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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

Apache bRPC Command Injection

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

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

SimFuzz: Similarity-Guided Block-Level Mutation for RISC-V Processor Fuzzing

The Instruction Set Architecture ISA defines processor operations and serves as the interface between hardware and software. As an open ISA, RISC-V lowers the barriers to processor design and encourages widespread adoption, but also exposes processors to security risks such as functional bugs...

Predicting Tail-Risk Escalation in IDS Alert Time Series

Network defenders face a steady stream of attacks, observed as raw Intrusion Detection System IDS alerts. The sheer volume of alerts demands prioritization, typically based on high-level risk classifications. This work expands the scope of risk measurement by examining alerts not only through the...

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...

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...

Gamifying Cyber Governance: A Virtual Escape Room to Transform Cybersecurity Policy Education

Serious games are gaining popularity as effective teaching and learning tools, providing engaging, interactive, and practical experiences for students. Gamified learning experiences, such as virtual escape rooms, have emerged as powerful tools in bridging theory and practice, fostering deeper...

Wireshark Analyzer 4.6.3

Wireshark is a GTK+-based network protocol analyzer that lets you capture and interactively browse the contents of network frames. The goal of the project is to create a commercial-quality analyzer for Unix and Win32 and to give Wireshark features that are missing from closed-source sniffers. Thi...

Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale

The rise of AI agent frameworks has introduced agent skills, modular packages containing instructions and executable code that dynamically extend agent capabilities. While this architecture enables powerful customization, skills execute with implicit trust and minimal vetting, creating a...

Advanced Encryption Technique for Multimedia Data Using Sudoku-Based Algorithms for Enhanced Security

Encryption and Decryption is the process of sending a message in a ciphered way that appears meaningless and could be deciphered using a key for security purposes to avoid data breaches. This paper expands on the previous work on Sudoku-based encryption methods, applying it to other forms of medi...

AJAR: Adaptive Jailbreak Architecture for Red-Teaming

As Large Language Models LLMs evolve from static chatbots into autonomous agents capable of tool execution, the landscape of AI safety is shifting from content moderation to action security. However, existing red-teaming frameworks remain bifurcated: they either focus on rigid, script-based text...

Notepad++ Plugin Persistence

This Metasploit module create persistence by adding a malicious plugin to Notepad++, as it blindly loads and executes DLL from its plugin directory on startup, meaning that the payload will be executed every time Notepad++ is launched...

Multi-Agent Taint Specification Extraction for Vulnerability Detection

Static Application Security Testing SAST tools using taint analysis are widely viewed as providing higher-quality vulnerability detection results compared to traditional pattern-based approaches. However, performing static taint analysis for JavaScript poses two major challenges. First,...

Blue Teaming Function-Calling Agents

We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three different attacks, and we measure the effectiveness of eight different defences. Our results show how these models are not safe by default, and how the...

A Novel Contrastive Loss for Zero-Day Network Intrusion Detection

Machine learning has achieved state-of-the-art results in network intrusion detection; however, its performance significantly degrades when confronted by a new attack class -- a zero-day attack. In simple terms, classical machine learning-based approaches are adept at identifying attack classes o...

WMI Event Subscription Event Log Persistence

This Metasploit module will create a permanent WMI event subscription to achieve file-less persistence using an event filter that will query the event log for an EVENTIDTRIGGER default: failed logon request id 4625 that also contains a specified USERNAMETRIGGER note: failed logon auditing must be...