The Age of Sensorial Zero Trust: Why We Can No Longer Trust Our Senses

In a world where deepfakes and cloned voices are emerging as sophisticated attack vectors, organizations require a new security mindset: Sensorial Zero Trust. This article presents a scientific analysis of the need to systematically doubt information perceived through the senses, establishing...

TestSSL 3.2.1

testssl.sh is a free command line tool which checks a server's service on any port for the support of TLS/SSL ciphers, protocols as well as recent cryptographic flaws, and much more. It is written in pure bash, makes only use of standard Unix utilities, openssl and last but not least bash sockets...

TestSSL 3.0.10

testssl.sh is a free command line tool which checks a server's service on any port for the support of TLS/SSL ciphers, protocols as well as recent cryptographic flaws, and much more. It is written in pure bash, makes only use of standard Unix utilities, openssl and last but not least bash sockets...

WordPress Custom Login and Signup Widget 1.0 Remote Code Execution

WordPress Custom Login and Signup Widget plugin versions 1.0 and below suffer from a remote code execution vulnerability...

CISA: Iranian Cyber Actors May Target Vulnerable US Networks and Entities of Interest

CISA, the Federal Bureau of Investigation FBI, the Department of Defense Cyber Crime Center DC3, and the National Security Agency NSA published Iranian Cyber Actors May Target Vulnerable US Networks and Entities of Interest. This joint fact sheet details the need for increased vigilance for...

ZigStrike 2.0

ZigStrike is a robust shellcode loader developed in Zig, offering a variety of injection techniques and anti-sandbox features. It leverages compile-time capabilities for efficient shellcode allocation, demonstrating proven success in bypassing advanced security solutions. ZigStrike includes a...

SkyEye: When Your Vision Reaches beyond IAM Boundary Scope in AWS Cloud

In recent years, cloud security has emerged as a primary concern for enterprises due to the increasing trend of migrating internal infrastructure and applications to cloud environments. This shift is driven by the desire to reduce the high costs and maintenance fees associated with traditional...

WATCHDOG: an Ontology-AWare Risk AssessmenT ApproaCH Via Object-Oriented DisruptiOn Graphs

When considering risky events or actions, we must not downplay the role of involved objects: a charged battery in our phone averts the risk of being stranded in the desert after a flat tyre, and a functional firewall mitigates the risk of a hacker intruding the network. The Common Ontology of Val...

Nuclei 3.4.5

Nuclei is a modern, high-performance vulnerability scanner that leverages simple YAML-based templates. It empowers you to design custom vulnerability detection scenarios that mimic real-world conditions, leading to zero false positives...

American Fuzzy Lop plus plus 4.33c

Google's American Fuzzy Lop is a brute-force fuzzer coupled with an exceedingly simple but rock-solid instrumentation-guided genetic algorithm. afl++ is a superior fork to Google's afl. It has more speed, more and better mutations, more and better instrumentation, custom module support, etc...

Linear Stability Analysis for a System of Singular Amplitude Equations Arising in Biomorphology

We study linear stability of exponential periodic solutions of a system of singular amplitude equations associated with convective Turing bifurcation in the presence of conservation laws, as arises in modern biomorphology models, binary fluids, and elsewhere. Consisting of a complex Ginzburg-Land...

Reconstructing Intelligible Speech from the Pressure Sensor Data in HVACs

Pressure sensors are an integrated component of modern Heating, Ventilation, and Air Conditioning HVAC systems. As these pressure sensors operate within the 0-10 Pa range, support high sampling frequencies of 0.5-2 kHz, and are often placed close to human proximity, they can be used to eavesdrop ...

Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey

Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and structural inequalities. Unfortunately, most work in this space provides partial treatment, often constrained by two...

One Video to Steal Them All: 3D-Printing IP Theft through Optical Side-Channels

The 3D printing industry is rapidly growing and increasingly adopted across various sectors including manufacturing, healthcare, and defense. However, the operational setup often involves hazardous environments, necessitating remote monitoring through cameras and other sensors, which opens the do...

Vite Arbitrary File Read

Vite suffers from an arbitrary file read vulnerability. Versions prior to 6.2.3, 6.1.2, 6.0.12, 5.4.15, and 4.5.10 are affected...

Reliability Analysis of Smart Contract Execution Architectures: a Comparative Simulation Study

The industrial market continuously needs reliable solutions to secure autonomous systems. Especially as these systems become more complex and interconnected, reliable security solutions are becoming increasingly important. One promising solution to tackle this challenge is using smart contracts...

Consumer Beware! Exploring Data Brokers' CCPA Compliance

Data brokers collect and sell the personal information of millions of individuals, often without their knowledge or consent. The California Consumer Privacy Act CCPA grants consumers the legal right to request access to, or deletion of, their data. To facilitate these requests, California maintai...

