In CKAN, versions 2.9.0 to 2.9.3 are affected by a stored XSS vulnerability via SVG file upload of users’ profile picture. This allows low privileged application users to store malicious scripts in their profile picture. These scripts are executed in a victim’s browser when they open the malicious profile picture

TensorFlow is an open source platform for machine learning. In affected versions during TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. In affected versions if `tf.image.resize` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. 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.

Incorrect Access Control in Lin-CMS-Flask v0.1.1 allows remote attackers to obtain sensitive information and/or gain privileges due to the application not invalidating a user's authentication token upon logout, which allows for replaying packets.

The rich text editor does not escape attribute data when previewing custom tags. This means XSS is possible if custom tags are used, for users who have access to editing rich text content. Frontend content view is not affected, but the vulnerability could be used by editors to attack other editors. The fix ensures custom tag attribute data is escaped in the editor.

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.

The Apigee Edge module allows connecting a Drupal site to Apigee Edge in order to build a developer portal.

The module did not properly validate user access for data creation in certain circumstances.

### Impact

It's easy to create a malign transaction which uses the dead cell as the DepGroup in the DepCells. The transaction can crash all the receiving nodes.

Please use the `aes` crate going forward. The new repository location is at:

<https://github.com/RustCrypto/block-ciphers/tree/master/aes>

The `aes` crate now has an optional `ctr` feature which autodetects SIMD
features on `i686`/`x86-64` targets and uses them if available, or otherwise
falls back to the implementation in the `ctr` crate.

If you would prefer not to have this autodetection performed, use the `aes`
crate directly with the `ctr` crate.

TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

The Social User Export module enables users within Open Social to create an export of users and download this to a CSV file.

The module doesn't sufficiently check access when building the CSV file, allowing logged-in users without the `manage members` permission to be able to export all data from a selected user in certain scenarios.

This vulnerability is mitigated by the fact that an attacker must have the authenticated user role and the site must have the configuration set in such a way a logged in user is able to export users.

### Impact
Contrary to the [OCI runtime specification](https://github.com/opencontainers/runtime-spec/blob/v1.0.2/config-linux.md#device-whitelist), `runc`'s implementation of the `linux.resources.devices` list was a black-list by default. This means that users who created their own `config.json` objects and didn't prefix a deny-all rule (`{"allow": false, "permissions": "rwm"}` or equivalent) were not provided protection by the `devices` cgroup. This would allow malicious containers (with sufficient privileges) to create arbitrary device inodes (assuming they have `CAP_MKNOD`) and operate on any device inodes they may have access to (assuming they have regular Unix DAC permissions).

However, most (if not all) programs that make use of `runc` include this deny-all rule. This was most likely added before the specification mandated a white-list of devices, and the fact that all programs wrote their own deny-all rule obscured the existence of this bug for several years. In fact, even the specification's examples include a default deny-all rule! We therefore believe that while this is a security bug (and has been fixed as such), it was almost certainly not exploitable in the wild due to the inclusion of default deny-all rules by all known users of `runc` -- hence why this advisory has low severity.

### Patches
This issue has been fixed in [a patch that was part of a larger rework of the devices cgroup code in runc](https://github.com/opencontainers/runc/pull/2391) -- which lead to the discovery of this security bug. Users should upgrade to 1.0.0-rc91 as soon as it is released, or wait for your distribution to backport the relevant fixes.

### Workarounds
If you are using `runc` directly, ensure that there is a deny-all entry at the beginning of `linux.resources.devices` -- such an entry would look like `{"allow": false, "permissions": "rwm"}` (all other fields are ignored, though `type` must be set to `"a"` or `null` if it is present).

Users which consume `runc` through another program should check whether their containers are operating under a white-list -- this can be done by reading `/sys/fs/cgroup/devices/devices.list` inside the container. If the file contains only the entry `a *:* rwm` (meaning the cgroup is in black-list mode, which likely means "allow all device access") then your containers are vulnerable to this issue.

As always, we recommend **in the strongest possible terms** that all of our users enable user namespaces on all of their workloads (or pressure their vendors to do so). User namespaces are one of the most significant defense-in-depth protections you can enable for containers, and have prevented many container-related vulnerabilities (both kernel 0days as well as bugs in container runtimes, such as this one).

### References
* https://www.kernel.org/doc/html/latest/admin-guide/cgroup-v1/devices.html
* [opencontainers/runtime-spec/config-linux.md#device-whitelist](https://github.com/opencontainers/runtime-spec/blob/v1.0.2/config-linux.md#device-whitelist)
* https://github.com/opencontainers/runc/pull/2391

### For more information
If you have any questions or comments about this advisory:
* [Open an issue in this repo](https://github.com/opencontainers/runc/issues/new).
* Email us at <security@opencontainers.org>.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `DeserializeSparse` can trigger a null pointer dereference. This is because the shape inference function assumes that the `serialize_sparse` tensor is a tensor with positive rank (and having `3` as the last dimension). 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.

dotenv by description is meant to be used in development or testing only.

