device-modeling-language

Device Modeling Language The Device Modeling Language DML is a domain-specific language for writing fast functional or transaction-level device models for virtual platforms. DML provides high-level abstractions suitable for functional device models, including constructs like register banks,...

Domain Specific Post Quantum Signatures for Blockchains

Blockchains need more than post quantum single signer signatures. They need consensus profiled authentication objects with canonical bytes, priced invalid input rejection, stable transaction identifiers, hybrid downgrade resistance, public aggregation, merge semantics, accountable signer evidence...

EUVD-2026-53533

Jenkins XML Job to Job DSL Plugin 0.1.13 and earlier does not perform permission checks, allowing attackers lacking appropriate permissions to invoke the conversion functionality...

A Cybersecurity MLPS Large Language Model with Multi-Path Retrieval Fusion

The Multi-Level Protection Scheme MLPS is a foundational system in China's cybersecurity governance framework. Therefore, accurate analysis and understanding of MLPS requirements are essential. At present, MLPS analysis still relies mainly on manual interpretation of standards and rule-based tool...

CVE-2026-65906

In JetBrains TeamCity before 2026.1.2, 2025.11.6 сode execution via Kotlin DSL sandbox escape was possible...

VeriChat: An Agentic Conversational AI Assistant for Hardware Security Verification

Hardware security verification is a multi-stage process in which engineers must navigate complex design analyses, threat considerations, and verification strategies. They often need security-focused guidance, yet current verification environments provide little structured support for such...

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis

Most TinyML hardware accelerators focus on supporting Quantized Neural Networks QNNs to meet stringent constraints on power consumption and size. Despite this, the security aspects of quantization within TinyML hardware remain largely unexplored. Although previous studies indicate that QNNs...

The Role of Domain-Specific Features in Malware Detection: A MacOS Case Study

Despite the growing popularity of macOS among end users and enterprise systems, malware research has primarily focused on Windows and Android operating systems, leaving the problem of macOS malware detection relatively unexplored. Indeed, the specificity of the operating system and the unique...

CVE-2026-41645 Nuclei: Environment variable disclosure via Response-Derived DSL Expressions

Nuclei is a vulnerability scanner built on a simple YAML-based DSL. From version 3.0.0 to before version 3.8.0, a vulnerability in Nuclei's expression evaluation engine makes it possible for a malicious target server to inject and execute supported DSL expressions. This happens when HTTP response...

CVE-2026-41645 Nuclei: Environment variable disclosure via Response-Derived DSL Expressions

Nuclei is a vulnerability scanner built on a simple YAML-based DSL. From version 3.0.0 to before version 3.8.0, a vulnerability in Nuclei's expression evaluation engine makes it possible for a malicious target server to inject and execute supported DSL expressions. This happens when HTTP response...

Arbitrary Code Injection

Overview org.apache.atlas:atlas-repository is an Apache Atlas Repository Module Affected versions of this package are vulnerable to Arbitrary Code Injection in the DSL search endpoint. An attacker can execute arbitrary code by placing malicious Gremlin traversal logic within grammar-allowed...

CVE-2026-40563

Description: Improper Control of Generation of Code 'Code Injection' vulnerability in Apache Atlas Apache Atlas exposes a DSL search endpoint that accepts user-supplied query strings. Attacker can alter Gremlin traversal logic within grammar-allowed characters to access unintended data Affect...

sinatra

Classy web-development dressed in a DSL official / canonical repo...

GHSA-JM34-66CF-QPVR Nuclei: Environment variable disclosure via Response-Derived DSL Expressions

A vulnerability in Nuclei's expression evaluation engine makes it possible for a malicious target server to inject and execute supported DSL expressions. This happens when HTTP response data containing helper/function syntax gets reused by multi-step templates. If the -env-vars / -ev option is...

Nuclei 安全漏洞

Nuclei is a fast-customizable vulnerability scanner based on simple YAML, open-sourced by ProjectDiscovery. Versions of Nuclei prior to 3.8.0 have security vulnerabilities, which stem from DSL expression injection and may affect the use of multi-step templates...

PHANTOM: Progressive High-Fidelity Adversarial Network for Threat Object Modeling

The scarcity of cyberattack data hinders the development of robust intrusion detection systems. This paper introduces PHANTOM, a novel adversarial variational framework for generating high-fidelity synthetic attack data. Its innovations include progressive training, a dual-path VAE-GAN...

Specification-Guided Vulnerability Detection with Large Language Models

Large language models LLMs have achieved remarkable progress in code understanding tasks. However, they demonstrate limited performance in vulnerability detection and struggle to distinguish vulnerable code from patched code. We argue that LLMs lack understanding of security specifications -- the...

Network Intrusion Detection: Evolution from Conventional Approaches to LLM Collaboration and Emerging Risks

This survey systematizes the evolution of network intrusion detection systems NIDS, from conventional methods such as signature-based and neural network NN-based approaches to recent integrations with large language models LLMs. It clearly and concisely summarizes the current status, strengths, a...

sinatra

This is the official repository for the Sinatra web framework. It is a DSL Domain Specific Language for web development, allowing developers to create web applications in a concise and elegant way. The repository contains the core code for Sinatra, as well as various plugins and extensions. The...

MH-FSF: a Unified Framework for Overcoming Benchmarking and Reproducibility Limitations in Feature Selection Evaluation

Feature selection is vital for building effective predictive models, as it reduces dimensionality and emphasizes key features. However, current research often suffers from limited benchmarking and reliance on proprietary datasets. This severely hinders reproducibility and can negatively impact...