Cryptocurrencies in the Quantum Age: Migration Paths to PQC

Quantum computers pose a fundamental threat to blockchain systems that rely on elliptic-curve cryptography. This work reviews the quantum vulnerabilities and associated economic risks of major blockchain platforms, with a focus on Bitcoin, Ethereum, and Solana. We distinguish between at-rest,...

CERTIoT-6G: Continuous Cybersecurity Certification for IoT Devices in 5G/6G Networks

The massive adoption of Internet of Things IoT devices across critical domains such as healthcare, smart cities, industrial automation, and critical infrastructure introduces significant cybersecurity and regulatory challenges. Current and forthcoming European regulations, including the Cyber...

CISA: Logging Reference Architecture

The Cybersecurity and Infrastructure Security Agency CISA developed the Logging Reference Architecture LRA in alignment with Office of Management and Budget Memorandum M-26-14: Ensuring Effective and Efficient Agency Logging and Network Visibility to Defend Against Evolving Cyber Threats, which w...

Verification-Guided Specification Synthesis with Large Language Models for Intrusion Detection Rules

Attacks against Internet-connected IoT devices continue to increase; however, transforming observed attack traffic into deployable intrusion detection system IDS rules remains largely a manual process. Recent studies have explored using large language models LLMs to generate IDS rules; nonetheles...

Adapter-Based Few-Shot Continual Learning for Malicious Packet Recognition

The continual evolution of malware variants necessitates detection systems that can adapt to new threats without retraining from scratch. However, continually updating models on new data often leads to catastrophic forgetting, where previously learned knowledge is overwritten. While continual...

Black Box Cryptanalysis of AES128

This paper presents computational results of cryptanalysis of AES using the Local Inversion by Black Box computations of the forward encryption and utilizes these results to develop a practically feasible approach for the key recovery of the full scale AES128 under Known Plaintext Attack KPA. It ...

The Surprising Effectiveness of LLMs in BGP Security: Mining an Unprecedented Amount of Incidents and Boosting Anomaly Detection

Border Gateway Protocol BGP security is critical to Internet infrastructure, yet progress in routing anomaly detection has been limited by the scarcity of publicly available incident datasets, which contain only 18 recorded cases. We observe that public operator mailing lists, e.g., NANOG and...

A Scenario-Based Evaluation of CRQC+AI Vulnerability Spectrum for TLS 1.3 Cryptographic Dependencies

This paper evaluates quantum and AI-accelerated risks to TLS 1.3 cryptographic dependencies under an evidence-tiered model, distinguishing mechanism-backed threats Shor algorithm against RSA and ECC from contingency-backed risks to lattice-based post-quantum cryptography PQC and hypothesis-only...

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

The Agent Payments Protocol AP2, introduced by Google, enables large language model LLM-driven shopping agents to authorize and execute payments on behalf of users. Its signed Checkout and Payment Mandates protect the integrity of transaction data after signing. Agent interactions and external...

Robustness of Anomaly Detection Models for Industrial Control Systems under Training-Time Data Contamination

Machine-learning-based anomaly detection is increasingly used in industrial control systems ICS, yet most studies assume that detector training data is trustworthy. In practice, training data may be corrupted through compromised logs, labeling errors, manipulated historian records, or unsafe...

YARA-X 1.20.0

YARA-X is a re-incarnation of YARA, a pattern matching tool designed with malware researchers in mind. This new incarnation intends to be faster, safer and more user-friendly than its predecessor. The ultimate goal of YARA-X is replacing YARA as the default pattern matching tool for malware...

WPProbe Plugin Enumeration Tool 0.12.9

A fast WordPress plugin and theme scanner that detects installed plugins via REST API enumeration and themes from HTML discovery, then maps them to known vulnerabilities. Over 5,000 plugins detectable without brute-force, thousands more with it...

