ARTA: Adaptive Reinforcement-Learning-Based Throttling Agent for RowHammer Vulnerabilities

RowHammer vulnerability continues to intensify with DRAM scaling, reducing the activation threshold needed to induce bitflips and rendering existing defenses such as TRR, ECC, and refresh-based mechanisms vulnerable to sophisticated multi-bank hammering patterns. This work presents ARTA, a...

Closing the Sim-To-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDR

Leading commercial endpoint detection and response EDR products have shifted from operator-configured rule sets to multi-component systems where autonomous AI components operate alongside, and increasingly in place of, operator-deployed policies. Autonomous defense agents using commercial EDR as...

Hiding in Plain Floats: Steganographic Carriers for Indirect Prompt and Content Injection

Text-centered prompt-injection defenses assume that the malicious signal is visible in one of the inspected text views. We study a reproducible LLM01-style indirect prompt/content-injection failure mode where that assumption breaks: a payload caught in plain English slips past the same detector...

An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response

University Academic Management Information Systems ACMIS are high-value targets for a wide spectrum of security threats including brute-force login attacks, payment fraud, privilege escalation, insider data theft, and academic integrity violations. Traditional rule-based intrusion detection syste...

Ternary Public-Key Cryptosystem

Public-key cryptosystems eliminate the requirement for pre-shared secret keys by enabling encryption with a publicly disclosed key and decryption with a corresponding private key. In this article we generalize the public-key cryptosystems to ternary algebraic structures, with particular attention...

Beyond Pass/Fail: Using Process Mining to Understand How LLMs Resist (And Fail) Red Team Attacks

Standard AI red teaming evaluations reduce adversarial campaigns to a single binary outcome, attack success rate ASR, not taking into account the sequential structure of how models resist or yield to attacks. We propose applying process mining, a discipline for discovering and analyzing process...

The Sound of Malware: A Memory Forensics Approach for Android Malware Analysis Via Audio Signals

Android malware analysis is currently facing increasing challenges in achieving robust classification and detecting stealth attacks. Modern threats employ advanced evasion strategies such as code obfuscation, dynamic loading, packing, and even steganographic manipulation of traditional static and...

FDM: A Framework for Decision-Making to Build ML-Based Malware Detection Systems

Selecting appropriate machine learning ML configurations for malware detection is a complex, multi-criteria problem. Model choice, feature engineering, and update mechanisms must jointly satisfy operational constraints that vary across deployment contexts. This paper proposes the Framework for...

MalSkillBench: A Runtime-Verified Benchmark of Malicious Agent Skills

AI coding agents such as Claude Code and Gemini CLI increasingly extend themselves with third-party skills: markdown packages bundling natural-language instructions, executable scripts, and tool permissions. Because a skill is at once code and agent-facing instruction, it introduces a supply chai...

Lyrion Music Server 9.2.0 metadata Persistent Cross Site Scripting

Lyrion Music Server version 9.2.0 stores media file metadata tags such as GENRE, ARTIST, and ALBUM exactly as written in the file and later renders them in its web interface without HTML-encoding, resulting in persistent cross site scripting. An attacker who gets a file with a malicious tag into...

FIFOFox: Windows Named-Pipe Security Auditor and Fuzzer

FIFOFox is a Windows named-pipe security assessment tool for identifying weak pipe permissions, pipe-squatting exposure, and named-pipe impersonation attack paths. It combines passive auditing with authorized active testing, including fuzzing and interception-style capture, to help defenders find...

Demand-Driven Vulnerability Detection for Cloud Security Posture Management: Removing Human Rule Authoring from the Disclosure-To-Protection Critical Path

Cloud Security Posture Management CSPM systems detect known vulnerabilities by maintaining a rule set, distributing it to customers, and evaluating it against periodically-collected asset inventories. To our knowledge, in publicly documented architectures the rule set is environment-agnostic and...

Lost in Migration: Exposing Android Framework Vulnerabilities in Parallel Java-Kotlin Implementations

Android has adopted Kotlin alongside Java across apps and core system components. During this shift, we observe parallel implementations in the Android Open Source Project AOSP where the same component is implemented in both Java and Kotlin. In principle, their functional purposes are identical. ...

RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks

Reasoning-capable large language models can be induced to spend their generation budget on injected decoy tasks rather than answering the user's question, causing denial of service when no final answer is produced and denial of wallet when excess output tokens are billed. Input-side safety...

ScaleDisturb: Exploiting Temporal Asymmetry to Amplify Read Disturbance in Modern DRAM Chips

DRAM suffers from read disturbance phenomena e.g., RowHammer and RowPress, where repeatedly accessing or continuously keeping open a DRAM row aggressor row induces bitflips in other physically nearby unaccessed rows victim rows. The disturbance mechanism is practically exploitable from the softwa...

