Every Keystroke You Make: a Tech-Law Measurement and Analysis of Event Listeners for Wiretapping

The privacy community has a long track record of investigating emerging types of web tracking techniques. Recent work has focused on compliance of web trackers with new privacy laws such as Europe's GDPR and California's CCPA. Despite the growing body of research documenting widespread lack of...

Attackers Strike Back? Not Anymore -- an Ensemble of RL Defenders Awakens for APT Detection

Advanced Persistent Threats APTs represent a growing menace to modern digital infrastructure. Unlike traditional cyberattacks, APTs are stealthy, adaptive, and long-lasting, often bypassing signature-based detection systems. This paper introduces a novel framework for APT detection that unites de...

MalLoc: toward Fine-Grained Android Malicious Payload Localization Via LLMs

The rapid evolution of Android malware poses significant challenges to the maintenance and security of mobile applications apps. Traditional detection techniques often struggle to keep pace with emerging malware variants that employ advanced tactics such as code obfuscation and dynamic behavior...

Training Language Model Agents to Find Vulnerabilities with CTF-Dojo

Large language models LLMs have demonstrated exceptional capabilities when trained within executable runtime environments, notably excelling at software engineering tasks through verified feedback loops. Yet, scalable and generalizable execution-grounded environments remain scarce, limiting...

WhatWeb Scanner 0.6.2

WhatWeb is a next-generation web scanner. WhatWeb recognizes web technologies including content management systems CMS, blogging platforms, statistic/analytics packages, JavaScript libraries, web servers, and embedded devices. WhatWeb has over 1800 plugins, each to recognize something different...

Cloudflare Image Resizing 1.5.6 Remote Code Execution

Cloudflare Image Resizing versions 1.5.6 and below suffer from an unauthenticated remote code execution vulnerability via the restpredispatch hook...

Optimizing Scalar Selection in Elliptic Curve Cryptography Using Differential Evolution for Enhanced Security

Elliptic Curve Cryptography ECC is a fundamental component of modern public-key cryptosystems that enable efficient and secure digital signatures, key exchanges, and encryption. Its core operation, scalar multiplication, denoted as $k \cdot P$, where $P$ is a base point and $k$ is a private scala...

Hashcat Advanced Password Recovery 7.1.1 Binary Release

Hashcat is an advanced GPU hash cracking utility that includes the World's fastest md5crypt, phpass, mscash2 and WPA / WPA2 cracker. It also has the first and only GPGPU-based rule engine, focuses on highly iterated modern hashes, single dictionary-based attacks, and more. This is the binary...

Prescriptive Zero Trust- Assessing the Impact of Zero Trust on Cyber Attack Prevention

Increasingly sophisticated and varied cyber threats necessitate ever improving enterprise security postures. For many organizations today, those postures have a foundation in the Zero Trust Architecture. This strategy sees trust as something an enterprise must not give lightly or assume too...

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 ...

Explainable Ensemble Learning for Graph-Based Malware Detection

Malware detection in modern computing environments demands models that are not only accurate but also interpretable and robust to evasive techniques. Graph neural networks GNNs have shown promise in this domain by modeling rich structural dependencies in graph-based program representations such a...

MADPromptS: Unlocking Zero-Shot Morphing Attack Detection with Multiple Prompt Aggregation

Face Morphing Attack Detection MAD is a critical challenge in face recognition security, where attackers can fool systems by interpolating the identity information of two or more individuals into a single face image, resulting in samples that can be verified as belonging to multiple identities by...

Developing a Transferable Federated Network Intrusion Detection System

Intrusion Detection Systems IDS are a vital part of a network-connected device. In this paper, we develop a deep learning based intrusion detection system that is deployed in a distributed setup across devices connected to a network. Our aim is to better equip deep learning models against unknown...

Chimera: Harnessing Multi-Agent LLMs for Automatic Insider Threat Simulation

Insider threats, which can lead to severe losses, remain a major security concern. While machine learning-based insider threat detection ITD methods have shown promising results, their progress is hindered by the scarcity of high-quality data. Enterprise data is sensitive and rarely accessible,...

A Comparative Analysis of Lightweight Hash Functions Using AVR ATXMega128 and ChipWhisperer

Lightweight hash functions have become important building blocks for security in embedded and IoT systems. A plethora of algorithms have been proposed and standardized, providing a wide range of performance trade-off options for developers to choose from. This paper presents a comparative analysi...

