Sensitive data leakage in TfidfVectorizer due to improper token storage.
A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up to and including 1.4.1.post1, which was fixed in version 1.5.0. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
Sensitive information exposure via arbitrary system path lookup in h2o-3.
In h2oai/h2o-3 version 3.40.0.4, an exposure of sensitive information vulnerability exists due to an arbitrary system path lookup feature. This vulnerability allows any remote user to view full paths in the entire file system where h2o-3 is hosted. Specifically, the issue resides in the Typeahead API call, which when requested with a typeahead lookup of '/', exposes the root filesystem including directories such as /home, /usr, /bin, among others. This vulnerability could allow attackers to explore the entire filesystem, and when combined with a Local File Inclusion (LFI) vulnerability, could make exploitation of the server trivial.
Path traversal in Mage AI allows file leakage for "Viewer" role users.
Mage AI allows remote users with the "Viewer" role to leak arbitrary files from the Mage server due to a path traversal in the "Git Content" request
RCE vulnerability in pytorch-lightning due to improper deserialization handling.
A remote code execution (RCE) vulnerability exists in the lightning-ai/pytorch-lightning library version 2.2.1 due to improper handling of deserialized user input and mismanagement of dunder attributes by the `deepdiff` library. The library uses `deepdiff.Delta` objects to modify application state based on frontend actions. However, it is possible to bypass the intended restrictions on modifying dunder attributes, allowing an attacker to construct a serialized delta that passes the deserializer whitelist and contains dunder attributes. When processed, this can be exploited to access other modules, classes, and instances, leading to arbitrary attribute write and total RCE on any self-hosted pytorch-lightning application in its default configuration, as the delta endpoint is enabled by default.
Local file inclusion vulnerability in gradio-app due to improper input validation.
A local file inclusion vulnerability exists in the JSON component of gradio-app/gradio version 4.25. The vulnerability arises from improper input validation in the `postprocess()` function within `gradio/components/json_component.py`, where a user-controlled string is parsed as JSON. If the parsed JSON object contains a `path` key, the specified file is moved to a temporary directory, making it possible to retrieve it later via the `/file=..` endpoint. This issue is due to the `processing_utils.move_files_to_cache()` function traversing any object passed to it, looking for a dictionary with a `path` key, and then copying the specified file to a temporary directory. The vulnerability can be exploited by an attacker to read files on the remote system, posing a significant security risk.
SSRF vulnerability in gradio 4.21.0 allows unauthorized network access.
A Server-Side Request Forgery (SSRF) vulnerability exists in the gradio-app/gradio version 4.21.0, specifically within the `/queue/join` endpoint and the `save_url_to_cache` function. The vulnerability arises when the `path` value, obtained from the user and expected to be a URL, is used to make an HTTP request without sufficient validation checks. This flaw allows an attacker to send crafted requests that could lead to unauthorized access to the local network or the AWS metadata endpoint, thereby compromising the security of internal servers.
Remote code execution via crafted prompt function request.
An issue in Gaberiele Venturi pandasai v.0.8.0 and before allows a remote attacker to execute arbitrary code via a crafted request to the prompt function.
Vyper allows signed integers as array indexes, leading to unpredictable behavior.
Vyper is a Pythonic Smart Contract Language for the Ethereum Virtual Machine. Arrays can be keyed by a signed integer, while they are defined for unsigned integers only. The typechecker doesn't throw when spotting the usage of an `int` as an index for an array. The typechecker allows the usage of signed integers to be used as indexes to arrays. The vulnerability is present in different forms in all versions, including `0.3.10`. For ints, the 2's complement representation is used. Because the array was declared very large, the bounds checking will pass Negative values will simply be represented as very large numbers. As of time of publication, a fixed version does not exist. There are three potential vulnerability classes: unpredictable behavior, accessing inaccessible elements and denial of service. Class 1: If it is possible to index an array with a negative integer without reverting, this is most likely not anticipated by the developer and such accesses can cause unpredictable behavior for the contract. Class 2: If a contract has an invariant in the form `assert index < x`, the developer will suppose that no elements on indexes `y | y >= x` are accessible. However, by using negative indexes, this can be bypassed. Class 3: If the index is dependent on the state of the contract, this poses a risk of denial of service. If the state of the contract can be manipulated in such way that the index will be forced to be negative, the array access can always revert (because most likely the array won't be declared extremely large). However, all these the scenarios are highly unlikely. Most likely behavior is a revert on the bounds check.
Remote file inclusion via vulnerable user-supplied JSON in Gradio API.
A local file include could be remotely triggered in Gradio due to a vulnerable user-supplied JSON value in an API request.
Vyper silently ignores value in delegatecall/staticcall, causing confusion.
Vyper is a pythonic Smart Contract Language for the ethereum virtual machine. Vyper compiler allows passing a value in builtin raw_call even if the call is a delegatecall or a staticcall. But in the context of delegatecall and staticcall the handling of value is not possible due to the semantics of the respective opcodes, and vyper will silently ignore the value= argument. If the semantics of the EVM are unknown to the developer, he could suspect that by specifying the `value` kwarg, exactly the given amount will be sent along to the target. This vulnerability affects 0.3.10 and earlier versions.
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.
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Sun Tzu – “The Art of War”
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