7964 matches found
Hashcat Advanced Password Recovery 7.0.0 Binary Release
Hashcat is an advanced GPU hash cracking utility that includes the World's fastest md5crypt, phpass, mscash2 and WPA / WPA2 cracker. It also has the first and only GPGPU-based rule engine, focuses on highly iterated modern hashes, single dictionary-based attacks, and more. This is the binary...
Whispering Agents: an Event-Driven Covert Communication Protocol for the Internet of Agents
The emergence of the Internet of Agents IoA introduces critical challenges for communication privacy in sensitive, high-stakes domains. While standard Agent-to-Agent A2A protocols secure message content, they are not designed to protect the act of communication itself, leaving agents vulnerable t...
Large Reasoning Models Are Autonomous Jailbreak Agents
Jailbreaking -- bypassing built-in safety mechanisms in AI models -- has traditionally required complex technical procedures or specialized human expertise. In this study, we show that the persuasive capabilities of large reasoning models LRMs simplify and scale jailbreaking, converting it into a...
ASINT: Learning AS-To-Organization Mapping from Internet Metadata
Accurately mapping Autonomous Systems ASNs to their owning or operating organizations underpins Internet measurement research and security applications. Yet existing approaches commonly rely solely on WHOIS or PeeringDB, missing important relationships e.g., cross-regional aliases, parent-child...
Can LLMs Effectively Provide Game-Theoretic-Based Scenarios for Cybersecurity?
Game theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large Language Models LLMs offers new tools and challenges for the security of computer systems; In this work, we investiga...
Gandia Integra Total 4.4.2236.1 SQL Injection
Gandia Integra Total versions 2.1.2217.3 through 4.4.2236.1 suffer from a remote SQL injection vulnerability...
A Survey on Data Security in Large Language Models
Large Language Models LLMs, now a foundation in advancing natural language processing, power applications such as text generation, machine translation, and conversational systems. Despite their transformative potential, these models inherently rely on massive amounts of training data, often...
LPAR2RRD Remote Code Execution
This repository contains a proof of concept exploit for CVE-2025-54769, a vulnerability found in lpar2rrd. The vulnerability allows remote code execution and directory traversal by abusing the /lpar2rrd-cgi/upgrade.sh endpoint...
Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems
As power systems evolve with increased integration of renewable energy sources, they become more complex and vulnerable to both cyber and physical threats. This study validates a centralized Dynamic State Estimation DSE algorithm designed to enhance the protection of power systems, particularly...
Copyparty 1.18.6 Cross Site Scripting
Copyparty versions 1.18.6 and below suffer from a cross site scripting vulnerability...
DINA: a Dual Defense Framework against Internal Noise and External Attacks in Natural Language Processing
As large language models LLMs and generative AI become increasingly integrated into customer service and moderation applications, adversarial threats emerge from both external manipulations and internal label corruption. In this work, we identify and systematically address these dual adversarial...
The Dark Side of Upgrades: Uncovering Security Risks in Smart Contract Upgrades
Smart contract upgrades are increasingly common due to their flexibility in modifying deployed contracts, such as fixing bugs or adding new functionalities. Meanwhile, upgrades compromise the immutability of contracts, introducing significant security concerns. While existing research has explore...
Coward: toward Practical Proactive Federated Backdoor Defense Via Collision-Based Watermark
Backdoor detection is currently the mainstream defense against backdoor attacks in federated learning FL, where malicious clients upload poisoned updates that compromise the global model and undermine the reliability of FL deployments. Existing backdoor detection techniques fall into two...
Experimental Evaluation of Post-Quantum Homomorphic Encryption for Privacy-Preserving V2X Communication
Intelligent Transportation Systems ITS fundamentally rely on vehicle-generated data for applications such as congestion monitoring and route optimization, making the preservation of user privacy a critical challenge. Homomorphic Encryption HE offers a promising solution by enabling computation on...
Secure MmWave Beamforming with Proactive-ISAC Defense against Beam-Stealing Attacks
Millimeter-wave mmWave communication systems face increasing susceptibility to advanced beam-stealing attacks, posing a significant physical layer security threat. This paper introduces a novel framework employing an advanced Deep Reinforcement Learning DRL agent for proactive and adaptive defens...
PentestJudge: Judging Agent Behavior against Operational Requirements
We introduce PentestJudge, a system for evaluating the operations of penetration testing agents. PentestJudge is a large language model LLM-as-judge with access to tools that allow it to consume arbitrary trajectories of agent states and tool call history to determine whether a security agent's...
