From Text to Actionable Intelligence: Automating STIX Entity and Relationship Extraction

Sharing methods of attack and their effectiveness is a cornerstone of building robust defensive systems. Threat analysis reports, produced by various individuals and organizations, play a critical role in supporting security operations and combating emerging threats. To enhance the timeliness and...

AUTOPSY: a Framework for Tackling Privacy Challenges in the Automotive Industry

With the General Data Protection Regulation GDPR in place, all domains have to ensure compliance with privacy legislation. However, compliance does not necessarily result in a privacy-friendly system as for example getting users' consent to process their data does not improve the...

SharePoint CVE-2025-53770 Scanner

This is a scanner for the SharePoint unauthenticated remote code execution vulnerability, assigned CVE number CVE-2025-53770. The code for this was written by reverse-engineering a payload seen in the wild...

From Cracks to Crooks: YouTube As a Vector for Malware Distribution

With billions of users and an immense volume of daily uploads, YouTube has become an attractive target for cybercriminals aiming to leverage its vast audience. The platform's openness and trustworthiness provide an ideal environment for deceptive campaigns that can operate under the radar of...

Explainable Vulnerability Detection in C/C++ Using Edge-Aware Graph Attention Networks

Detecting security vulnerabilities in source code remains challenging, particularly due to class imbalance in real-world datasets where vulnerable functions are under-represented. Existing learning-based methods often optimise for recall, leading to high false positive rates and reduced usability...

PhishIntentionLLM: Uncovering Phishing Website Intentions through Multi-Agent Retrieval-Augmented Generation

Phishing websites remain a major cybersecurity threat, yet existing methods primarily focus on detection, while the recognition of underlying malicious intentions remains largely unexplored. To address this gap, we propose PhishIntentionLLM, a multi-agent retrieval-augmented generation RAG...

SVAgent: AI Agent for Hardware Security Verification Assertion

Verification using SystemVerilog assertions SVA is one of the most popular methods for detecting circuit design vulnerabilities. However, with the globalization of integrated circuit design and the continuous upgrading of security requirements, the SVA development model has exposed major...

Realistic Vulnerabilities of Decoy-State Quantum Key Distribution

We analyze realistic vulnerabilities of decoy-state quantum key distribution QKD arising from the combination of laser damage attack LDA and unambiguous state discrimination USD. While decoy-state QKD is designed to protect against photon-number-splitting and beam-splitting attacks by accurately...

Deepfiction AI Insecure Direct Object Reference

Deepfiction AI is an AI entertainment company with a mission to revolutionize personalized storytelling. Deepfiction AI provides a web application to create stories via chat and is susceptible to an insecure direct object reference vulnerability. An attacker can exploit this IDOR to chat with the...

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...

MFAz: Historical Access Based Multi-Factor Authorization

Unauthorized access remains one of the critical security challenges in the realm of cybersecurity. With the increasing sophistication of attack techniques, the threat of unauthorized access is no longer confined to the conventional ones, such as exploiting weak access control policies. Instead,...

BACFuzz: Exposing the Silence on Broken Access Control Vulnerabilities in Web Applications

Broken Access Control BAC remains one of the most critical and widespread vulnerabilities in web applications, allowing attackers to access unauthorized resources or perform privileged actions. Despite its severity, BAC is underexplored in automated testing due to key challenges: the lack of...

Dippyis Insecure Direct Object Reference / Brute Force

Dippyis a popular website to chat with millions of proactive AI characters. The Dippy chat suffers from an insecure direct object reference vulnerability. Conversation histories for all users are stored on the server. However, Dippy's server does not distinguish the ownership or sharing status of...

Optimizing Canaries for Privacy Auditing with Metagradient Descent

In this work we study black-box privacy auditing, where the goal is to lower bound the privacy parameter of a differentially private learning algorithm using only the algorithm's outputs i.e., final trained model. For DP-SGD the most successful method for training differentially private deep...

QSAF: a Novel Mitigation Framework for Cognitive Degradation in Agentic AI

We introduce Cognitive Degradation as a novel vulnerability class in agentic AI systems. Unlike traditional adversarial external threats such as prompt injection, these failures originate internally, arising from memory starvation, planner recursion, context flooding, and output suppression. Thes...

In-Context Learning of Vision Language Models for Detection of Physical and Digital Attacks against Face Recognition Systems

Recent advances in biometric systems have significantly improved the detection and prevention of fraudulent activities. However, as detection methods improve, attack techniques become increasingly sophisticated. Attacks on face recognition systems can be broadly divided into physical and digital...

Cyber Security of Mega Events: a Case Study of Securing the Digital Infrastructure for MahaKumbh 2025 -- a 45 Days Mega Event of 600 Million Footfalls

Mega events such as the Olympics, World Cup tournaments, G-20 Summit, religious events such as MahaKumbh are increasingly digitalized. From event ticketing, vendor booth or lodging reservations, sanitation, event scheduling, customer service, crime reporting, media streaming and messaging on...

Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems

Large Language Models LLMs deployed in enterprise settings e.g., as Microsoft 365 Copilot face novel security challenges. One critical threat is prompt inference attacks: adversaries chain together seemingly benign prompts to gradually extract confidential data. In this paper, we present a...

SynthCTI: LLM-Driven Synthetic CTI Generation to Enhance MITRE Technique Mapping

Cyber Threat Intelligence CTI mining involves extracting structured insights from unstructured threat data, enabling organizations to understand and respond to evolving adversarial behavior. A key task in CTI mining is mapping threat descriptions to MITRE ATT&CK techniques. However, this process...

TelegAI Insecure Direct Object Reference

TelegAI, a web application for constructing and chatting with AI Characters, is vulnerable to insecure direct object reference in its chat component. An attacker can exploit this IDOR to tamper other users' conversation. Additionally, malicious contents and cross site scripting payloads can be...

FaultLine: Automated Proof-Of-Vulnerability Generation Using LLM Agents

Despite the critical threat posed by software security vulnerabilities, reports are often incomplete, lacking the proof-of-vulnerability PoV tests needed to validate fixes and prevent regressions. These tests are crucial not only for ensuring patches work, but also for helping developers understa...

Liner Insecure Direct Object Reference / Brute Force

Liner is a reliable AI search engine with over 10 million users worldwide. It is vulnerable to an insecure direct object reference vulnerability. Conversation histories for all users are stored on the server. However, Liner's server does not distinguish the ownership or sharing status of individu...

Pulse-Level Simulation of Crosstalk Attacks on Superconducting Quantum Hardware

Hardware crosstalk in multi-tenant superconducting quantum computers poses a severe security threat, allowing adversaries to induce targeted errors across tenant boundaries by injecting carefully engineered pulses. We present a simulation-based study of active crosstalk attacks at the pulse level...

Attacking Interpretable NLP Systems

Studies have shown that machine learning systems are vulnerable to adversarial examples in theory and practice. Where previous attacks have focused mainly on visual models that exploit the difference between human and machine perception, text-based models have also fallen victim to these attacks...

AIBOX Cross Site Scripting

AIBOX is a web application for exploring AI consulting and trying out multiple LLMs. It allows users to chat with various LLMs. A reflected cross site scripting XSS vulnerability exists in the chat component, which could lead to JWT token theft and remote account hijacking...

Chaindesk Cross Site Scripting

Chaindesk, a web application for constructing AI Agents, is vulnerable to a persistent cross site scripting vulnerability in its agent chat component. An attacker can achieve arbitrary client-side script execution by crafting an AI agent whose system prompt instructs the underlying Large Language...

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...

ChatGPTUtil Cross Site Scripting

ChatGPTUtil is an AI-powered chatbot assistant, providing access to both ChatGPT and an AI image generator. A self cross site scripting vulnerability exists in the chat component. This can lead to cookie theft leading to remote account hijacking...

ChatPlayground.ai Cross Site Scripting / Insecure Direct Object Reference

ChatPlayground.ai is a popular web application for comparing AI models. A cross site scripting vulnerability exists in the chat component. This can lead to JWT token theft and remote account hijacking. Additionally, the /api/chat-history endpoint exhibits weak access control allowing for insecure...

PiMRef: Detecting and Explaining Ever-Evolving Spear Phishing Emails with Knowledge Base Invariants

Phishing emails are a critical component of the cybercrime kill chain due to their wide reach and low cost. Their ever-evolving nature renders traditional rule-based and feature-engineered detectors ineffective in the ongoing arms race between attackers and defenders. The rise of large language...

Scaling Decentralized Learning with FLock

Fine-tuning the large language models LLMs are prevented by the deficiency of centralized control and the massive computing and communication overhead on the decentralized schemes. While the typical standard federated learning FL supports data privacy, the central server requirement creates a...

DP2Guard: a Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT

Privacy-Preserving Federated Learning PPFL has emerged as a secure distributed Machine Learning ML paradigm that aggregates locally trained gradients without exposing raw data. To defend against model poisoning threats, several robustness-enhanced PPFL schemes have been proposed by integrating...

PromptArmor: Simple yet Effective Prompt Injection Defenses

Despite their potential, recent research has demonstrated that LLM agents are vulnerable to prompt injection attacks, where malicious prompts are injected into the agent's input, causing it to perform an attacker-specified task rather than the intended task provided by the user. In this paper, we...

Jamming-Resistant AAV Communications: a Multichannel-Aided Approach

Jamming cancellation is essential to reliable unmanned autonomous vehicle AAV communications in the presence of malicious jammers. In this paper, we develop a practical multichannel-aided jamming cancellation method to realize secure AAV communications. The proposed method is capable of...