MOLOT System Card: Malicious Operational Logic Observation Transformer

MOLOT Malicious Operational Logic Observation Transformer is a static malicious-code detection system designed for SAST setup where package metadata, maintainer history, and dynamic execution traces may be unavailable or unreliable. The system represents source code as behavior sequences derived...

Revive Adserver 6.0.6 XSS / SQL Injection / Code Injection

Revive Adserver versions 6.0.6 and below suffer from access control, code injection, cross site scripting, and remote SQL injection vulnerabilities...

Rethinking IoT Intrusion Detection: Augmenting Routing Metrics with Radio Features

Machine learning-based intrusion detection systems IDS for RPL-based IoT networks often rely solely on routing layer features, which provide only a partial view of network behaviour. In this work, we investigate whether incorporating Transmit TX and Receive RX radio features alongside the standar...

ClickFix Server Creation

This Metasploit module creates a web server which hosts a ClickFix type exploit. When a user visits the site they are given instructions on pasting our payload into a run dialog. When using a custom html page, please use INSERTPAYLOADHERE as the spot to put the generated payload in...

Drupal Core SQL Injection Scanner

CVE-2026-9082 is a remote SQL Injection vulnerability in Drupal Core's database abstraction layer. It affects only sites using PostgreSQL as the database backend. This code simply checks to see if vulnerability endpoints exist and reports back. It is not an exploit...

Synthetic APTs: The Collapse of TTP-Based Attribution

Cyber Threat Intelligence CTI attribution relies on identifying the Tactics, Techniques, and Procedures TTPs that distinguish one threat actor from another. This approach presupposes that each adversary leaves a recognizable operational fingerprint. This work investigates whether AI driven...

Empirical Evaluation of Large Language Models for Migration of Code Fragments to Post-Quantum Cryptography

The transition to post-quantum cryptography PQC requires not only replacing vulnerable cryptographic primitives, but also refactoring the surrounding software logic. While existing PQC migration frameworks provide organizational guidance, practical code-level remediation remains largely manual an...

POISE: Position-Aware Undetectable Skill Injection on LLM Agents

Agent skills provide a lightweight mechanism for extending general-purpose agents, but their open format exposes them to skill-poisoning attacks. A practically dangerous injection must stay invisible: if executing the payload derails the user's legitimate task, the resulting failure signal invite...

TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection

Autonomous spacecraft require rapid, lightweight, and reliable onboard detection of cyber-RF threats. Using the SPARTA attack model, we analyze the latency-accuracy trade-offs of TinyML-compatible classical models -- Random Forest, Logistic Regression, SVM, and MLP -- for detecting uplink jamming...

CodeQL 2.25.6

Discover vulnerabilities across a codebase with CodeQL, an industry-leading semantic code analysis engine. CodeQL lets you query code as though it were data. Write a query to find all variants of a vulnerability, eradicating it forever. Then share your query to help others do the same...

Joern 4.0.554

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...

WebMCP Tool Surface Poisoning: Runtime Manipulation Attacks on LLM Agents

WebMCP is a newly emerging protocol that enables websites to expose tools directly to AI agents, bypassing traditional user interfaces and introducing new security risks. The dynamic exposure of agent-accessible tools in WebMCP expands the attack surface of web sessions, especially when third-par...

Membrane: A Self-Evolving Contrastive Safety Memory for LLM Agent Defense

Despite advances in safety alignment, large language models remain vulnerable to continuously evolving jailbreaks. Existing fine-tuned safety classifiers cannot adapt to these evolving attacks, while adaptive memory-based guardrails tend to over-refuse benign queries that resemble stored attacks...

Cognitive Threat Intelligence and Explainable Federated Security Analytics for Distributed Infrastructure Systems

The increasing adoption of distributed infrastructure systems, cloud computing, Internet of Things IoT technologies, and edge-based architectures has significantly expanded the cybersecurity attack surface and introduced increasingly sophisticated cyber threats. Conventional centralized intrusion...

Securing the Sandbox: A Rootless Containerized Framework for Process-Oriented Monitoring in Computer Graphics Education

Computer Science education fundamentally depends on intensive laboratory hours to foster true programming mastery and logical reasoning. However, the widespread adoption of Generative Artificial Intelligence AI has made it virtually impossible to distinguish authentic student effort from instant ...

Exploring the Connection between Coding Habits and Cognitive Styles in Malware Developers

Malware research primarily studies the results, the methods, and the impact. Even from an offensive security perspective, what is examined is the method, not the development strategy of the offender. This study investigates the behavioral signatures and coding patterns embedded in the malware...