LMDG: Advancing Lateral Movement Detection through High-Fidelity Dataset Generation
Lateral Movement LM attacks continue to pose a significant threat to enterprise security, enabling adversaries to stealthily compromise critical assets. However, the development and evaluation of LM detection systems are impeded by the absence of realistic, well-labeled datasets. To address this...
Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools
Large language model LLM agents have demonstrated remarkable capabilities in complex reasoning and decision-making by leveraging external tools. However, this tool-centric paradigm introduces a previously underexplored attack surface: adversaries can manipulate tool metadata -- such as names,...
Microsoft Edge Information Disclosure
Microsoft Edge Chromium-based suffers from an information disclosure vulnerability...
Towards Effective Offensive Security LLM Agents: Hyperparameter Tuning, LLM As a Judge, and a Lightweight CTF Benchmark
Recent advances in LLM agentic systems have improved the automation of offensive security tasks, particularly for Capture the Flag CTF challenges. We systematically investigate the key factors that drive agent success and provide a detailed recipe for building effective LLM-based offensive securi...
Thwart Me If You Can: an Empirical Analysis of Android Platform Armoring against Stalkerware
Stalkerware is a serious threat to individuals' privacy that is receiving increased attention from the security and privacy research communities. Existing works have largely focused on studying leading stalkerware apps, dual-purpose apps, monetization of stalkerware, or the experience of survivor...
PRIME: Plasticity-Robust Incremental Model for Encrypted Traffic Classification in Dynamic Network Environments
With the continuous development of network environments and technologies, ensuring cyber security and governance is increasingly challenging. Network traffic classificationETC can analyzes attributes such as application categories and malicious intent, supporting network management services like...
Beyond Vulnerabilities: a Survey of Adversarial Attacks As Both Threats and Defenses in Computer Vision Systems
Adversarial attacks against computer vision systems have emerged as a critical research area that challenges the fundamental assumptions about neural network robustness and security. This comprehensive survey examines the evolving landscape of adversarial techniques, revealing their dual nature a...
"Energon": Unveiling Transformers from GPU Power and Thermal Side-Channels
Transformers have become the backbone of many Machine Learning ML applications, including language translation, summarization, and computer vision. As these models are increasingly deployed in shared Graphics Processing Unit GPU environments via Machine Learning as a Service MLaaS, concerns aroun...
LLM-Assisted Model-Based Fuzzing of Protocol Implementations
Testing network protocol implementations is critical for ensuring the reliability, security, and interoperability of distributed systems. Faults in protocol behavior can lead to vulnerabilities and system failures, especially in real-time and mission-critical applications. A common approach to...
A Survey on Privacy-Preserving Computing in the Automotive Domain
As vehicles become increasingly connected and autonomous, they accumulate and manage various personal data, thereby presenting a key challenge in preserving privacy during data sharing and processing. This survey reviews applications of Secure Multi-Party Computation MPC and Homomorphic Encryptio...
BeDKD: Backdoor Defense Based on Dynamic Knowledge Distillation and Directional Mapping Modulator
Although existing backdoor defenses have gained success in mitigating backdoor attacks, they still face substantial challenges. In particular, most of them rely on large amounts of clean data to weaken the backdoor mapping but generally struggle with residual trigger effects, resulting in...
IMU: Influence-Guided Machine Unlearning
Recent studies have shown that deep learning models are vulnerable to attacks and tend to memorize training data points, raising significant concerns about privacy leakage. This motivates the development of machine unlearning MU, i.e., a paradigm that enables models to selectively forget specific...
Proactive Disentangled Modeling of Trigger-Object Pairings for Backdoor Defense
Deep neural networks DNNs and generative AI GenAI are increasingly vulnerable to backdoor attacks, where adversaries embed triggers into inputs to cause models to misclassify or misinterpret target labels. Beyond traditional single-trigger scenarios, attackers may inject multiple triggers across...
Hard-Earned Lessons in Access Control at Scale: Enforcing Identity and Policy across Trust Boundaries with Reverse Proxies and MTLS
In today's enterprise environment, traditional access methods such as Virtual Private Networks VPNs and application-specific Single Sign-On SSO often fall short when it comes to securely scaling access for a distributed and dynamic workforce. This paper presents our experience implementing a...
Semantic Encryption: Secure and Effective Interaction with Cloud-Based Large Language Models Via Semantic Transformation
The increasing adoption of Cloud-based Large Language Models CLLMs has raised significant concerns regarding data privacy during user interactions. While existing approaches primarily focus on encrypting sensitive information, they often overlook the logical structure of user inputs. This oversig...