Using this in production may or may not be advisable.

## Alternatives

The below may or may not be feasible alternative(s):
- [dotenvy_codegen_impl](https://crates.io/crates/dotenvy_codegen_impl)

`TlsWyRand`'s implementation of `Deref` unconditionally dereferences a raw pointer, and returns 
multiple mutable references to the same object, which is undefined behavior.

Affected versions of this crate unconditionally implement Send/Sync for `RcuCell<T>`.
This allows users to send `T: !Send` to other threads (while `T` enclosed within `RcuCell<T>`), and allows users to concurrently access `T: !Sync` by using the APIs of `RcuCell<T>` that provide access to `&T`.

This can result in memory corruption caused by data races.


Affected versions of list-n-stream package (0.0.10 and before), are vulnerable to a directory traversal issue.

Due to improper HTTP header santization, a malicious user can spoof their
source IP address by setting the X-Forwarded-For header. This may allow
a user to bypass IP based restrictions, or obfuscate their true source.


The npm `an0n-chat-lib` package has been identified as malicious and removed from the npm package registry.

## Remediation

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outside entity, there is no guarantee that removing the package will remove all malicious software resulting from installing it.

Affected versions of this crate passes an uninitialized buffer to a user-provided `Read` implementation (`ColumnarReadExt::read_typed_vec()`).

Arbitrary `Read` implementations can read from the uninitialized buffer (memory exposure) and also can return incorrect number of bytes written to the buffer.
Reading from uninitialized memory produces undefined values that can quickly invoke undefined behavior.

During creation of new libfuse session with `fuse_session_new` operation list was passed as NULL incorrectly. libfuse expects this argument to always point to list of operations. This caused uninitialized memory read and leaks in libfuse.so

Rejected reason: Non Security Issue. See the binutils security policy for more details, https://sourceware.org/cgit/binutils-gdb/tree/binutils/SECURITY.txt

An attacker can forge signatures on arbitrary messages that will verify for any public key. This may allow attackers to authenticate as any user within the Stark Bank platform, and bypass signature verification needed to perform operations on the platform, such as send payments and transfer funds. Additionally, the ability for attackers to forge signatures may impact other users and projects using these libraries in different and unforeseen ways.

Due to unchecked type assertions, maliciously crafted messages can cause panics, which may be used as a denial of service vector.

Affected versions of this crate passes an uninitialized buffer to a user-provided `Read` implementation.
There are two of such cases (`go_offset_log::read_entry()` & `offset_log::read_entry()`).

Arbitrary `Read` implementations can read from the uninitialized buffer (memory exposure) and also can return incorrect number of bytes written to the buffer.
Reading from uninitialized memory produces undefined values that can quickly invoke undefined behavior.

Versions of `millisecond` prior to 0.1.2 are affected by a regular expression denial of service vulnerability when extremely long version strings are parsed.


## Proof of concept
```
var ms = require('millisecond');
var genstr = function (len, chr) {
   var result = "";
   for (i=0; i<=len; i++) {
       result = result + chr;
   }

   return result;
}

ms(genstr(process.argv[2], "5") + " minutea");
```


## Recommendation

Update to version 0.1.2 or later.

`rdiff` performs a diff of two provided strings or files. As part of its reading
code it uses the return value of a `Read` instance to set the length of
its internal character vector.

If the `Read` implementation claims that it has read more bytes than the length
of the provided buffer, the length of the vector will be set to longer than its
capacity. This causes `rdiff` APIs to return uninitialized memory in its API
methods.

Users can authenticate this way even if their user account is disabled. This is a high risk vulnerability when account disabling is used to block users' access to the system. (Someone who never had an account cannot exploit this vulnerability.) The fix ensures tokens are generated only for enabled user accounts, and is distributed via Composer as ezsystems/ezplatform-rest v1.3.8

SwaggerUI supports displaying remote OpenAPI definitions through the `?url` parameter. This enables robust demonstration capabilities on sites like `petstore.swagger.io`, `editor.swagger.io`, and similar sites, where users often want to see what their OpenAPI definitions would look like rendered.

However, this functionality may pose a risk for users who host their own SwaggerUI instances. In particular, including remote OpenAPI definitions opens a vector for phishing attacks by abusing the trusted names/domains of self-hosted instances.

An example scenario abusing this functionality could take the following form:
- `https://example.com/api-docs` hosts a version of SwaggerUI with `?url=` query parameter enabled.
- Users will trust the domain `https://example.com` and the contents of the OpenAPI definition.
- A malicious actor may craft a similar OpenAPI definition and service that responds to the defined APIs at `https://evildomain`.
- Users mistakenly click a phishing URL like `https://example.com/api-docs?url=https://evildomain/fakeapi.yaml` and enters sensitive data via the "Try-it-out" feature.

