FirmReBugger: A Benchmark Framework for Monolithic Firmware Fuzzers

Monolithic Firmware is widespread. Unsurprisingly, fuzz testing firmware is an active research field with new advances addressing the unique challenges in the domain. However, understanding and evaluating improvements by deriving metrics such as code coverage and unique crashes are problematic,...

Logwatch 7.14

Logwatch analyzes and reports on unix system logs. It is a customizable and pluggable log monitoring system which will go through the logs for a given period of time and make a customizable report. It should work right out of the package on most systems...

Introducing the Generative Application Firewall (GAF)

This paper introduces the Generative Application Firewall GAF, a new architectural layer for securing LLM applications. Existing defenses -- prompt filters, guardrails, and data-masking -- remain fragmented; GAF unifies them into a single enforcement point, much like a WAF coordinates defenses fo...

CAFE-GB: Scalable and Stable Feature Selection for Malware Detection Via Chunk-Wise Aggregated Gradient Boosting

High-dimensional malware datasets often exhibit feature redundancy, instability, and scalability limitations, which hinder the effectiveness and interpretability of machine learning-based malware detection systems. Although feature selection is commonly employed to mitigate these issues, many...

CISA: Suspicious Unmanned Aircraft System Activity Guidance V2

Suspicious Unmanned Aircraft System Activity Guidance for Critical Infrastructure Owners and Operators is intended for critical infrastructure stakeholders who are concerned with unmanned aircraft system UAS activity near or around their facilities. This is version 2 of CISA's document...

CISA: Principles for the Secure Integration of Artificial Intelligence in Operational Technology V2

Artificial intelligence AI has the potential to increase efficiency and productivity, enhance decision-making, cut costs and improve customer experience, but introducing AI in operational technology OT environments can introduce risks that require careful management to support the safety, securit...

On Implementing Hybrid Post-Quantum End-To-End Encryption

The emergence of quantum computing poses a fundamental threat to current public key cryptographic systems. This threat is necessitating a transition to quantum resistant cryptographic alternatives in all the applications. In this work, we present the implementation of a practical hybrid end-to-en...

Lightweight LLMs for Network Attack Detection in IoT Networks

The rapid growth of Internet of Things IoT devices has increased the scale and diversity of cyberattacks, exposing limitations in traditional intrusion detection systems. Classical machine learning ML models such as Random Forest and Support Vector Machine perform well on known attacks but requir...

Side-Channel Attacks on Open VSwitch

Virtualization is widely adopted in cloud systems to manage resource sharing among users. A virtualized environment usually deploys a virtual switch within the host system to enable virtual machines to communicate with each other and with the physical network. The Open vSwitch OVS is one of the...

DCeption: Real-World Wireless Man-In-The-Middle Attacks against CCS EV Charging

The adoption of Electric Vehicles EVs is happening at a rapid pace. To ensure fast and safe charging, complex communication is required between the vehicle and the charging station. In the globally used Combined Charging System CCS, this communication is carried over the HomePlug Green PHY HPGP...

SAGA: Detecting Security Vulnerabilities Using Static Aspect Analysis

Python is one of the most popular programming languages; as such, projects written in Python involve an increasing number of diverse security vulnerabilities. However, existing state-of-the-art analysis tools for Python only support a few vulnerability types. Hence, there is a need to detect a...

Burp Global Match and Replace Extension 1.0.0

This archive provides a system-wide match and replace table that applies to all Burp tools including Burp AI. This goes beyond Proxy Match and Replace, which only affects Proxy...

Malicious PixelCode Delivery Technique

Malicious PixelCode is a security research project that demonstrates a covert technique for encoding executable files into pixel data and storing them inside images or videos. A lightweight loader retrieves the media file, reconstructs the original binary, and executes it in memory. This project...

Stegano 2.1.0

Stegano is a basic Python Steganography module. Stegano implements two methods of hiding: using the red portion of a pixel to hide ASCII messages, and using the Least Significant Bit LSB technique. It is possible to use a more advanced LSB method based on integers sets. The sets Sieve of...

Towards Cybersecurity Superintelligence: From AI-Guided Humans to Human-Guided AI

Cybersecurity superintelligence -- artificial intelligence exceeding the best human capability in both speed and strategic reasoning -- represents the next frontier in security. This paper documents the emergence of such capability through three major contributions that have pioneered the field o...

PINA: Prompt Injection Attack against Navigation Agents

Navigation agents powered by large language models LLMs convert natural language instructions into executable plans and actions. Compared to text-based applications, their security is far more critical: a successful prompt injection attack does not just alter outputs but can directly misguide...

AttackMate: Realistic Emulation and Automation of Cyber Attack Scenarios across the Kill Chain

Adversary emulation tools facilitate scripting and automated execution of cyber attack chains, thereby reducing costs and manual expert effort required for security testing, cyber exercises, and intrusion detection research. However, due to the fact that existing tools typically rely on agents...

A Survey of Security Challenges and Solutions for Advanced Air Mobility and EVTOL Aircraft

This survey reviews the existing and envisioned security vulnerabilities and defense mechanisms relevant to Advanced Air Mobility AAM systems, with a focus on electric vertical takeoff and landing eVTOL aircraft. Drawing from vulnerabilities in the avionics in commercial aviation and the automate...

