Custom API Generator for Cross Platform and Import Export in WP 2.0.3 Privilege Escalation

WordPress REST API | Custom API Generator For Cross Platform And Import Export In WP plugin versions 1.0.0 through 2.0.3 are susceptible to a privilege escalation vulnerability due to a missing capability check on the processhandler...

Firefox JavaScript Use-After-Free

Firefox has an issues where JavaScript can run during XSLTProcessor transform, leading to a use-after-free condition...

Bhatt Conjectures: on Necessary-But-Not-Sufficient Benchmark Tautology for Human like Reasoning

The Bhatt Conjectures framework introduces rigorous, hierarchical benchmarks for evaluating AI reasoning and understanding, moving beyond pattern matching to assess representation invariance, robustness, and metacognitive self-awareness. The agentreasoning-sdk demonstrates practical implementatio...

Training RL Agents for Multi-Objective Network Defense Tasks

Open-ended learning OEL -- which emphasizes training agents that achieve broad capability over narrow competency -- is emerging as a paradigm to develop artificial intelligence AI agents to achieve robustness and generalization. However, despite promising results that demonstrate the benefits of...

GOLIATH: a Decentralized Framework for Data Collection in Intelligent Transportation Systems

Intelligent Transportation Systems ITSs technology has advanced during the past years, and it is now used for several applications that require vehicles to exchange real-time data, such as in traffic information management. Traditionally, road traffic information has been collected using on-site...

ChineseHarm-Bench: a Chinese Harmful Content Detection Benchmark

Large language models LLMs have been increasingly applied to automated harmful content detection tasks, assisting moderators in identifying policy violations and improving the overall efficiency and accuracy of content review. However, existing resources for harmful content detection are...

CyFence: Securing Cyber-Physical Controllers Via Trusted Execution Environment

In the last decades, Cyber-physical Systems CPSs have experienced a significant technological evolution and increased connectivity, at the cost of greater exposure to cyber-attacks. Since many CPS are used in safety-critical systems, such attacks entail high risks and potential safety harms...

SOFT: Selective Data Obfuscation for Protecting LLM Fine-Tuning against Membership Inference Attacks

Whitepaper called SOFT: Selective Data Obfuscation For Protecting LLM Fine-Tuning Against Membership Inference Attacks...

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

In Large Language Models, Retrieval-Augmented Generation RAG systems can significantly enhance the performance of large language models by integrating external knowledge. However, RAG also introduces new security risks. Existing research focuses mainly on how poisoning attacks in RAG systems affe...

User Perceptions and Attitudes toward Untraceability in Messaging Platforms

Mainstream messaging platforms offer a variety of features designed to enhance user privacy, such as disappearing messages, password-protected chats, and end-to-end encryption E2EE, which primarily protect message contents. Beyond contents, the transmission of messages generates metadata that can...

Uncovering Reliable Indicators: Improving IoC Extraction from Threat Reports

Indicators of Compromise IoCs are critical for threat detection and response, marking malicious activity across networks and systems. Yet, the effectiveness of automated IoC extraction systems is fundamentally limited by one key issue: the lack of high-quality ground truth. Current extraction too...

TED-LaST: Towards Robust Backdoor Defense against Adaptive Attacks

Deep Neural Networks DNNs are vulnerable to backdoor attacks, where attackers implant hidden triggers during training to maliciously control model behavior. Topological Evolution Dynamics TED has recently emerged as a powerful tool for detecting backdoor attacks in DNNs. However, TED can be...

From IOCs to Group Profiles: on the Specificity of Threat Group Behaviors in CTI Knowledge Bases

Indicators of Compromise IOCs such as IP addresses, file hashes, and domain names are commonly used for threat detection and attribution. However, IOCs tend to be short-lived as they are easy to change. As a result, the cybersecurity community is shifting focus towards more persistent behavioral...

SMB NTLM Hash Leakage

This is a proof of concept for exploiting CVE-2025-24071, a vulnerability in Windows that allows NTLM hash leakage via .library-ms files. This version diverges slightly from others by using a .tar archive instead of a .zip, which improves compatibility in SMB-only environments...

Quantifying Azure RBAC Wildcard Overreach

Azure RBAC leverages wildcard permissions to simplify policy authoring, but this abstraction often obscures the actual set of allowed operations and undermines least-privilege guarantees. We introduce Belshazaar, a two-stage framework that targets both the effective permission set problem and the...

Single Block On

In the digital age, individuals increasingly maintain active presences across multiple platforms ranging from social media and messaging applications to professional and communication tools. However, the current model for managing user level privacy and abuse is siloed, requiring users to block...

SoK: Evaluating Jailbreak Guardrails for Large Language Models

Large Language Models LLMs have achieved remarkable progress, but their deployment has exposed critical vulnerabilities, particularly to jailbreak attacks that circumvent safety mechanisms. Guardrails--external defense mechanisms that monitor and control LLM interaction--have emerged as a promisi...