We do want to stress that this attack vector is limited to scenarios that actively trick users into divulging sensitive information. The ease of this is highly contextual and, therefore, the threat model may be different for individual users and organizations. It is *not* possible to perform non-interactive attacks (e.g., cross-site scripting or code injection) through this mechanism.

### Resolution 
We've made the decision to [disable query parameters (#4872)](https://github.com/swagger-api/swagger-ui/issues/4872) by default starting with SwaggerUI version `4.1.3`. Please update to this version when it becomes available (**ETA: 2021 December**). Users will still be able to be re-enable the options at their discretion. We'll continue to enable query parameters on the Swagger demo sites.

### Workaround
If you host a version of SwaggerUI and wish to mitigate this issue immediately, you are encouraged to add the following custom plugin code:

```js
SwaggerUI({
  //  ...other configuration options,
  plugins: [function UrlParamDisablePlugin() {
    return {
      statePlugins: {
        spec: {
          wrapActions: {
            // Remove the ?url parameter from loading an external OpenAPI definition.
            updateUrl: (oriAction) => (payload) => {
              const url = new URL(window.location.href)
              if (url.searchParams.has('url')) {
                url.searchParams.delete('url')
                window.location.replace(url.toString())
              }
              return oriAction(payload)
            }
          }
        }
      }
    }
  }],
})
```

### Future UX work

Through the exploration of this issue, it became apparent that users may not be aware to which web server the Try-it-out function will send requests. While this information is currently presented at the top of the page, understanding may improve by displaying it closer to the "Execute" button where requests are actually made. We'll be exploring these UX improvements over the coming months and welcome community input. Please create a Feature Request under the GitHub Issue tab to start a conversation with us and the community.

## Reflected XSS attack

**Warning** in versions < 3.38.0, it is possible to combine the URL options (as mentioned above) with a vulnerability in DOMPurify (https://www.cvedetails.com/cve/CVE-2020-26870/) to create a reflected XSS vector. If your version of Swagger UI is older than 3.38.0, we suggest you upgrade or implement the workaround as mentioned above.


TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. 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.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.

The package jointjs before 3.3.0 are vulnerable to Prototype Pollution via util.setByPath (https://resources.jointjs.com/docs/jointjs/v3.2/joint.htmlutil.setByPath). The path used the access the object's key and set the value is not properly sanitized, leading to a Prototype Pollution.

TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseBinCount` is vulnerable to a heap OOB access. This is because of missing validation between the elements of the `values` argument and the shape of the sparse output. 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.

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's Grappler optimizer has a use of unitialized variable. If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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.

libsecp256k1 accepts signatures whose R or S parameter is larger than the
secp256k1 curve order, which differs from other implementations. This could
lead to invalid signatures being verified.

The error is resolved in 0.5.0 by adding a `check_overflow` flag.