HardSecBench: Benchmarking the Security Awareness of LLMs for Hardware Code Generation

Large language models LLMs are being increasingly integrated into practical hardware and firmware development pipelines for code generation. Existing studies have primarily focused on evaluating the functional correctness of LLM-generated code, yet paid limited attention to its security issues...

Enhanced Cyber Threat Intelligence by Network Forensic Analysis for Ransomware As a Service(RaaS) Malwares

In the current era of interconnected cyberspace, there is an adverse effect of ransomware on individuals, startups, and large companies. Cybercriminals hold digital assets till the demand for payment is made. The success of ransomware upsurged with the introduction of Ransomware as a ServiceRaaS...

AI Agents Vs. Human Investigators: Balancing Automation, Security, and Expertise in Cyber Forensic Analysis

In an era where cyber threats are rapidly evolving, the reliability of cyber forensic analysis has become increasingly critical for effective digital investigations and cybersecurity responses. AI agents are being adopted across digital forensic practices due to their ability to automate processe...

Holmes: An Evidence-Grounded LLM Agent for Auditable DDoS Investigation in Cloud Networks

Cloud environments face frequent DDoS threats due to centralized resources and broad attack surfaces. Modern cloud-native DDoS attacks further evolve rapidly and often blend multi-vector strategies, creating an operational dilemma: defenders need wire-speed monitoring while also requiring...

Rethinking On-Device LLM Reasoning: Why Analogical Mapping Outperforms Abstract Thinking for IoT DDoS Detection

The rapid expansion of IoT deployments has intensified cybersecurity threats, notably Distributed Denial of Service DDoS attacks, characterized by increasingly sophisticated patterns. Leveraging Generative AI through On-Device Large Language Models ODLLMs provides a viable solution for real-time...

A Prompt-Based Framework for Loop Vulnerability Detection Using Local LLMs

Loop vulnerabilities are one major risky construct in software development. They can easily lead to infinite loops or executions, exhaust resources, or introduce logical errors that degrade performance and compromise security. The problem are often undetected by traditional static analyzers becau...

LLM Security and Safety: Insights from Homotopy-Inspired Prompt Obfuscation

In this study, we propose a homotopy-inspired prompt obfuscation framework to enhance understanding of security and safety vulnerabilities in Large Language Models LLMs. By systematically applying carefully engineered prompts, we demonstrate how latent model behaviors can be influenced in...

SecureSplit: Mitigating Backdoor Attacks in Split Learning

Split Learning SL offers a framework for collaborative model training that respects data privacy by allowing participants to share the same dataset while maintaining distinct feature sets. However, SL is susceptible to backdoor attacks, in which malicious clients subtly alter their embeddings to...

Constructing Multi-Label Hierarchical Classification Models for MITRE ATT&CK Text Tagging

MITRE ATT&CK is a cybersecurity knowledge base that organizes threat actor and cyber-attack information into a set of tactics describing the reasons and goals threat actors have for carrying out attacks, with each tactic having a set of techniques that describe the potential methods used in these...

An Empirical Study on Remote Code Execution in Machine Learning Model Hosting Ecosystems

Model-sharing platforms, such as Hugging Face, ModelScope, and OpenCSG, have become central to modern machine learning development, enabling developers to share, load, and fine-tune pre-trained models with minimal effort. However, the flexibility of these ecosystems introduces a critical security...

Unpacking Security Scanners for GitHub Actions Workflows

GitHub Actions is a widely used platform that allows developers to automate the build and deployment of their projects through configurable workflows. As the platform's popularity continues to grow, it has become a target of choice for recent software supply chain attacks. These attacks exploit...

VulnResolver: A Hybrid Agent Framework for LLM-Based Automated Vulnerability Issue Resolution

As software systems grow in complexity, security vulnerabilities have become increasingly prevalent, posing serious risks and economic costs. Although automated detection tools such as fuzzers have advanced considerably, effective resolution still often depends on human expertise. Existing...

Uncovering and Understanding FPR Manipulation Attack in Industrial IoT Networks

In the network security domain, due to practical issues -- including imbalanced data and heterogeneous legitimate network traffic -- adversarial attacks in machine learning-based NIDSs have been viewed as attack packets misclassified as benign. Due to this prevailing belief, the possibility of...

PrivFly: A Privacy-Preserving Self-Supervised Framework for Rare Attack Detection in IoFT

The Internet of Flying Things IoFT plays a vital role in modern applications such as aerial surveillance and smart mobility. However, it remains highly vulnerable to cyberattacks that threaten the confidentiality, integrity, and availability of sensitive data. Developing effective intrusion...

Techniques of Modern Attacks

The techniques used in modern attacks have become an important factor for investigation. As we advance further into the digital age, cyber attackers are employing increasingly sophisticated and highly threatening methods. These attacks target not only organizations and governments but also extend...

