Identifying Key Expert Actors in Cybercrime Forums Based on Their Technical Expertise

The advent of Big Data has made the collection and analysis of cyber threat intelligence challenging due to its volume, leading research to focus on identifying key threat actors; yet these studies have failed to consider the technical expertise of these actors. Expertise, especially towards...

Sylva: Tailoring Personalized Adversarial Defense in Pre-Trained Models Via Collaborative Fine-Tuning

Whitepaper called Sylva: Tailoring Personalized Adversarial Defense In Pre-Trained Models Via Collaborative Fine-Tuning...

When Blockchain Meets Crawlers: Real-Time Market Analytics in Solana NFT Markets

In this paper, we design and implement a web crawler system based on the Solana blockchain for the automated collection and analysis of market data for popular non-fungible tokens NFTs on the chain. Firstly, the basic information and transaction data of popular NFTs on the Solana chain are...

Mind the Gap: a Practical Attack on GGUF Quantization

With the increasing size of frontier LLMs, post-training quantization has become the standard for memory-efficient deployment. Recent work has shown that basic rounding-based quantization schemes pose security risks, as they can be exploited to inject malicious behaviors into quantized models tha...

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation

Federated Learning FL enables collaborative machine learning across decentralized data sources without sharing raw data. It offers a promising approach to privacy-preserving AI. However, FL remains vulnerable to adversarial threats from malicious participants, referred to as Byzantine clients, wh...

Youpot Worm Honeypot

Youpot listens on all TCP ports and connects to the attacker IP on the same port they connected to you on, proxying traffic back at them. This allows you to watch the attacker attack themselves. This project was presented at Confidence 2025...

Heterogeneous Secure Transmissions in IRS-Assisted NOMA Communications: CO-GNN Approach

Intelligent Reflecting Surfaces IRS enhance spectral efficiency by adjusting reflection phase shifts, while Non-Orthogonal Multiple Access NOMA increases system capacity. Consequently, IRS-assisted NOMA communications have garnered significant research interest. However, the passive nature of the...

Combining Threat Intelligence with IoT Scanning to Predict Cyber Attack

While the Web has become a global platform for communication, malicious actors, including hackers and hacktivist groups, often disseminate ideological content and coordinate activities through the "Dark Web", an obscure counterpart of the conventional web. Presently, challenges such as informatio...

Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference

Neural network inference typically operates on raw input data, increasing the risk of exposure during preprocessing and inference. Moreover, neural architectures lack efficient built-in mechanisms for directly authenticating input data. This work introduces a novel encryption method for ensuring...

Tarallo: Evading Behavioral Malware Detectors in the Problem Space

Machine learning algorithms can effectively classify malware through dynamic behavior but are susceptible to adversarial attacks. Existing attacks, however, often fail to find an effective solution in both the feature and problem spaces. This issue arises from not addressing the intrinsic...

How Stealthy Is Stealthy? Studying the Efficacy of Black-Box Adversarial Attacks in the Real World

Deep learning systems, critical in domains like autonomous vehicles, are vulnerable to adversarial examples crafted inputs designed to mislead classifiers. This study investigates black-box adversarial attacks in computer vision. This is a realistic scenario, where attackers have query-only acces...

Differentially Private Distribution Release of Gaussian Mixture Models Via KL-Divergence Minimization

Gaussian Mixture Models GMMs are widely used statistical models for representing multi-modal data distributions, with numerous applications in data mining, pattern recognition, data simulation, and machine learning. However, recent research has shown that releasing GMM parameters poses significan...

Measuring Likelihood in Cybersecurity

In cybersecurity risk is commonly measured by impact and probability, the former is objectively measured based on the consequences from the use of technology to obtain business gains, or by achieving business objectives. The latter has been measured, in sectors such as financial or insurance, bas...

Decentralized COVID-19 Health System Leveraging Blockchain

With the development of the Internet, the amount of data generated by the medical industry each year has grown exponentially. The Electronic Health Record EHR manages the electronic data generated during the user's treatment process. Typically, an EHR data manager belongs to a medical institution...

SAP GuiXT Scripting Issues

Multiple vulnerabilities have been discovered in SAP GuiXT scripting, which could allow an attacker to perform remote code execution, steal NTLM hashes, conduct client-side request forgery attacks, and launch denial of service DoS attacks. These vulnerabilities arise from insecure design principl...

Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack

Membership inference attack MIA has become one of the most widely used and effective methods for evaluating the privacy risks of machine learning models. These attacks aim to determine whether a specific sample is part of the model's training set by analyzing the model's output. While traditional...

Poster: FedBlockParadox -- a Framework for Simulating and Securing Decentralized Federated Learning

A significant body of research in decentralized federated learning focuses on combining the privacy-preserving properties of federated learning with the resilience and transparency offered by blockchain-based systems. While these approaches are promising, they often lack flexible tools to evaluat...

