8d4c9926b69fa3fa1](https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1) and [045deec1cbdebb27d817008ad5df94d96a08b1bf](https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
Vulnerability: GHSA-qw5h-7f53-xrp6
Summary: Stack overflow in `ParseAttrValue` with nested tensors
Aliases: CVE-2021-29615
Severity: LOW
CWE: CWE-674
Published: 2021-05-21T14:28:45Z

### Impact
The implementation of [`ParseAttrValue`](https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/framework/attr_value_util.cc#L397-L453) can be tricked into stack overflow due to recursion by giving in a specially crafted input.

### Patches
We have patched the issue in GitHub commit [e07e1c3d26492c06f078c7e5bf2d138043e199c1](https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
Vulnerability: PYSEC-2020-222
Aliases: CVE-2020-13948
Published: 2020-09-17T13:15:00Z

While investigating a bug report on Apache Superset, it was determined that an authenticated user could craft requests via a number of templated text fields in the product that would allow arbitrary access to Python’s `os` package in the web application process in versions < 0.37.1. It was thus possible for an authenticated user to list and access files, environment variables, and process information. Additionally it was possible to set environment variables for the current process, create and update files in folders writable by the web process, and execute arbitrary programs accessible by the web process. All other operations available to the `os` package in Python were also available, even if not explicitly enumerated in this CVE.
Vulnerability: GHSA-6g87-ff9q-v847
Summary: High severity vulnerability that affects websockets
Aliases: CVE-2018-1000518
Severity: HIGH
CWE: CWE-400
Published: 2018-09-17T20:46:52Z

The Python websockets library version 4 contains a CWE-409: Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Servers and clients, unless configured with compression=None that can result in Denial of Service by memory exhaustion. This attack appears to be exploitable via sending a specially crafted frame on an established connection. This vulnerability appears to have been fixed in version 5.0
Vulnerability: PYSEC-2021-672
Aliases: CVE-2021-29546, GHSA-m34j-p8rj-wjxq
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2021-388
Aliases: CVE-2020-26705, GHSA-v899-28g4-qmh8
Published: 2021-10-31T20:15:00Z

The parseXML function in Easy-XML 0.5.0 was discovered to have a XML External Entity (XXE) vulnerability which allows for an attacker to expose sensitive data or perform a denial of service (DOS) via a crafted external entity entered into the XML content as input.
Vulnerability: PYSEC-2021-222
Aliases: GHSA-mv78-g7wq-mhp4, CVE-2021-29585
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2021-737
Aliases: GHSA-9rpc-5v9q-5r7f, CVE-2021-29611
Published: 2021-05-14T20:15:00Z

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. The implementation(https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments specify a valid sparse tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions.
Vulnerability: PYSEC-2022-102
Aliases: GHSA-gwcx-jrx4-92w2, CVE-2022-23593
Published: 2022-02-04T23:15:00Z

Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.
Vulnerability: PYSEC-2020-10
Aliases: CVE-2020-1738, GHSA-f85h-23mf-2fwh
Published: 2020-03-16T16:15:00Z

A flaw was found in Ansible Engine when the module package or service is used and the parameter 'use' is not specified. If a previous task is executed with a malicious user, the module sent can be selected by the attacker using the ansible facts file. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable.
Vulnerability: PYSEC-2018-96
Aliases: GHSA-vqgp-4jgj-5j64, CVE-2018-18920
Published: 2018-11-12T02:29:00Z

Py-EVM v0.2.0-alpha.33 allows attackers to make a vm.execute_bytecode call that triggers computation._stack.values with '"stack": [100, 100, 0]' where b'\x' was expected, resulting in an execution failure because of an invalid opcode. This is reportedly related to "smart contracts can be executed indefinitely without gas being paid."
Vulnerability: PYSEC-2016-8
Aliases: GHSA-rwr3-c2q8-gm56, CVE-2016-9189
Published: 2016-11-04T10:59:00Z

Pillow before 3.3.2 allows context-dependent attackers to obtain sensitive information by using the "crafted image file" approach, related to an "Integer Overflow" issue affecting the Image.core.map_buffer in map.c component.
Vulnerability: PYSEC-2021-808
Aliases: GHSA-gh8h-7j2j-qv4f, CVE-2021-41200
Published: 2021-11-05T20:15:00Z

TensorFlow is an open source platform for machine learning. In affected versions if `tf.summary.create_file_writer` is called with non-scalar arguments code crashes due to a `CHECK`-fail. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Vulnerability: PYSEC-2010-19
Aliases: CVE-2010-2422
Published: 2010-06-24T12:17:00Z

