Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

Threat hunting increasingly depends on converting unstructured knowledge e.g., Cyber Threat Intelligence reports into actionable hunt leads: concise, investigable hypotheses grounded in observable artifacts and adversary techniques. Producing such leads manually is a tedious and hard-to-scale tas...

A Novel Steganography Scheme Using Quantum Hilbert Transform

The main goal of steganography is to transmit hidden messages in legitimate-looking communication messages. Phase-domain information hiding, however, has not been fully explored for quantum systems. This work introduces a finite-dimensional Quantum Hilbert Transform QHT as a unitary phase operato...

EventSpec: Defining and Detecting Event-Semantic Issues in Blockchain Ecosystems

In recent years, smart contracts have become the backbone of decentralized applications DApps, and off-chain systems such as bridges, wallets, and indexers rely heavily on event logs to track contract execution and state changes. However, the Ethereum Virtual Machine EVM does not validate or...

Merging Cyber Threat Intelligence through Retrieval-Augmented Generation and Small Language Models for Rich Threat Representation

Modern cybersecurity operations rely on CTI collected from heterogeneous sources, including semi-structured threat representations, IoCs, and narrative technical reports. However, these artifacts are often insufficient in isolation to reconstruct how an attack unfolds, under which conditions each...

One Is Not Enough: The Untold Story of Multiple Security Patches for One Vulnerability

Security patches SPs are the main mechanism for fixing software vulnerabilities, yet a single vulnerability is not always resolved by a single patch: fixes may be completed incrementally, propagated across maintained branches, or replicated across related repositories. When patch records are...

5GDescrambler: Locating, Descrambling, and Decoding 5G Scheduling Information (Long Version)

Tracking users in 5G NR has recently been successfully demonstrated by exploiting various side-channels. This allows for identification of individuals, classification of user activity in real time as well as tracking by fingerprinting, affecting billions of users with a 5G subscription and...

libpcap 1.10.7

Libpcap is a portable packet capture library which is used in many packet sniffers, including tcpdump...

Towards a Resilience-Theoretic Foundation for Adversarial Robustness in Industrial Control System Anomaly Detection

Anomaly-based intrusion detection systems in industrial control systems ICS and operational technology OT environments are increasingly required to meet formal resilience criteria: absorbed adversarial disturbances, graceful degradation under sustained attack, and certified system-level guarantee...

Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain

AI coding assistants now select, install, and configure software, and attackers have exploited that position through invented package names, compromised maintainer accounts, and manipulated repository text. In response, the supply-chain community publishes machine-checkable trust signals: softwar...

Benchmarking LLMs for Threat Level Determination

The fast progress of large language models LLMs opens new opportunities in the management of cyber threat intelligence, but their reliability for operational tasks remains unclear. In this work, we benchmark LLMs on the task of threat level determination. First, we construct a curated dataset...

Enhancing Privacy, Neglecting Harms: An Analysis of Real-World Digital Privacy Incidents

Privacy-enhancing technologies PETs have emerged as a technical means for providing individuals with greater control over their information. Yet despite the growing deployment of PETs, people continue to experience privacy harms. In this work, we revisit our understanding of privacy incidents and...

VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities

The software supply chain has become an increasingly exposed attack surface because of its reliance on intricate yet fragile dependencies. Existing defenses such as GitHub Dependabot often raise many false alerts because their coarse-grained matching cannot determine whether a vulnerable dependen...

AVP-Inspect: Coordinated Cyber-Physical Testing for Privacy Analysis of COTS Apple Vision Pro Applications

XR devices introduce substantial privacy concerns due to their comprehensive data collection capabilities that surpass traditional computing platforms. While existing works have demonstrated privacy concerns on Android-based XR devices such as Meta Quest series by performing network traffic...

Joern 4.0.621

Joern is the bug hunter's workbench. With this tool, you can uncover attack surface, sloppy coding practices, and variants of known vulnerabilities using an interactive code analysis shell. Joern supports C, C++, LLVM bitcode, x86 binaries via Ghidra, JVM bytecode via Soot, and Javascript...

Construction and Natural Language Querying of a Cybersecurity Knowledge Graph

Cybersecurity vulnerability information is distributed across numerous platforms and databases, making it difficult for researchers and practitioners to obtain a unified and structured understanding of existing threats. This is a critical issue in cybersecurity, where timely access to accurate...

Grid Trouble in Paradise: Uncovering Vulnerable Distributed Energy Resources and Their Grid-Level Risks

Grid-connected solar distributed energy resources DERs, such as solar inverters and monitoring platforms, have been deployed at unprecedented scale over the past few years, with global solar capacity more than doubling since 2022. To support monitoring and control, many of these systems are...

TrojanWorld: Backdooring World-Model Agents Via Imagination Steering

World models increasingly serve as the predictive core of model-based reinforcement learning agents, enabling them to simulate future dynamics and reason over imagined trajectories before acting. Their substantial training demands make pretrained world models attractive for distribution and reuse...

