www-project-top-10-for-large-language-model-applications

www-project-top-10-for-large-language-model-applications OWASP 基金会网站仓库 OWASP 大型语言模型应用 Top 10 欢迎来到 OWASP 大型语言模型应用 Top 10 的官方仓库！ 关于本仓库...

kong

Kong: 自主逆向工程师 用于逆向工程二进制文件的LLM编排 Kong是什么？ 大多数任务遵循线性关系：任务越难，通常耗时越长。逆向工程（及二进制分析）是一种任务，其实际难度其实并不高，但执行时间却可能长达数小时甚至数天，即使是只有几百个函数的二进制文件也是如此。 Kong 使用NSA级别的逆向工程框架，将机械层自动化。Kong 可以接收一个完全混淆且剥离了符号的二进制文件，运行完整的分析管线：对函数进行分类、构建调用图上下文、通过LLM引导的反编译恢复类型和符号，并将结果写回 Ghidra 的程序数据库。输出的二进制文件中，某个 FUN00401a30 变成了...

oss-fuzz-gen

Un framework para la generación y evaluación de fuzz targets Este framework genera fuzz targets para proyectos reales de C/C++/Java/Python con varios modelos de lenguaje de gran tamaño LLM y los evalúa mediante la plataforma OSS-Fuzz. Más detalles disponibles en Fuzzing impulsado por IA: rompiend...

markdown-exfil-tester

valtik-markdown-exfil-tester Probador de caja negra para inyección indirecta de instrucciones que conduce a la exfiltración de markdown / HTML en chatbots basados en LLM. Esta es la clase de vulnerabilidad que afectó a Microsoft 365 Copilot CVE-2025-32711, también conocido como EchoLeak, ChatGPT...

birdy-edwards

BIRDY-EDWARDS 2.0 Infiltrar y Exponer Herramienta automatizada de inteligencia de Facebook impulsada por IA para perfilado de objetivos, análisis de redes y reporte de amenazas. Se ejecuta completamente en el dispositivo mediante Ollama. Plataforma SOCMINT de Facebook impulsada por IA — 100% loca...

Using LLMs to Elicit Security Requirements for Service-Oriented Cyber Ranges

Cyber ranges are complex environments comprising many interacting components and stakeholders with different security concerns. The Service-Oriented Cyber Range SOR is no exception, particularly when it comes to training scenarios targeting critical infrastructure. Security concerns are translate...

MalTotal: Cost-Effective and Language-Agnostic Malicious Code Poisoning Detection for Millions of Repositories

The widespread adoption of open source software OSS has introduced significant security risks, with malicious code poisoning attacks increasingly targeting public package registries and open-source platforms. Existing detection approaches, including heuristic-, learning-, and LLM-based methods,...

EUVD-2026-52405

Emlog Pro through 2.6.23 contains a disabled TLS certificate validation vulnerability in include/service/ai.php that allows network-adjacent attackers to intercept outbound HTTPS requests to configured LLM providers by presenting arbitrary TLS certificates, as CURLOPTSSLVERIFYPEER and...

NPM: n8n: Custom Header Credential Values Leaked in Plaintext into LLM Node Execution Data

NPM: n8n: Custom Header Credential Values Leaked in Plaintext into LLM Node Execution Data vulnerability discovered by ? in WordPress Npm n8n versions 1.123.64...

EUVD-2026-47633

n8n versions before 1.123.64 fail to properly mask custom HTTP header credentials in LLM sub-node execution data, writing plaintext API keys and secrets to workflow execution records. Authenticated users with access to execution data can read exposed header values and credentials that persist in...

CVE-2026-65589 n8n before 1.123.64 Credential Exposure via LLM Node Execution Data

n8n versions before 1.123.64 fail to properly mask custom HTTP header credentials in LLM sub-node execution data, writing plaintext API keys and secrets to workflow execution records. Authenticated users with access to execution data can read exposed header values and credentials that persist in...

CVE-2026-65589

CVE-2026-65589 affects n8n versions before 1.123.64. The vulnerability arises because custom HTTP header credentials used by the LLM sub-node execution data are not masked, causing plaintext API keys and secrets to be written to workflow execution records. Authenticated users with access to execu...

CVE-2026-65589

n8n versions before 1.123.64 fail to properly mask custom HTTP header credentials in LLM sub-node execution data, writing plaintext API keys and secrets to workflow execution records. Authenticated users with access to execution data can read exposed header values and credentials that persist in...

EUVD-2026-18522

vLLM: Processing differential in multi-channel audio downmixing enables hidden-input/moderation bypass for audio models...

CVE-2026-56259 Crawl4AI - LLM Credential Exfiltration via base_url and Environment Variable Resolution

Crawl4AI before 0.8.8 contains credential exfiltration vulnerabilities in the Docker API server that allow attackers to redirect LLM API calls to attacker-controlled endpoints and read arbitrary environment variables. Attackers can exploit the unauthenticated /md, /llm, and /llm/job endpoints by...

CVE-2026-55615 Langroid: Neo4jChatAgent executes LLM-generated Cypher without validation (prompt-to-Cypher injection; config-conditional RCE), mirroring the SQLChatAgent bug fixed in CVE-2026-25879

Langroid is a framework for building large-language-model-powered applications. Prior to version 0.65.5, Neo4jChatAgent passes LLM-generated Cypher queries straight to the Neo4j driver with no validation, no statement-type allowlist, and no opt-out gate. The query text is influenceable by prompt...

CVE-2026-58473

CVE-2026-58473 (Cognee) vulnerability affects Cognee prior to 1.2.0. An improper access-control flaw allows unauthenticated attackers to overwrite the global LLM provider configuration by self-registering an account and calling the settings endpoint, which lacks admin/superuser checks. This enabl...

GO-2026-5925 Suspended Coder users retain access to AI Bridge LLM proxy endpoints in github.com/coder/coder

Suspended Coder users retain access to AI Bridge LLM proxy endpoints in github.com/coder/coder...

CVE-2026-55574

CVE-2026-55574 affects vLLM prior to 0.24.0, where structured_outputs.regex passes an unguarded user-supplied regex to grammar backends (xgrammar and outlines). In xgrammar, the string reaches the regex compiler without a timeout guard; in outlines, validation overlooks regex complexity (e.g., ne...

CVE-2026-44934

A information disclosure when DEBUG loglevel is set in SUSE Rancher AI Agent 1.0 before 1.0.2 could leak API keys or LLM response text with potential sensitive data into logfiles, allowing local attackers to misuse respective gained data or credentials...