Unifying Communication Paradigms in Delegated Quantum Computing

Delegated quantum computing DQC allows clients with low quantum capabilities to outsource computations to a server hosting a quantum computer. This process is typically envisioned within the measurement-based quantum computing framework, as it naturally facilitates blindness of inputs and...

Pseudo-Equilibria, Or: How to Stop Worrying about Crypto and Just Analyze the Game

Whitepaper called Pseudo-Equilibria, Or: How To Stop Worrying About Crypto And Just Analyze The Game...

Under the Hood of BlotchyQuasar: DLL-Based RAT Campaigns against Latin America

A sophisticated malspam campaign was recently uncovered targeting Latin American countries, with a particular focus on Brazil. This operation utilizes a highly deceptive phishing email to trick users into executing a malicious MSI file, initiating a multi-stage infection. The core of the attack...

ARMOR: Robust Reinforcement Learning-Based Control for UAVs under Physical Attacks

Unmanned Aerial Vehicles UAVs depend on onboard sensors for perception, navigation, and control. However, these sensors are susceptible to physical attacks, such as GPS spoofing, that can corrupt state estimates and lead to unsafe behavior. While reinforcement learning RL offers adaptive control...

Advancing Jailbreak Strategies: a Hybrid Approach to Exploiting LLM Vulnerabilities and Bypassing Modern Defenses

The advancement of Pre-Trained Language Models PTLMs and Large Language Models LLMs has led to their widespread adoption across diverse applications. Despite their success, these models remain vulnerable to attacks that exploit their inherent weaknesses to bypass safety measures. Two primary...

Mobius Forensic Toolkit 2.16

Mobius Forensic Toolkit is a forensic framework written in Python/GTK that manages cases and case items, providing an abstract interface for developing extensions. Cases and item categories are defined using XML files for easy integration with other tools...

Adversarial Threats in Quantum Machine Learning: a Survey of Attacks and Defenses

Quantum Machine Learning QML integrates quantum computing with classical machine learning, primarily to solve classification, regression and generative tasks. However, its rapid development raises critical security challenges in the Noisy Intermediate-Scale Quantum NISQ era. This chapter examines...

Practical and Accurate Local Edge Differentially Private Graph Algorithms

Whitepaper called Practical And Accurate Local Edge Differentially Private Graph Algorithms...

IDGraphs: Intrusion Detection and Analysis Using Stream Compositing

Traffic anomalies and attacks are commonplace in today's networks and identifying them rapidly and accurately is critical for large network operators. For a statistical intrusion detection system IDS, it is crucial to detect at the flow-level for accurate detection and mitigation. However, existi...

Boosting Generative Adversarial Transferability with Self-Supervised Vision Transformer Features

The ability of deep neural networks DNNs come from extracting and interpreting features from the data provided. By exploiting intermediate features in DNNs instead of relying on hard labels, we craft adversarial perturbation that generalize more effectively, boosting black-box transferability...

Balancing Privacy and Utility in Correlated Data: a Study of Bayesian Differential Privacy

Privacy risks in differentially private DP systems increase significantly when data is correlated, as standard DP metrics often underestimate the resulting privacy leakage, leaving sensitive information vulnerable. Given the ubiquity of dependencies in real-world databases, this oversight poses a...

PhishKey: a Novel Centroid-Based Approach for Enhanced Phishing Detection Using Adaptive HTML Component Extraction

Phishing attacks pose a significant cybersecurity threat, evolving rapidly to bypass detection mechanisms and exploit human vulnerabilities. This paper introduces PhishKey to address the challenges of adaptability, robustness, and efficiency. PhishKey is a novel phishing detection method using...

TEMPEST-LoRa: Cross-Technology Covert Communication

Electromagnetic EM covert channels pose significant threats to computer and communications security in air-gapped networks. Previous works exploit EM radiation from various components e.g., video cables, memory buses, CPUs to secretly send sensitive information. These approaches typically require...

CyGym: a Simulation-Based Game-Theoretic Analysis Framework for Cybersecurity

We introduce a novel cybersecurity encounter simulator between a network defender and an attacker designed to facilitate game-theoretic modeling and analysis while maintaining many significant features of real cyber defense. Our simulator, built within the OpenAI Gym framework, incorporates...

On the Feasibility of Poisoning Text-To-Image AI Models Via Adversarial Mislabeling

Today's text-to-image generative models are trained on millions of images sourced from the Internet, each paired with a detailed caption produced by Vision-Language Models VLMs. This part of the training pipeline is critical for supplying the models with large volumes of high-quality image-captio...

Inside Job: Defending Kubernetes Clusters against Network Misconfigurations

Kubernetes has emerged as the de facto standard for container orchestration. Unfortunately, its increasing popularity has also made it an attractive target for malicious actors. Despite extensive research on securing Kubernetes, little attention has been paid to the impact of network configuratio...