PhiShark2026: A Multi-Layer Active-Web Raw-Evidence Dataset for Phishing Website Research

Phishing websites are short-lived and rapidly changing, yet many phishing datasets reduce observations to URLs or precomputed features, constraining researchers to predefined representations and discarding the underlying evidence needed to derive alternative features, apply new extraction methods...

Towards Automated Cyber Threat Intelligence Elicitation in Underground Forums

Cyber threat intelligence from underground forums has traditionally relied on passive monitoring. However, as users have become more aware of large-scale data collection, valuable intelligence has become increasingly rare in open forums, often migrating instead to private or harder-to-reach space...

RAD: Rule-Augmented Relational Anomaly Detection

Anomaly detection is often applied to data stored in relational databases, yet most existing methods require flattening multiple tables into a single feature matrix. This flattening can obscure entity identity, schema structure, and multi-hop dependencies, limiting the detection of anomalies that...

Names Can Hurt: Spotting Slopsquatting Risks Caused by Package Name Hallucinations in Local Coding LLMs

When a code generating language model fabricates a Python package name, an adversary who has pre-registered that name on PyPI can convert that hallucination into a supply chain compromise. This event has been termed as 'slopsquatting'. We propose a two layer detector to counter this issue. The...

SoK: ARCUS: On the Efficiency and Efficacy of Hardware Fuzzing

This work presents a comprehensive analysis of contemporary hardware fuzzing techniques applied across three major abstraction layers: Instruction Set Architecture ISA, microarchitecture, and Register-Transfer Level RTL. Our study examines key factors including input stimulus quality, mutation...

InjecMEM: Memory Injection Attack on LLM Agent Memory Systems

Memory is becoming a default subsystem in deployed LLM agents to provide persistent personalization and continuity. This naturally prompts a question: will memory system introduce new vulnerabilities into agents? Thus we propose InjecMEM, a novel memory injection attack paradigm that requires onl...

Elementor Pro 4.2.1 Unrestricted File Upload Checker

Elementor Pro version 4.2.1 and below contains an unrestricted file upload vulnerability caused by insufficient validation of uploaded file types. Under vulnerable configurations, an unauthenticated attacker may be able to upload dangerous files that can subsequently result in remote code executi...

Effective Pivot Attack Detection Via System and Network Information

Perimeter-based security appliances, such as firewalls or Intrusion Detection Systems, are ineffective against modern attacks that use pivoting, wherein attackers "pivot" traffic through compromised hosts to gain access to additional targets that would otherwise be inaccessible. Due to the...

AgentFlow: A Flow-Centric Policy Language and Framework for Securing LLM Agent Systems

LLM agents increasingly read untrusted content, invoke external tools, access private data, and delegate work to other agents. Harm often arises not from a single unsafe action but from the flow of sensitive data across a sequence of otherwise plausible steps. We present AgentFlow, a flow-centric...

Rust for Secure Backend Development: A Critical Review and Extended Vulnerability Comparison with Node.Js and Django

The Rust programming language is widely credited with eliminating entire classes of memory-safety and concurrency vulnerabilities, but the security implications of adopting it in practice extend well beyond memory safety. This paper presents a critical review of prior work on Rust's security...

A Study of Bluetooth Access Control Based on NFT Soft Pairing

This paper proposes a Non-Fungible Token NFT soft pairing framework for Bluetooth service access control. Unlike conventional Bluetooth systems where pairing implicitly grants persistent service access, the proposed approach decouples native Bluetooth pairing from authorization without modifying...

MCSI: A Masked Commutative Supersingular Isogeny Key Exchange with Blinded Ephemeral Keys

We introduce MCSI, a two message key exchange we design over the CSIDH class group action, in which each party sends its ephemeral public element under an authenticated encryption keyed by the value the two static keys determine. The design gives implicit mutual authentication, hides the ephemera...

