ArtistAuditor: Auditing Artist Style Pirate in Text-To-Image Generation Models

Text-to-image models based on diffusion processes, such as DALL-E, Stable Diffusion, and Midjourney, are capable of transforming texts into detailed images and have widespread applications in art and design. As such, amateur users can easily imitate professional-level paintings by collecting an...

Adversary-Augmented Simulation for Fairness Evaluation and Defense in Hyperledger Fabric

This paper presents an adversary model and a simulation framework specifically tailored for analyzing attacks on distributed systems composed of multiple distributed protocols, with a focus on assessing the security of blockchain networks. Our model classifies and constrains adversarial actions...

Omnissa Unified Access Gateway (UAG) CORS Bypass

A cross-origin resource sharing bypass vulnerability was privately reported in Omnissa Unified Access Gateway UAG. An update is available to remediate this vulnerability in impacted versions of the product. The fixed version is 2503...

Security-First AI: Foundations for Robust and Trustworthy Systems

The conversation around artificial intelligence AI often focuses on safety, transparency, accountability, alignment, and responsibility. However, AI security i.e., the safeguarding of data, models, and pipelines from adversarial manipulation underpins all of these efforts. This manuscript posits...

CISA: Key Secure by Demand Elements for Operational Technology Fact Sheet

This fact sheet addresses key elements for operational technology OT owners and operators to consider when purchasing digital products that automate physical processes, e.g. programmable logic controllers PLCs, human-machine interfaces HMIs, and remote terminal units RTUs. CISA strongly advises...

FoxCMS 1.2.5 Remote Code Execution

FoxCMS version 1.2.5 proof of concept remote code execution exploit...

OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques

This technical report presents a comprehensive analysis of malware classification using OpCode sequences. Two distinct approaches are evaluated: traditional machine learning using n-gram analysis with Support Vector Machine SVM, K-Nearest Neighbors KNN, and Decision Tree classifiers; and a deep...

EXAM: Exploiting Exclusive System-Level Cache in Apple M-Series SoCs for Enhanced Cache Occupancy Attacks

Cache occupancy attacks exploit the shared nature of cache hierarchies to infer a victim's activities by monitoring overall cache usage, unlike access-driven cache attacks that focus on specific cache lines or sets. There exists some prior work that target the last-level cache LLC of Intel...

WordPress Custom CSS, JS and PHP 2.4.1 CSRF / Remote Code Execution

WordPress Custom CSS, JS and PHP versions 2.4.1 and below suffer from a cross site request forgery vulnerability that leads to remote code execution...

Overlapping Error Correction Codes on Two-Dimensional Structures

The growing demand for highly reliable communication systems drives the research and development of algorithms that identify and correct errors during data transmission and storage. This need becomes even more critical in hard-to-access or sensitive systems, such as those used in space...

I Know What You Bought Last Summer: Investigating User Data Leakage in E-Commerce Platforms

In the digital age, e-commerce has transformed the way consumers shop, offering convenience and accessibility. Nevertheless, concerns about the privacy and security of personal information shared on these platforms have risen. In this work, we investigate user privacy violations, noting the risks...

The Chronicles of Foundation AI for Forensics of Multi-Agent Provenance

Provenance is the chronology of things, resonating with the fundamental pursuit to uncover origins, trace connections, and situate entities within the flow of space and time. As artificial intelligence advances towards autonomous agents capable of interactive collaboration on complex tasks, the...

The Evolution of Zero Trust Architecture (ZTA) from Concept to Implementation

Zero Trust Architecture ZTA is one of the paradigm changes in cybersecurity, from the traditional perimeter-based model to perimeterless. This article studies the core concepts of ZTA, its beginning, a few use cases and future trends. Emphasising the always verify and least privilege access, some...

ARCeR: an Agentic RAG for the Automated Definition of Cyber Ranges

The growing and evolving landscape of cybersecurity threats necessitates the development of supporting tools and platforms that allow for the creation of realistic IT environments operating within virtual, controlled settings as Cyber Ranges CRs. CRs can be exploited for analyzing vulnerabilities...

GLPI SQL Injection

GLPI suffers from an unauthenticated remote SQL injection vulnerability. This issue is fixed in version 10.0.18...

Advanced MST3 Encryption Scheme Based on Generalized Suzuki 2-Groups

This article presents a method for enhancing the encryption algorithm in the MST3 cryptosystem for generalized Suzuki 2-groups. The conventional MST cryptosystem based on Suzuki groups utilizes logarithmic signatures LS restricted to the center of the group, resulting in an expansive array of...

