AIJon: Automated Generation of Annotations for Fuzzing

Modern fuzzers use code coverage as feedback to guide their exploration which has proven to be an effective strategy for driving exploration. However, this strategy overlooks inputs that may be interesting to the target program even without uncovering new code paths. Fortunately, prior research h...

A GAN-Based Framework for Robust DDoS Attack Detection

The availability and consistency of online services remain vulnerable due to Distributed Denial of Service DDoS attacks. These attacks are evolving by adopting more complex strategies to evade traditional network security systems. Despite the effectiveness of machine learning models in detecting...

Measuring and Exploiting Implicit Trust in LLM Tool-Calling Pipelines

The Model Context Protocol MCP enables LLMs to invoke external tools, but every tool interaction exposes the model to attacker-controlled text through multiple input channels tool descriptions, tool results, sampling messages that share a single context window without privilege separation. In thi...

Beyond Direct Sensing: Harnessing Indirect Observations from Third-Party Sensors in Vehicle Tracking

Vehicle tracking is fundamental to applications ranging from urban mobility and public safety to security and defense. Conventional tracking relies on direct access to sensors that provide strong observations such as vehicle identity and location. In practice, however, factors such as ownership,...

Red-Teaming Auto Mode: Improving Blocking Classifiers against Malign Coding Agents

To keep coding agents from going off the rails, production systems now review each proposed action with a blocking monitor that can reject it before it runs Auto Mode in Claude Code, Guardian in OpenAI's Codex. Prior evaluations of such monitors largely measure robustness to accidental harm or...

When Agents Look like Beacons: NIDS Evasion by Model Context Protocol Traffic

The Model Context Protocol MCP standardizes communication between autonomous Artificial Intelligence AI agents and remote tools over Streamable HTTP. This shift introduces a class of machine-generated, authenticated, and high-frequency JSON-RPC traffic directly into enterprise networks. Enterpris...

CASHEWS: Source Preprocessor for LLM-Based Malicious Package Detection

Malicious npm package detection tools now leverage LLMs' semantic understanding of source code to detect malicious intent at scale. This capability has proven invaluable in identifying packages involved in recent supply-chain attacks such as Shai-Hulud. However, threat actors exploit the limited...

A Security Risk Assessment Framework for AI-Powered Development Tools

AI-powered development tools are now widely used to generate code and assist developers with routine programming tasks. Although existing work has identified vulnerabilities in AI-generated code, security-oriented work is often focused on vulnerability detection rather than risk assessment. To...

CISA: Using Cyber Decoys to Strengthen Detection and Response

CISA developed this guidance to help defensive teams at varying levels of cybersecurity maturity plan and implement cyber decoy strategies that strengthen their detection and response capabilities. Many organizations struggle to detect adversaries who use legitimate credentials, native tools, and...

AgentLSD: Evaluating AI Security Agents under Adversarial Task Contamination

AI agents for security inspect web pages, source code, logs, configuration files, and command outputs. These environments may contain deceptive artifacts that influence the agent's behavior. We call this adversarial task contamination. Whereas prompt injection relies on attacker-supplied...

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, automated testing unaffordable for the smaller organisations that need it most. This paper presents PentestChain, a ten-phase automated penetration...

Cyber Exodus: Burnout Symptoms, Exit Intention, and Peer Response in Online Cybersecurity Communities

Security practitioners burn out at high rates, and the resulting attrition is itself a security problem. This workforce is hard to study: security operations centers are closed to outside researchers, studies that reach practitioners recruit through employers, and those who have disengaged most m...

An Exploratory Study of Dependabot Cooldown Adoption in Open-Source GitHub Projects

Automated dependency updates can rapidly propagate malicious package releases before maintainers and the broader community have enough time to detect them. In July 2025, GitHub made Dependabot cooldown generally available as a defense against software supply chain attacks. However, the effects of...

From Hypervisor to Container: Cloud Security Vulnerabilities, Defense Mechanisms, and Open Challenges

In cloud computing, different users share the same physical hardware, which creates serious security risks. To protect data, cloud systems rely on virtual machines and containers to keep users isolated. This paper reviews over 120 security publications from 2008 to 2025, focusing on how these...

Toward Secure AI-Powered Penetration Testing Agents: Security Threats, Guardrails, and Architectural Perspectives

LLM-powered autonomous agents are transforming the penetration testing space with dynamic, multi-step offensive security workflows that require minimal supervision by humans. These agents leverage sophisticated reasoning abilities and external security tools to independently carry out...

Cybersecurity in Power Grids: Standards and Research Challenges

This paper examines Smart Grid cybersecurity, emphasizing the critical distinctions between IT and OT environments. It analyzes grid architecture, substation threats, and key international standards, specifically IEC 62351, IEC 62443, and ISO 27001. Finally, it overviews latest research trends,...

Integrated Quantum-Secured Cryptographic Memory in Customizable Single Nanodiamonds

As advanced physical cloning and cyber-extraction techniques proliferate, achieving absolute hardware-level information security has become a paramount global challenge. Conventional architectures systems are fundamentally vulnerable because deterministic memory and cryptographic hardware are...