Memory Safe Languages: Reducing Vulnerabilities in Modern Software Development

This report, released by NSA and CISA, acknowledges the challenges and aims to provide a balanced view of the state of MSLs. Reducing memory safety vulnerabilities requires understanding when MSLs are appropriate, knowing how to adopt them effectively, and recognizing where non-MSLs remain...

WordPress Simple User Registration 6.3 Privilege Escalation

WordPress Simple User Registration plugin versions 6.3 and below suffer from an unauthenticated privilege escalation vulnerability. This is due to insufficient restrictions on user meta values that can be supplied during registration. This makes it possible for unauthenticated attackers to regist...

httpx 1.7.0 Denial of Service / Out-Of-Bounds Read

httpx version 1.7.0 suffers from an out-of-bounds read in trimTitleTags due to a missing bounds check when slicing the title string...

The Discovery, Disclosure, and Investigation of CVE-2024-25825

CVE-2024-25825 is a vulnerability found in FydeOS. This thesis describes its discovery, disclosure, and its further investigation in connection to a nation state actor. The vulnerability is CWE-1392: Use of Default Credentials, CWE-1393: Use of Default Password, and CWE-258: Empty Password in...

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs

Large Language Models LLMs for code generation i.e., Code LLMs have demonstrated impressive capabilities in AI-assisted software development and testing. However, recent studies have shown that these models are prone to generating vulnerable or even malicious code under adversarial settings...

MacOS Sandbox Escape via Double Free in coreaudiod/CoreAudio Framework

MacOS suffers from a sandbox escape vulnerability due to a double-free condition in coreaudiod/CoreAudio Framework...

Counterfactual Influence As a Distributional Quantity

Machine learning models are known to memorize samples from their training data, raising concerns around privacy and generalization. Counterfactual self-influence is a popular metric to study memorization, quantifying how the model's prediction for a sample changes depending on the sample's...

AppleAVD AV1_Syntax::Parse_Header Out-Of-Bounds Read

There is an issue in AppleAVD kernel extension with decoding AV1 video files that could potentially be used to read out-of bound data or potentially cause a kernel crash when rendering a malformed video file. The issue was observed on macOS Sonoma 14.5...

AppleAVD AV1_Syntax::Parse_Header Integer Underflow / Out-Of-Bounds Read

There is an issue in AppleAVD kernel extension with decoding AV1 video files that could potentially be used to read out-of bound data or potentially cause a kernel crash when rendering a malformed video file. The issue was observed on macOS Sonoma 14.5...

Don'T Hash Me like That: Exposing and Mitigating Hash-Induced Unfairness in Local Differential Privacy

Local differential privacy LDP has become a widely accepted framework for privacy-preserving data collection. In LDP, many protocols rely on hash functions to implement user-side encoding and perturbation. However, the security and privacy implications of hash function selection have not been...

Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-To-Peer Learning

The growing adoption of Artificial Intelligence AI in Internet of Things IoT ecosystems has intensified the need for personalized learning methods that can operate efficiently and privately across heterogeneous, resource-constrained devices. However, enabling effective personalized learning in...

On the Impact of Sybil-Based Attacks on Mobile Crowdsensing for Transportation

Mobile Crowd-Sensing MCS enables users with personal mobile devices PMDs to gain information on their surroundings. Users collect and contribute data on different phenomena using their PMD sensors, and the MCS system processes this data to extract valuable information for end users. Navigation...

PrivacyGo: Privacy-Preserving Ad Measurement with Multidimensional Intersection

This paper tackles the challenging and practical problem of multi-identifier private user profile matching for privacy-preserving ad measurement, a cornerstone of modern advertising analytics. We introduce a comprehensive cryptographic framework leveraging reversed Oblivious Pseudorandom Function...

Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS

Adversarial attacks, wherein slight inputs are carefully crafted to mislead intelligent models, have attracted increasing attention. However, a critical gap persists between theoretical advancements and practical application, particularly in structured data like network traffic, where...

Universal and Efficient Detection of Adversarial Data through Nonuniform Impact on Network Layers

Deep Neural Networks DNNs are notoriously vulnerable to adversarial input designs with limited noise budgets. While numerous successful attacks with subtle modifications to original input have been proposed, defense techniques against these attacks are relatively understudied. Existing defense...

SV-LLM: an Agentic Approach for SoC Security Verification Using Large Language Models

Ensuring the security of complex system-on-chips SoCs designs is a critical imperative, yet traditional verification techniques struggle to keep pace due to significant challenges in automation, scalability, comprehensiveness, and adaptability. The advent of large language models LLMs, with their...

Leaner Training, Lower Leakage: Revisiting Memorization in LLM Fine-Tuning with LoRA

Memorization in large language models LLMs makes them vulnerable to data extraction attacks. While pre-training memorization has been extensively studied, fewer works have explored its impact in fine-tuning, particularly for LoRA fine-tuning, a widely adopted parameter-efficient method. In this...