Bypassing Prompt Injection and Jailbreak Detection in LLM Guardrails

Large Language Models LLMs guardrail systems are designed to protect against prompt injection and jailbreak attacks. However, they remain vulnerable to evasion techniques. We demonstrate two approaches for bypassing LLM prompt injection and jailbreak detection systems via traditional character...

The Digital Cybersecurity Expert: How Far Have We Come?

The increasing deployment of large language models LLMs in the cybersecurity domain underscores the need for effective model selection and evaluation. However, traditional evaluation methods often overlook specific cybersecurity knowledge gaps that contribute to performance limitations. To addres...

On the Feasibility of Using MultiModal LLMs to Execute AR Social Engineering Attacks

Augmented Reality AR and Multimodal Large Language Models LLMs are rapidly evolving, providing unprecedented capabilities for human-computer interaction. However, their integration introduces a new attack surface for social engineering. In this paper, we systematically investigate the feasibility...

Provable Secure Steganography Based on Adaptive Dynamic Sampling

The security of private communication is increasingly at risk due to widespread surveillance. Steganography, a technique for embedding secret messages within innocuous carriers, enables covert communication over monitored channels. Provably Secure Steganography PSS is state of the art for making...

From Data Behavior to Code Analysis: a Multimodal Study on Security and Privacy Challenges in Blockchain-Based DApp

The recent proliferation of blockchain-based decentralized applications DApp has catalyzed transformative advancements in distributed systems, with extensive deployments observed across financial, entertainment, media, and cybersecurity domains. These trustless architectures, characterized by the...

Privacy-Preserving CNN Training with Transfer Learning: Two Hidden Layers

Whitepaper called Privacy-Preserving CNN Training With Transfer Learning: Two Hidden Layers...

ZkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing

Whitepaper called ZkVC: Fast Zero-Knowledge Proof For Private And Verifiable Computing...

ZkFuzz: Foundation and Framework for Effective Fuzzing of Zero-Knowledge Circuits

Zero-knowledge ZK circuits enable privacy-preserving computations and are central to many cryptographic protocols. Systems like Circom simplify ZK development by combining witness computation and circuit constraints in one program. However, even small errors can compromise security of ZK programs...

PCDiff: Proactive Control for Ownership Protection in Diffusion Models with Watermark Compatibility

With the growing demand for protecting the intellectual property IP of text-to-image diffusion models, we propose PCDiff -- a proactive access control framework that redefines model authorization by regulating generation quality. At its core, PCDIFF integrates a trainable fuser module and...

OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine

As Ethereum continues to thrive, the Ethereum Virtual Machine EVM has become the cornerstone powering tens of millions of active smart contracts. Intuitively, security issues in EVMs could lead to inconsistent behaviors among smart contracts or even denial-of-service of the entire blockchain...

Watermarking Needs Input Repetition Masking

Whitepaper called Watermarking Needs Input Repetition Masking...

InjectLab: a Tactical Framework for Adversarial Threat Modeling against Large Language Models

Large Language Models LLMs are changing the way people interact with technology. Tools like ChatGPT and Claude AI are now common in business, research, and everyday life. But with that growth comes new risks, especially prompt-based attacks that exploit how these models process language. InjectLa...

Langflow Code Injection

Langflow versions prior to 1.3.0 are susceptible to code injection in the /api/v1/validate/code endpoint. A remote and unauthenticated attacker can send crafted HTTP requests to execute arbitrary code...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

Naming Is Framing: How Cybersecurity'S Language Problems Are Repeating in AI Governance

Language is not neutral; it frames understanding, structures power, and shapes governance. This paper argues that misnomers like cybersecurity and artificial intelligence AI are more than semantic quirks; they carry significant governance risks by obscuring human agency, inflating expectations, a...

A Scalable Framework for Post-Quantum Authentication in Public Key Infrastructures

This work explores the performance and scalability of a hierarchical certificate authority framework with automated certificate issuance employing post-quantum cryptographic PQC signature algorithms. The system is designed for compatibility with both classical and PQC algorithms, promoting...

Network-Centric Countermeasures against Integrated Sensing Enabled Jamming Adversaries

Recent developments in Integrated Sensing and Communication have led to new adversarial models in wireless security through Integrated Sensing and Jamming ISAJ adversaries. ISAJ adversaries, owing to their sensing capabilities, are known to inject jamming energy over the victim's frequency band,...

