Certifiably Robust Malware Detectors by Design

Malware analysis involves analyzing suspicious software to detect malicious payloads. Static malware analysis, which does not require software execution, relies increasingly on machine learning techniques to achieve scalability. Although such techniques obtain very high detection accuracy, they c...

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information...

Enhancing Privacy in Decentralized Min-Max Optimization: a Differentially Private Approach

Decentralized min-max optimization allows multi-agent systems to collaboratively solve global min-max optimization problems by facilitating the exchange of model updates among neighboring agents, eliminating the need for a central server. However, sharing model updates in such systems carry a ris...

Cognitive Cybersecurity for Artificial Intelligence: Guardrail Engineering with CCS-7

Language models exhibit human-like cognitive vulnerabilities, such as emotional framing, that escape traditional behavioral alignment. We present CCS-7 Cognitive Cybersecurity Suite, a taxonomy of seven vulnerabilities grounded in human cognitive security research. To establish a human benchmark,...

Neural Network-Based Detection and Multi-Class Classification of FDI Attacks in Smart Grid Home Energy Systems

False Data Injection Attacks FDIAs pose a significant threat to smart grid infrastructures, particularly Home Area Networks HANs, where real-time monitoring and control are highly adopted. Owing to the comparatively less stringent security controls and widespread availability of HANs, attackers...

Balancing Privacy and Efficiency: Music Information Retrieval Via Additive Homomorphic Encryption

In the era of generative AI, ensuring the privacy of music data presents unique challenges: unlike static artworks such as images, music data is inherently temporal and multimodal, and it is sampled, transformed, and remixed at an unprecedented scale. These characteristics make its core vector...

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection

Ensuring LLM alignment is critical to information security as AI models become increasingly widespread and integrated in society. Unfortunately, many defenses against adversarial attacks and jailbreaking on LLMs cannot adapt quickly to new attacks, degrade model responses to benign prompts, or...

Who'S the Evil Twin? Differential Auditing for Undesired Behavior

Detecting hidden behaviors in neural networks poses a significant challenge due to minimal prior knowledge and potential adversarial obfuscation. We explore this problem by framing detection as an adversarial game between two teams: the red team trains two similar models, one trained solely on...

EU Digital Regulation and Guatemala: AI, 5G, and Cybersecurity

The paper examines how EU rules in AI, 5G, and cybersecurity operate as transnational governance and shape policy in Guatemala. It outlines the AI Act's risk approach, the 5G Action Plan and Security Toolbox, and the cybersecurity regime built on ENISA, NIS2, the Cybersecurity Act, and the Cyber...

Symbolic Execution in Practice: a Survey of Applications in Vulnerability, Malware, Firmware, and Protocol Analysis

Symbolic execution is a powerful program analysis technique that allows for the systematic exploration of all program paths. Path explosion, where the number of states to track becomes unwieldy, is one of the biggest challenges hindering symbolic execution's practical application. To combat this,...

Latent Fusion Jailbreak: Blending Harmful and Harmless Representations to Elicit Unsafe LLM Outputs

Large language models LLMs demonstrate impressive capabilities in various language tasks but are susceptible to jailbreak attacks that circumvent their safety alignments. This paper introduces Latent Fusion Jailbreak LFJ, a representation-based attack that interpolates hidden states from harmful...

MALRIS: Malicious Hardware in RIS-Assisted Wireless Communications

Reconfigurable intelligent surfaces RIS enhance wireless communication by dynamically shaping the propagation environment, but their integration introduces hardware-level security risks. This paper presents the concept of Malicious RIS MALRIS, where compromised components behave adversarially, ev...

Confluence Broken Access Control

This script is designed to exploit the CVE-2023-22515 vulnerability in Confluence, which allows for unauthorized access to Confluence Server and Confluence Data Center instances. The vulnerability is categorized as a broken access control issue and has a CVSS base score of 10.0...

CitrixBleed 2 Mass Scanner

This script is a mass scanner for the CitrixBleed 2 vulnerability...

Beyond Uniform Criteria: Scenario-Adaptive Multi-Dimensional Jailbreak Evaluation

Precise jailbreak evaluation is vital for LLM red teaming and jailbreak research. Current approaches employ binary classification e.g., string matching, toxic text classifiers, LLM-driven methods, yielding only "yes/no" labels without quantifying harm intensity. Existing multi-dimensional...

ScamAgents: How AI Agents Can Simulate Human-Level Scam Calls

Large Language Models LLMs have demonstrated impressive fluency and reasoning capabilities, but their potential for misuse has raised growing concern. In this paper, we present ScamAgent, an autonomous multi-turn agent built on top of LLMs, capable of generating highly realistic scam call scripts...

Topology Generation of UAV Covert Communication Networks: a Graph Diffusion Approach with Incentive Mechanism

With the growing demand for Uncrewed Aerial Vehicle UAV networks in sensitive applications, such as urban monitoring, emergency response, and secure sensing, ensuring reliable connectivity and covert communication has become increasingly vital. However, dynamic mobility and exposure risks pose...