Byzantine Outside, Curious Inside: Reconstructing Data through Malicious Updates

Federated learning FL enables decentralized machine learning without sharing raw data, allowing multiple clients to collaboratively learn a global model. However, studies reveal that privacy leakage is possible under commonly adopted FL protocols. In particular, a server with access to client...

WebKit Cross Site CSS Rule / Redirect URL Disclosure

WebKit suffers from a cross site CSS rule and redirect URL disclosure vulnerability...

Commitment Schemes for Multi-Party Computation

The paper presents an analysis of Commitment Schemes CSs used in Multi-Party Computation MPC protocols. While the individual properties of CSs and the guarantees offered by MPC have been widely studied in isolation, their interrelation in concrete protocols and applications remains mostly...

Chain-Of-Code Collapse: Reasoning Failures in LLMs Via Adversarial Prompting in Code Generation

Large Language Models LLMs have achieved remarkable success in tasks requiring complex reasoning, such as code generation, mathematical problem solving, and algorithmic synthesis -- especially when aided by reasoning tokens and Chain-of-Thought prompting. Yet, a core question remains: do these...

ME: Trigger Element Combination Backdoor Attack on Copyright Infringement

The capability of generative diffusion models DMs like Stable Diffusion SD in replicating training data could be taken advantage of by attackers to launch the Copyright Infringement Attack, with duplicated poisoned image-text pairs. SilentBadDiffusion SBD is a method proposed recently, which shew...

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR

Extended reality XR systems, which consist of virtual reality VR, augmented reality AR, and mixed reality XR, offer a transformative interface for immersive, multi-modal, and embodied human-computer interaction. In this paper, we envision that multi-modal multi-task M3T federated foundation model...

Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation

The security of modern vehicles has become increasingly important, with the controller area network CAN bus serving as a critical communication backbone for various Electronic Control Units ECUs. The absence of robust security measures in CAN, coupled with the increasing connectivity of vehicles,...

TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems

Federated Learning has emerged as a privacy-oriented alternative to centralized Machine Learning, enabling collaborative model training without direct data sharing. While extensively studied for neural networks, the security and privacy implications of tree-based models remain underexplored. This...

A Crack in the Bark: Leveraging Public Knowledge to Remove Tree-Ring Watermarks

We present a novel attack specifically designed against Tree-Ring, a watermarking technique for diffusion models known for its high imperceptibility and robustness against removal attacks. Unlike previous removal attacks, which rely on strong assumptions about attacker capabilities, our attack on...

FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks

Graph Convolutional Neural Networks GCNs have gained widespread popularity in various fields like personal healthcare and financial systems, due to their remarkable performance. Despite the growing demand for cloud-based GCN services, privacy concerns over sensitive graph data remain significant...

ObfusBFA: a Holistic Approach to Safeguarding DNNs from Different Types of Bit-Flip Attacks

Bit-flip attacks BFAs represent a serious threat to Deep Neural Networks DNNs, where flipping a small number of bits in the model parameters or binary code can significantly degrade the model accuracy or mislead the model prediction in a desired way. Existing defenses exclusively focus on...

TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning

Deep reinforcement learning DRL has achieved remarkable success in a wide range of sequential decision-making domains, including robotics, healthcare, smart grids, and finance. Recent research demonstrates that attackers can efficiently exploit system vulnerabilities during the training phase to...

Adaptive Chosen-Ciphertext Security of Distributed Broadcast Encryption

Distributed broadcast encryption DBE is a specific kind of broadcast encryption BE where users independently generate their own public and private keys, and a sender can efficiently create a ciphertext for a subset of users by using the public keys of the subset users. Previously proposed DBE...

MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark

Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwords. Despite their potential, inconsistencies and inadequate evaluation methodologies in prior research have hindered...

Differentially Private Relational Learning with Entity-Level Privacy Guarantees

Learning with relational and network-structured data is increasingly vital in sensitive domains where protecting the privacy of individual entities is paramount. Differential Privacy DP offers a principled approach for quantifying privacy risks, with DP-SGD emerging as a standard mechanism for...

Guardians of the Regime: When and Why Autocrats Create Secret Police

Autocrats use secret police to stay in power, as these organizations deter and suppress opposition to their rule. Existing research shows that secret police are very good at this but, surprisingly, also that they are not as ubiquitous in autocracies as one may assume, existing in less than 50% of...

Identity and Access Management for the Computing Continuum

The computing continuum introduces new challenges for access control due to its dynamic, distributed, and heterogeneous nature. In this paper, we propose a Zero-Trust ZT access control solution that leverages decentralized identification and authentication mechanisms based on Decentralized...

Beyond Personalization: Federated Recommendation with Calibration Via Low-Rank Decomposition

Federated recommendation FR is a promising paradigm to protect user privacy in recommender systems. Distinct from general federated scenarios, FR inherently needs to preserve client-specific parameters, i.e., user embeddings, for privacy and personalization. However, we empirically find that...

