The Application of Transformer-Based Models for Predicting Consequences of Cyber Attacks

Cyberattacks are increasing, and securing against such threats is costing industries billions of dollars annually. Threat Modeling, that is, comprehending the consequences of these attacks, can provide critical support to cybersecurity professionals, enabling them to take timely action and alloca...

Addressing Side-Channel Threats in Quantum Key Distribution Via Deep Anomaly Detection

Traditional countermeasures against security side channels in quantum key distribution QKD systems often suffer from poor compatibility with deployed infrastructure, the risk of introducing new vulnerabilities, and limited applicability to specific types of attacks. In this work, we propose an...

Consiglieres in the Shadow: Understanding the Use of Uncensored Large Language Models in Cybercrimes

The advancement of AI technologies, particularly Large Language Models LLMs, has transformed computing while introducing new security and privacy risks. Prior research shows that cybercriminals are increasingly leveraging uncensored LLMs ULLMs as backends for malicious services. Understanding the...

Tenda AC20 16.03.08.12 Command Injection

Tenda AC20 version 16.03.08.12 suffers from a command injection vulnerability in /goform/telnet...

Lantronix Provisioning Manager 7.10.3 XML Injection

Lantronix Provisioning Manager version 7.10.3 suffers from an XML injection vulnerability...

Sni5Gect: a Practical Approach to Inject aNRchy into 5G NR

In this paper, the authors propose and design SNI5GECT – a framework that sniffs messages from pre-authentication 5G communication in real-time and injects targeted attack payload in downlink communication towards the UE...

MCPSecBench: a Systematic Security Benchmark and Playground for Testing Model Context Protocols

Large Language Models LLMs are increasingly integrated into real-world applications via the Model Context Protocol MCP, a universal, open standard for connecting AI agents with data sources and external tools. While MCP enhances the capabilities of LLM-based agents, it also introduces new securit...

ChamaleoNet: Programmable Passive Probe for Enhanced Visibility on Erroneous Traffic

Traffic visibility remains a key component for management and security operations. Observing unsolicited and erroneous traffic, such as unanswered traffic or errors, is fundamental to detect misconfiguration, temporary failures or attacks. ChamaleoNet transforms any production network into a...

Systematic Analysis of MCP Security

The Model Context Protocol MCP has emerged as a universal standard that enables AI agents to seamlessly connect with external tools, significantly enhancing their functionality. However, while MCP brings notable benefits, it also introduces significant vulnerabilities, such as Tool Poisoning...

Reducing False Positives with Active Behavioral Analysis for Cloud Security

Rule-based cloud security posture management CSPM solutions are known to produce a lot of false positives based on the limited contextual understanding and dependence on static heuristics testing. This paper introduces a validation-driven methodology that integrates active behavioral testing in...

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers

Ensemble-based attacks have been proven to be effective in enhancing adversarial transferability by aggregating the outputs of models with various architectures. However, existing research primarily focuses on refining ensemble weights or optimizing the ensemble path, overlooking the exploration ...

False Data-Injection Attack Detection in Cyber-Physical Systems: a Wasserstein Distributionally Robust Reachability Optimization Approach

Cyber-physical system CPS is the foundational backbone of modern critical infrastructures, so ensuring its security and resilience against cyber-attacks is of pivotal importance. This paper addresses the challenge of designing anomaly detectors for CPS under false-data injection FDI attacks and...

A Robust Cross-Domain IDS Using BiGRU-LSTM-Attention for Medical and Industrial IoT Security

The increased Internet of Medical Things IoMT and the Industrial Internet of Things IIoT interconnectivity has introduced complex cybersecurity challenges, exposing sensitive data, patient safety, and industrial operations to advanced cyber threats. To mitigate these risks, this paper introduces ...

CISA: FY 2023 Tribal Cybersecurity Grant Program FAQs

This is the CISA FAQ for the Tribal Cybersecurity Grant Program TCGP which assists eligible Tribal governments addressing cybersecurity risks and threats to their information systems...

Adversarial Attacks on VQA-NLE: Exposing and Alleviating Inconsistencies in Visual Question Answering Explanations

Natural language explanations in visual question answering VQA-NLE aim to make black-box models more transparent by elucidating their decision-making processes. However, we find that existing VQA-NLE systems can produce inconsistent explanations and reach conclusions without genuinely understandi...

Fortifying the Agentic Web: a Unified Zero-Trust Architecture against Logic-Layer Threats

This paper presents a Unified Security Architecture that fortifies the Agentic Web through a Zero-Trust IAM framework. This architecture is built on a foundation of rich, verifiable agent identities using Decentralized Identifiers DIDs and Verifiable Credentials VCs, with discovery managed by a...

Passive Hack-Back Strategies for Cyber Attribution: Covert Vectors in Denied Environment

Attributing cyberattacks remains a central challenge in modern cybersecurity, particularly within denied environments where defenders have limited visibility into attacker infrastructure and are restricted by legal or operational rules of engagement. This perspective examines the strategic value ...

