Windows Persistent Service Installer

This Metasploit module will generate and upload an executable to a remote host. It will create a new service which will start the payload whenever the service is running. Admin or system privilege is required...

A Unified Compositional View of Attack Tree Metrics

Attack trees ATs are popular graphical models for reasoning about the security of complex systems, allowing for the quantification of risk through so-called AT metrics. A large variety of different such AT metrics have been proposed, and despite their wide-spread practical use, no systematic...

Squid Heap Buffer Overflow

Squid versions prior to 6.4 suffer from a heap-based buffer overflow that is triggered during URN Trivial-HTTP response handling...

Towards Classifying Benign and Malicious Packages Using Machine Learning

Recently, the number of malicious open-source packages in package repositories has been increasing dramatically. While major security scanners focus on identifying known Common Vulnerabilities and Exposures CVEs in open-source packages, there are very few studies on detecting malicious packages...

LFreeDA: Label-Free Drift Adaptation for Windows Malware Detection

Machine learning ML-based malware detectors degrade over time as concept drift introduces new and evolving families unseen during training. Retraining is limited by the cost and time of manual labeling or sandbox analysis. Existing approaches mitigate this via drift detection and selective...

From Topology to Behavioral Semantics: Enhancing BGP Security by Understanding BGP's Language with LLMs

The trust-based nature of Border Gateway Protocol BGP makes it vulnerable to disruptions like prefix hijacking and misconfigurations, threatening routing stability. Traditional detection relies on manual inspection with limited scalability. Machine/Deep Learning M/DL approaches automate detection...

Steganographic Backdoor Attacks in NLP: Ultra-Low Poisoning and Defense Evasion

Transformer models are foundational to natural language processing NLP applications, yet remain vulnerable to backdoor attacks introduced through poisoned data, which implant hidden behaviors during training. To strengthen the ability to prevent such compromises, recent research has focused on...

Structured Extraction of Vulnerabilities in OpenVAS and Tenable WAS Reports Using LLMs

This paper proposes an automated LLM-based method to extract and structure vulnerabilities from OpenVAS and Tenable WAS scanner reports, converting unstructured data into a standardized format for risk management. In an evaluation using a report with 34 vulnerabilities, GPT-4.1 and DeepSeek...

Certified but Fooled! Breaking Certified Defences with Ghost Certificates

Certified defenses promise provable robustness guarantees. We study the malicious exploitation of probabilistic certification frameworks to better understand the limits of guarantee provisions. Now, the objective is to not only mislead a classifier, but also manipulate the certification process t...

Interpretable Ransomware Detection Using Hybrid Large Language Models: A Comparative Analysis of BERT, RoBERTa, and DeBERTa through LIME and SHAP

Ransomware continues to evolve in complexity, making early and explainable detection a critical requirement for modern cybersecurity systems. This study presents a comparative analysis of three Transformer-based Large Language Models LLMs BERT, RoBERTa, and DeBERTa for ransomware detection using...

macos-collector - Automated Collection of macOS Forensic Artifacts for DFIR

macos-collector.sh is a Shell script utilized to collect macOS Forensic Artifacts from a compromised macOS endpoint using primarily Aftermath by Jamf Threat Labs...

nfstream 6.5.4

nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python...

VEIL: Jailbreaking Text-To-Video Models Via Visual Exploitation from Implicit Language

Jailbreak attacks can circumvent model safety guardrails and reveal critical blind spots. Prior attacks on text-to-video T2V models typically add adversarial perturbations to obviously unsafe prompts, which are often easy to detect and defend. In contrast, we show that benign-looking prompts...

DualTAP: A Dual-Task Adversarial Protector for Mobile MLLM Agents

The reliance of mobile GUI agents on Multimodal Large Language Models MLLMs introduces a severe privacy vulnerability: screenshots containing Personally Identifiable Information PII are often sent to untrusted, third-party routers. These routers can exploit their own MLLMs to mine this data,...

LogPurge: Log Data Purification for Anomaly Detection Via Rule-Enhanced Filtering

Log anomaly detection, which is critical for identifying system failures and preempting security breaches, detects irregular patterns within large volumes of log data, and impacts domains such as service reliability, performance optimization, and database log analysis. Modern log anomaly detectio...

GNUnet P2P Framework 0.26.1

GNUnet is a peer-to-peer framework with focus on providing security. All peer-to-peer messages in the network are confidential and authenticated. The framework provides a transport abstraction layer and can currently encapsulate the network traffic in UDP IPv4 and IPv6, TCP IPv4 and IPv6, HTTP, o...

Jailbreaking Large Vision Language Models in Intelligent Transportation Systems

Large Vision Language Models LVLMs demonstrate strong capabilities in multimodal reasoning and many real-world applications, such as visual question answering. However, LVLMs are highly vulnerable to jailbreaking attacks. This paper systematically analyzes the vulnerabilities of LVLMs integrated ...