TraceLens: Question-Driven Debugging for Taint Flow Understanding

Taint analysis is a security analysis technique used to track the flow of potentially dangerous data through an application and its dependent libraries. Investigating why certain unexpected flows appear and why expected flows are missing is an important sensemaking process during end-user taint...

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...

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...

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...

Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy

Large Language Models LLMs are gaining traction as a method to generate consensus statements and aggregate preferences in digital democracy experiments. Yet, LLMs may introduce critical vulnerabilities in these systems. Here, we explore the impact of prompt-injection attacks targeting consensus...

BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS

In this paper, we endeavor to address the challenges of backdoor attacks countermeasures in black-box scenarios, thereby fortifying the security of inference under MLaaS. We first categorize backdoor triggers from a new perspective, i.e., their impact on the patched area, and divide them into:...

ASINT: Learning AS-To-Organization Mapping from Internet Metadata

Accurately mapping Autonomous Systems ASNs to their owning or operating organizations underpins Internet measurement research and security applications. Yet existing approaches commonly rely solely on WHOIS or PeeringDB, missing important relationships e.g., cross-regional aliases, parent-child...

Thwart Me If You Can: an Empirical Analysis of Android Platform Armoring against Stalkerware

Stalkerware is a serious threat to individuals' privacy that is receiving increased attention from the security and privacy research communities. Existing works have largely focused on studying leading stalkerware apps, dual-purpose apps, monetization of stalkerware, or the experience of survivor...

"Energon": Unveiling Transformers from GPU Power and Thermal Side-Channels

Transformers have become the backbone of many Machine Learning ML applications, including language translation, summarization, and computer vision. As these models are increasingly deployed in shared Graphics Processing Unit GPU environments via Machine Learning as a Service MLaaS, concerns aroun...

LLM-Assisted Model-Based Fuzzing of Protocol Implementations

Testing network protocol implementations is critical for ensuring the reliability, security, and interoperability of distributed systems. Faults in protocol behavior can lead to vulnerabilities and system failures, especially in real-time and mission-critical applications. A common approach to...

Semantic Encryption: Secure and Effective Interaction with Cloud-Based Large Language Models Via Semantic Transformation

The increasing adoption of Cloud-based Large Language Models CLLMs has raised significant concerns regarding data privacy during user interactions. While existing approaches primarily focus on encrypting sensitive information, they often overlook the logical structure of user inputs. This oversig...

Rtpengine mr13.4.1.1 Injection / Redirection

Rtpengine starting at version mr13.4.1.1 allows for redirection to an attacker-controlled host and insertion of arbitrary RTP packet into active calls...

Strategic Deflection: Defending LLMs from Logit Manipulation

With the growing adoption of Large Language Models LLMs in critical areas, ensuring their security against jailbreaking attacks is paramount. While traditional defenses primarily rely on refusing malicious prompts, recent logit-level attacks have demonstrated the ability to bypass these safeguard...

Program Analysis for High-Value Smart Contract Vulnerabilities: Techniques

A widespread belief in the blockchain security community is that automated techniques are only good for detecting shallow bugs, typically of small value. In this paper, we present the techniques and insights that have led us to repeatable success in automatically discovering high-value smart...

SDD: Self-Degraded Defense against Malicious Fine-Tuning

Open-source Large Language Models LLMs often employ safety alignment methods to resist harmful instructions. However, recent research shows that maliciously fine-tuning these LLMs on harmful data can easily bypass these safeguards. To counter this, we theoretically uncover why malicious fine-tuni...

HumanSAM: Classifying Human-Centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly

Numerous synthesized videos from generative models, especially human-centric ones that simulate realistic human actions, pose significant threats to human information security and authenticity. While progress has been made in binary forgery video detection, the lack of fine-grained understanding ...

Unmasking Synthetic Realities in Generative AI: a Comprehensive Review of Adversarially Robust Deepfake Detection Systems

The rapid advancement of Generative Artificial Intelligence has fueled deepfake proliferation-synthetic media encompassing fully generated content and subtly edited authentic material-posing challenges to digital security, misinformation mitigation, and identity preservation. This systematic revi...

Regression-Aware Continual Learning for Android Malware Detection

Malware evolves rapidly, forcing machine learning ML-based detectors to adapt continuously. With antivirus vendors processing hundreds of thousands of new samples daily, datasets can grow to billions of examples, making full retraining impractical. Continual learning CL has emerged as a scalable...

