osint-pattern-analyzer

Analizador de Patrones OSINT Herramienta para automatizar investigaciones OSINT a través de múltiples vectores de identidad números de teléfono, nombres de usuario y soporte futuro para correo electrónico, diseñada para extraer datos estructurados y permitir la detección de patrones y el análisis...

CVE-2026-105757

A flaw was found in vLLM. A remote authenticated attacker can cause a Denial of Service DoS by submitting specially crafted structured-output requests. Due to improper exception handling around structured-output processing, certain request-level errors fail to be contained and propagate directly...

vLLM: Structured-output request errors escape the request boundary and terminate the shared EngineCore — engine-fatal denial of service (3 sites)

Affected - Ecosystem / package: pip / vllm - Affected versions: vLLM ≤ 0.25.1 confirmed on 0.25.1, commit 752a3a504485. The lower bound predates 0.25.1; maintainers can confirm how far back each path reaches. Summary Three structured-output request paths let an ordinary request reach a condition...

EUVD-2026-92847

vLLM: Structured-output request errors escape the request boundary and terminate the shared EngineCore — engine-fatal denial of service 3 sites...

CVE-2026-105757

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by t...

CVE-2026-105757

The vLLM inference and serving engine for large language models is vulnerable to a denial of service (DoS) condition in versions prior to 0.30.0 . The root cause is that structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. Specific tri...

CVE-2026-105757 vLLM: Structured-output request errors escape the request boundary and terminate the shared EngineCore — engine-fatal denial of service (3 sites)

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by t...

OST-C2-Spec

Draft: Request for Discussion Abstract This document provides an overview of Version 1 of the OST C&C Specification. It is intended to provide a detailed description of messages and the fields within those messages. Introduction The motivation behind this specification is to provide a C&C messagi...

standalone_tdo

TDO Standalone Extractor A powerful, standalone command-line tool for extracting Cyber Threat Intelligence CTI from documents using Large Language Models with advanced structured output capabilities. 🚀 Features Multi-format Document Support : PDF, DOCX, TXT, and Markdown files Advanced LLM...

EUVD-2026-58063

vLLM: ReDoS via structuredoutputs.regex in the lm-format-enforcer backend no compile timeout — missed sibling of GHSA-rwxx-mrjm-wc2m...

Allocation of Resources Without Limits or Throttling

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling via the structuredoutputs.regex parameter in the lm-format-enforcer backend. An attacker can...

CVE-2026-73556

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structuredoutputs.regex parameter in vllm/v1/structuredoutput/backendlmformatenforcer.py is passed to lmformatenforcer.RegexParser without compileregexwithtimeout or validation in...

CVE-2026-73556

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structuredoutputs.regex parameter in vllm/v1/structuredoutput/backendlmformatenforcer.py is passed to lmformatenforcer.RegexParser without compileregexwithtimeout or validation in...

CVE-2026-73556 vLLM: ReDoS via structured_outputs.regex in the lm-format-enforcer backend (no compile timeout) — missed sibling of CVE-2026-55574

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structuredoutputs.regex parameter in vllm/v1/structuredoutput/backendlmformatenforcer.py is passed to lmformatenforcer.RegexParser without compileregexwithtimeout or validation in...

Self-Correcting Structured Output in Spring AI 2.0

Large language models are text-in, text-out systems — their interface is natural language. Natural language is a great interface for humans and a poor one for software. The moment downstream code needs to route on a field, persist a value, or branch on a result, the conversation has to become a...

Exploit for Improper Handling of Length Parameter Inconsistency in Mongodb

MongoBleed CVE-2025-14847 – Vulnerability Checker Systemhaus Sc...

VScanX

VScanX - Ethical Vulnerability Scanner !Versionhttps://img...

Exploit for Deserialization of Untrusted Data in Facebook React

React2Shell Scanner – with PoC CVE-2025-55182 – React Ser...

PYSEC-2025-55

vLLM is an inference and serving engine for large language models LLMs. Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service ReDoS that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to...

vLLM 安全漏洞

vLLM is a high throughput and memory efficient inference and service engine for LLM from the vLLM open source. A security vulnerability exists in vLLM versions prior to 0.8.0 through 0.9.0, which stems from the fact that supplying an invalid regular expression when using structured output may...