You Shall Not Pass into Ring-0! a User Privacy-Friendly Anti-Cheat Architecture for Personal Computers

Kernel-level anti-cheats are effective against malicious player behavior in competitive video games, but raise significant user privacy concerns regarding installing unverifiable components at privileged modes i.e., ring-0 in x86. While existing research has focused on improving the effectiveness...

Evaluating the Impact of Personalization in Conversational Cybersecurity Assistants

Users increasingly turn to Large Language Models to answer a variety of questions, including cybersecurity questions. We study how personalization strategies can help improve the effectiveness of answers to questions asked to an LLM-based cybersecurity assistant. Beyond accuracy, we focus on the...

Joern 4.0.628

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...

Suricata IDPE 8.0.7

Suricata is a network intrusion detection and prevention engine developed by the Open Information Security Foundation and its supporting vendors. The engine is multi-threaded and has native IPv6 support. It's capable of loading existing Snort rules and signatures and supports the Barnyard and...

Wazuh 4.10.5

Wazuh is a free and open source security platform that unifies XDR and SIEM capabilities. It protects workloads across on-premises, virtualized, containerized, and cloud-based environments. This is the source code release...

Zeek 9.0.0

Zeek is a powerful network analysis framework that is much different from the typical IDS you may know. While focusing on network security monitoring, Zeek provides a comprehensive platform for more general network traffic analysis as well. Well grounded in more than 15 years of research, Zeek ha...

GANADI: Uncovering C/C++ OSS Reuse Genealogies Via Pivotal Function-Based Clustering to Enhance Supply Chain Security

We present GANADI, a systematic approach for identifying C/C++ OSS reuse genealogies to enhance software supply chain security. Understanding OSS reuse genealogy is crucial for improving SBOM completeness and prioritizing security remediation across supply chains. Although existing approaches can...

DDRop: Active Memory Interposer Attacks on Confidential VMs by Dropping DDR5 Writes

Trusted Execution Environments TEEs are increasingly deployed in the cloud to protect sensitive workloads through hardware-enforced isolation, remote attestation, and transparent memory encryption. However, to meet memory performance and size demands, modern TEEs omit cryptographic freshness...

SEMA-GUARD: Semantic and Graph-Based Vulnerability Detection in Assembly Code

In cases where source code is not available, such as malware analysis, firmware analysis, and embedded systems analysis, vulnerability detection in compiled programs has gained importance. Current methods are heavily reliant on syntactical regularities or higher level representations that are...

RobResilience: Implementing and Evaluating a Resilience Framework for Cyber-Physical Embodied Systems

In embodied cyber-physical systems, active cyberattacks pose an immediate threat not just to data, but to physical integrity and human safety. While existing security approaches excel at detection, they lack the runtime mechanisms to determine whether a disruption is tolerable or if performance...

Unconditional Security of Discrete-Modulated CV-QKD from Infinite-Dimensional MEAT

Discrete-Modulated DM Continuous-Variable CV Quantum Key Distribution QKD is an experimentally attractive approach to quantum cryptography, offering high key rates over metropolitan-scale distances while relying on state-of-the-art telecom infrastructure. However, a fundamental gap has remained...

Docker Containers Vs. Virtual Machines: A Comparative Study of Architecture, Performance, Configuration, and Security

Modern application platforms must isolate workloads while preserving deployment speed, portability, resource efficiency, and security. Virtual machines VMs and Docker containers address this requirement at different abstraction layers: VMs virtualize hardware and run independent guest operating...

Permutation-Based Stegomalware in Large Language Models: Threats and Countermeasures

The difficulty of training large language models LLMs, together with their ubiquity, raises the threat of stegomalware, where malicious payloads are embedded into model weights. Recent work has demonstrated the use of permutation symmetry in model weights to mitigate these threats, but failed to...

Mapping U.S. Federal AI Governance against Sector Vulnerability

Artificial intelligence AI poses different levels of risk across sectors, but are these differences reflected in U.S. federal AI governance? To help answer this question, we assess 684 federal AI governance documents for their coverage of 14 sectors and 24 AI risks. We measure coverage as breadth...

Understanding the Usability of Cryptographic Verification Tools

Cryptographic protocol verification tools are widely used to analyze the security of complex protocols, yet how users interact with these tools remains comparatively understudied. We present an exploratory human-centered study of experienced users of Tamarin, ProVerif, and related protocol...

Illusion of Depth: Revealing Hidden Stereo Vision Vulnerabilities in Depth Estimation

Stereo cameras are integrated into autonomous systems such as self-driving cars, drones, and robots to offer precise depth estimation in a cost-effective manner compared to LiDAR technology. In this work, we reveal an intrinsic vulnerability in stereo cameras that stems from their pixel sampling...

