CVE’s

Relative Path Traversal in GitHub repository dnnsoftware/dnn.platform prior to 9.11.0.

Lodestar is a TypeScript implementation of the Ethereum Consensus specification. Prior to version 0.36.0, there is a possible consensus split given maliciously-crafted `AttesterSlashing` or `ProposerSlashing` being included on-chain. Because the developers represent `uint64` values as native javascript `number`s, there is an issue when those variables with large (greater than 2^53) `uint64` values are included on chain. In those cases, Lodestar may view valid_`AttesterSlashing` or `ProposerSlashing` as invalid, due to rounding errors in large `number` values. This causes a consensus split, where Lodestar nodes are forked away from the main network. Similarly, Lodestar may consider invalid `ProposerSlashing` as valid, thus including in proposed blocks that will be considered invalid by the network. Version 0.36.0 contains a fix for this issue. As a workaround, use `BigInt` to represent `Slot` and `Epoch` values in `AttesterSlashing` and `ProposerSlashing` objects. `BigInt` is too slow to be used in all `Slot` and `Epoch` cases, so one may carefully use `BigInt` just where necessary for consensus.

RubyGems is a package registry used to supply software for the Ruby language ecosystem. An ordering mistake in the code that accepts gem uploads allowed some gems (with platforms ending in numbers, like `arm64-darwin-21`) to be temporarily replaced in the CDN cache by a malicious package. The bug has been patched, and is believed to have never been exploited, based on an extensive review of logs and existing gems by rubygems. The easiest way to ensure that an application has not been exploited by this vulnerability is to verify all downloaded .gems checksums match the checksum recorded in the RubyGems.org database. RubyGems.org has been patched and is no longer vulnerable to this issue.

PyJWT is a Python implementation of RFC 7519. PyJWT supports multiple different JWT signing algorithms. With JWT, an attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify `jwt.algorithms.get_default_algorithms()` to get support for all algorithms, or specify a single algorithm. The issue is not that big as `algorithms=jwt.algorithms.get_default_algorithms()` has to be used. Users should upgrade to v2.4.0 to receive a patch for this issue. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

RegionProtect is a plugin that allows users to manage certain events in certain regions of the world. Versions prior to 1.1.0 contain a YAML injection vulnerability that can cause an instant server crash if the passed arguments are not matched. Version 1.1.0 contains a patch for this issue. As a workaround, restrict operator permissions to untrusted people and avoid entering arguments likely to cause a crash.

NextAuth.js (next-auth) is am open source authentication solution for Next.js applications. Prior to versions 3.29.3 and 4.3.3, an open redirect vulnerability is present when the developer is implementing an OAuth 1 provider. Versions 3.29.3 and 4.3.3 contain a patch for this issue. The maintainers recommend adding a certain configuration to one's `callbacks` option as a workaround for those unable to upgrade.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.