Opportunities and Challenges in Securely Reusing and Repurposing Mobile Devices

An estimated 5.3 billion mobile phones became electronic waste in 2022. Many of these devices can be repurposed and used in different contexts to extend their lifetime and to reduce ecological impacts. An often overlooked aspect of smartphone reuse is cybersecurity: these devices embed...

Steering LLM Viewpoints through Fabricated Evidence Injection

As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cognitive vulnerability in LLMs: their tendency to uncritically trust external context when presented with fabricated...

ExploitBench AI Exploit Benchmark Tool

ExploitBench measures how far AI agents climb, from reaching vulnerable code, to triggering the bug, to building exploit primitives, to arbitrary code execution...

Next.js Concurrent Version Exposure / Vulnerability Audit Tool

This Python script is a lightweight defensive auditing utility designed to identify websites running Next.js and determine whether their detected version falls within predefined potentially vulnerable version ranges...

GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

Rule-based Intrusion Detection and Prevention Systems IDPS offer precise attack detection as well as mitigation, however their manually crafted, signature-driven rules limit adaptability to emerging and zero-day threats. Additionally, existing public datasets e.g., CICIDS2017, UNSW-NB15 focus on...

RedEdit: Agentic Red-Teaming of Image Safety Classifiers Via MCTS-Guided Photo-Editing

Image safety classifiers serve as a critical component of contemporary content moderation systems on the internet. However, their resilience against user-style malicious image editing remains underexplored. Such behaviors are highly prevalent in daily scenarios but difficult to fully reproduce. T...

ExploitGym AI Exploit Benchmark Tool

ExploitGym is a large-scale, realistic benchmark built from real-world vulnerabilities designed to evaluate AI agents' ability to develop exploits...

Credential Disclosure in (EU) Digital Identity Wallets: Privacy Risks and Practical Mitigations

The European Union will introduce the EUDI Wallet by late 2026, which allows users to hold digital credentials i.e., representations of physical official identity documents on their devices. This will allow users to securely and privately disclose identity attributes to websites. Although such a...

angr 9.2.221

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

The increasing penetrations of the critical infrastructure sector in the United States with intelligent digital technologies have greatly increased exposure to advanced cyber adversaries and operational vulnerabilities. AI-powered governance and automated decision-making systems are becoming a ke...

MalTree: Tracing Malware Evolution from Embeddings at Scale

Malware detection remains largely reactive: machine learning models trained on known samples degrade as threats evolve. Understanding evolutionary relationships among malware families can inform proactive defense, but traditional reverse engineering can take months to years to uncover such lineag...

An Improved CNN-LSTM Based Intrusion Detection System for IoT Networks

With the rapid proliferation of IoT devices, security concerns have dramatically escalated and intrusion detection systems have become critical for protecting networked environments. This paper presents an improved CNN-LSTM based intrusion detection model that combines multi-class classification,...

Dimensionality Reduction for Cyberattack Classification: A Comparative Evaluation of PCA and Linear Predictive Coding

High-dimensional feature representations are widely used in machine learning-based cyberattack detection systems. However, they increase computational complexity and may hinder deployment in resource-constrained environments. In this paper, we investigate feature compression techniques for...

CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-To-End Cybersecurity Capabilities

AI has the potential to transform cybersecurity by enabling systems that can autonomously detect, analyze, and remediate software vulnerabilities. However, existing cybersecurity evaluations of AI systems are limited in scale or scope, and fail to capture the end-to-end lifecycle of real-world...

NLLog: Lightweight, Explainable SOC Anomaly Detection Via Log-To-Language Rewriting

System-generated logs underpin security monitoring, yet their rigid template-based format hinders both automated analysis and human comprehension. We present NLLog Natural-Language Log, a lightweight pipeline that deterministically rewrites parsed templates into WHO-WHAT-SEVERITY sentences, pools...

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-Based Vulnerability Detection with Open-Weight Models

Large language models LLMs have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generation RAG settings. However, for approaches relying on proprietary models and APIs, reproducibility and replicability remain largely unexplored, raising...

MCPJam Inspector 1.4.2 Defensive API Security Assessment Tool

This Python-based defensive auditing tool evaluates the exposure and security posture of MCP-related API endpoints in a controlled and authorized environment. It is designed to assist security teams in identifying insecure API configurations, exposed execution interfaces, and potential operationa...

Remote Sunrise Helper for Windows GUI Boundary / Access Control Integrity Auditor

This is a script that tests GUI boundary and access controls in Remote Sunrise Helper for Windows. It launches the application, waits for the target window, and provides manual testing guidance. It does not validate process-boundary handling by itself, does not target any specific known...

Linux Kernel FD-Race Monitoring

This C program is a defensive process-monitoring utility, not a privilege-escalation exploit. It continuously inspects /proc/pid/fd to detect suspicious activity related to excessive file descriptor usage, activity from sensitive SUID binaries, and potential file descriptor leakage or theft...