Mitigating Explanation Leakage in Financial Fraud Detection Systems

Financial fraud detection relies heavily on centralized machine learning models. This creates serious data privacy risks. Federated Learning FL decentralizes data processing, but financial regulations still require models to be transparent. This means using Explainable AI XAI tools such as...

CodeMechanic: Bug-Property-Guided Program Mitigation

Automated testing discovers vulnerabilities faster than developers can investigate and repair them, leaving an interval in which known memory corruptions remain exploitable. End- to-end LLM repair agents can shorten this interval, but they synthesize open-ended code changes and commonly validate...

ThreatLens: Evidence-Guided Ranking of High-Priority CVEs

Security teams must prioritize vulnerabilities before exploitation evidence is complete. Existing signals, such as CVSS, EPSS, advisories, and public exploits, are useful but fragmented and time-sensitive; retrospective rankings can therefore overstate performance by using evidence unavailable at...

How Reliable Are NVD CWE Labels? A Large-Scale Semantic Audit with Seclometry

CWE labels in the National Vulnerability Database NVD are widely treated as ground truth for vulnerability search, scanner evaluation, benchmark construction, learning-based security tools, and vulnerability prioritization. Yet their reliability has not been systematically measured at scale,...

AI Grinding for Fun and Cryptanalysis

We present an autonomous cryptanalysis workflow in which agents generate, test, and refine hypotheses before human review. The autonomous stage returns reproducible candidates with exact witnesses, controls, code, and run records. A researcher then decides whether the evidence establishes a break...

MARL-Based Sequential RIS Auctions: A Physical-Layer Security Analysis

Reconfigurable intelligent surfaces RISs hold great potential to enhance coverage, spectral efficiency, and communication security by intelligently configuring their reflecting elements. When owned by a neutral RIS operator, these elements can be offered as resources for which legitimate receiver...

On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study

Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security analysts typically assign CVSS scores, but this manual triage does not scale with the growth of disclosed vulnerabilities and often depends on clo...

SkillBloat: Token Amplification Attacks Via Skill Injection in LLM Coding Agents

Agent skills extend coding agents with task-specific instructions, scripts, and resources, but they also create a trusted instruction channel that can be abused beyond conventional security attacks. This paper studies token amplification through skill injection: an economic resource-abuse threat ...

Lessons from the Hardware Hacking Competitions: Verification Techniques, Findings, and Insights

Hardware hacking competitions have emerged as practical platforms for evaluating security weaknesses in complex System-on-Chip SoC designs while promoting security-aware verification and tool development. This paper presents a systematic study of SoC security verification through open-box hardwar...

Eavesdropper-Blind Remote State Preparation and Applications to Quantum Public-Key Encryption

Remote state preparation RSP is a central primitive in quantum cryptography, enabling classical parties to remotely construct quantum states using only classical communication. As a result, RSP serves as a key building block in numerous protocols involving classical clients and quantum servers,...

Explainable Adaptive Zero Trust Framework for AWS with Adversarial Robustness Evaluation

Cloud environments built on Amazon Web Services face a structural security vulnerability: once a credential passes authentication, the resulting session is often treated as trusted for its entire duration. This assumption fails when credentials are stolen. We introduce the Explainable Adaptive Ze...

Workplace Surveillance and Insider Threat Risk Management: Legal Limits and Privacy Harms

Workplace surveillance is used by organizations to protect corporate assets and monitor employee productivity. This research presents two central arguments on workplace surveillance: although surveillance serves legitimate organizational purposes, over-surveillance can violate legal requirements...

Structured but Fragile: On the Limits of LLMs in Cybersecurity Decision-Making

Large language models LLMs are increasingly used in cybersecurity workflows, yet it remains unclear whether they can perform structured security reasoning or merely rely on superficial cues and prior knowledge. We study this question in the context of defence selection over attack graphs derived...

Nimux 1.0.6

Nimux is a native command surface for authorized security assessments. It combines network enumeration, credential validation, Active Directory operations, Kerberos workflows, remote execution, file movement, secrets collection, DCSync, GPO operations, database clients, and SOCKS routing into one...

