Writeup Exploits
63,687 exploits tracked across all sources.
TensorFlow < 2.6.4 - Denial of Service via tf.raw_ops.StagePeek Index Validation
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.raw_ops.StagePeek` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `index` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow < 2.6.4 - Denial of Service via Conv3DBackpropFilterV2 Input Validation
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.raw_ops.Conv3DBackpropFilterV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate that the `filter_sizes` argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow < 2.6.4 - Denial of Service via UnsortedSegmentJoin Input Validation
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.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow < 2.6.4 - Denial of Service via SparseTensorToCSRSparseMatrix Input Validation
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.raw_ops.SparseTensorToCSRSparseMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow < 2.6.4 - Denial of Service via LoadAndRemapMatrix Input Validation
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.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0, 2.8.1, 2.7.2, 2.6.4 - DoS
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.raw_ops.LSTMBlockCell` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in `CHECK`-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Info Disclosure
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.raw_ops.QuantizedConv2D` does not fully validate the input arguments. In this case, references get bound to `nullptr` for each argument that is empty. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow < 2.6.4 - Denial of Service via tf.ragged.constant Input Validation
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.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0, 2.8.1, 2.7.2, 2.6.4 - DoS
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.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Use After Free
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, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Memory Corruption
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.raw_ops.SparseTensorDenseAdd` does not fully validate the input arguments. In this case, a reference gets bound to a `nullptr` during kernel execution. This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Info Disclosure
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, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Info Disclosure
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 macros that TensorFlow uses for writing assertions (e.g., `CHECK_LT`, `CHECK_GT`, etc.) have an incorrect logic when comparing `size_t` and `int` values. Due to type conversion rules, several of the macros would trigger incorrectly. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
TensorFlow 2.8.0 - Heap-based Buffer Overflow in TensorKey Hash Function
TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function used total estimated `AllocatedBytes()`, which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. `int32_t`). It also tried to access individual tensor bytes through `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the `.data()` buffer. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.
CVSS 5.5
TensorFlow <2.9.0, <2.8.1, <2.7.2, <2.6.4 - Memory Corruption
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.
CVSS 5.5
TensorFlow <2.9.0-2.6.4 - Info Disclosure
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.
CVSS 5.5
TensorFlow <2.9.0, 2.8.1, 2.7.2, 2.6.4 - Code Injection
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.
CVSS 7.8
Smarty <3.1.45, <4.1.1 - Code Injection
Smarty is a template engine for PHP, facilitating the separation of presentation (HTML/CSS) from application logic. Prior to versions 3.1.45 and 4.1.1, template authors could inject php code by choosing a malicious {block} name or {include} file name. Sites that cannot fully trust template authors should upgrade to versions 3.1.45 or 4.1.1 to receive a patch for this issue. There are currently no known workarounds.
CVSS 8.8
GOST engine <3.0.1 - Buffer Overflow
GOST engine is a reference implementation of the Russian GOST crypto algorithms for OpenSSL. TLS clients using GOST engine when ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is agreed and the server uses 512 bit GOST secret keys are vulnerable to buffer overflow. GOST engine version 3.0.1 contains a patch for this issue. Disabling ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is a possible workaround.
CVSS 5.9
Deno 1.44.0 - Exposure of Sensitive Information via .npmrc Credential Leak
An issue in `.npmrc` support in Deno 1.44.0 was discovered where Deno would send `.npmrc` credentials for the scope to the tarball URL when the registry provided URLs for a tarball on a different domain. All users relying on .npmrc are potentially affected by this vulnerability if their private registry references tarball URLs at a different domain. This includes usage of deno install subcommand, auto-install for npm: specifiers and LSP usage. It is recommended to upgrade to Deno 1.44.1 and if your private registry ever serves tarballs at a different domain to rotate your registry credentials.
CVSS 7.6
npm <7.9.0-7.13.0 - Info Disclosure
npm pack ignores root-level .gitignore and .npmignore file exclusion directives when run in a workspace or with a workspace flag (ie. `--workspaces`, `--workspace=<name>`). Anyone who has run `npm pack` or `npm publish` inside a workspace, as of v7.9.0 and v7.13.0 respectively, may be affected and have published files into the npm registry they did not intend to include. Users should upgrade to the latest, patched version of npm v8.11.0, run: npm i -g npm@latest . Node.js versions v16.15.1, v17.19.1, and v18.3.0 include the patched v8.11.0 version of npm.
CVSS 7.5
npm <7.9.0-7.13.0 - Info Disclosure
npm pack ignores root-level .gitignore and .npmignore file exclusion directives when run in a workspace or with a workspace flag (ie. `--workspaces`, `--workspace=<name>`). Anyone who has run `npm pack` or `npm publish` inside a workspace, as of v7.9.0 and v7.13.0 respectively, may be affected and have published files into the npm registry they did not intend to include. Users should upgrade to the latest, patched version of npm v8.11.0, run: npm i -g npm@latest . Node.js versions v16.15.1, v17.19.1, and v18.3.0 include the patched v8.11.0 version of npm.
CVSS 7.5
npm <7.9.0-7.13.0 - Info Disclosure
npm pack ignores root-level .gitignore and .npmignore file exclusion directives when run in a workspace or with a workspace flag (ie. `--workspaces`, `--workspace=<name>`). Anyone who has run `npm pack` or `npm publish` inside a workspace, as of v7.9.0 and v7.13.0 respectively, may be affected and have published files into the npm registry they did not intend to include. Users should upgrade to the latest, patched version of npm v8.11.0, run: npm i -g npm@latest . Node.js versions v16.15.1, v17.19.1, and v18.3.0 include the patched v8.11.0 version of npm.
CVSS 7.5
npm <7.9.0-7.13.0 - Info Disclosure
npm pack ignores root-level .gitignore and .npmignore file exclusion directives when run in a workspace or with a workspace flag (ie. `--workspaces`, `--workspace=<name>`). Anyone who has run `npm pack` or `npm publish` inside a workspace, as of v7.9.0 and v7.13.0 respectively, may be affected and have published files into the npm registry they did not intend to include. Users should upgrade to the latest, patched version of npm v8.11.0, run: npm i -g npm@latest . Node.js versions v16.15.1, v17.19.1, and v18.3.0 include the patched v8.11.0 version of npm.
CVSS 7.5
npm 7.0.0-8.1.3 - Insufficient Verification of Data Authenticity in npm ci Command
The npm ci command in npm 7.x and 8.x through 8.1.3 proceeds with an installation even if dependency information in package-lock.json differs from package.json. This behavior is inconsistent with the documentation, and makes it easier for attackers to install malware that was supposed to have been blocked by an exact version match requirement in package-lock.json. NOTE: The npm team believes this is not a vulnerability. It would require someone to socially engineer package.json which has different dependencies than package-lock.json. That user would have to have file system or write access to change dependencies. The npm team states preventing malicious actors from socially engineering or gaining file system access is outside the scope of the npm CLI.
CVSS 9.0
By Source