| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Singularity (an open source container platform) from version 3.1.1 through 3.6.3 has a vulnerability. Due to insecure handling of path traversal and the lack of path sanitization within `unsquashfs`, it is possible to overwrite/create any files on the host filesystem during the extraction with a crafted squashfs filesystem. The extraction occurs automatically for unprivileged (either installation or with `allow setuid = no`) run of Singularity when a user attempt to run an image which is a local SIF image or a single file containing a squashfs filesystem and is coming from remote sources `library://` or `shub://`. Image build is also impacted in a more serious way as it can be used by a root user, allowing an attacker to overwrite/create files leading to a system compromise, so far bootstrap methods `library`, `shub` and `localimage` are triggering the squashfs extraction. This issue is addressed in Singularity 3.6.4. All users are advised to upgrade to 3.6.4 especially if they use Singularity mainly for building image as root user. There is no solid workaround except to temporary avoid to use unprivileged mode with single file images in favor of sandbox images instead. Regarding image build, temporary avoid to build from `library` and `shub` sources and as much as possible use `--fakeroot` or a VM for that. |
| In the `@actions/core` npm module before version 1.2.6,`addPath` and `exportVariable` functions communicate with the Actions Runner over stdout by generating a string in a specific format. Workflows that log untrusted data to stdout may invoke these commands, resulting in the path or environment variables being modified without the intention of the workflow or action author. The runner will release an update that disables the `set-env` and `add-path` workflow commands in the near future. For now, users should upgrade to `@actions/core v1.2.6` or later, and replace any instance of the `set-env` or `add-path` commands in their workflows with the new Environment File Syntax. Workflows and actions using the old commands or older versions of the toolkit will start to warn, then error out during workflow execution. |
| Nette versions before 2.0.19, 2.1.13, 2.2.10, 2.3.14, 2.4.16, 3.0.6 are vulnerable to an code injection attack by passing specially formed parameters to URL that may possibly leading to RCE. Nette is a PHP/Composer MVC Framework. |
| In GLPI before version 9.5.2, there is a SQL Injection in the API's search function. Not only is it possible to break the SQL syntax, but it is also possible to utilise a UNION SELECT query to reflect sensitive information such as the current database version, or database user. The most likely scenario for this vulnerability is with someone who has an API account to the system. The issue is patched in version 9.5.2. A proof-of-concept with technical details is available in the linked advisory. |
| django-filter is a generic system for filtering Django QuerySets based on user selections. In django-filter before version 2.4.0, automatically generated `NumberFilter` instances, whose value was later converted to an integer, were subject to potential DoS from maliciously input using exponential format with sufficiently large exponents. Version 2.4.0+ applies a `MaxValueValidator` with a a default `limit_value` of 1e50 to the form field used by `NumberFilter` instances. In addition, `NumberFilter` implements the new `get_max_validator()` which should return a configured validator instance to customise the limit, or else `None` to disable the additional validation. Users may manually apply an equivalent validator if they are not able to upgrade. |
| In Open Enclave before version 0.12.0, an information disclosure vulnerability exists when an enclave application using the syscalls provided by the sockets.edl is loaded by a malicious host application. An attacker who successfully exploited the vulnerability could read privileged data from the enclave heap across trust boundaries. To exploit this vulnerability, an attacker would have to log on to an affected system and run a specially crafted application. The vulnerability would not allow an attacker to elevate user rights directly, but it could be used to obtain information otherwise considered confidential in an enclave, which could be used in further compromises. The issue has been addressed in version 0.12.0 and the current master branch. Users will need to to recompile their applications against the patched libraries to be protected from this vulnerability. |
| In ORY Fosite (the security first OAuth2 & OpenID Connect framework for Go) before version 0.34.0, the `TokenRevocationHandler` ignores errors coming from the storage. This can lead to unexpected 200 status codes indicating successful revocation while the token is still valid. Whether an attacker can use this for her advantage depends on the ability to trigger errors in the store. This is fixed in version 0.34.0 |
| In ORY Fosite (the security first OAuth2 & OpenID Connect framework for Go) before version 0.31.0, when using "private_key_jwt" authentication the uniqueness of the `jti` value is not checked. When using client authentication method "private_key_jwt", OpenId specification says the following about assertion `jti`: "A unique identifier for the token, which can be used to prevent reuse of the token. These tokens MUST only be used once, unless conditions for reuse were negotiated between the parties". Hydra does not seem to check the uniqueness of this `jti` value. This problem is fixed in version 0.31.0. |
| Combodo iTop is a web based IT Service Management tool. In iTop before versions 2.7.2 and 3.0.0, by modifying target browser local storage, an XSS can be generated in the iTop console breadcrumb. This is fixed in versions 2.7.2 and 3.0.0. |
| Combodo iTop is a web based IT Service Management tool. In iTop before versions 2.7.2 and 3.0.0, two cookies are created for the same session, which leads to a possibility to steal user session. This is fixed in versions 2.7.2 and 3.0.0. |
| Combodo iTop is a web based IT Service Management tool. In iTop before versions 2.7.2 and 3.0.0, when a download error is triggered in the user portal, an SQL query is displayed to the user. This is fixed in versions 2.7.2 and 3.0.0. |
| Combodo iTop is a web based IT Service Management tool. In iTop before versions 2.7.2 and 3.0.0, admin pages are cached, so that their content is visible after deconnection by using the browser back button. This is fixed in versions 2.7.2 and 3.0.0. |
| In GLPI before version 9.5.2, there is a leakage of user information through the public FAQ. The issue was introduced in version 9.5.0 and patched in 9.5.2. As a workaround, disable public access to the FAQ. |
| In goxmldsig (XML Digital Signatures implemented in pure Go) before version 1.1.0, with a carefully crafted XML file, an attacker can completely bypass signature validation and pass off an altered file as a signed one. A patch is available, all users of goxmldsig should upgrade to at least revision f6188febf0c29d7ffe26a0436212b19cb9615e64 or version 1.1.0 |
| Electron before versions 11.0.0-beta.6, 10.1.2, 9.3.1 or 8.5.2 is vulnerable to a context isolation bypass. Apps using both `contextIsolation` and `sandbox: true` are affected. Apps using both `contextIsolation` and `nodeIntegrationInSubFrames: true` are affected. This is a context isolation bypass, meaning that code running in the main world context in the renderer can reach into the isolated Electron context and perform privileged actions. |
| In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. |
| In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. |
| In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. |
| In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. This results in special casing during validation at model loading time. Unfortunately, this means that the `-1` index is a valid tensor index for any operator, including those that don't expect optional inputs and including for output tensors. Thus, this allows writing and reading from outside the bounds of heap allocated arrays, although only at a specific offset from the start of these arrays. This results in both read and write gadgets, albeit very limited in scope. The issue is patched in several commits (46d5b0852, 00302787b7, e11f5558, cd31fd0ce, 1970c21, and fff2c83), and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that only operators which accept optional inputs use the `-1` special value and only for the tensors that they expect to be optional. Since this allow-list type approach is erro-prone, we advise upgrading to the patched code. |
| In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. |