Samsung S24 MP3 Decoder Out-Of-Bounds Read

There is an out-of-bounds read in the MP3 decoder in the Samsung S24. The function smp123djointstereov1 indexes into several tables for decoding, and does not check that the index is valid, allowing the tables to be read out of bounds. It may be possible to use this bug to bypass ASLR, as loading...

Robust Anti-Backdoor Instruction Tuning in LVLMs

Large visual language models LVLMs have demonstrated excellent instruction-following capabilities, yet remain vulnerable to stealthy backdoor attacks when finetuned using contaminated data. Existing backdoor defense techniques are usually developed for single-modal visual or language models under...

BadReward: Clean-Label Poisoning of Reward Models in Text-To-Image RLHF

Reinforcement Learning from Human Feedback RLHF is crucial for aligning text-to-image T2I models with human preferences. However, RLHF's feedback mechanism also opens new pathways for adversaries. This paper demonstrates the feasibility of hijacking T2I models by poisoning a small fraction of...

VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents

Computer-Use Agents CUAs with full system access enable powerful task automation but pose significant security and privacy risks due to their ability to manipulate files, access user data, and execute arbitrary commands. While prior work has focused on browser-based agents and HTML-level attacks,...

Samsung S24 VC1 Decoder Out-Of-Bounds Write

There is an out-of-bounds write to a heap buffer in the Samsung S24 VC1 decoder. The function svc1drrfrm can write outside of the allocated frame buffers in several locations due to incorrect calculations of buffer offsets...

CyberGym: Evaluating AI Agents' Cybersecurity Capabilities with Real-World Vulnerabilities at Scale

Large language model LLM agents are becoming increasingly skilled at handling cybersecurity tasks autonomously. Thoroughly assessing their cybersecurity capabilities is critical and urgent, given the high stakes in this domain. However, existing benchmarks fall short, often failing to capture...

BitBypass: a New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage

The inherent risk of generating harmful and unsafe content by Large Language Models LLMs, has highlighted the need for their safety alignment. Various techniques like supervised fine-tuning, reinforcement learning from human feedback, and red-teaming were developed for ensuring the safety alignme...

Request-Baskets Server-Side Request Forgery

Request-Baskets versions up to 1.2.1 proof of concept server-side request forgery exploit...

Singularity Blockchain Key Management Via Non-Custodial Key Management

web3 wallets are key to managing user identity on blockchain. The main purpose of a web3 wallet application is to manage the private key for the user and provide an interface to interact with the blockchain. The key management scheme KMS used by the wallet to store and recover the private key can...

Policy As Code, Policy As Type

Policies are designed to distinguish between correct and incorrect actions; they are types. But badly typed actions may cause not compile errors, but financial and reputational harm We demonstrate how even the most complex ABAC policies can be expressed as types in dependently typed languages suc...

ETDI: Mitigating Tool Squatting and Rug Pull Attacks in Model Context Protocol (MCP) by Using OAuth-Enhanced Tool Definitions and Policy-Based Access Control

The Model Context Protocol MCP plays a crucial role in extending the capabilities of Large Language Models LLMs by enabling integration with external tools and data sources. However, the standard MCP specification presents significant security vulnerabilities, notably Tool Poisoning and Rug Pull...

Silence Is Golden: Leveraging Adversarial Examples to Nullify Audio Control in LDM-Based Talking-Head Generation

Advances in talking-head animation based on Latent Diffusion Models LDM enable the creation of highly realistic, synchronized videos. These fabricated videos are indistinguishable from real ones, increasing the risk of potential misuse for scams, political manipulation, and misinformation. Hence,...

Peyara Remote Mouse 1.0.1 Unauthenticated Arbitrary File Upload

Peyara Remote Mouse version 1.0.1 suffers from an unauthenticated arbitrary file upload vulnerability...

Which Factors Make Code LLMs More Vulnerable to Backdoor Attacks? A Systematic Study

Code LLMs are increasingly employed in software development. However, studies have shown that they are vulnerable to backdoor attacks: when a trigger a specific input pattern appears in the input, the backdoor will be activated and cause the model to generate malicious outputs. Researchers have...

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models

Model extraction attacks aim to replicate the functionality of a black-box model through query access, threatening the intellectual property IP of machine-learning-as-a-service MLaaS providers. Defending against such attacks is challenging, as it must balance efficiency, robustness, and utility...

Predictive-CSM: Lightweight Fragment Security for 6LoWPAN IoT Networks

Fragmentation is a routine part of communication in 6LoWPAN-based IoT networks, designed to accommodate small frame sizes on constrained wireless links. However, this process introduces a critical vulnerability fragments are typically stored and processed before their legitimacy is confirmed,...