GPU in the Blind Spot: Overlooked Security Risks in Transportation
Graphics processing units GPUs are becoming an essential part of the intelligent transportation system ITS for enabling video-based and artificial intelligence AI based applications. GPUs provide high-throughput and energy-efficient computing for tasks like sensor fusion and roadside video...
Complete Evasion, Zero Modification: PDF Attacks on AI Text Detection
AI-generated text detectors have become essential tools for maintaining content authenticity, yet their robustness against evasion attacks remains questionable. We present PDFuzz, a novel attack that exploits the discrepancy between visual text layout and extraction order in PDF documents. Our...
Analyzing the Mirai IoT Botnet and Its Recent Variants: Satori, Mukashi, Moobot, and Sonic
Mirai is undoubtedly one of the most significant Internet of Things IoT botnet attacks in history. In terms of its detrimental effects, seamless spread, and low detection rate, it surpassed its predecessors. Its developers released the source code, which triggered the development of several...
A Provably Secure Network Protocol for Private Communication with Analysis and Tracing Resistance
Anonymous communication networks have emerged as crucial tools for obfuscating communication pathways and concealing user identities. However, their practical deployments face significant challenges, including susceptibility to artificial intelligence AI-powered metadata analysis, difficulties in...
Generative AI-Empowered Secure Communications in Space-Air-Ground Integrated Networks: a Survey and Tutorial
Space-air-ground integrated networks SAGINs face unprecedented security challenges due to their inherent characteristics, such as multidimensional heterogeneity and dynamic topologies. These characteristics fundamentally undermine conventional security methods and traditional artificial...
DUP: Detection-Guided Unlearning for Backdoor Purification in Language Models
As backdoor attacks become more stealthy and robust, they reveal critical weaknesses in current defense strategies: detection methods often rely on coarse-grained feature statistics, and purification methods typically require full retraining or additional clean models. To address these challenges...
VWAttacker: a Systematic Security Testing Framework for Voice over WiFi User Equipments
We present VWAttacker, the first systematic testing framework for analyzing the security of Voice over WiFi VoWiFi User Equipment UE implementations. VWAttacker includes a complete VoWiFi network testbed that communicates with Commercial-Off-The-Shelf COTS UEs based on a simple interface to test...
Think Broad, Act Narrow: CWE Identification with Multi-Agent Large Language Models
Machine learning and Large language models LLMs for vulnerability detection has received significant attention in recent years. Unfortunately, state-of-the-art techniques show that LLMs are unsuccessful in even distinguishing the vulnerable function from its benign counterpart, due to three main...
Leveraging Machine Learning for Botnet Attack Detection in Edge-Computing Assisted IoT Networks
The increase of IoT devices, driven by advancements in hardware technologies, has led to widespread deployment in large-scale networks that process massive amounts of data daily. However, the reliance on Edge Computing to manage these devices has introduced significant security vulnerabilities, a...
Packet Storm New Exploits for July, 2025
This archive contains all of the 132 exploits added to Packet Storm in July, 2025...
Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Supply Chain
The pharmaceutical supply chain faces escalating cybersecurity challenges threatening patient safety and operational continuity. This paper examines the transformative potential of zero trust architecture for enhancing security and resilience within this critical ecosystem. We explore the...
Rtpengine mr13.4.1.1 Injection / Redirection
Rtpengine starting at version mr13.4.1.1 allows for redirection to an attacker-controlled host and insertion of arbitrary RTP packet into active calls...
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
Despite outstanding results, machine learning-based Android malware detection models struggle with concept drift, where rapidly evolving malware characteristics degrade model effectiveness. This study examines the impact of concept drift on Android malware detection, evaluating two datasets and...
Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection
With the rapid expansion of web-based applications and cloud services, malicious JavaScript code continues to pose significant threats to user privacy, system integrity, and enterprise security. But, detecting such threats remains challenging due to sophisticated code obfuscation techniques and...
Apple Security Advisory 07-29-2025-3
Apple Security Advisory 07-29-2025-3 - macOS Sequoia 15.6 addresses bypass, cross site scripting, integer overflow, out of bounds access, out of bounds read, out of bounds write, and use-after-free vulnerabilities...
Apple Security Advisory 07-29-2025-4
Apple Security Advisory 07-29-2025-4 - macOS Sonoma 14.7.7 addresses bypass, code execution, integer overflow, out of bounds access, out of bounds read, and use-after-free vulnerabilities...
Apple Security Advisory 07-29-2025-5
Apple Security Advisory 07-29-2025-5 - macOS Ventura 13.7.7 addresses bypass, code execution, integer overflow, out of bounds access, out of bounds read, and use-after-free vulnerabilities...