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

CVE ID↕	Published↕	CVSS↓
DLA-2515-1	Jan 4, 2021	N/A
DLA-2785-1	Oct 12, 2021	N/A
DLA-2748-1	Aug 23, 2021	N/A
PYSEC-2021-841	Dec 1, 2021	N/A
PYSEC-2021-397	Nov 5, 2021	N/A
DLA-2707-1	Jul 12, 2021	N/A
DLA-2665-1	May 23, 2021	N/A
DLA-2591-1	Mar 13, 2021	N/A
DSA-4975-1	Sep 20, 2021	N/A
DSA-4984-1	Oct 12, 2021	N/A
PYSEC-2021-392	Nov 5, 2021	N/A
PYSEC-2021-341	Aug 16, 2021	N/A
DSA-4915-1	May 13, 2021	N/A
DSA-4884-1	Apr 2, 2021	N/A
DLA-2594-1	Mar 15, 2021	N/A
DSA-4876-1	Mar 25, 2021	N/A
DSA-4877-1	Mar 27, 2021	N/A
DLA-2595-1	Mar 17, 2021	N/A
DLA-2560-1	Feb 16, 2021	N/A
DSA-4849-1	Feb 9, 2021	N/A
DLA-2605-1	Mar 22, 2021	N/A
DSA-4867-1	Mar 2, 2021	N/A
DLA-2683-1	Jun 9, 2021	N/A
GHSA-fxwm-rx68-p5vx	Dec 1, 2021	N/A
PYSEC-2021-217	May 14, 2021	N/A
DLA-2664-1	May 17, 2021	N/A
DRUPAL-CONTRIB-2021-020	Jun 30, 2021	N/A
GHSA-45p7-c959-rgcm	Aug 25, 2021	N/A
DLA-2547-1	Feb 6, 2021	N/A
RUSTSEC-2021-0061	Apr 29, 2021	N/A
DLA-2549-1	Feb 8, 2021	N/A
DLA-2794-1	Oct 27, 2021	N/A
DLA-2545-1	Feb 3, 2021	N/A
DSA-4898-1	Apr 22, 2021	N/A
PYSEC-2021-811	Nov 5, 2021	N/A
DLA-2859-1	Dec 28, 2021	N/A
DLA-2718-1	Jul 23, 2021	N/A
DSA-4836-1	Jan 22, 2021	N/A
DLA-2535-1	Jan 27, 2021	N/A
DSA-4870-1	Mar 12, 2021	N/A
DRUPAL-CONTRIB-2021-002	Jan 27, 2021	N/A
GHSA-g54h-m393-cpwq	Dec 20, 2021	N/A
PYSEC-2021-822	Nov 5, 2021	N/A
DLA-2680-1	Jun 7, 2021	N/A
DLA-2691-1	Jun 25, 2021	N/A
DLA-2810-1	Nov 5, 2021	N/A
DSA-4994-1	Oct 28, 2021	N/A
DLA-2839-1	Dec 3, 2021	N/A
RUSTSEC-2021-0142	Dec 24, 2021	N/A
DLA-2732-1	Aug 4, 2021	N/A
RUSTSEC-2021-0114	Sep 23, 2021	N/A
DSA-4951-1	Aug 7, 2021	N/A
DLA-2775-1	Oct 2, 2021	N/A
DSA-5006-1	Nov 11, 2021	N/A
GHSA-jh2g-xhqq-x4w9	Aug 25, 2021	N/A
DSA-4864-1	Feb 27, 2021	N/A
DSA-4993-1	Oct 25, 2021	N/A
DLA-2597-1	Mar 17, 2021	N/A
DLA-2618-3	Oct 20, 2021	N/A
DSA-4902-1	Apr 24, 2021	N/A
DLA-2761-1	Sep 18, 2021	N/A
GHSA-26hg-crh6-mjrw	Feb 23, 2021	N/A
GO-2020-0029	Apr 14, 2021	N/A
GHSA-7xcv-wvr7-4h6p	Jan 29, 2021	N/A
RUSTSEC-2021-0087	Jan 7, 2021	N/A
RUSTSEC-2021-0154	Sep 10, 2021	N/A
ALPINE-CVE-2021-3487	Apr 15, 2021	N/A
DLA-2660-1	May 13, 2021	N/A
DLA-2743-1	Aug 16, 2021	N/A
DLA-2742-2	Aug 22, 2021	N/A
DLA-2869-1	Dec 29, 2021	N/A
GHSA-9wx7-jrvc-28mm	Nov 8, 2021	N/A
DLA-2781-1	Oct 11, 2021	N/A
DLA-2581-1	Mar 3, 2021	N/A
GO-2020-0040	Apr 14, 2021	N/A
DLA-2787-1	Oct 18, 2021	N/A
DLA-2705-1	Jul 7, 2021	N/A
DLA-2740-1	Aug 12, 2021	N/A
DLA-2587-1	Mar 9, 2021	N/A
DSA-4979-1	Oct 1, 2021	N/A
RUSTSEC-2021-0086	Jan 7, 2021	N/A
GHSA-m489-xr35-fjxr	Sep 22, 2021	N/A
RUSTSEC-2021-0094	Feb 3, 2021	N/A
GHSA-36mj-6r7r-mqhf	Sep 29, 2021	N/A
DLA-2703-1	Jul 5, 2021	N/A
DLA-2863-1	Dec 29, 2021	N/A
DLA-2627-1	Apr 15, 2021	N/A
DLA-2809-1	Nov 5, 2021	N/A
GHSA-qrmm-w75w-3wpx	Dec 9, 2021	N/A
DLA-2800-1	Oct 30, 2021	N/A
PYSEC-2021-460	May 14, 2021	N/A
PYSEC-2021-482	May 14, 2021	N/A
GHSA-qwp9-52h8-xgg8	Jan 20, 2021	N/A
PYSEC-2021-833	Nov 5, 2021	N/A
DSA-5011-1	Nov 19, 2021	N/A
PYSEC-2021-832	Nov 5, 2021	N/A
PYSEC-2021-789	Aug 12, 2021	N/A
DLA-2766-1	Sep 27, 2021	N/A
RUSTSEC-2021-0076	Jul 13, 2021	N/A
PYSEC-2021-183	May 14, 2021	N/A

Know every vulnerability
before it knows you.

2021 CVE Vulnerabilities — DevGuard Vulnerability Database

Know every vulnerabilitybefore it knows you.

2021 CVE Vulnerabilities — DevGuard Vulnerability Database

Know every vulnerability
before it knows you.