SMOTE-DP: Improving Privacy-Utility Tradeoff with Synthetic Data

Privacy-preserving data publication, including synthetic data sharing, often experiences trade-offs between privacy and utility. Synthetic data is generally more effective than data anonymization in balancing this trade-off, however, not without its own challenges. Synthetic data produced by...

Are Crypto Ecosystems (De)Centralizing? A Framework for Longitudinal Analysis

Blockchain technology relies on decentralization to resist faults and attacks while operating without trusted intermediaries. Although industry experts have touted decentralization as central to their promise and disruptive potential, it is still unclear whether the crypto ecosystems built around...

COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing among Team of Autonomous LLM Agents

The meteoric rise and proliferation of autonomous Large Language Model LLM agents promise significant capabilities across various domains. However, their deployment is increasingly constrained by substantial computational demands, specifically for Graphics Processing Unit GPU resources. This pape...

WordPress TI WooCommerce Wishlist 2.9.2 Arbitrary File Upload

WordPress TI WooCommerce Wishlist plugin versions 2.9.2 and below suffer from an arbitrary file upload vulnerability...

Trojan Horse Hunt in Time Series Forecasting for Space Operations

This competition hosted on Kaggle https://www.kaggle.com/competitions/trojan-horse-hunt-in-space is the first part of a series of follow-up competitions and hackathons related to the "Assurance for Space Domain AI Applications" project funded by the European Space Agency...

SoK: Concurrency in Blockchain -- a Systematic Literature Review and the Unveiling of a Misconception

Smart contracts, the cornerstone of blockchain technology, enable secure, automated distributed execution. Given their role in handling large transaction volumes across clients, miners, and validators, exploring concurrency is critical. This includes concurrent transaction execution or validation...

Align Is Not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models

Large Language Models LLMs have evolved into Multimodal Large Language Models MLLMs, significantly enhancing their capabilities by integrating visual information and other types, thus aligning more closely with the nature of human intelligence, which processes a variety of data forms beyond just...

Duality on the Thermodynamics of the Kirchhoff-Law-Johnson-Noise (KLJN) Secure Key Exchange Scheme

This study investigates a duality approach to information leak detection in the generalized Kirchhoff-Law-Johnson-Noise secure key exchange scheme proposed by Vadai, Mingesz, and Gingl VMG-KLJN. While previous work by Chamon and Kish sampled voltages at zero-current instances, this research...

Synchronic Web Digital Identity: Speculations on the Art of the Possible

As search, social media, and artificial intelligence continue to reshape collective knowledge, the preservation of trust on the public infosphere has become a defining challenge of our time. Given the breadth and versatility of adversarial threats, the best--and perhaps only--defense is an equall...

CSVAR: Enhancing Visual Privacy in Federated Learning Via Adaptive Shuffling against Overfitting

Although federated learning preserves training data within local privacy domains, the aggregated model parameters may still reveal private characteristics. This vulnerability stems from clients' limited training data, which predisposes models to overfitting. Such overfitting enables models to...

Peyara Remote Mouse 1.0.1 Remote Code Execution

Peyara Remote Mouse version 1.0.1 contains an unauthenticated remote code execution vulnerability in its WebSocket command interface port 1313. The application fails to validate or sanitize simulated keyboard input commands received via WebSocket connections, allowing attackers to chain malicious...

Packet Storm New Exploits for May, 2025

This archive contains all of the 129 exploits added to Packet Storm in May, 2025...

Fingerprinting Deep Learning Models Via Network Traffic Patterns in Federated Learning

Federated Learning FL is increasingly adopted as a decentralized machine learning paradigm due to its capability to preserve data privacy by training models without centralizing user data. However, FL is susceptible to indirect privacy breaches via network traffic analysis-an area not explored in...

Formal Security Analysis of SPV Clients Versus Home-Based Full Nodes in Bitcoin-Derived Systems

This paper presents a mathematically rigorous formal analysis of Simplified Payment Verification SPV clients, as specified in Section 8 of the original Bitcoin white paper, versus non-mining full nodes operated by home users. It defines security as resistance to divergence from global consensus a...

An Accurate and Efficient Vulnerability Propagation Analysis Framework

Identifying the impact scope and scale is critical for software supply chain vulnerability assessment. However, existing studies face substantial limitations. First, prior studies either work at coarse package-level granularity, producing many false positives, or fail to accomplish whole-ecosyste...

ReGA: Representation-Guided Abstraction for Model-Based Safeguarding of LLMs

Large Language Models LLMs have achieved significant success in various tasks, yet concerns about their safety and security have emerged. In particular, they pose risks in generating harmful content and vulnerability to jailbreaking attacks. To analyze and monitor machine learning models,...

Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping

Differential privacy DP has become an essential framework for privacy-preserving machine learning. Existing DP learning methods, however, often have disparate impacts on model predictions, e.g., for minority groups. Gradient clipping, which is often used in DP learning, can suppress larger...