Sockpuppetting: Jailbreaking LLMs without Optimization through Output Prefix Injection

As open-weight large language models LLMs increase in capabilities, safeguarding them against malicious prompts and understanding possible attack vectors becomes ever more important. While automated jailbreaking methods like GCG Zou et al., 2023 remain effective, they often require substantial...

StackWarp: Breaking AMD SEV-SNP Integrity via Deterministic Stack-Pointer Manipulation through the CPU's Stack Engine

In this paper, the authors present StackWarp, a software-based architectural attack exploiting the stack engine on AMD Zen CPUs to modify the stack pointer within an SEV-SNP guest, fully breaking integrity...

Unicornscan 0.4.43

Unicornscan is an information gathering and correlation engine built for and by members of the security research and testing communities. It was designed to provide an engine that is Scalable, Accurate, Flexible, and Efficient. It is released for the community to use under the terms of the GPL...

ChartAttack: Testing the Vulnerability of LLMs to Malicious Prompting in Chart Generation

Multimodal large language models MLLMs are increasingly used to automate chart generation from data tables, enabling efficient data analysis and reporting but also introducing new misuse risks. In this work, we introduce ChartAttack, a novel framework for evaluating how MLLMs can be misused to...

Post-Quantum Secure Aggregation Via Code-Based Homomorphic Encryption

Secure aggregation enables aggregation of inputs from multiple parties without revealing individual contributions to the server or other clients. Existing post-quantum approaches based on homomorphic encryption offer practical efficiency but predominantly rely on lattice-based hardness assumption...

Apache bRPC Command Injection

The Apache bRPC heap profiler suffers from a command injection vulnerability. Versions below 1.15.0 are affected...

Static Detection of Core Structures in Tigress Virtualization-Based Obfuscation Using an LLVM Pass

Malware often uses obfuscation to hinder security analysis. Among these techniques, virtualization-based obfuscation is particularly strong because it protects programs by translating original instructions into attacker-defined virtual machine VM bytecode, producing long and complex code that is...

Quantum Encryption Resilience Score (QERS) for MQTT, HTTP, and HTTPS under Post-Quantum Cryptography in Computer, IoT, and IIoT Systems

Post-quantum cryptography PQC introduces significant computational and communication overhead, which poses challenges for resource-constrained computer systems, Internet of Things IoT, and Industrial IoT IIoT devices. This paper presents an experimental evaluation of the Quantum Encryption...

Abusing the Internet of Medical Things: Evaluating Threat Models and Forensic Readiness for Multi-Vector Attacks on Connected Healthcare Devices

Individuals experiencing interpersonal violence IPV, who depend on medical devices, represent a uniquely vulnerable population as healthcare technologies become increasingly connected. Despite rapid growth in MedTech innovation and "health-at-home" ecosystems, the intersection of MedTech...

TrojanPraise: Jailbreak LLMs Via Benign Fine-Tuning

The demand of customized large language models LLMs has led to commercial LLMs offering black-box fine-tuning APIs, yet this convenience introduces a critical security loophole: attackers could jailbreak the LLMs by fine-tuning them with malicious data. Though this security issue has recently bee...

An Optimized Decision Tree-Based Framework for Explainable IoT Anomaly Detection

The increase in the number of Internet of Things IoT devices has tremendously increased the attack surface of cyber threats thus making a strong intrusion detection system IDS with a clear explanation of the process essential towards resource-constrained environments. Nevertheless, current IoT ID...

Hybrid IDS Using Signature-Based and Anomaly-Based Detection

Intrusion detection systems IDS are essential for protecting computer systems and networks against a wide range of cyber threats that continue to evolve over time. IDS are commonly categorized into two main types, each with its own strengths and limitations, such as difficulty in detecting...

Enhancing Fuzz Testing Efficiency through Automated Fuzz Target Generation

Fuzzing continues to be the most effective method for identifying security vulnerabilities in software. In the context of fuzz testing, the fuzzer supplies varied inputs to fuzz targets, which are designed to comprehensively exercise critical sections of the client code. Various studies have...

Many Hands Make Light Work: An LLM-Based Multi-Agent System for Detecting Malicious PyPI Packages

Malicious code in open-source repositories such as PyPI poses a growing threat to software supply chains. Traditional rule-based tools often overlook the semantic patterns in source code that are crucial for identifying adversarial components. Large language models LLMs show promise for software...

Shaping a Quantum-Resistant Future: Strategies for Post-Quantum PKI

As the quantum computing era approaches, securing classical cryptographic protocols becomes imperative. Public key cryptography is widely used for signature and key exchange but it is the type of cryptography more threatened by quantum computing. Its application typically requires support via a...

A Defender-Attacker-Defender Model for Optimizing the Resilience of Hospital Networks to Cyberattacks

Considering the increasing frequency of cyberattacks affecting multiple hospitals simultaneously, improving resilience at a network level is essential. Various countermeasures exist to improve resilience against cyberattacks, such as deploying controls that strengthen IT infrastructures to limit...

LoRA As Oracle

Backdoored and privacy-leaking deep neural networks pose a serious threat to the deployment of machine learning systems in security-critical settings. Existing defenses for backdoor detection and membership inference typically require access to clean reference models, extensive retraining, or...