Evaluating the NIST Bugs Framework against CWE As a Successor for Automated Vulnerability Classification

Vulnerability classification based on root cause weaknesses is essential for numerous cybersecurity activities, where the Common Weakness Enumeration CWE serves as a public repository of such flaws. However, its overlapping entries create a non-orthogonal structure. The result is the same...

GPUThor: Amplifying Rowhammer Attacks Via Non-Uniform Patterns to Exploit ECC-Protected GPUs

GDDR memory in GPUs is vulnerable to Rowhammer attacks, where rapid memory accesses induce bit flips in adjacent cells, enabling data tampering and privilege escalation. However, prior GPU Rowhammer attacks trigger only tens to hundreds of bit flips, orders of magnitude fewer than CPU attacks,...

Windows Print Processor Persistence

This Metasploit module establishes persistence by registering a malicious Print Processor DLL under HKLM\SYSTEM\CurrentControlSet\Control\Print\Environments\arch\Print Processors. The Print Spooler service loads configured processor DLLs at startup, causing payload execution when the spooler...

libpcap 1.11.0

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

Windows Push Notifications Local Privilege Escalation Research

Microsoft Windows contains a race condition in the Push Notifications service that can result in local privilege escalation. Research into patched and unpatched versions of wpncore.dll identifies a use-after-free condition involving PresentationEndpointFacade methods during notification platform...

Security Framework for Practical Quantum Key Distribution with Imperfect Devices

Practical quantum key distribution QKD systems inevitably exhibit imperfections in both the source and detector. At the same time, the behavior of these imperfect devices is never exactly known due to characterization uncertainty, parameter fluctuations, and potential influence by an adversary. I...

PIDS-Bench: Evaluating Prompt-Injection Detectors under Over-Defense, Obfuscation, and Distribution Shift

Prompt-injection detectors are typically evaluated using aggregate F1 on in-distribution test data, which offers limited insight into behavior under distribution shift, particularly on the benign side of the decision boundary, where false positives impose direct operational cost yet are seldom...

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

Backdoor poisoning attacks add poisoned examples to otherwise-clean finetuning data, pairing a trigger with a target behavior that the model learns to produce when the trigger appears. Existing evaluations typically fix the number of poisoned examples and sample them at random from a candidate...

SpliTEE: Improving LLM Inference on Trusted Hardware with Differentially Private GPU Outsourcing

User prompts provided to large language models LLMs may contain sensitive or private information that can be misused by remotely deployed models, such as through inadvertent memorization during retraining. One way to protect user prompts is to execute the LLM inside a trusted execution environmen...

Sociotechnical Aspects of Tor Relay Rejection

In 2019, the Tor Project enforced an end-of-life EoL policy for Tor versions, leading to the rejection of outdated relays, amounting to a notable fraction of consensus weight. While this policy aids network maintenance, reduces backporting efforts, and shortens vulnerability exposure, its...

An Empirical Security Analysis of Open-Source Software Used in Onboard Satellite Systems

The use of open-source software OSS in satellite flight systems is increasing as missions adopt reusable frameworks, shared libraries, and community-maintained components. While this accelerates development, it also introduces software-security risks into systems where patching is costly and...

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic frameworks such as MulVAL to contemporary security workflows or agentic pipelines, however, requires translating scanner evidence to initial facts, and...

Tractable Defense against Advanced Persistent Threats in Networked Settings

Recently, the theory of Boolean Dynamical Systems was proposed to study the decision theory surrounding the defense of computer networks against Advanced Persistent Threats APTs. Boolean Dynamical Systems naturally capture four first principle primitives of APTs: the stealthy nature of attacks,...

HYDRA: Quantifying Botnet Resource Thresholds for Efficient Link-Flooding Attacks on LEO Satellite Networks

Low Earth orbit LEO satellite constellations, such as Starlink and Kuiper, are rapidly emerging as a critical backbone for low-latency global connectivity. As these systems expand, they become more attractive attack targets, necessitating increased resilience and security. Threat actors seek to...

The Model Proposes, the Code Disposes: A Pre-Registered Ablation of a Verifier-And-Acceptance Stage in an LLM-Orchestrated Offensive-Security Agent

We evaluate whether a verifier-and-acceptance stage - a model verifier whose verdicts are enforced by deterministic code - changes what an LLM-driven offensive-security agent reports. We report a 15-run exploratory pilot, a pre-registered 20-run confirmatory ablation, and a pre-registered 2 x 2...

Vulnerability Localization Benchmark: Measuring Agentic Security Analysis at Repository Scale

Language-model agents increasingly operate over complete software repositories, yet cybersecurity evaluations primarily measure whether they can detect, reproduce, or repair vulnerabilities rather than whether they can locate the relevant code. We study vulnerability localization: given a weaknes...

Adversarial Testing of Automated Program Repair Agents for Security Vulnerabilities

Software agents with Large Language Models LLMs are designed for Automated Program Repair APR tasks, raising the possibility that, in the near future, APR agents will fix bugs automatically without much human intervention. Can we trust an APR agent to produce both functionally correct and secure...