Tailored Prompts, Targeted Protection: Vulnerability-Specific LLM Analysis for Smart Contracts

Smart contracts on blockchains are prone to diverse security vulnerabilities that can lead to significant financial losses due to their immutable nature. Existing detection approaches often lack flexibility across vulnerability types and rely heavily on manually crafted expert rules. In this pape...

Exploit for Missing Authentication for Critical Function in Cpanel

CVE-2026-41940 Detection & Verification !License: MIThttp...

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection

How code representation format shapes false positive behaviour in cross-language LLM vulnerability detection remains poorly understood. We systematically vary training intensity and code representation format, comparing raw source text with pruned Abstract Syntax Trees at both training time and...

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree AST structure, and code stylometry CStyle features. Prior work in code representation primarily leverages token-level models or full AST...

A Systematic Literature Review for Transformer-Based Software Vulnerability Detection

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic...

Symbolic Execution Meets Multi-LLM Orchestration: Detecting Memory Vulnerabilities in Incomplete Rust CVE Snippets

This paper presents a system combining symbolic execution KLEE with a 4-agent multi-LLM architecture for detecting memory vulnerabilities in Rust unsafe code. A central challenge we address is the incomplete-code problem: CVE database entries provide only isolated code snippets that lack struct...

DarkWin-NGASR

🌌 DARKWIN — Next-Gen Automated Security Research Develope...

MetInfo CMS 8.1 WeChat Module Vulnerability Detection Scanner

This Metasploit auxiliary module is a non-exploit vulnerability detection scanner designed to assess potential security weaknesses in the MetInfo CMS WeChat module, specifically related to weixinreply.class.php handling logic...

Strategic Heterogeneous Multi-Agent Architecture for Cost-Effective Code Vulnerability Detection

Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection accuracy and computational cost. We propose a heterogeneous multi-agent architecture inspired by game-theoretic principles, combining cloud-based LLM...

A Ground-Truth-Based Evaluation of Vulnerability Detection across Multiple Ecosystems

Automated vulnerability detection tools are widely used to identify security vulnerabilities in software dependencies. However, the evaluation of such tools remains challenging due to the heterogeneous structure of vulnerability data sources, inconsistent identifier schemes, and ambiguities in...

Taint-Style Vulnerability Detection and Confirmation for Node.Js Packages Using LLM Agent Reasoning

The rapidly evolving Node$.$js ecosystem currently includes millions of packages and is a critical part of modern software supply chains, making vulnerability detection of Node$.$js packages increasingly important. However, traditional program analysis struggles in this setting because of dynamic...

Security Is Relative: Training-Free Vulnerability Detection Via Multi-Agent Behavioral Contract Synthesis

Deep learning for vulnerability detection has shown promising results on early benchmarks, but recent evaluations reveal catastrophic degradation: models achieving F1 0.68 on legacy datasets collapse to 0.031 under strict deduplication. We identify the root cause as the semantic ambiguity problem...

InduGuard_vul_poc

ICS Vulnerability PoC Library — SCAA Benchmark Support Proof-...

SUSE: Security Advisory (SUSE-SU-2026:20997-1)

The remote host is missing an update for the SPDX-FileCopyrightText: 2026 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only ifdescription...

cyber-punk

Cyber Punk Security Vulnerability Scanner A Claude Code plu...

BayreuthWing

A transformer-based deep learning system for detecting securit...

Vulnerability Detection with Interprocedural Context in Multiple Languages: Assessing Effectiveness and Cost of Modern LLMs

Large Language Models LLMs have been a promising way for automated vulnerability detection. However, most prior studies have explored the use of LLMs to detect vulnerabilities only within single functions, disregarding those related to interprocedural dependencies. These studies overlook...

Ubuntu: Security Advisory (USN-8158-1)

The remote host is missing an update for the SPDX-FileCopyrightText: 2026 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only ifdescription...

PT-2026-31562

Open AI models detect vulnerabilities by analyzing code, configs, and system behavior step-by-step—like spotting the FreeBSD zero-day CVE-2024-47467 in the Mythos showcase. Even a 3B open model nailed it, matching bigger ones. The chart shows rankings flip across tasks: OWASP easy stuff vs. gnarl...

Argus: Reorchestrating Static Analysis Via a Multi-Agent Ensemble for Full-Chain Security Vulnerability Detection

Recent advancements in Large Language Models LLMs have sparked interest in their application to Static Application Security Testing SAST, primarily due to their superior contextual reasoning capabilities compared to traditional symbolic or rule-based methods. However, existing LLM-based approache...