| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Zope is an open-source web application server. Zope versions prior to versions 4.6.3 and 5.3 have a remote code execution security issue. In order to be affected, one must use Python 3 for one's Zope deployment, run Zope 4 below version 4.6.3 or Zope 5 below version 5.3, and have the optional `Products.PythonScripts` add-on package installed. By default, one must have the admin-level Zope "Manager" role to add or edit Script (Python) objects through the web. Only sites that allow untrusted users to add/edit these scripts through the web are at risk. Zope releases 4.6.3 and 5.3 are not vulnerable. As a workaround, a site administrator can restrict adding/editing Script (Python) objects through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing these scripts through the web should be restricted to trusted users only. This is the default configuration in Zope. |
| The module `AccessControl` defines security policies for Python code used in restricted code within Zope applications. Restricted code is any code that resides in Zope's object database, such as the contents of `Script (Python)` objects. The policies defined in `AccessControl` severely restrict access to Python modules and only exempt a few that are deemed safe, such as Python's `string` module. However, full access to the `string` module also allows access to the class `Formatter`, which can be overridden and extended within `Script (Python)` in a way that provides access to other unsafe Python libraries. Those unsafe Python libraries can be used for remote code execution. By default, you need to have the admin-level Zope "Manager" role to add or edit `Script (Python)` objects through the web. Only sites that allow untrusted users to add/edit these scripts through the web - which would be a very unusual configuration to begin with - are at risk. The problem has been fixed in AccessControl 4.3 and 5.2. Only AccessControl versions 4 and 5 are vulnerable, and only on Python 3, not Python 2.7. As a workaround, a site administrator can restrict adding/editing `Script (Python)` objects through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing these scripts through the web should be restricted to trusted users only. This is the default configuration in Zope. |
| mod_auth_openidc is an authentication/authorization module for the Apache 2.x HTTP server that functions as an OpenID Connect Relying Party, authenticating users against an OpenID Connect Provider. When mod_auth_openidc versions prior to 2.4.9 are configured to use an unencrypted Redis cache (`OIDCCacheEncrypt off`, `OIDCSessionType server-cache`, `OIDCCacheType redis`), `mod_auth_openidc` wrongly performed argument interpolation before passing Redis requests to `hiredis`, which would perform it again and lead to an uncontrolled format string bug. Initial assessment shows that this bug does not appear to allow gaining arbitrary code execution, but can reliably provoke a denial of service by repeatedly crashing the Apache workers. This bug has been corrected in version 2.4.9 by performing argument interpolation only once, using the `hiredis` API. As a workaround, this vulnerability can be mitigated by setting `OIDCCacheEncrypt` to `on`, as cache keys are cryptographically hashed before use when this option is enabled. |
| think-helper defines a set of helper functions for ThinkJS. In versions of think-helper prior to 1.1.3, the software receives input from an upstream component that specifies attributes that are to be initialized or updated in an object, but it does not properly control modifications of attributes of the object prototype. The vulnerability is patched in version 1.1.3. |
| A format string vulnerability in mpv through 0.33.0 allows user-assisted remote attackers to achieve code execution via a crafted m3u playlist file. |
| IBM Spectrum Scale 5.0.0 through 5.0.5.6 and 5.1.0 through 5.1.0.3 system core component is affected by a format string security vulnerability. An attacker could execute arbitrary code in the context of process memory, potentially escalating their system privileges and taking control over the entire system with root access. IBM X-Force ID: 201474. |
| TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.RaggedTensorToTensor`, an attacker can exploit an undefined behavior if input arguments are empty. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L356-L360) only checks that one of the tensors is not empty, but does not check for the other ones. There are multiple `DCHECK` validations to prevent heap OOB, but these are no-op in release builds, hence they don't prevent anything. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits 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 trigger a denial of service via a `CHECK`-fail in converting sparse tensors to CSR Sparse matrices. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/800346f2c03a27e182dd4fba48295f65e7790739/tensorflow/core/kernels/sparse/kernels.cc#L66) does a double redirection to access an element of an array allocated on the heap. If the value at `indices(i, 0)` is such that `indices(i, 0) + 1` is outside the bounds of `csr_row_ptr`, this results in writing outside of bounds of heap allocated data. 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 heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements. If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`. 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 heap buffer overflow in `QuantizedResizeBilinear` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/50711818d2e61ccce012591eeb4fdf93a8496726/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L705-L706) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. 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 heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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 heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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 trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. 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. 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. |
| In Node.js mixme, prior to v0.5.1, an attacker can add or alter properties of an object via '__proto__' through the mutate() and merge() functions. The polluted attribute will be directly assigned to every object in the program. This will put the availability of the program at risk causing a potential denial of service (DoS). |
| A Format String vulnerablity exists in TRENDnet TEW-755AP 1.11B03, TEW-755AP2KAC 1.11B03, TEW-821DAP2KAC 1.11B03, and TEW-825DAP 1.11B03, which could let a remote malicious user cause a denial of service due to a logic bug at address 0x40dcd0 when calling fprintf with "%s: key len = %d, too long\n" format. The two variables seem to be put in the wrong order. The vulnerability could be triggered by sending the POST request to apply_cgi with a long and unknown key in the request body. |
| The is-svg package 2.1.0 through 4.2.1 for Node.js uses a regular expression that is vulnerable to Regular Expression Denial of Service (ReDoS). If an attacker provides a malicious string, is-svg will get stuck processing the input for a very long time. |
| An issue was discovered in the Linux kernel 5.9.x through 5.11.3, as used with Xen. In some less-common configurations, an x86 PV guest OS user can crash a Dom0 or driver domain via a large amount of I/O activity. The issue relates to misuse of guest physical addresses when a configuration has CONFIG_XEN_UNPOPULATED_ALLOC but not CONFIG_XEN_BALLOON_MEMORY_HOTPLUG. |
| org/mitre/oauth2/web/OAuthConfirmationController.java in the OpenID Connect server implementation for MITREid Connect through 1.3.3 contains a Mass Assignment (aka Autobinding) vulnerability. This arises due to unsafe usage of the @ModelAttribute annotation during the OAuth authorization flow, in which HTTP request parameters affect an authorizationRequest. |
| An issue was discovered in the rand_core crate before 0.6.2 for Rust. Because read_u32_into and read_u64_into mishandle certain buffer-length checks, a random number generator may be seeded with too little data. |