Cyber Risks to Next-Gen Brain-Computer Interfaces: Analysis and Recommendations

Brain-computer interfaces BCIs show enormous potential for advancing personalized medicine. However, BCIs also introduce new avenues for cyber-attacks or security compromises. In this article, we analyze the problem and make recommendations for device manufacturers to better secure devices and to...

Mitigating Jailbreaks with Intent-Aware LLMs

Despite extensive safety-tuning, large language models LLMs remain vulnerable to jailbreak attacks via adversarially crafted instructions, reflecting a persistent trade-off between safety and task performance. In this work, we propose Intent-FT, a simple and lightweight fine-tuning approach that...

Design and Implementation of a Controlled Ransomware Framework for Educational Purposes Using Flutter Cryptographic APIs on Desktop PCs and Android Devices

This study focuses on the creation and implementation of ransomware for educational purposes that leverages Python's native cryptographic APIs in a controlled environment. Additionally, an Android version of the framework is implemented using Flutter and Dart. For both versions, open-source...

Ethereum Crypto Wallets under Address Poisoning: How Usable and Secure Are They?

Blockchain address poisoning is an emerging phishing attack that crafts "similar-looking" transfer records in the victim's transaction history, which aims to deceive victims and lure them into mistakenly transferring funds to the attacker. Recent works have shown that millions of Ethereum users...

AUTOVR: Automated UI Exploration for Detecting Sensitive Data Flow Exposures in Virtual Reality Apps

The rise of Virtual Reality VR has provided developers with an unprecedented platform for creating games and applications apps that require distinct inputs, different from those of conventional devices like smartphones. The Meta Quest VR platform, driven by Meta, has democratized VR app publishin...

The Passwordless Authentication with Passkey Technology from an Implementation Perspective

With the rise of sophisticated authentication bypass techniques, passwords are no longer considered a reliable method for securing authentication systems. In recent years, new authentication technologies have shifted from traditional password-based logins to passwordless security. Among these,...

Effect of Phase Shift Errors on the Security of UAV-Assisted STAR-RIS IoT Networks

Unmanned aerial vehicles UAV-mounted simultaneous transmitting and reflecting reconfigurable intelligent surface STAR-RIS systems can provide full-dimensional coverage and flexible deployment opportunities in future 6G-enabled IoT networks. However, practical imperfections such as jittering and...

CAN Networks Security in Smart Grids Communication Technologies

The rapid evolution of smart grids requires effective communication protocols to transfer data reliably and securely. Controller Area Network CAN is one of the most recognized protocols that offer reliable data transmission in smart grids due to its robustness, real-time capabilities, and...

PP-STAT: an Efficient Privacy-Preserving Statistical Analysis Framework Using Homomorphic Encryption

With the widespread adoption of cloud computing, the need for outsourcing statistical analysis to third-party platforms is growing rapidly. However, handling sensitive data such as medical records and financial information in cloud environments raises serious privacy concerns. In this paper, we...

Attack Graph Generation on HPC Clusters

Attack graphs AGs are graphical tools to analyze the security of computer networks. By connecting the exploitation of individual vulnerabilities, AGs expose possible multi-step attacks against target networks, allowing system administrators to take preventive measures to enhance their network's...

Unlearning at Scale: Implementing the Right to Be Forgotten in Large Language Models

We study the right to be forgotten GDPR Art. 17 for large language models and frame unlearning as a reproducible systems problem. Our approach treats training as a deterministic program and logs a minimal per-microbatch record ordered ID hash, RNG seed, learning-rate value, optimizer-step counter...

Invitation Is All You Need! Promptware Attacks against LLM-Powered Assistants in Production Are Practical and Dangerous

The growing integration of LLMs into applications has introduced new security risks, notably known as Promptware - maliciously engineered prompts designed to manipulate LLMs to compromise the CIA triad of these applications. While prior research warned about a potential shift in the threat...

CryptoScope: Utilizing Large Language Models for Automated Cryptographic Logic Vulnerability Detection

Cryptographic algorithms are fundamental to modern security, yet their implementations frequently harbor subtle logic flaws that are hard to detect. We introduce CryptoScope, a novel framework for automated cryptographic vulnerability detection powered by Large Language Models LLMs. CryptoScope...

Securing Sideways: Thwarting Lateral Movement by Implementing Active Directory Tiering

The advancement of computing equipment and the advances in services over the Internet has allowed corporations, higher education, and many other organizations to pursue the shared computing network environment. A requirement for shared computing environments is a centralized identity system to...

Machine Learning-Based AES Key Recovery Via Side-Channel Analysis on the ASCAD Dataset

Cryptographic algorithms like AES and RSA are widely used and they are mathematically robust and almost unbreakable but its implementation on physical devices often leak information through side channels, such as electromagnetic EM emissions, potentially compromising said theoretically secure...

RMSL: Weakly-Supervised Insider Threat Detection with Robust Multi-Sphere Learning

Insider threat detection aims to identify malicious user behavior by analyzing logs that record user interactions. Due to the lack of fine-grained behavior-level annotations, detecting specific behavior-level anomalies within user behavior sequences is challenging. Unsupervised methods face high...

