MAAD-AF

MAAD Attack Framework MAAD-AF is an open-source cloud attack tool for Microsoft 365 & Entra IDAzure AD environments. MAAD-AF offers simple, fast and effective security testing. Validate Microsoft cloud controls and test detection & response capabilities with a virutally zero-setup process, comple...

AdStrike

AdStrike — v5.0 «AdStrike» AI Powered Professional Active Directory Attack Framework Authorized use only. Do not run this tool against systems without explicit written permission. Release status: beta/research build. Menu and import health checks pass; individual modules still depend on target...

teatime

=========================================== Teatime - A Blockchain RPC Attack Framework .. image:: https://img.shields.io/pypi/v/teatime.svg :target: https://pypi.python.org/pypi/teatime .. image:: https://img.shields.io/travis/dmuhs/teatime.svg :target: https://travis-ci.com/dmuhs/teatime...

siemframework

SIEMS FRAMEWORK MultiSIEM Modular Python3 Attack Framework By ElevenPaths https://www.elevenpaths.com/ Usage: python3 ./siemsframework.py INTRODUCTION SIEMs are defensive tools increasingly used in the field of cybersecurity, especially by major companies and companies intended to monitor highly...

beef

Copyright c 2006-2026 Wade Alcorn - [email protected] Browser Exploitation Framework BeEF - https://beefproject.com Vedi il file 'doc/COPYING' per i permessi di copia =============================================================================== Cos'è BeEF? BeEF è l'acronimo di The Browser...

HijackKV: New Threat in Position-Independent KV Cache Reuse

Key-Value KV cache reduces inference latency in large language models LLMs. Traditional prefix-based reuse has low cache hit rates across inference requests because it requires exact token and position matches. To improve efficiency, recent system optimizations introduce position-independent KV...

Decoys Cannot Go Everywhere: Mapping the Deception Surface in MITRE ATT&CK

Cyber deception research often assumes that a decoy can be placed wherever there is attacker behavior. This work tests that assumption across MITRE ATT&CK v18.1. We introduce a four-criterion rubric for infrastructure deception and apply it to all 250 ATT&CK techniques. The rubric evaluates wheth...

The-Full-Attack-Chain

⚔️ The Full Attack Chain — Capstone Red Team Engagement Int...

Operation-Molasses

🍯 OPERATION MOLASSES PEKMEZ Zencefil Efendi's Cyber Dow...

Skill Description Deception Attack against Task Routing in Internet of Agents

A new paradigm, Internet of Agents IoA, is transforming networked systems into LLM-driven service networks, where heterogeneous agents collaborate through task routing based on their self-declared skill descriptions. Although this promising paradigm enables agentic, distributed, and advanced...

Position: AI Security Policy Should Target Systems, Not Models

We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory, parallel exploration, and evolutionary optimization. Together, our results demonstrate that both safety bypass of frontier models and software...

Poisoning the Pixels: Revisiting Backdoor Attacks on Semantic Segmentation

Semantic segmentation models are widely deployed in safety-critical applications such as autonomous driving, yet their vulnerability to backdoor attacks remains largely underexplored. Prior segmentation backdoor studies transfer threat settings from existing image classification tasks, focusing...

DeepStage: Learning Autonomous Defense Policies against Multi-Stage APT Campaigns

This paper presents DeepStage, a deep reinforcement learning DRL framework for adaptive, stage-aware defense against Advanced Persistent Threats APTs. The enterprise environment is modeled as a partially observable Markov decision process POMDP, where host provenance and network telemetry are fus...

Jailbreaking Embodied LLMs Via Action-Level Manipulation

Embodied Large Language Models LLMs enable AI agents to interact with the physical world through natural language instructions and actions. However, beyond the language-level risks inherent to LLMs themselves, embodied LLMs with real-world actuation introduce a new vulnerability: instructions tha...

Automating Agent Hijacking Via Structural Template Injection

Agent hijacking, highlighted by OWASP as a critical threat to the Large Language Model LLM ecosystem, enables adversaries to manipulate execution by injecting malicious instructions into retrieved content. Most existing attacks rely on manually crafted, semantics-driven prompt manipulation, which...

The Crown Jewels of Active Directory: How Trellix Helix Detects NTDS.dit Theft

The Crown Jewels of Active Directory: How Trellix Helix Detects NTDS.dit Theft By Adithya Chandra and Maulik Maheta · February 2, 2026 Executive summary Active Directory serves as the central repository for an organization's authentication infrastructure. Malicious actors frequently focus on...

Turning threat reports into detection insights with AI

Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...

Turning threat reports into detection insights with AI

Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...

RunawayEvil: Jailbreaking the Image-To-Video Generative Models

Image-to-Video I2V generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the security of such multimodal systems, particularly their vulnerability to jailbreak attacks, remains critically underexplored. To bridge this gap, we...

A Practical Honeypot-Based Threat Intelligence Framework for Cyber Defence in the Cloud

In cloud environments, conventional firewalls rely on predefined rules and manual configurations, limiting their ability to respond effectively to evolving or zero-day threats. As organizations increasingly adopt platforms such as Microsoft Azure, this static defense model exposes cloud assets to...