Vibe Coding and Web Application Security: A Twin-Prompt Study

Large language models increasingly generate complete web applications from natural-language prompts, raising the question of whether explicitly requesting security best practice improves the result. We study six functionally distinct web applications, each generated in two prompt variants that ar...

ClawSentry: A Progressive Multi-Tier Security Monitor for Safeguarding Autonomous LLM Agents

As large language model LLM agents move from conversation to executing code, reading local files, and orchestrating external tools, a single agent hijacked by a malicious third-party skill can cause data exfiltration, privilege escalation, or cascading compromise. We argue that agentic risk is...

Security Games on Series-Parallel Attack Graphs with Adaptive Attackers

We study security games on attack graphs, where an adaptive attacker seeks to reach a target by sequentially attempting stochastic controls along the current attack frontier, while a defender allocates limited resources across controls to delay compromise. The attacker may choose among...

Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems

Retrieval-Augmented Generation RAG grounds Large Language Model LLM outputs in external knowledge, but RAG systems usually trust whatever they retrieve, creating a Security-Reliability Gap: high semantic relevance does not guarantee factual truth. Adversaries exploit this through knowledge...

TraceGrant: A Contract-Governed Security Framework for the Task-Effect Lifecycle of Networked LLM Agents

Networked large language model LLM agents retrieve information from email, cloud storage, calendars, transaction platforms, and Web services to complete multistep tasks that produce persistent external effects. The same content needed for legitimate execution may also contain indirect prompt...

Breaking High Confidence: Practical Face Impersonation under High-Security Thresholds

Face recognition systems FRSs are increasingly deployed in critical real-world services for authentication, such as banking applications and airport identity checks, necessitating stringent security configurations. Consequently, the security vulnerabilities of FRSs have garnered significant...

Enhancing User Resilience against AI-Augmented Phishing: A Two-Stage Framework for Detection and Personalized Training

The rapid development of artificial intelligence, including agents and deepfake techniques, has accelerated phishing attacks and lowered the threshold for attackers. Modern phishing attacks now blend multiple tactics, including social engineering, URL spoofing, and AI deepfakes enabling adversari...

Survival Of~The~Stealthiest: Evolving Low-Entropy Ransomware Via~Genetic Algorithms

Traditional ransomware deployment often relies on massive encryption procedure, triggering immediate detection by modern defense systems. This work introduces a paradigm shift in cryptographic attacks by framing ransomware execution as a Search-Based Software Engineering SBSE optimization problem...

Structural Inference in Undocumented Mobile Databases: A Reproducible Benchmark for Evaluating Agentic Reasoning in Digital Forensics

Agentic large language models are increasingly used in digital forensic analysis, yet their ability to infer relational structure inside undocumented mobile application databases remains poorly understood. In forensic contexts, structurally incorrect inferences can yield results that appear...

Securing Filesystems for Confidential Computing

Confidential computing protects applications inside Trusted Execution Environments TEEs, but it leaves storage vulnerable. Even with disk encryption, a malicious cloud provider can roll back, replay, fork, or tamper with disk state, breaking the integrity and freshness guarantees required by...

The Software Supply Chain As a Market for Lemons: A Multivocal Review of Trust Signal Collapse

Practitioners evaluating open-source dependencies rely on cheap trust signals, e.g., stars, download counts, and contributor activity, as substitutes for direct code inspection, assuming those signals reflect genuine trustworthiness. Prior work has documented individual signal gaming, but the...

Beyond End-To-End Success: Diagnosing Failures in Long-Horizon Security LLM Agents

Long-horizon security LLM agents must carry information and decisions across many dependent interactions, where later actions often depend on services, state, or access discovered much earlier. This makes final task success difficult to interpret: an agent may fail before it ever reaches the poin...