VAITP

picklescan before 0.0.29 fails to detect the built-in Python trace.Trace.runctx function when used in pickle file reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with trace.Trace.runctx payloads that bypass picklescan detection and execute code upon pickle.load() invocation.

Orkes Conductor 3.21.21 before 3.30.2 contains an unauthenticated remote code execution vulnerability that allows remote attackers to execute arbitrary OS commands by submitting inline workflow definitions containing malicious JavaScript or Python expressions to the workflow API endpoint prior to authentication. Attackers can exploit unsandboxed GraalVM evaluators configured with HostAccess.ALL or allowAllAccess(true) through INLINE, LAMBDA, DO_WHILE, and SWITCH task types to invoke arbitrary system commands via Java reflection or direct subprocess calls.

LLaMA-Factory through 0.9.5 contains a remote code execution vulnerability that allows attackers with WebUI access to execute arbitrary Python code by supplying a malicious model path in the Chat or Training interfaces. The application passes user-supplied model path input unvalidated into AutoTokenizer.from_pretrained() and AutoModel.from_pretrained() with a hardcoded trust_remote_code=True parameter, causing the Hugging Face transformers library to fetch and execute arbitrary code from a remote or local model repository with the privileges of the server process.

NLTK version 3.9.4 is vulnerable to a path traversal attack due to an incomplete fix for GitHub Issue #3504. The `_UNSAFE_NO_PROTOCOL_RE` regex in `nltk/data.py` checks for literal `../` sequences but fails to account for percent-encoded traversal sequences such as `..%2f`. The `url2pathname()` function decodes these sequences after the validation step, allowing an attacker to bypass the protection. This vulnerability enables an attacker to read arbitrary files accessible to the Python process by controlling the resource name parameter passed to `nltk.data.load()` or `nltk.data.find()`. The issue affects applications that rely on NLTK for resource loading, including NLP web applications, Jupyter notebooks, and CLI tools. The default `pathsec.ENFORCE=False` setting exacerbates the impact by not blocking the file read at the `open()` stage.

Improper neutralization in the Snowpark annotation processor callback template in Snowflake CLI versions prior to 3.19 allowed arbitrary code execution during application bundling or deployment. An attacker could exploit this by supplying crafted project content that is interpolated into generated Python code, causing Snowflake CLI to execute attacker-controlled code in the local context of the user running the CLI. Successful exploitation requires the victim to run the relevant bundling or deployment workflow against attacker-controlled project content, and any resulting code runs with the privileges of that local execution context. The fix is available in Snowflake CLI version 3.19, and users must manually upgrade.

Patool before 4.0.5 contains a path traversal vulnerability in the safe_extract() function in patoolib/programs/py_tarfile.py when running on Python before 3.12, where the is_within_directory() helper uses os.path.commonprefix() for character-level string comparison instead of path-level comparison, allowing a crafted archive member path to bypass the containment check. Attackers can supply a malicious archive with specially crafted member paths to write arbitrary files.

picklescan through 0.0.26 fails to detect malicious pickle files that invoke idlelib.pyshell.ModifiedInterpreter.runcode in __reduce__ methods. Attackers can embed undetected code in pickle files that executes arbitrary commands when the file is loaded via pickle.load(), enabling supply chain attacks on PyTorch models and saved Python objects. This is fixed in version 0.0.30.

Vim is an open source, command line text editor. Prior to 9.2.0699, Vim's Python omni-completion (runtime/autoload/python3complete.vim and the legacy pythoncomplete.vim) executes reconstructed function and class definitions from the current buffer with exec() as part of populating the completion dictionary. When reconstructing that source, each scope's docstring is inserted verbatim between triple quotes with no escaping, so a hostile buffer can break out of the triple-quoted literal and execute attacker-controlled Python during omni-completion. This vulnerability is fixed in 9.2.0699.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions prior to 0.6.52, the Fill Text Template block is vulnerable to a Denial of Service (DoS) attack. While the backend implements a SandboxedEnvironment to prevent unauthorized attribute access (e.g., blocking __class__), it fails to limit the computational complexity or execution time of the expressions. An attacker can input computationally expensive Python/Jinja2 expressions that consume the server's CPU and memory, leading to a complete system hang or crash. In multi-tenant or self-hosted environments, this results in a complete service outage and "noisy neighbor" effects that require manual administrative intervention to recover. This issue has been fixed in version 0.6.52.

py7zr is a Python-based library and utility to support 7zip archive compression, decompression, encryption and decryption. Versions 1.1.2 and below contain an an arbitrary file write vulnerability, which allows symbolic links to be recreated outside the destination directory via crafted malicious symbolic link chains. When using extractall to extract an archive, the library restores these symbolic links, linking them to arbitrary directories on the host file system. During extraction, the program only checks the link arcname within the destination directory, but ignores the combined symlink path resolution. Attackers can exploit this vulnerability by constructing malicious archives, thereby bypassing the directory boundary restrictions implemented by the extractor. Subsequent extraction of regular files through these symbolic links can result in arbitrary file writes. This vulnerability may lead to remote code execution, privilege escalation, data corruption, or denial of service. This issue has been fixed in version 1.1.3.