Fine-Grained Distributed Backdoor Attacks in Federated Learning

Federated learning, as a privacy-preserving distributed machine learning paradigm, faces significant threats from backdoor attacks. Compared to centralized attacks, distributed backdoor attacks are more harmful but require more poisoned samples to compensate for the loss of trigger strength due t...

Frequency-Domain Mixing Data Augmentation for Malicious Traffic Detection

The strong dynamics of network traffic often force malicious traffic detection models to handle out-of-distribution data. Typically, deep learning-based malicious traffic detection models require a large amount of high-quality training data. However, owing to challenges such as high labeling...

Crossing the Streams: SSH Plaintext Recovery Via a Common Compression Context in Multiplexed Channels

SSH is the standard protocol for secure remote administration of servers. At the transport layer, SSH uses the Binary Packet Protocol BPP for encrypted and authenticated communication. Above this, the SSH Connection Protocol multiplexes one or more logical channels over a single connection,...

LLM-Based Penetration Testing in the Presence of Honeypots

Large language model LLM agents are increasingly employed for offensive cybersecurity tasks such as automated vulnerability discovery, reconnaissance, and penetration testing. This new capability also threatens one of the defender's most valuable tools: deception. Traditional honeypots rely on...

Staying on the Attack Path: Structured State for Long-Horizon Automated Penetration Testing

Large language model LLM based agents are increasingly applied to cybersecurity tasks such as vulnerability discovery and automated penetration testing. On long-horizon security tasks, however, such agents remain limited by context forgetting and intent drift: early critical facts and causal...

Efficient Hardware Information-Flow Tracking for Pre-Silicon Security Testing

Register-Transfer Level RTL simulation is widely used to test hardware before it is fabricated. To allow testing for security related information flow properties, such as confidentiality and integrity, taint logic can be automatically added to the design to track how information flows through it...

MOLE: Detecting Insider Threats in AI Agents

Model misalignment, prompt injection, or operator misuse could lead AI agents operating frontier-lab accounts to exfiltrate model weights, poison training data, or weaken release gates. Existing benchmarks do not test whether defenders can detect this activity among routine work under a limited...

AgentDrift: A Step-Labeled Benchmark of Injection-Hijacked LLM Agent Trajectories

LLM agents complete tasks by issuing sequences of tool calls, and every observation they read is a channel through which an indirect prompt injection can enter. A successful injection has a characteristic shape when the trajectory is read in order: a benign prefix gives way to actions that serve...

WAPP: Safe Learning of Positive Security WAF Policies from Live Traffic

Web Application Firewalls WAFs mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payloads. Positive security provides a complementary approach by learning legitimate traffic and blocking inputs that fall outside the learned profile...

AURA-Eval: Evaluation Framework for Acting under Risk Awareness in LLM Agent Trajectories

LLM agents operate in workflows where unsafe actions can have real consequences. Existing safety evaluations often reduce behavior to a single score, obscuring risk recognition, pre-action detection, and safe task completion when a safe solution exists. We introduce AURA-Eval, a framework combini...

Characterizing Contention-Induced Reliability Collapse in KV-Cache Timing Side Channels for Multi-Tenant LLM Serving

Shared key--value KV cache reuse improves large language model LLM serving, but it can also create a timing side channel that reveals whether a prefix is already cached. Previous work shows that such attacks are possible, but their reliability under realistic multi-tenant contention is less...

Skynet: Workflow-Level Anomaly Detection for Agentic AI Via Semantic and Structural Modeling

Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these systems often originate from a single step, such as an injected prompt or a flawed plan, and are then amplified through downstream dependencies as th...

Lightweight Detection of Electromagnetic Signal Injection Attacks on Image Sensors

Electromagnetic signal injection attacks ESIA pose a growing threat to image sensors, which are increasingly used in different intelligent systems. By emitting electromagnetic interference, adversaries can manipulate pixel values, potentially misleading downstream artificial intelligence AI model...

A Queryable Graph-Based Security Analysis Framework for O-RAN

The Open Radio Access Network O-RAN replaces vendor-locked RANs with a modular and interoperable architecture that fosters competition and accelerates innovation. With this openness comes increased complexity and a larger attack surface, making security a critical concern. Today, assessing O-RAN...

AgentHijack: Visual Patch Attacks on Multimodal Computer-Use Agents

This paper presents an end-to-end evaluation framework for image-triggered command injection against computer-use agents CUAs. The goal is to test whether a local visual patch can induce verifiable environmental consequences along the full chain of screenshot input, VLM generation, action parsing...

Step-by-Step Malware Development: Evading EDR from Loaders to the Kernel

These are the workshop materials for "Step-by-Step Malware Development: Evading EDR from Loaders to the Kernel", presented at DEF CON 34 and BSidesLV 2026. This workshop explores custom malware development, EDR Architecture and Evasion, C2 customization, and kernel-level techniques using Elastic...

