34 matches found
anamnesis-release
Anamnesis: LLM Exploit Generation Evaluation This repository contains the evaluation framework for studying how LLM agents generate exploits from vulnerability reports in the presence of exploit mitigations. Given a bug report and proof-of-concept trigger, agents analyze vulnerable software and...
CVE-2022-30190
CVE-2022-30190 - Microsoft Support Diagnostic Tool About This script will attempt to create a Microsoft Office document which will remotely execute code. Setup git clone https://github.com/joshuavanderpoll/CVE-2022-30190.git cd CVE-2022-30190 python3 CVE-2022-30190.py --help Options usage:...
CVE-2018-4878
CVE-2018-4878 Samples Sample source: https://github.com/brianwrf/CVE-2017-4878-Samples Analysis report: http://blog.talosintelligence.com/2018/02/group-123-goes-wild.html Exploit source in Python script: https://github.com/vysec/CVE-2018-4878 cve-2018-4878.py is the exploit generation script, the...
MEGALODON
MEGALODON Automated w...
vulnclaw
基于 LLM Agent + MCP 工具链 + 渗透 Skill 编排， 配合 OpenAI / MiniMax / DeepSeek 等兼容模型， 自然语言输入 → 自动完成「...
PoCHarness
!licensehttps://img.shields.io/badge/license-Apache--2.0-gree...
Does AI Help Cyber Attackers or Defenders? Evidence from Nonpublic Vulnerabilities and Subsequent Attacks
The release decision for frontier AI systems increasingly relies on cyber capability benchmarks, yet public vulnerability benchmarks can expose agents to previously published advisories, exploits, and fixes, making it difficult to distinguish prior exposure from capability on unseen...
Ai-Vulnerability-Code-Detector
AI-Powered Vulnerability Scanner A comprehensive security sca...
PoCEvolve: Generating Proof-Of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution
Ideally, the detailed information about a vulnerability should be made available together with the fixing commit. In practice, however, such details often become available only long after the commit, even when a CVE has already been published. During this window, the patch is already public, so...
CyberChainBench: Can AI Agents Secure Smart Contracts against Real-World On-Chain Vulnerabilities?
We present CyberChainBench, a benchmark for evaluating LLM-based agents on smart contract security across three complementary tasks: vulnerability detection, exploit generation, and patch synthesis. Built from 541 real-world exploit incidents from DeFiHackLabs spanning 9 EVM chains, the benchmark...
xploit
AutoExploit - Automated Exploit Development Framework Over...
opencode-apk-forge
APKForge - The Dark Version of OpenCode ███╗ ███╗ ██╗...
Data-Centric Benchmarking of Exploit Generation in LLMs: Understanding the Impact of Fine-Tuning
We study the task of CVE-conditioned exploit generation, where a model drafts proof-of-concept PoC exploits given software vulnerability context. We adopt a data-centric approach, constructing a high-quality dataset via multi-stage preprocessing and introducing a scalable evaluation framework wit...
AI_AutoExploitGeneration
🎯 AI-POWERED AUTOMATED EXPLOIT GENERATION AEG SYSTEM Vers...
unverified_exploits
Unverified Exploits - Rule-Based Exploit Generation & Testing...
claude-skills-exploit
Security Research Skills Reusable skills for vulnerability an...
ExploitMind
ExploitMind Overview ExploitMind is an en...
Automation-Exploit-Legacy
Automation-Exploit Legacy Prototype This repository contain...
V2E: Validating Smart Contract Vulnerabilities through Profit-Driven Exploit Generation and Execution
Smart contracts are a critical component of blockchain systems. Due to the large amount of digital assets carried by smart contracts, their security is of critical importance. Although numerous tools have been developed for detecting smart contract vulnerability, their effectiveness remains...