Another Supply Chain Vulnerability

ProPublica is reporting: Microsoft is using engineers in China to help maintain the Defense Department's computer systems--with minimal supervision by U.S. personnel--leaving some of the nation's most sensitive data vulnerable to hacking from its leading cyber adversary, a ProPublica investigatio...

Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems

Large Language Models LLMs deployed in enterprise settings e.g., as Microsoft 365 Copilot face novel security challenges. One critical threat is prompt inference attacks: adversaries chain together seemingly benign prompts to gradually extract confidential data. In this paper, we present a...

DP2Guard: a Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT

Privacy-Preserving Federated Learning PPFL has emerged as a secure distributed Machine Learning ML paradigm that aggregates locally trained gradients without exposing raw data. To defend against model poisoning threats, several robustness-enhanced PPFL schemes have been proposed by integrating...

Scaling Decentralized Learning with FLock

Fine-tuning the large language models LLMs are prevented by the deficiency of centralized control and the massive computing and communication overhead on the decentralized schemes. While the typical standard federated learning FL supports data privacy, the central server requirement creates a...

PromptArmor: Simple yet Effective Prompt Injection Defenses

Despite their potential, recent research has demonstrated that LLM agents are vulnerable to prompt injection attacks, where malicious prompts are injected into the agent's input, causing it to perform an attacker-specified task rather than the intended task provided by the user. In this paper, we...

Microsoft at Black Hat USA 2025: A unified approach to modern cyber defense

Microsoft will be at Black Hat USA 2025, August 5–7 in Las Vegas, and we’re bringing you a unified, practitioner-driven experience built around real-world insights, threat intelligence, incident response, and hands-on AI expertise. We believe security teams are strongest when intelligence, tools,...

Toward an Intent-Based and Ontology-Driven Autonomic Security Response in Security Orchestration Automation and Response

Modern Security Orchestration, Automation, and Response SOAR platforms must rapidly adapt to continuously evolving cyber attacks. Intent-Based Networking has emerged as a promising paradigm for cyber attack mitigation through high-level declarative intents, which offer greater flexibility and...

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques

Large Language Models LLMs are transforming cybersecurity by enabling intelligent, adaptive, and automated approaches to threat detection, vulnerability assessment, and incident response. With their advanced language understanding and contextual reasoning, LLMs surpass traditional methods in...

Architectural Backdoors in Deep Learning: a Survey of Vulnerabilities, Detection, and Defense

Architectural backdoors pose an under-examined but critical threat to deep neural networks, embedding malicious logic directly into a model's computational graph. Unlike traditional data poisoning or parameter manipulation, architectural backdoors evade standard mitigation techniques and persist...

Thought Purity: Defense Paradigm for Chain-Of-Thought Attack

While reinforcement learning-trained Large Reasoning Models LRMs, e.g., Deepseek-R1 demonstrate advanced reasoning capabilities in the evolving Large Language Models LLMs domain, their susceptibility to security threats remains a critical vulnerability. This weakness is particularly evident in...

Deepfakes. Fake Recruiters. Cloned CFOs — Learn How to Stop AI-Driven Attacks in Real Time

Social engineering attacks have entered a new era—and they're coming fast, smart, and deeply personalized. It's no longer just suspicious emails in your spam folder. Today's attackers use generative AI, stolen branding assets, and deepfake tools to mimic your executives, hijack your social...

Safeguarding Federated Learning-Based Road Condition Classification

Federated Learning FL has emerged as a promising solution for privacy-preserving autonomous driving, specifically camera-based Road Condition Classification RCC systems, harnessing distributed sensing, computing, and communication resources on board vehicles without sharing sensitive image data...

DOGE Denizen Marko Elez Leaked API Key for xAI

Marko Elez , a 25-year-old employee at Elon Musk's Department of Government Efficiency DOGE, has been granted access to sensitive databases at the U.S. Social Security Administration, the Treasury and Justice departments, and the Department of Homeland Security. So it should fill all Americans wi...

Hashed Watermark As a Filter: Defeating Forging and Overwriting Attacks in Weight-Based Neural Network Watermarking

As valuable digital assets, deep neural networks necessitate robust ownership protection, positioning neural network watermarking NNW as a promising solution. Among various NNW approaches, weight-based methods are favored for their simplicity and practicality; however, they remain vulnerable to...

Secure Goal-Oriented Communication: Defending against Eavesdropping Timing Attacks

Goal-oriented Communication GoC is a new paradigm that plans data transmission to occur only when it is instrumental for the receiver to achieve a certain goal. This leads to the advantage of reducing the frequency of transmissions significantly while maintaining adherence to the receiver's...

Multi-Trigger Poisoning Amplifies Backdoor Vulnerabilities in LLMs

Recent studies have shown that Large Language Models LLMs are vulnerable to data poisoning attacks, where malicious training examples embed hidden behaviours triggered by specific input patterns. However, most existing works assume a phrase and focus on the attack's effectiveness, offering limite...

Scattered Spider: Rapid7 Insights, Observations, and Recommendations

Overview of Scattered Spider and recent activity Scattered Spider also tracked as UNC3944, Scatter Swine, Muddled Libra, among other aliases is a financially motivated cybercriminal group active since at least May 2022. The group is notorious for targeting large enterprises — especially...

The Man behind the Sound: Demystifying Audio Private Attribute Profiling Via Multimodal Large Language Model Agents

Our research uncovers a novel privacy risk associated with multimodal large language models MLLMs: the ability to infer sensitive personal attributes from audio data -- a technique we term audio private attribute profiling. This capability poses a significant threat, as audio can be covertly...

LaSM: Layer-Wise Scaling Mechanism for Defending Pop-Up Attack on GUI Agents

Graphical user interface GUI agents built on multimodal large language models MLLMs have recently demonstrated strong decision-making abilities in screen-based interaction tasks. However, they remain highly vulnerable to pop-up-based environmental injection attacks, where malicious visual element...

Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats

Protecting cyberspace requires not only advanced tools but also a shift in how we reason about threats, trust, and autonomy. Traditional cybersecurity methods rely on manual responses and brittle heuristics. To build proactive and intelligent defense systems, we need integrated theoretical...