Rethinking HSM and TPM Security in the Cloud: Real-World Attacks and Next-Gen Defenses

As organizations rapidly migrate to the cloud, the security of cryptographic key management has become a growing concern. Hardware Security Modules HSMs and Trusted Platform Modules TPMs, traditionally seen as the gold standard for securing encryption keys and digital trust, are increasingly...

Enabling Cyber Security Education through Digital Twins and Generative AI

Digital Twins DTs are gaining prominence in cybersecurity for their ability to replicate complex IT Information Technology, OT Operational Technology, and IoT Internet of Things infrastructures, allowing for real time monitoring, threat analysis, and system simulation. This study investigates how...

Zeek 7.0.9

Zeek is a powerful network analysis framework that is much different from the typical IDS you may know. While focusing on network security monitoring, Zeek provides a comprehensive platform for more general network traffic analysis as well. Well grounded in more than 15 years of research, Zeek ha...

SoK: Securing the Final Frontier for Cybersecurity in Space-Based Infrastructure

With the advent of modern technology, critical infrastructure, communications, and national security depend increasingly on space-based assets. These assets, along with associated assets like data relay systems and ground stations, are, therefore, in serious danger of cyberattacks. Strong securit...

TelegAI Cross Site Scripting

TelegAI, a web application for constructing and chatting with AI Characters, is vulnerable to persistent cross site scripting vulnerabilities in its chat component and character container component. An attacker can achieve arbitrary client-side script execution by crafting an AI Character with SV...

Ai2 Insecure Direct Object Reference

Ai2 is a Seattle based non-profit AI research institute. Ai2 provides a playground web application to chat that is susceptible to an insecure direct object reference vulnerability. An attacker can exploit this IDOR to tamper other users' conversation...

Data-Plane Telemetry to Mitigate Long-Distance BGP Hijacks

Poor security of Internet routing enables adversaries to divert user data through unintended infrastructures hijack. Of particular concern -- and the focus of this paper -- are cases where attackers reroute domestic traffic through foreign countries, exposing it to surveillance, bypassing legal...

Quantum Blockchain Survey: Foundations, Trends, and Gaps

Quantum computing poses fundamental risks to classical blockchain systems by undermining widely used cryptographic primitives. In response, two major research directions have emerged: post-quantum blockchains, which integrate quantum-resistant algorithms, and quantum blockchains, which leverage...

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...

MAD-Spear: a Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems

Multi-agent debate MAD systems leverage collaborative interactions among large language models LLMs agents to improve reasoning capabilities. While recent studies have focused on increasing the accuracy and scalability of MAD systems, their security vulnerabilities have received limited attention...

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...

FacialMotionID: Identifying Users of Mixed Reality Headsets Using Abstract Facial Motion Representations

Facial motion capture in mixed reality headsets enables real-time avatar animation, allowing users to convey non-verbal cues during virtual interactions. However, as facial motion data constitutes a behavioral biometric, its use raises novel privacy concerns. With mixed reality systems becoming...

WaFusion: a Wavelet-Enhanced Diffusion Framework for Face Morph Generation

Biometric face morphing poses a critical challenge to identity verification systems, undermining their security and robustness. To address this issue, we propose WaFusion, a novel framework combining wavelet decomposition and diffusion models to generate high-quality, realistic morphed face image...

Crypto-Assisted Graph Degree Sequence Release under Local Differential Privacy

Whitepaper called Crypto-Assisted Graph Degree Sequence Release Under Local Differential Privacy...

"Is It Always Watching? Is It Always Listening?" Exploring Contextual Privacy and Security Concerns toward Domestic Social Robots

Equipped with artificial intelligence AI and advanced sensing capabilities, social robots are gaining interest among consumers in the United States. These robots seem like a natural evolution of traditional smart home devices. However, their extensive data collection capabilities, anthropomorphic...

From Alerts to Intelligence: a Novel LLM-Aided Framework for Host-Based Intrusion Detection

Host-based intrusion detection system HIDS is a key defense component to protect the organizations from advanced threats like Advanced Persistent Threats APT. By analyzing the fine-grained logs with approaches like data provenance, HIDS has shown successes in capturing sophisticated attack traces...

Split Happens: Combating Advanced Threats with Split Learning and Function Secret Sharing

Split Learning SL -- splits a model into two distinct parts to help protect client data while enhancing Machine Learning ML processes. Though promising, SL has proven vulnerable to different attacks, thus raising concerns about how effective it may be in terms of data privacy. Recent works have...