Resilient Distribution Network Planning against Dynamic Malicious Power Injection Attacks

Active distribution networks facilitating bidirectional power exchange with renewable energy resources are susceptible to cyberattacks due to integration of a diverse array of cyber components. This study introduces a grid-level defense strategy aimed at enhancing attack resiliency based on...

Average Hardness of SIVP for Module Lattices of Fixed Rank

The problem of finding short vectors in Euclidean lattices is a central hard problem in complexity theory. The case of module lattices i.e., lattices which are also modules over a number ring is of particular interest for cryptography and computational number theory. The hardness of finding short...

Nuclei 3.5.1

Nuclei is a modern, high-performance vulnerability scanner that leverages simple YAML-based templates. It empowers you to design custom vulnerability detection scenarios that mimic real-world conditions, leading to zero false positives...

New Data Security Requirements and the Proceduralization of Mass Surveillance Law after the European Data Retention Case

This paper discusses the regulation of mass metadata surveillance in Europe through the lens of the landmark judgment in which the Court of Justice of the European Union struck down the Data Retention Directive. The controversial directive obliged telecom and Internet access providers in Europe t...

Beyond Fixed and Dynamic Prompts: Embedded Jailbreak Templates for Advancing LLM Security

As the use of large language models LLMs continues to expand, ensuring their safety and robustness has become a critical challenge. In particular, jailbreak attacks that bypass built-in safety mechanisms are increasingly recognized as a tangible threat across industries, driving the need for...

Wapiti Web Application Vulnerability Scanner 3.2.10

Wapiti is a web application vulnerability scanner. It will scan the web pages of a deployed web application and will fuzz the URL parameters and forms to find common web vulnerabilities. This is the binary release...

It's a Feature, Not a Bug: Secure and Auditable State Rollback for Confidential Cloud Applications

Replay and rollback attacks threaten cloud application integrity by reintroducing authentic yet stale data through an untrusted storage interface to compromise application decision-making. Prior security frameworks mitigate these attacks by enforcing forward-only state transitions state continuit...

Examining the Security Posture of an Anti-Crime Ecosystem

Whitepaper called Examining the security posture of an Anti-Crime Ecosystem. The prevalence of anti-crime technology has seen a steep incline in the past few years. Since the introduction of cell phones, the expectation of privacy has gone steeply down. With that in mind, independent security...

A Fuzzy Logic-Based Cryptographic Framework for Real-Time Dynamic Key Generation for Enhanced Data Encryption

With the ever-growing demand for cybersecurity, static key encryption mechanisms are increasingly vulnerable to adversarial attacks due to their deterministic and non-adaptive nature. Brute-force attacks, key compromise, and unauthorized access have become highly common cyber threats. This resear...

TaskHound - Windows Privileged Scheduled Task Discovery Tool

TaskHound is a tool that hunts for Windows scheduled tasks that run with privileged accounts and stored credentials. It enumerates tasks over SMB, parses XMLs, and identifies high-value attack opportunities through BloodHound support...

SmartPoC: Generating Executable and Validated PoCs for Smart Contract Bug Reports

Smart contracts are prone to vulnerabilities and are analyzed by experts as well as automated systems, such as static analysis and AI-assisted solutions. However, audit artifacts are heterogeneous and often lack reproducible, executable PoC tests suitable for automated validation, leading to...

MalRAG: A Retrieval-Augmented LLM Framework for Open-Set Malicious Traffic Identification

Fine-grained identification of IDS-flagged suspicious traffic is crucial in cybersecurity. In practice, cyber threats evolve continuously, making the discovery of novel malicious traffic a critical necessity as well as the identification of known classes. Recent studies have advanced this goal wi...

Randomized Controlled Trials for Phishing Triage Agent

Security operations centers SOCs face a persistent challenge: efficiently triaging a high volume of user-reported phishing emails while maintaining robust protection against threats. This paper presents the first randomized controlled trial RCT evaluating the impact of a domain-specific AI agent ...

AutoMalDesc: Large-Scale Script Analysis for Cyber Threat Research

Generating thorough natural language explanations for threat detections remains an open problem in cybersecurity research, despite significant advances in automated malware detection systems. In this work, we present AutoMalDesc, an automated static analysis summarization framework that, followin...

The Battle of Metasurfaces: Understanding Security in Smart Radio Environments

Metasurfaces, or Reconfigurable Intelligent Surfaces RISs, have emerged as a transformative technology for next-generation wireless systems, enabling digitally controlled manipulation of electromagnetic wave propagation. By turning the traditionally passive radio environment into a smart,...

Wapiti Web Application Vulnerability Scanner 3.2.10 Source Code

Wapiti is a web application vulnerability scanner. It will scan the web pages of a deployed web application and will fuzz the URL parameters and forms to find common web vulnerabilities. This is the source code release...

Scaling Patterns in Adversarial Alignment: Evidence from Multi-LLM Jailbreak Experiments

Large language models LLMs increasingly operate in multi-agent and safety-critical settings, raising open questions about how their vulnerabilities scale when models interact adversarially. This study examines whether larger models can systematically jailbreak smaller ones - eliciting harmful or...

