Sec5GLoc

Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture Our work addresses security and privacy challenges in 5G indoor localization by proposing an adversary-resilient deep learning architecture. Sec5GLoc combines Channel Impulse Response CIR fingerprinting...

augustus

Augustus - LLM vulnerability scanner for prompt injection, jailbreak, and adversarial attack testing Augustus - LLM Vulnerability Scanner Test large language models against 210+ adversarial attacks covering prompt injection, jailbreaks, encoding exploits, and data extraction. Augustus is a Go-bas...

cerebro-red-v2

CEREBRO-RED v2 Research Edition Autonomous Local LLM Red Teaming Suite A research-grade framework for automated vulnerability discovery in local LLMs using Agentic Fuzzing and Adaptive Adversarial Mutation AAM. Research Goals Implement PAIR Algorithm Prompt Automatic Iterative Refinement from...

StealthRL

StealthRL: Reinforcement Learning Paraphrase Attacks for Multi-Detector Evasion of AI-Text Detectors Paper arXiv Demo Model Hugging Face Benchmark Dataset Hugging Face Abstract AI-text detectors are increasingly used in high-stakes settings, yet their robustness to meaning-preserving adversarial...

PoisonCraft

PoisonCraft This repository provides the official implementation of POISONCRAFT: Practical Poisoning of Retrieval-Augmented Generation for Large Language Models. Overview POISONCRAFT aims to demonstrate how a malicious actor can plant “poisoned” content into the corpus used by Retrieval-Augmented...

redeval

RedEval - LLM Safety Evaluation Framework A comprehensive framework for evaluating the safety of Large Language Models LLMs through systematic attack and refusal testing. RedEval provides a unified, secure, and extensible platform for assessing LLM robustness against adversarial prompts and harmf...

Ruse

Ruse Mobile camera-based application that attempts to alter photos to preserve their utility to humans while making them unusable for facial recognition systems. Installation 1 Easy Method: Wait and download app from appropriate app store. 2 Download and run ios app via XCode see Development setu...

Prompt-Injection-in-the-Wild

Prompt Injection in the Wild A tracker of publicly reported prompt-injection techniques from roughly the last two years, maintained by Rachel James cybershujin. Each technique is broken down into the three elements of a prompt injection: 1. Delivery method — how the injected instructions reach th...

ai-security-battle

🤖 AI Security Battle System Red Team vs Blue Team: Adversarial ML Combat Simulation A comprehensive adversarial machine learning security simulation where Red Team attackers battle against Blue Team defenders in a 30-minute AI/ML security warfare scenario. 🎯 Project Overview This system simulates...

BrokenHill

!\ Broken Hill logo \https://assets.kitploit.com/production/public/readmes/44608/c14154675c6f33f5c3887887afcdb39351c82f269ee2772cf31847106a20a871.jpg Broken Hill Broken Hill is a productionized, ready-to-use automated attack tool that generates crafted prompts to bypass restrictions in large...

WebMirage

WebMirage Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution Wanjing Han, Levi Taiji Li, Mu Zhang, Yue Jiang, Guanhong Tao — University of Utah WebMirage is a red-teaming framework for vision-grounded web agents. It crafts localized adversarial perturbations on...

Awesome-MoAI-Security

Awesome Mobile On-Device AI Security SoK: Attack and Defense Landscape of Mobile On-device AI Systems Mobile on-device AI systems execute AI models locally through ML frameworks such as LiteRT/TFLite , Core ML , ExecuTorch , ONNX , and hardware-backed accelerators. This repo tracks the security...

QuasarNix

QuasarNix: Adversarially Robust Living-off-the-Land Reverse-Shell Detection Dmitrijs Trizna · Luca Demetrio · Battista Biggio · Fabio Roli Overview Linux living-off-the-land LOTL reverse shells abuse legitimate binaries bash, python, nc, … to establish covert outbound connections, making...

PacketPatch

PacketPatch: Practical Generation and Deployment of Adversarial Packets for Byte-Feature-Based Encrypted Traffic Classification Paper : PacketPatch: Practical Generation and Deployment of Adversarial Packets for Byte-Feature-Based Encrypted Traffic Classification Authors : Yuwei Xu, Yuanyuan Xu,...

DARWIN

🧬 DARWIN Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection An evolutionary attack–defense framework that couples DARWIN-Attack with DARWIN-Guard through online adversarial training. Paper · Guard Checkpoint · Installation · Use DARWIN-Attack · Use DARWIN-Guard ·...

Defenses-for-Tool-Integrated-LLM

Universal Defences for Tool-Integrated LLM Agents Against Adversarial Attacks This repository contains the code and experiments for our project on defending tool-integrated large language model LLM agents against adversarial attacks. Overview We build upon Agent Security Bench ASB to evaluate how...

T-MAP

T-MAP: Red-Teaming LLM Agents with Trajectory-aware Evolutionary Search T-MAP is a trajectory-aware evolutionary search framework for red-teaming LLM agents over MCP servers. It iteratively generates and mutates adversarial prompts guided by execution trajectories, mapping the agent's vulnerabili...

DeepTrap

DeepTrap English | 中文 Open-world security evaluation for OpenClaw agents under adversarial execution contexts. DeepTrap is a security benchmark for evaluating whether OpenClaw agents can complete benign user tasks while resisting malicious execution-context pressure: poisoned workspace files,...

CyberArena: Benchmarking AI Agents in Live Symmetric Attack-And-Defense Combat

AI agents are demonstrating increasingly strong offensive and defensive cybersecurity capabilities in the real world. Current benchmarks mostly evaluate agents in isolation against static targets. Real cyber operations, however, are dynamic and coupled: security postures constantly change as...

red-kube

Emulación de adversario K8S para Red Team basada en kubectl Red Kube es una colección de comandos de kubectl diseñados para evaluar la postura de seguridad de los clústeres de Kubernetes desde la perspectiva del atacante. Los comandos son pasivos para recopilación de datos y divulgación de...