VAITP

Vyper is a Pythonic Smart Contract Language for the Ethereum Virtual Machine (EVM). Contracts containing large arrays might underallocate the number of slots they need by 1. Prior to v0.3.8, the calculation to determine how many slots a storage variable needed used `math.ceil(type_.size_in_bytes / 32)`. The intermediate floating point step can produce a rounding error if there are enough bits set in the IEEE-754 mantissa. Roughly speaking, if `type_.size_in_bytes` is large (> 2**46), and slightly less than a power of 2, the calculation can overestimate how many slots are needed by 1. If `type_.size_in_bytes` is slightly more than a power of 2, the calculation can underestimate how many slots are needed by 1. This issue is patched in version 0.3.8.

PyCryptodome and pycryptodomex before 3.19.1 allow side-channel leakage for OAEP decryption, exploitable for a Manger attack.

Hyperledger Aries Cloud Agent Python (ACA-Py) is a foundation for building decentralized identity applications and services running in non-mobile environments. When verifying W3C Format Verifiable Credentials using JSON-LD with Linked Data Proofs (LDP-VCs), the result of verifying the presentation `document.proof` was not factored into the final `verified` value (`true`/`false`) on the presentation record. The flaw enables holders of W3C Format Verifiable Credentials using JSON-LD with Linked Data Proofs (LDPs) to present incorrectly constructed proofs, and allows malicious verifiers to save and replay a presentation from such holders as their own. This vulnerability has been present since version 0.7.0 and fixed in version 0.10.5.

Hail is an open-source, general-purpose, Python-based data analysis tool with additional data types and methods for working with genomic data. Hail relies on OpenID Connect (OIDC) email addresses from ID tokens to verify the validity of a user's domain, but because users have the ability to change their email address, they could create accounts and use resources in clusters that they should not have access to. For example, a user could create a Microsoft or Google account and then change their email to `test@example.org`. This account can then be used to create a Hail Batch account in Hail Batch clusters whose organization domain is `example.org`. The attacker is not able to access private data or impersonate another user, but they would have the ability to run jobs if Hail Batch billing projects are enabled and create Azure Tenants if they have Azure Active Directory Administrator access.

cdo-local-uuid project provides a specialized UUID-generating function that can, on user request, cause a program to generate deterministic UUIDs. An information leakage vulnerability is present in `cdo-local-uuid` at version `0.4.0`, and in `case-utils` in unpatched versions (matching the pattern `0.x.0`) at and since `0.5.0`, before `0.15.0`. The vulnerability stems from a Python function, `cdo_local_uuid.local_uuid()`, and its original implementation `case_utils.local_uuid()`.

cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. Calling `load_pem_pkcs7_certificates` or `load_der_pkcs7_certificates` could lead to a NULL-pointer dereference and segfault. Exploitation of this vulnerability poses a serious risk of Denial of Service (DoS) for any application attempting to deserialize a PKCS7 blob/certificate. The consequences extend to potential disruptions in system availability and stability. This vulnerability has been patched in version 41.0.6.

Gradio is an open-source Python package that allows you to quickly build a demo or web application for your machine learning model, API, or any arbitary Python function. Versions of `gradio` prior to 4.11.0 contained a vulnerability in the `/file` route which made them susceptible to file traversal attacks in which an attacker could access arbitrary files on a machine running a Gradio app with a public URL (e.g. if the demo was created with `share=True`, or on Hugging Face Spaces) if they knew the path of files to look for. This issue has been patched in version 4.11.0.

SAP BTP Security Services Integration Library ([Python] sap-xssec) - versions < 4.1.0, allow under certain conditions an escalation of privileges. On successful exploitation, an unauthenticated attacker can obtain arbitrary permissions within the application.

An issue was found in CPython 3.12.0 `subprocess` module on POSIX platforms. The issue was fixed in CPython 3.12.1 and does not affect other stable releases. When using the `extra_groups=` parameter with an empty list as a value (ie `extra_groups=[]`) the logic regressed to not call `setgroups(0, NULL)` before calling `exec()`, thus not dropping the original processes' groups before starting the new process. There is no issue when the parameter isn't used or when any value is used besides an empty list. This issue only impacts CPython processes run with sufficient privilege to make the `setgroups` system call (typically `root`).

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.