Metaverse Security and Privacy Research: a Systematic Review

The rapid growth of metaverse technologies, including virtual worlds, augmented reality, and lifelogging, has accelerated their adoption across diverse domains. This rise exposes users to significant new security and privacy challenges due to sociotechnical complexity, pervasive connectivity, and...

Frame-Level Temporal Difference Learning for Partial Deepfake Speech Detection

Detecting partial deepfake speech is essential due to its potential for subtle misinformation. However, existing methods depend on costly frame-level annotations during training, limiting real-world scalability. Also, they focus on detecting transition artifacts between bonafide and deepfake...

Exploiting Context-Dependent Duration Features for Voice Anonymization Attack Systems

The temporal dynamics of speech, encompassing variations in rhythm, intonation, and speaking rate, contain important and unique information about speaker identity. This paper proposes a new method for representing speaker characteristics by extracting context-dependent duration embeddings from...

Time Entangled Quantum Blockchain with Phase Encoding for Classical Data

With rapid advancements in quantum computing, it is widely believed that there will be quantum hardware capable of compromising classical cryptography and hence, the internet and the current information security infrastructure in the coming decade. This is mainly due to the operational realizatio...

Quantum Skyshield: Quantum Key Distribution and Post-Quantum Authentication for Low-Altitude Wireless Networks in Adverse Skies

Recently, low-altitude wireless networks LAWNs have emerged as a critical backbone for supporting the low-altitude economy, particularly with the densification of unmanned aerial vehicles UAVs and high-altitude platforms HAPs. To meet growing data demands, some LAWN deployments incorporate...

Adaptive Network Security Policies Via Belief Aggregation and Rollout

Evolving security vulnerabilities and shifting operational conditions require frequent updates to network security policies. These updates include adjustments to incident response procedures and modifications to access controls, among others. Reinforcement learning methods have been proposed for...

A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption

Federated Learning FL enables collaborative model training without sharing raw data, making it a promising approach for privacy-sensitive domains. Despite its potential, FL faces significant challenges, particularly in terms of communication overhead and data privacy. Privacy-preserving Technique...

Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data

False Data Injection Attacks FDIAs pose severe security risks to smart grids by manipulating measurement data collected from spatially distributed devices such as SCADA systems and PMUs. These measurements typically exhibit Non-Independent and Identically Distributed Non-IID characteristics acros...

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...

Hybrid Classical-Quantum Rainbow Table Attack on Human Passwords

Passwords that are long and human-generated pose a challenge for both classical and quantum attacks due to their irregular structure and large search space. In this work, we present an enhanced classical-quantum hybrid attack tailored to this scenario. We build rainbow tables using dictionary-bas...

CANDoSA: a Hardware Performance Counter-Based Intrusion Detection System for DoS Attacks on Automotive CAN Bus

The Controller Area Network CAN protocol, essential for automotive embedded systems, lacks inherent security features, making it vulnerable to cyber threats, especially with the rise of autonomous vehicles. Traditional security measures offer limited protection, such as payload encryption and...

Manipulating LLM Web Agents with Indirect Prompt Injection Attack Via HTML Accessibility Tree

This work demonstrates that LLM-based web navigation agents offer powerful automation capabilities but are vulnerable to Indirect Prompt Injection IPI attacks. We show that adversaries can embed universal adversarial triggers in webpage HTML to hijack agent behavior that utilizes the accessibilit...

Enhancing Resilience against Jamming Attacks: a Cooperative Anti-Jamming Method Using Direction Estimation

The inherent vulnerability of wireless communication necessitates strategies to enhance its security, particularly in the face of jamming attacks. This paper uses the collaborations of multiple sensing nodes SNs in the wireless network to present a cooperative anti-jamming approach CAJ designed t...

Privacy-Preserving Drone Navigation through Homomorphic Encryption for Collision Avoidance

As drones increasingly deliver packages in neighborhoods, concerns about collisions arise. One solution is to share flight paths within a specific zip code, but this compromises business privacy by revealing delivery routes. For example, it could disclose which stores send packages to certain...

Collusion-Resilient Hierarchical Secure Aggregation with Heterogeneous Security Constraints

Motivated by federated learning FL, secure aggregation SA aims to securely compute, as efficiently as possible, the sum of a set of inputs distributed across many users. To understand the impact of network topology, hierarchical secure aggregation HSA investigated the communication and secret key...

Measuring CEX-DEX Extracted Value and Searcher Profitability: the Darkest of the MEV Dark Forest

This paper provides a comprehensive empirical analysis of the economics and dynamics behind arbitrages between centralized and decentralized exchanges CEX-DEX on Ethereum. We refine heuristics to identify arbitrage transactions from on-chain data and introduce a robust empirical framework to...