ProxyPrints: From Database Breach to Spoof, a Plug-And-Play Defense for Biometric Systems

Fingerprint recognition systems are widely deployed for authentication and forensic applications, but the security of stored fingerprint data remains a critical vulnerability. While many systems avoid storing raw fingerprint images in favor of minutiae-based templates, recent research shows that...

An Evaluation Framework for Network IDS/IPS Datasets: Leveraging MITRE ATT&CK and Industry Relevance Metrics

The performance of Machine Learning ML and Deep Learning DL-based Intrusion Detection and Prevention Systems IDS/IPS is critically dependent on the relevance and quality of the datasets used for training and evaluation. However, current AI model evaluation practices for developing IDS/IPS focus...

T2I-Based Physical-World Appearance Attack against Traffic Sign Recognition Systems in Autonomous Driving

Traffic Sign Recognition TSR systems play a critical role in Autonomous Driving AD systems, enabling real-time detection of road signs, such as STOP and speed limit signs. While these systems are increasingly integrated into commercial vehicles, recent research has exposed their vulnerability to...

Adaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection

Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimate traffic, leading to limited efficacy in threat detection. To overcome these...

Whose Narrative Is It Anyway? A KV Cache Manipulation Attack

The Key ValueKV cache is an important component for efficient inference in autoregressive Large Language Models LLMs, but its role as a representation of the model's internal state makes it a potential target for integrity attacks. This paper introduces "History Swapping," a novel block-level...

Offensive Tool Determination Strategy R.I.D.D.L.E. + (C)

Intentional threats are a major risk factor related to vulnerabilities in critical infrastructure assets, and an accurate risk assessment is necessary to analyze threats, assess vulnerabilities, and evaluate potential impacts on assets and systems. This research proposes a methodology that can be...

Scalable Hierarchical AI-Blockchain Framework for Real-Time Anomaly Detection in Large-Scale Autonomous Vehicle Networks

The security of autonomous vehicle networks is facing major challenges, owing to the complexity of sensor integration, real-time performance demands, and distributed communication protocols that expose vast attack surfaces around both individual and network-wide safety. Existing security schemes...

Cybersecurity of High-Altitude Platform Stations: Threat Taxonomy, Attacks and Defenses with Standards Mapping - DDoS Attack Use Case

High-Altitude Platform Stations HAPS are emerging stratospheric nodes within non-terrestrial networks. We provide a structured overview of HAPS subsystems and principal communication links, map cybersecurity and privacy exposure across communication, control, and power subsystems, and propose a...

Efficient Adversarial Malware Defense Via Trust-Based Raw Override and Confidence-Adaptive Bit-Depth Reduction

The deployment of robust malware detection systems in big data environments requires careful consideration of both security effectiveness and computational efficiency. While recent advances in adversarial defenses have demonstrated strong robustness improvements, they often introduce computationa...

Explainable Transformer-Based Email Phishing Classification with Adversarial Robustness

Phishing and related cyber threats are becoming more varied and technologically advanced. Among these, email-based phishing remains the most dominant and persistent threat. These attacks exploit human vulnerabilities to disseminate malware or gain unauthorized access to sensitive information. Dee...

Exploring AI in Steganography and Steganalysis: Trends, Clusters, and Sustainable Development Potential

Steganography and steganalysis are strongly related subjects of information security. Over the past decade, many powerful and efficient artificial intelligence AI - driven techniques have been designed and presented during research into steganography as well as steganalysis. This study presents a...

GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs

Text-attributed graphs TAGs, which combine structural and textual node information, are ubiquitous across many domains. Recent work integrates Large Language Models LLMs with Graph Neural Networks GNNs to jointly model semantics and structure, resulting in more general and expressive models that...

RulePilot: An LLM-Powered Agent for Security Rule Generation

The real-time demand for system security leads to the detection rules becoming an integral part of the intrusion detection life-cycle. Rule-based detection often identifies malicious logs based on the predefined grammar logic, requiring experts with deep domain knowledge for rule generation...

Software Supply Chain Security of Web3

Web3 applications, built on blockchain technology, manage billions of dollars in digital assets through decentralized applications dApps and smart contracts. These systems rely on complex, software supply chains that introduce significant security vulnerabilities. This paper examines the software...

BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-Tuning

Knowledge Distillation KD is essential for compressing large models, yet relying on pre-trained "teacher" models downloaded from third-party repositories introduces serious security risks -- most notably backdoor attacks. Existing KD backdoor methods are typically complex and computationally...

Multi-Agent Collaborative Fuzzing with Continuous Reflection for Smart Contracts Vulnerability Detection

Fuzzing is a widely used technique for detecting vulnerabilities in smart contracts, which generates transaction sequences to explore the execution paths of smart contracts. However, existing fuzzers are falling short in detecting sophisticated vulnerabilities that require specific attack...