Quantum Opacity, Classical Clarity: a Hybrid Approach to Quantum Circuit Obfuscation

Quantum computing leverages quantum mechanics to achieve computational advantages over classical hardware, but the use of third-party quantum compilers in the Noisy Intermediate-Scale Quantum NISQ era introduces risks of intellectual property IP exposure. We address this by proposing a novel...

MorphMark: Flexible Adaptive Watermarking for Large Language Models

Watermarking by altering token sampling probabilities based on red-green list is a promising method for tracing the origin of text generated by large language models LLMs. However, existing watermark methods often struggle with a fundamental dilemma: improving watermark effectiveness the...

Defending the Edge: Representative-Attention for Mitigating Backdoor Attacks in Federated Learning

Federated learning FL enhances privacy and reduces communication cost for resource-constrained edge clients by supporting distributed model training at the edge. However, the heterogeneous nature of such devices produces diverse, non-independent, and identically distributed non-IID data, making t...

Adversarial Suffix Filtering: a Defense Pipeline for LLMs

Large Language Models LLMs are increasingly embedded in autonomous systems and public-facing environments, yet they remain susceptible to jailbreak vulnerabilities that may undermine their security and trustworthiness. Adversarial suffixes are considered to be the current state-of-the-art...

Vendor-Agnostic Security: The Key To Smarter Risk Management

Security teams are investing in more tools than ever – but visibility into real risk is still elusive. Why? Because too many tools are locked inside closed ecosystems that don’t share data or context. A vendor-agnostic security strategy changes that. It gives you the flexibility to integrate...

LiteLMGuard: Seamless and Lightweight On-Device Prompt Filtering for Safeguarding Small Language Models against Quantization-Induced Risks and Vulnerabilities

The growing adoption of Large Language Models LLMs has influenced the development of their lighter counterparts-Small Language Models SLMs-to enable on-device deployment across smartphones and edge devices. These SLMs offer enhanced privacy, reduced latency, server-free functionality, and improve...

RuleGenie: SIEM Detection Rule Set Optimization

SIEM systems serve as a critical hub, employing rule-based logic to detect and respond to threats. Redundant or overlapping rules in SIEM systems lead to excessive false alerts, degrading analyst performance due to alert fatigue, and increase computational overhead and response latency for actual...

BadLingual: a Novel Lingual-Backdoor Attack against Large Language Models

In this paper, we present a new form of backdoor attack against Large Language Models LLMs: lingual-backdoor attacks. The key novelty of lingual-backdoor attacks is that the language itself serves as the trigger to hijack the infected LLMs to generate inflammatory speech. They enable the precise...

Protocol-Agnostic and Data-Free Backdoor Attacks on Pre-Trained Models in RF Fingerprinting

While supervised deep neural networks DNNs have proven effective for device authentication via radio frequency RF fingerprinting, they are hindered by domain shift issues and the scarcity of labeled data. The success of large language models has led to increased interest in unsupervised pre-train...

T2VShield: Model-Agnostic Jailbreak Defense for Text-To-Video Models

The rapid development of generative artificial intelligence has made text to video models essential for building future multimodal world simulators. However, these models remain vulnerable to jailbreak attacks, where specially crafted prompts bypass safety mechanisms and lead to the generation of...

What Lurks Within? Concept Auditing for Shared Diffusion Models at Scale

Diffusion models DMs have revolutionized text-to-image generation, enabling the creation of highly realistic and customized images from text prompts. With the rise of parameter-efficient fine-tuning PEFT techniques like LoRA, users can now customize powerful pre-trained models using minimal...

Building a Custom Risk Prioritization and Risk Scoring Methodology with Surface Command

Over the 15 years I spent as a practitioner and consultant prior to joining Rapid7, a metric that I found to be ever elusive was a true custom prioritization score. You could get close- with enough time, energy, spreadsheets, and logs. But even then it wasn’t without fault. There were still...

Spring AI Embraces OpenAI's Structured Outputs: Enhancing JSON Response Reliability

OpenAI recently introduced a powerful feature called Structured Outputs, which ensures that AI-generated responses adhere strictly to a predefined JSON schema. This feature significantly improves the reliability and usability of AI-generated content in real-world applications. Today, we're excite...

MAL-2024-6531 Malicious code in agnostic_duplicate (RubyGems)

--- -= Per source details. Do not edit below this line.=-...

Malicious code in agnostic_duplicate (RubyGems)

--- -= Per source details. Do not edit below this line.=-...

Google Introduces Project Naptime for AI-Powered Vulnerability Research

Google has developed a new framework called Project Naptime that it says enables a large language model LLM to carry out vulnerability research with an aim to improve automated discovery approaches. "The Naptime architecture is centered around the interaction between an AI agent and a target...

How to Use Tines's SOC Automation Capability Matrix

Created by John Tuckner and the team at automation and AI-powered workflow platform Tines, the SOC Automation Capability Matrix SOC ACM is a set of techniques designed to help security operations teams understand their automation capabilities and respond more effectively to incidents. A...

CVE-2024-37902

Summary: CVE-2024-37902 affects the Java DeepJavaLibrary (DJL) up to version 0.27.0. The root cause is an absolute-path handling flaw in archived artifacts that can insert files directly into the system and overwrite system files. The issue is fixed in DJL v0.28.0 and also patched in the DJL Larg...

CVE-2024-36129

OpenTelemetry Collector is affected by CVE-2024-36129, an unsafe decompression vulnerability that allows unauthenticated remote DoS via excessive memory consumption. The issue affects the OpenTelemetry Collector and its modules, with fixes published in version 0.102.1 of the collector and 0.102.1...

[SECURITY] Fedora 39 Update: rust-python-launcher-1.0.0-12.fc39

The Python Launcher for Unix. Launch your Python interpreter the lazy/smart way! This launcher is an implementation of the py command for Unix-based platforms. The goal is to have py become the cross-platform command that Python users typically use to launch an interpreter while doing development...