Booz Allen Cyber Weapon Index

The new Booz Allen Cyber Weapon Index CWI confirms that autonomous offensive cyber has arrived. A leading frontier AI model can now independently execute the full cyber kill chain against a real network—crossing a critical threshold from AI-assisted hacking to autonomous cyber operations. This is...

Joern 4.0.618

Joern is the bug hunter's workbench. With this tool, you can uncover attack surface, sloppy coding practices, and variants of known vulnerabilities using an interactive code analysis shell. Joern supports C, C++, LLVM bitcode, x86 binaries via Ghidra, JVM bytecode via Soot, and Javascript...

TIER: Threat Implicitness Benchmark for Evaluating LLM Safety Behaviors

Current LLM safety benchmarks largely rely on binary metrics, overlooking how models respond to harmful prompts with varying threat implicitness. We introduce TIER, a Threat Implicitness Benchmark for behavioral safety evaluation of LLMs. TIER covers four risk domains and four threat levels, from...

Conformal Prediction for Offensive Security

Despite its introduction more than a quarter century ago, Conformal Prediction CP has seen surprisingly few applications to the cyber security world thus far. In particular, we observe that, while CP has been employed as a defensive measure in many recent works, its use for carrying out attacks...

Android Debug Bridge Remote Code Execution

CVE-2026-78745 affects HiDPT / Weyon HiDPTAndroid devices using the Hi3751V350 and Hi3751V352EDMO platforms. The vulnerability allows a remote attacker to execute arbitrary code through the Android Debug Bridge adbd daemon...

Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

Ransomware detection and family attribution require analysis of different modalities because it can use packing, obfuscation, process manipulation and runtime evasion techniques. However, conventional multimodal usually uses all available modalities for every sample resulting in unnecessary...

Zimbra CVE-2026-73570 Incident Response Toolkit

Zimbra CVE-2026-73570 Incident Response Toolkit is a collection of detection and evidence-preservation utilities for administrators investigating suspected exploitation of CVE-2026-73570. The toolkit searches Zimbra and mail logs for exploitation indicators, examines JSP persistence locations,...

Governing Bring Your Own AI: A Parameterized Maturity Model

Employees are increasingly using personally owned generative AI tools such as ChatGPT, Gemini, and Claude for their daily work. This practice is known as Bring Your Own AI BYOAI, which is a distinct form of Shadow AI in which employee-authenticated personal accounts are used outside of enterprise...

Faraday 5.24.0

Faraday is a tool that introduces a new concept called IPE, or Integrated Penetration-Test Environment. It is a multiuser penetration test IDE designed for distribution, indexation and analysis of the generated data during the process of a security audit. The main purpose of Faraday is to re-use...

The History Is the Detector: Executing CVE Patch History, End-To-End

Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related patches. Fixing commits provide the exact code changes that removed these flaws. While these records capture why the original code was unsafe, they...

Understanding the Privacy-Preserving Potential of HTTP/2 against Webpage Fingerprinting

Website fingerprinting WF attacks can infer which webpage a user visits from encrypted HTTPS traffic alone, compromising privacy even without decryption. WF defenses commonly shape traffic through noise, padding, delays, or flow splitting, yet they are most often studied from the perspective of...

Federated Attack Campaign Detection Via Contrastive Encoding of Threat Indicators in Gradient Updates

Detecting orchestrated cyberattack campaigns that span multiple organizations traditionally requires sharing sensitive telemetry and threat intelligence across institutional boundaries and country borders, a barrier that Federated Learning removes by training shared threat detectors directly on...

The Security Feature Location Problem

Software security must be realized through security features such as authentication and encryption, but which features does a system implement, and where? We present security feature location: the task of relating code locations to security features, enabling developers to understand security...

CONTINUITY: Security-Context Contracts for Composable LLM Agent Controls

LLM agent systems increasingly combine provenance tracking, authorization, policy enforcement, protocol adapters, and execution controls. However, individually correct security mechanisms do not necessarily compose into an end-to-end secure system: security-critical context may be dropped, widene...

Injected and Leaked: Actively Inducing Side-Channel Leakage Using Electromagnetic Injection and Hardware Nonlinearity

Electromagnetic EM side-channel leakage and injection are typically treated as distinct physical phenomena, threatening data confidentiality and integrity respectively. This work investigates how EM injection can be used to amplify side-channel leakage that is otherwise infeasible. We introduce a...

AI-Assisted Design of a Post-Quantum Cryptographic Accelerator: A Deployed-Silicon Case Study

Post-quantum migration is mandated on published timelines, and silicon that ships with a defect cannot be patched remotely. The standard acceptance gate cannot detect an entire class of ML-DSA defects. Signing resamples until a candidate meets its norm bounds, so the executed path varies with the...

Candidate Comparability Before Promotion: Conditional Validation in Adaptive Network Intrusion Detection

Adaptive network intrusion detection systems retrain classifiers after drift alarms, but an alarm detects change; it does not establish that a challenger should replace the deployed incumbent. Promotion is security-relevant because it changes the model responsible for subsequent attack detection,...