Cross-site scripting (XSS) vulnerability in PortalTransforms in Plone 2.1 through 3.3.4 before hotfix 20100612 allows remote attackers to inject arbitrary web script or HTML via the safe_html transform.
Vulnerability: PYSEC-2018-79
Aliases: GHSA-6g87-ff9q-v847, CVE-2018-1000518
Published: 2018-06-26T16:29:00Z

aaugustin websockets version 4 contains a CWE-409: Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Servers and clients, unless configured with compression=None that can result in Denial of Service by memory exhaustion. This attack appear to be exploitable via Sending a specially crafted frame on an established connection. This vulnerability appears to have been fixed in 5.
Vulnerability: GHSA-x5h4-9gqw-942j
Summary: Improper Verification of Cryptographic Signature in aws-encryption-sdk
Severity: MODERATE
CWE: CWE-347
Published: 2021-06-01T21:17:53Z

### Impact

This advisory addresses several LOW severity issues with streaming signed messages and restricting processing of certain types of invalid messages. 

This ESDK supports a streaming mode where callers may stream the plaintext of signed messages before the ECDSA signature is validated. In addition to these signatures, the ESDK uses AES-GCM encryption and all plaintext is verified before being released to a caller. There is no impact on the integrity of the ciphertext or decrypted plaintext, however some callers may rely on the the ECDSA signature for non-repudiation. Without validating the ECDSA signature, an actor with trusted KMS permissions to decrypt a message may also be able to encrypt messages. This update introduces a new API for callers who wish to stream only unsigned messages. 

For customers who process ESDK messages from untrusted sources, this update also introduces a new configuration to limit the number of Encrypted Data Keys (EDKs) that the ESDK will attempt to process per message. This configuration provides customers with a way to limit the number of AWS KMS Decrypt API calls that the ESDK will make per message. This setting will reject messages with more EDKs than the configured limit.

Finally, this update adds early rejection of invalid messages with certain invalid combinations of algorithm suite and header data.

### Patches

Fixed in versions 1.9 and 2.2. We recommend that all users upgrade to address these issues.

Customers leveraging the ESDK’s streaming features have several options to protect signature validation. One is to ensure that client code reads to the end of the stream before using released plaintext. With this release, using the new API for streaming and falling back to the non-streaming decrypt API for signed messages prevents using any plaintext from signed data before the signature is validated. See https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x

Users processing ESDK messages from untrusted sources should use the new maximum encrypted data keys parameter. See https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x

### Workarounds

None

### For more information

https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/concepts.html#digital-sigs

https://docs.aws.amazon.com/encryption-sdk/latest/developer-guide/about-versions.html#version2.2.x
Vulnerability: PYSEC-2021-275
Aliases: GHSA-qjj8-32p7-h289, CVE-2021-37653
Published: 2021-08-12T18:15:00Z

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.
Vulnerability: GHSA-gf2j-f278-xh4v
Summary: Division by zero in TFLite
Aliases: CVE-2022-23557
Severity: MODERATE
CWE: CWE-369
Published: 2022-02-09T23:47:57Z

### Impact 
An attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75):

```cc
inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
                         const float* bias_data, int array_size,
                         float* array_data) {
  // ...
  TFLITE_DCHECK_EQ((array_size % bias_size), 0);
  // ...
} 
```
  
There is no check that the `bias_size` is non zero.
  
### Patches
We have patched the issue in GitHub commit [8c6f391a2282684a25cbfec7687bd5d35261a209](https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

### Attribution
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team.
Vulnerability: GHSA-2j58-pwwv-x666
Summary: Cross-Site Request Forgery in sqlite-web
Aliases: CVE-2021-23404
Severity: HIGH
CWE: CWE-352
Published: 2021-09-09T17:10:35Z

This affects all versions of package sqlite-web. The SQL dashboard area allows sensitive actions to be performed without validating that the request originated from the application. This could enable an attacker to trick a user into performing these actions unknowingly through a Cross Site Request Forgery (CSRF) attack.
Vulnerability: GHSA-m4fw-77v7-924m
Summary: Moderate severity vulnerability that affects qutebrowser
Aliases: CVE-2018-1000559
Severity: MODERATE
CWE: CWE-79
Published: 2018-09-13T15:47:57Z

qutebrowser version introduced in v0.11.0 (1179ee7a937fb31414d77d9970bac21095358449) contains a Cross Site Scripting (XSS) vulnerability in history command, qute://history page that can result in Via injected JavaScript code, a website can steal the user's browsing history. This attack appear to be exploitable via the victim must open a page with a specially crafted <title> attribute, and then open the qute://history site via the :history command. This vulnerability appears to have been fixed in fixed in v1.3.3 (4c9360237f186681b1e3f2a0f30c45161cf405c7, to be released today) and v1.4.0 (5a7869f2feaa346853d2a85413d6527c87ef0d9f, released later this week).
Vulnerability: PYSEC-2021-625
Aliases: CVE-2021-41216, GHSA-3ff2-r28g-w7h9
Published: 2021-11-05T23:15:00Z

TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Vulnerability: GHSA-h4m5-qpfp-3mpv
Summary: Directory Traversal in Babel
Aliases: CVE-2021-42771
Severity: HIGH
CWE: CWE-22
Published: 2021-10-21T17:49:59Z

Babel.Locale in Babel before 2.9.1 allows attackers to load arbitrary locale .dat files (containing serialized Python objects) via directory traversal, leading to code execution.
Vulnerability: GHSA-pvhp-v9qp-xf5r
Summary: High severity vulnerability that affects django-piston and django-tastypie
Aliases: CVE-2011-4103
Severity: HIGH
CWE: CWE-20
Published: 2018-07-23T19:50:48Z

emitters.py in Django Piston before 0.2.3 and 0.2.x before 0.2.2.1 does not properly deserialize YAML data, which allows remote attackers to execute arbitrary Python code via vectors related to the yaml.load method.

Django Tastypie has a very similar vulnerability.
Vulnerability: PYSEC-2020-275
Aliases: GHSA-63xm-rx5p-xvqr, CVE-2020-15195
Published: 2020-09-25T19:15:00Z

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Vulnerability: GHSA-r8wq-qrxc-hmcm
Summary: ReDoS in LDAP schema parser
Severity: MODERATE
CWE: CWE-1333
Published: 2021-11-29T17:58:59Z

https://github.com/python-ldap/python-ldap/issues/424

### Impact
The LDAP schema parser of python-ldap 3.3.1 and earlier are vulnerable to a regular expression denial-of-service attack. The issue affects clients that use ``ldap.schema`` package to parse LDAP schema definitions from an untrusted source.

### Patches
The upcoming release of python-ldap 3.4.0 will contain a workaround to prevent ReDoS attacks. The schema parser refuses schema definitions with an excessive amount of backslashes.

### Workarounds
As a workaround, users can check input for excessive amount of backslashes in schemas. More than a dozen backslashes per line are atypical.

### References
[CWE-1333](https://cwe.mitre.org/data/definitions/1333.html)

### For more information
If you have any questions or comments about this advisory:
* Open an issue in [python-ldap](https://github.com/python-ldap/python-ldap) tracker
Vulnerability: GHSA-939m-4xpw-v34v
Summary: Arbitrary Code Execution in blazar-dashboard
Aliases: CVE-2020-26943
Severity: MODERATE
CWE: CWE-94
Published: 2020-10-27T17:55:04Z

An issue was discovered in OpenStack blazar-dashboard before 1.3.1, 2.0.0, and 3.0.0. A user allowed to access the Blazar dashboard in Horizon may trigger code execution on the Horizon host as the user the Horizon service runs under (because the Python eval function is used). This may result in Horizon host unauthorized access and further compromise of the Horizon service. All setups using the Horizon dashboard with the blazar-dashboard plugin are affected.
Vulnerability: PYSEC-2019-233
Aliases: CVE-2018-8825
Published: 2019-04-23T21:29:00Z

Google TensorFlow 1.7 and below is affected by: Buffer Overflow. The impact is: execute arbitrary code (local).
Vulnerability: PYSEC-2015-20
Aliases: GHSA-h582-2pch-3xv3, CVE-2015-5143
Published: 2015-07-14T17:59:00Z

The session backends in Django before 1.4.21, 1.5.x through 1.6.x, 1.7.x before 1.7.9, and 1.8.x before 1.8.3 allows remote attackers to cause a denial of service (session store consumption) via multiple requests with unique session keys.
Vulnerability: PYSEC-2020-330
Aliases: GHSA-rrfp-j2mp-hq9c, CVE-2020-15265
Published: 2020-10-21T21:15:00Z

In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Vulnerability: PYSEC-2021-85
Aliases: CVE-2021-33513, GHSA-fj67-w3m4-rfmp
Published: 2021-05-21T22:15:00Z

Plone through 5.2.4 allows XSS via the inline_diff methods in Products.CMFDiffTool.
Vulnerability: PYSEC-2021-330
Aliases: GHSA-m87f-9fvv-2mgg, CVE-2021-24040, GHSA-mwgj-7x7j-6966
Published: 2021-09-10T22:15:00Z

Due to use of unsafe YAML deserialization logic, an attacker with the ability to modify local YAML configuration files could provide malicious input, resulting in remote code execution or similar risks. This issue affects ParlAI prior to v1.1.0.