Salty Seagull: a VSAT Honeynet to Follow the Bread Crumb of Attacks in Ship Networks

Cyber threats against the maritime industry have increased notably in recent years, highlighting the need for innovative cybersecurity approaches. Ships, as critical assets, possess highly specialized and interconnected network infrastructures, where their legacy systems and operational constrain...

AegisBlock: a Privacy-Preserving Medical Research Framework Using Blockchain

Due to HIPAA and other privacy regulations, it is imperative to maintain patient privacy while conducting research on patient health records. In this paper, we propose AegisBlock, a patient-centric access controlled framework to share medical records with researchers such that the anonymity of th...

Defending a City from Multi-Drone Attacks: a Sequential Stackelberg Security Games Approach

To counter an imminent multi-drone attack on a city, defenders have deployed drones across the city. These drones must intercept/eliminate the threat, thus reducing potential damage from the attack. We model this as a Sequential Stackelberg Security Game, where the defender first commits to a mix...

Activate Me!: Designing Efficient Activation Functions for Privacy-Preserving Machine Learning with Fully Homomorphic Encryption

The growing adoption of machine learning in sensitive areas such as healthcare and defense introduces significant privacy and security challenges. These domains demand robust data protection, as models depend on large volumes of sensitive information for both training and inference. Fully...

Online Tour and Travel Management System 1.0 SQL Injection

Online Tour and Travel Management System version 1.0 suffers from a remote SQL injection vulnerability in the /admin/operations/travellers.php endpoint...

Pushing the Limits of Frequency Analysis in Leakage Abuse Attacks

Searchable encryption SE is the most scalable cryptographic primitive for searching on encrypted data. Typical SE constructions often allow access-pattern leakage, revealing which encrypted records are retrieved in the server's responses. All the known generic cryptanalyses assume either that the...

Multichannel Hybrid Quantum Cryptography for Submarine Optical Communications

We present a multichannel hybrid quantum cryptography approach intended for submarine quantum optical communications between Alice and Bob separated a distance beyond the current QKD possibilities, each located on a coastline. It is based on the difficult of a simultaneous access to $M$ optical...

Routing and Wavelength Assignment with Minimal Attack Radius for QKD Networks

Quantum Key Distribution QKD can distribute keys with guaranteed security but remains susceptible to key exchange interruption due to physical-layer threats, such as high-power jamming attacks. To address this challenge, we first introduce a novel metric, namely Maximum Number of Affected Request...

Searching for Privacy Risks in LLM Agents Via Simulation

The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively engage others in multi-turn interactions to extract sensitive information. These dynamic dialogues enable adaptive attack strategies that can cause severe privacy...

Can Multi-Modal (Reasoning) LLMs Detect Document Manipulation?

Document fraud poses a significant threat to industries reliant on secure and verifiable documentation, necessitating robust detection mechanisms. This study investigates the efficacy of state-of-the-art multi-modal large language models LLMs-including OpenAI O1, OpenAI 4o, Gemini Flash thinking,...

Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts

Evaluating jailbreak attacks is challenging when prompts are not overtly harmful or fail to induce harmful outputs. Unfortunately, many existing red-teaming datasets contain such unsuitable prompts. To evaluate attacks accurately, these datasets need to be assessed and cleaned for maliciousness...

A Hierarchical IDS for Zero-Day Attack Detection in Internet of Medical Things Networks

The Internet of Medical Things IoMT is driving a healthcare revolution but remains vulnerable to cyberattacks such as denial of service, ransomware, data hijacking, and spoofing. These networks comprise resource constrained, heterogeneous devices e.g., wearable sensors, smart pills, implantables,...

MirGuard: Towards a Robust Provenance-Based Intrusion Detection System against Graph Manipulation Attacks

Learning-based Provenance-based Intrusion Detection Systems PIDSes have become essential tools for anomaly detection in host systems due to their ability to capture rich contextual and structural information, as well as their potential to detect unknown attacks. However, recent studies have shown...

Data and Context Matter: Towards Generalizing AI-Based Software Vulnerability Detection

The performance of AI-based software vulnerability detection systems is often limited by their poor generalization to unknown codebases. In this research, we explore the impact of data quality and model architecture on the generalizability of vulnerability detection systems. By generalization we...

Code Vulnerability Detection across Different Programming Languages with AI Models

Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do not work well at detecting the context-dependent bugs and...

Advancing Autonomous Incident Response: Leveraging LLMs and Cyber Threat Intelligence

Effective incident response IR is critical for mitigating cyber threats, yet security teams are overwhelmed by alert fatigue, high false-positive rates, and the vast volume of unstructured Cyber Threat Intelligence CTI documents. While CTI holds immense potential for enriching security operations...

A Transformer-Based Approach for DDoS Attack Detection in IoT Networks

DDoS attacks have become a major threat to the security of IoT devices and can cause severe damage to the network infrastructure. IoT devices suffer from the inherent problem of resource constraints and are therefore susceptible to such resource-exhausting attacks. Traditional methods for detecti...