A Comprehensive Survey of Unmanned Aerial Systems' Risks and Mitigation Strategies

In the last decade, the rapid growth of Unmanned Aircraft Systems UAS and Unmanned Aircraft Vehicles UAV in communication, defense, and transportation has increased. The application of UAS will continue to increase rapidly. This has led researchers to examine security vulnerabilities in various...

Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions

In an era of increasing interaction with artificial intelligence AI, users face evolving privacy decisions shaped by complex, uncertain factors. This paper introduces Multiverse Privacy Theory, a novel framework in which each privacy decision spawns a parallel universe, representing a distinct...

From Concept to Measurement: a Survey of How the Blockchain Trilemma Can Be Analyzed

To meet non-functional requirements, practitioners must identify Pareto-optimal configurations of the degree of decentralization, scalability, and security of blockchain systems. Maximizing all of these subconcepts is, however, impossible due to the trade-offs highlighted by the blockchain...

Mapping NVD Records to Their VFCs: How Hard Is It?

Mapping National Vulnerability Database NVD records to vulnerability-fixing commits VFCs is crucial for vulnerability analysis but challenging due to sparse explicit links in NVD references.This study explores this mapping's feasibility through an empirical approach. Manual analysis of NVD...

Efficient Modular Multiplier over GF (2^M) for ECPM

Elliptic curve cryptography ECC has emerged as the dominant public-key protocol, with NIST standardizing parameters for binary field GF2^m ECC systems. This work presents a hardware implementation of a Hybrid Multiplication technique for modular multiplication over binary field GF2m, targeting NI...

Oracle-Based Multistep Strategy for Solving Polynomial Systems over Finite Fields and Algebraic Cryptanalysis of the Aradi Cipher

The multistep solving strategy consists in a divide-and-conquer approach: when a multivariate polynomial system is computationally infeasible to solve directly, one variable is assigned over the elements of the base finite field, and the procedure is recursively applied to the resulting simplifie...

Effective Red-Teaming of Policy-Adherent Agents

Task-oriented LLM-based agents are increasingly used in domains with strict policies, such as refund eligibility or cancellation rules. The challenge lies in ensuring that the agent consistently adheres to these rules and policies, appropriately refusing any request that would violate them, while...

SALAD: Systematic Assessment of Machine Unlearing on LLM-Aided Hardware Design

Large Language Models LLMs offer transformative capabilities for hardware design automation, particularly in Verilog code generation. However, they also pose significant data security challenges, including Verilog evaluation data contamination, intellectual property IP design leakage, and the ris...

LLMail-Inject: a Dataset from a Realistic Adaptive Prompt Injection Challenge

Indirect Prompt Injection attacks exploit the inherent limitation of Large Language Models LLMs to distinguish between instructions and data in their inputs. Despite numerous defense proposals, the systematic evaluation against adaptive adversaries remains limited, even when successful attacks ca...

First-Spammed, First-Served: MEV Extraction on Fast-Finality Blockchains

This research analyzes the economics of spam-based arbitrage strategies on fast-finality blockchains. We begin by theoretically demonstrating that, splitting a profitable MEV opportunity into multiple small transactions is the optimal strategy for CEX-DEX arbitrageurs. We then empirically validat...

Differentially Private Federated $K$-Means Clustering with Server-Side Data

Clustering is a cornerstone of data analysis that is particularly suited to identifying coherent subgroups or substructures in unlabeled data, as are generated continuously in large amounts these days. However, in many cases traditional clustering methods are not applicable, because data are...

ELFuzz: Efficient Input Generation Via LLM-Driven Synthesis over Fuzzer Space

Generation-based fuzzing produces appropriate testing cases according to specifications of input grammars and semantic constraints to test systems and software. However, these specifications require significant manual efforts to construct. This paper proposes a new approach, ELFuzz Evolution...

Design Patterns for Securing LLM Agents against Prompt Injections

As AI agents powered by Large Language Models LLMs become increasingly versatile and capable of addressing a broad spectrum of tasks, ensuring their security has become a critical challenge. Among the most pressing threats are prompt injection attacks, which exploit the agent's resilience on...

On the Virtues of Information Security in the UK Climate Movement

We report on an ethnographic study with members of the climate movement in the United Kingdom UK. We conducted participant observation and interviews at protests and in various activist settings. Reporting on the findings as they relate to information security, we show that members of the UK...

TRIDENT -- a Three-Tier Privacy-Preserving Propaganda Detection Model in Mobile Networks Using Transformers, Adversarial Learning, and Differential Privacy

The proliferation of propaganda on mobile platforms raises critical concerns around detection accuracy and user privacy. To address this, we propose TRIDENT - a three-tier propaganda detection model implementing transformers, adversarial learning, and differential privacy which integrates syntact...