Codes over Finite Ring $\Mathbb{Z}_k$, MacWilliams Identity and Theta Function

Whitepaper called Codes Over Finite Ring $\MathbbZk$, MacWilliams Identity And Theta Function...

Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients

Whitepaper called Local Data Quantity-Aware Weighted Averaging For Federated Learning With Dishonest Clients...

Topological Analysis of Mixer Activities in the Bitcoin Network

Cryptocurrency users increasingly rely on obfuscation techniques such as mixers, swappers, and decentralised or no-KYC exchanges to protect their anonymity. However, at the same time, these services are exploited by criminals to conceal and launder illicit funds. Among obfuscation services, mixer...

Accountable Liveness

Safety and liveness are the two classical security properties of consensus protocols. Recent works have strengthened safety with accountability: should any safety violation occur, a sizable fraction of adversary nodes can be proven to be protocol violators. This paper studies to what extent...

ISPConfig Code Injection

ISPConfig versions prior to 3.2.11p1 suffer from a code injection vulnerability...

How to Enhance Downstream Adversarial Robustness (Almost) without Touching the Pre-Trained Foundation Model?

With the rise of powerful foundation models, a pre-training-fine-tuning paradigm becomes increasingly popular these days: A foundation model is pre-trained using a huge amount of data from various sources, and then the downstream users only need to fine-tune and adapt it to specific downstream...

MULTI-LF: a Unified Continuous Learning Framework for Real-Time DDoS Detection in Multi-Environment Networks

Detecting Distributed Denial of Service DDoS attacks in Multi-Environment M-En networks presents significant challenges due to diverse malicious traffic patterns and the evolving nature of cyber threats. Existing AI-based detection systems struggle to adapt to new attack strategies and lack...

Improved MST3 Encryption Scheme Based on Small Ree Groups

This article presents an encryption scheme based on the small Ree groups. We propose utilizing the small Ree group structure to enhance the overall security parameters of the encryption scheme. By extending the logarithmic signature to encompass the entire group and modifying the encryption...

From Cyber Threat to Data Shield: Constructing Provably Secure File Erasure with Repurposed Ransomware Cryptography

Ransomware has emerged as a persistent cybersecurity threat,leveraging robust encryption schemes that often remain unbroken even after public disclosure of source code. Motivated by the technical resilience of such mechanisms, this paper presents SEER Secure and Efficient Encryption-based Erasure...

Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation

Differentially Private Synthetic Data Generation DP-SDG is a key enabler of private and secure tabular-data sharing, producing artificial data that carries through the underlying statistical properties of the input data. This typically involves adding carefully calibrated statistical noise to...

X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents

Multi-turn interactions with language models LMs pose critical safety risks, as harmful intent can be strategically spread across exchanges. Yet, the vast majority of prior work has focused on single-turn safety, while adaptability and diversity remain among the key challenges of multi-turn...

RAID: an In-Training Defense against Attribute Inference Attacks in Recommender Systems

In various networks and mobile applications, users are highly susceptible to attribute inference attacks, with particularly prevalent occurrences in recommender systems. Attackers exploit partially exposed user profiles in recommendation models, such as user embeddings, to infer private attribute...

WalletProbe: a Testing Framework for Browser-Based Cryptocurrency Wallet Extensions

Serving as the first touch point for users to the cryptocurrency world, cryptocurrency wallets allow users to manage, receive, and transmit digital assets on blockchain networks and interact with emerging decentralized finance DeFi applications. Unfortunately, cryptocurrency wallets have always...

Clustering and Analysis of User Behaviour in Blockchain: a Case Study of Planet IX

Decentralised applications dApps that run on public blockchains have the benefit of trustworthiness and transparency as every activity that happens on the blockchain can be publicly traced through the transaction data. However, this introduces a potential privacy problem as this data can be track...

Cartesian Merkle Tree

This paper introduces the Cartesian Merkle Tree, a deterministic data structure that combines the properties of a Binary Search Tree, a Heap, and a Merkle tree. The Cartesian Merkle Tree supports insertions, updates, and removals of elements in $O\log n$ time, requires $n$ space, and enables...

WordPress SoftClever Limited Sync Posts 1.0 Shell Upload

WordPress SoftClever Limited Sync Posts plugin version 1.0 suffers from a remote shell upload vulnerability...

On-Device Watermarking: a Socio-Technical Imperative for Authenticity in the Age of Generative AI

As generative AI models produce increasingly realistic output, both academia and industry are focusing on the ability to detect whether an output was generated by an AI model or not. Many of the research efforts and policy discourse are centered around robust watermarking of AI outputs. While...