ProvX: Generating Counterfactual-Driven Attack Explanations for Provenance-Based Detection

Provenance graph-based intrusion detection systems are deployed on hosts to defend against increasingly severe Advanced Persistent Threat. Using Graph Neural Networks to detect these threats has become a research focus and has demonstrated exceptional performance. However, the widespread adoption...

Label Inference Attacks against Federated Unlearning

Federated Unlearning FU has emerged as a promising solution to respond to the right to be forgotten of clients, by allowing clients to erase their data from global models without compromising model performance. Unfortunately, researchers find that the parameter variations of models induced by FU...

WordPress Bricks 1.9.6 Remote Code Execution

This tool is designed to exploit the CVE-2024-25600 vulnerability found in the Bricks Builder plugin for WordPress versions 1.9.6 and below. The vulnerability allows for unauthenticated remote code execution on affected websites. The tool automates the exploitation process by retrieving nonces an...

Microsoft SharePoint Privilege Escalation

This script exploits a vulnerability in Microsoft SharePoint Server allowing remote attackers to escalate privileges on affected installations. While this script focuses on elevation of privilege, attackers with malicious intent might chain this vulnerability with a remote code execution...

Membership Inference Attack with Partial Features

Machine learning models have been shown to be susceptible to membership inference attack, which can be used to determine whether a given sample appears in the training data. Existing membership inference methods commonly assume that the adversary has full access to the features of the target...

Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models: a Unified and Accurate Approach

Despite extensive alignment efforts, Large Vision-Language Models LVLMs remain vulnerable to jailbreak attacks, posing serious safety risks. Although recent detection works have shifted to internal representations due to their rich cross-modal information, most methods rely on heuristic rules...

Mitigating Distribution Shift in Graph-Based Android Malware Classification Via Function Metadata and LLM Embeddings

Graph-based malware classifiers can achieve over 94% accuracy on standard Android datasets, yet we find they suffer accuracy drops of up to 45% when evaluated on previously unseen malware variants from the same family - a scenario where strong generalization would typically be expected. This...

Simulation in Cybersecurity: Understanding Techniques, Applications, and Goals

Modeling and simulation are widely used in cybersecurity research to assess cyber threats, evaluate defense mechanisms, and analyze vulnerabilities. However, the diversity of application areas, the variety of cyberattacks scenarios, and the differing objectives of these simulations makes it...

WordPress Backup Migration 1.3.7 Remote Code Execution

The Backup Migration plugin for WordPress is vulnerable to remote Code execution in all versions up to, and including, 1.3.7 via the /includes/backup-heart.php file. An attacker can control the values passed to an include statement, leveraging that to achieve remote code execution. This...

Zimbra Postjournal Command Execution

CVE-2024-45519 is a vulnerability in Zimbra Collaboration ZCS that allows unauthenticated users to execute commands through the postjournal service. This guide walks you through setting up a lab environment to reproduce the issue and execute the exploit...

Secure and Practical Quantum Digital Signatures

Digital signatures represent a crucial cryptographic asset that must be protected against quantum adversaries. Quantum Digital Signatures QDS can offer solutions that are information-theoretically IT secure and thus immune to quantum attacks. In this work, we analyze three existing practical QDS...

Efficient Mediated Multiparty Semi-Quantum Secret Sharing Protocol Based on Single-Qubit Reordering

Typical multiparty semi-quantum secret sharing MSQSS protocols require the dealer to possess full quantum capabilities, while the classical users usually need to perform three operations. To address this practical limitation, this paper introduces a new mediated MSQSS protocol that enables Alice,...

Tigo Energy CCA Command Injection

This repository contains a proof of concept exploit exploit for CVE‑2025‑7769, a critical remote command injection vulnerability found in Tigo Energy CCA appliances exposing the /cgi-bin/mobileapi endpoint...

An Overview of 7726 User Reports: Uncovering SMS Scams and Scammer Strategies

Mobile network operators implement firewalls to stop illicit messages, but scammers find ways to evade detection. Previous work has looked into SMS texts that are blocked by these firewalls. However, there is little insight into SMS texts that bypass them and reach users. To this end, we...

PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction

Redacting Personally Identifiable Information PII from unstructured text is critical for ensuring data privacy in regulated domains. While earlier approaches have relied on rule-based systems and domain-specific Named Entity Recognition NER models, these methods fail to generalize across formats...

Secure Quantum Key Distribution Via Entangled Quantum Walkers

Quantum Key Distribution QKD is an emerging cryptographic method designed for secure key sharing. Its security is theoretically guaranteed by fundamental principles of quantum mechanics, making it a leading candidate for future communication protocols. Quantum Random Walks QRWs, on the other hand...

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security

The integration of Terrestrial Networks TN and Non-Terrestrial Networks NTN, including 5G Advanced/6G and the Internet of Things IoT technologies, using Low Earth Orbit LEO satellites, high-altitude platforms HAPS, and Unmanned Aerial Vehicles UAVs, is redefining the landscape of global...

Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucination

Timely and effective incident response is key to managing the growing frequency of cyberattacks. However, identifying the right response actions for complex systems is a major technical challenge. A promising approach to mitigate this challenge is to use the security knowledge embedded in large...

RL-MoE: an Image-Based Privacy Preserving Approach in Intelligent Transportation System

The proliferation of AI-powered cameras in Intelligent Transportation Systems ITS creates a severe conflict between the need for rich visual data and the fundamental right to privacy. Existing privacy-preserving mechanisms, such as blurring or encryption, are often insufficient, creating an...

Semi-Supervised Supply Chain Fraud Detection with Unsupervised Pre-Filtering

Detecting fraud in modern supply chains is a growing challenge, driven by the complexity of global networks and the scarcity of labeled data. Traditional detection methods often struggle with class imbalance and limited supervision, reducing their effectiveness in real-world applications. This...

Optimizing IoT Threat Detection with Kolmogorov-Arnold Networks (KANs)

The exponential growth of the Internet of Things IoT has led to the emergence of substantial security concerns, with IoT networks becoming the primary target for cyberattacks. This study examines the potential of Kolmogorov-Arnold Networks KANs as an alternative to conventional machine learning...

Non-Omniscient Backdoor Injection with a Single Poison Sample: Proving the One-Poison Hypothesis for Linear Regression and Linear Classification

Backdoor injection attacks are a threat to machine learning models that are trained on large data collected from untrusted sources; these attacks enable attackers to inject malicious behavior into the model that can be triggered by specially crafted inputs. Prior work has established bounds on th...

A Comparative Performance Evaluation of Kyber, Sntrup761, and FrodoKEM for Post-Quantum Cryptography

Post-quantum cryptography PQC aims to develop cryptographic algorithms that are secure against attacks from quantum computers. This paper compares the leading postquantum cryptographic algorithms, such as Kyber, sntrup761, and FrodoKEM, in terms of their security, performance, and real-world...

Performance and Storage Analysis of CRYSTALS Kyber As a Post Quantum Replacement for RSA and ECC

The steady advancement in quantum computer error correction technology has pushed the current record to 48 stable logical qubits, bringing us closer to machines capable of running Shor's algorithm at scales that threaten RSA and ECC cryptography. While the timeline for developing such quantum...

Exploring Satellite Quantum Key Distribution under Atmospheric Constraints

Satellite Quantum Key Distribution creates a pathway for secure global communication with a level of security that is peerless. However, ground-to-satellite Quantum Key Distribution links are degraded due to the atmospheric turbulence. This paper gives a numerical framework using angular spectrum...

Quantum Circuit Benchmarking on IBM Brisbane: Performance Insights from Superconducting Qubit Models

This paper investigates quantum communication using superconducting qubits, emphasizing the simulation and control of quantum systems via IBM Brisbane quantum processor. We focus on implementing fundamental quantum gates and analyzing the evolution of entangled states, which are essential for...

Enhancing Software Vulnerability Detection through Adaptive Test Input Generation Using Genetic Algorithm

Software vulnerabilities continue to undermine the reliability and security of modern systems, particularly as software complexity outpaces the capabilities of traditional detection methods. This study introduces a genetic algorithm-based method for test input generation that innovatively...

AuthPrint: Fingerprinting Generative Models against Malicious Model Providers

Generative models are increasingly adopted in high-stakes domains, yet current deployments offer no mechanisms to verify the origin of model outputs. We address this gap by extending model fingerprinting techniques beyond the traditional collaborative setting to one where the model provider may a...

Multi-Stage Knowledge-Distilled VGAE and GAT for Robust Controller-Area-Network Intrusion Detection

The Controller Area Network CAN protocol is a standard for in-vehicle communication but remains susceptible to cyber-attacks due to its lack of built-in security. This paper presents a multi-stage intrusion detection framework leveraging unsupervised anomaly detection and supervised graph learnin...

From Split to Share: Private Inference with Distributed Feature Sharing

Cloud-based Machine Learning as a Service MLaaS raises serious privacy concerns when handling sensitive client data. Existing Private Inference PI methods face a fundamental trade-off between privacy and efficiency: cryptographic approaches offer strong protection but incur high computational...

atjiu pybbs 6.0.0 Cross Site Scripting

atjiu pybbs versions 6.0.0 and below suffer from a cross site scripting vulnerability...

SelectiveShield: Lightweight Hybrid Defense against Gradient Leakage in Federated Learning

Federated Learning FL enables collaborative model training on decentralized data but remains vulnerable to gradient leakage attacks that can reconstruct sensitive user information. Existing defense mechanisms, such as differential privacy DP and homomorphic encryption HE, often introduce a...

Secure Development of a Hooking-Based Deception Framework against Keylogging Techniques

Keyloggers remain a serious threat in modern cybersecurity, silently capturing user keystrokes to steal credentials and sensitive information. Traditional defenses focus mainly on detection and removal, which can halt malicious activity but do little to engage or mislead adversaries. In this pape...