27 matches found
PT-2026-42830
Name of the Vulnerable Software and Affected Versions Docker Model Runner on macOS affected versions not specified Description The vllm-metal inference backend unconditionally sets trust remote code=True when loading model tokenizers and operates without sandboxing. This allows the...
NuGet Package 'Microsoft.ML.Tokenizers' Detection
The remote host has a 'Microsoft.ML.Tokenizers' with a Verified NuGet package status and is installed on the remote host. Nessus has not tested for this issue but has instead relied only on the application's self-reported version number. %NASLMINLEVEL 80900 C Tenable, Inc. include'compat.inc'; if...
CVE-2024-34359
CVE-2024-34359 affects llama-cpp-python (Python bindings for llama.cpp). The vulnerability arises when init loads a model’s chat template from the gguf metadata and constructs self.chat_handler via llama_chat_format.Jinja2ChatFormatter.to_chat_handler(), using a sandbox-less Jinja2 Environment. R...
SUSE CVE-2021-43854
NLTK Natural Language Toolkit is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Versions prior to 3.6.5 are vulnerable to regular expression denial of service ReDoS attacks. The vulnerability is present in...
PYSEC-2021-859
NLTK Natural Language Toolkit is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Versions prior to 3.6.5 are vulnerable to regular expression denial of service ReDoS attacks. The vulnerability is present in...
python-pygments: ReDoS in multiple lexers
A denial of service attack was discovered against pygments. Some of the regular expressions used to tokenise source code for highlighting have exponential complexity. A specially crafted input file could cause pygments to take effectively infinite time to parse, consuming CPU resources and denyin...
From Regular Expressions to AI
Three generations of attack detection methodology The oldest and well-studied approach is based on signatures and heuristics. From before the internet times, this approach was implemented in most kinds of detection systems from firewalls to anti-viruses. The second genera- tion represents an...