8784 matches found
Poster: ClawdGo: Endogenous Security Awareness Training for Autonomous AI Agents
Autonomous AI agents deployed on platforms such as OpenClaw face prompt injection, memory poisoning, supply-chain attacks, and social engineering, yet existing defences address only the platform perimeter, leaving the agent's own threat judgement entirely untrained. We present ClawdGo, a framewor...
Vulnerability Identification by Harnessing Inter-Connected Multi-Source Information
The utilization of third-party open-source libraries is widespread in modern software development. Due to the dependency relationships, vulnerabilities within open-source libraries pose significant security threats to downstream software. However, the library vulnerabilities are usually implicitl...
AgentVisor: Defending LLM Agents against Prompt Injection Via Semantic Virtualization
Large Language Model LLM agents are increasingly used to automate complex workflows, but integrating untrusted external data with privileged execution exposes them to severe security risks, particularly direct and indirect prompt injection. Existing defenses face significant challenges in balanci...
SNF - Shadow Network Fingerprinting Engine
SNF Shadow Network Fingerprinting Engine is a 100% offline, air-gap-native passive network intelligence engine written entirely in Rust. It was designed from the ground up for environments where outbound connectivity is not just unavailable but prohibited: classified defense networks, nuclear...
Converging Zero Trust and IoT Security: A Multivocal Literature Review
The convergence of Internet of Things IoT security and Zero Trust ZT principles is a trending topic, demanding a comprehensive, multi-perspective analysis. We present the first multivocal literature review MLR on this topic, combining 68 academic and 36 industrial studies. This comprehensive revi...
V8 BigInt SharedArrayBuffer Concurrency Synchronization
This JavaScript code is a concurrency demonstration using SharedArrayBuffer, Web Workers, and Atomics to coordinate execution between the main thread and a worker thread...
GoAT-X: A Graph of Auditing Thoughts for Securing Token Transactions in Cross-Chain Contracts
Cross-chain bridges, the critical infrastructure of the multi-chain ecosystem, have become a primary target for attackers, resulting in over $2.8 billion in losses due to subtle implementation flaws. Existing defenses, such as bytecode-level static analysis, are ill-equipped to handle the semanti...
Jailbreaking Frontier Foundation Models through Intention Deception
Large vision-language models exhibit remarkable capability but remain highly susceptible to jailbreaking. Existing safety training approaches aim to have the model learn a refusal boundary between safe and unsafe, based on the user's intent. It has been found that this binary training regime ofte...
Detecting Avalanche Effect in Adversarial Settings: Spotting the Encryption Loops in Ransomware
Spotting encryption loops in binary-only ransomware is a critical reverse engineering task. Since the existence of avalanche effect, an intrinsic characteristic of any secure encryption algorithms, is unavoidable during a victim data encryption attack, it is a very promising direction to spot...
Machine-Checked Cardinality Bounds for Masked Barrett Reduction: A 1-Bit Side-Channel Leakage Barrier in Post-Quantum Cryptographic Hardware
Barrett reduction is the nonlinear core of every practical NTT-based post-quantum cryptography implementation. Existing composition frameworks ISW, t-SNI, PINI, DOM address Boolean masking over GF2; none provides a machine-checked characterization of Barrett's leakage under first-order arithmetic...
A Systematic Literature Review for Transformer-Based Software Vulnerability Detection
Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic...
Evaluating Cryptographic API Misuse Detectors for Go
Cryptographic API misuse represents a critical vulnerability class that undermines the security foundations of modern software. Yet, it remains largely unexplored in Go despite its dominance in security-critical infrastructure. This paper presents the first comprehensive study of cryptographic AP...
A Comparative Evaluation of AI Agent Security Guardrails
This report presents a comparative evaluation of DKnownAI Guard in AI agent security scenarios, benchmarked against three competing products: AWS Bedrock Guardrails, Azure Content Safety, and Lakera Guard. Using human annotation as the ground truth, we assess each guardrail's ability to detect tw...
Joern 4.0.528
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...
System-Aware Contextual Digital Twin for ICS Anomaly Diagnosis
Industrial Control Systems ICS integrate computing, physical processes, and communication to operate critical infrastructures such as power grids, water treatment plants, and oil and gas facilities. As ICS become increasingly targeted by cyberattacks, timely and reliable anomaly diagnosis is...
The Vehicle May Be Sick: Denial of Diagnostic Services by Exploiting the CAN Transport Protocol
Vehicle diagnostics has become essential for detecting in-vehicle errors and ensuring safety. While the Unified Diagnostic Services UDS protocol is widely adopted for diagnostic operations, it relies on the ISO 15765-2 standard as the transport protocol over the Controller Area Network CAN, which...
Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery
Decompilation -- recovering source code from compiled binaries -- is essential for security analysis, malware reverse engineering, and legacy software maintenance. However, existing decompilers produce code that often fails to compile or execute correctly, limiting their practical utility. We...
SMSI: System Model Security Inference: Automated Threat Modeling for Cyber-Physical Systems
Threat modeling for cyber-physical systems CPS remains a largely manual exercise. This project presents SMSI System Model Security Inference, a hybrid neuro-symbolic pipeline that starts from a SysML architecture model and produces a prioritized list of NIST 800-53 security controls. The prototyp...
SeqShield: A Behavioral Analysis Approach to Uncover Rootkits
Rootkits are among the most elusive types of malware, capable of bypassing traditional static analysis methods due to their metamorphic behavior. Signature-based detection techniques struggle against these threats, necessitating a shift toward dynamic analysis approaches. We propose SeqShield, a...
Evaluation of Prompt Injection Defenses in Large Language Models
LLM-powered applications routinely embed secrets in system prompts, yet models can be tricked into revealing them. We built an adaptive attacker that evolves its strategies over hundreds of rounds and tested it against nine defense configurations across more than 20,000 attacks. Every defense tha...
Safeguarding Skies: Airport Cybersecurity in the Digital Age
The aviation industry faces significant vulnerabilities from both physical and cybersecurity threats, highlighting the urgent need for enhanced cybersecurity measures amid increasingly sophisticated attacks. This paper systematically reviews emerging threats at airports, analyzing real-world...
Analysis of Personal Data Exposure in Thailand
In the digital era, personal data, particularly sensitive identifiers such as the Social Security Number and National Identification Number, have become a highly valuable asset, raising significant concerns regarding privacy and security. This study examines the risks associated with the online...
AsmRAG: LLM-Driven Malware Detection by Retrieving Functionally Similar Assembly Code
Deep learning malware detectors achieve high classification accuracy but suffer from severe interpretability limitations, typically returning probabilistic verdicts that lack forensic context. We introduce AsmRAG, a framework performing malware analysis through Assembly-Level Retrieval-Augmented...
UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks
Emerging AR-LLM-based Social Engineering attack e.g., SEAR is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attack, the attacker can leverage AR Augmented Reality glass to capture the image and vocal information of the target, using the LLM to identify the targe...
Evaluating Jailbreaking Vulnerabilities in LLMs Deployed As Assistants for Smart Grid Operations: A Benchmark against NERC Standards
The deployment of Large Language Models LLMs as assistants in electric grid operations promises to streamline compliance and decision-making but exposes new vulnerabilities to prompt-based adversarial attacks. This paper evaluates the risk of jailbreaking LLMs, i.e., circumventing safety alignmen...
Semantic Denial of Service in LLM-Controlled Robots
Safety-oriented instruction-following is supposed to keep LLM-controlled robots safe. We show it also creates an availability attack surface. By injecting short safety-plausible phrases 1-5 tokens into a robots audio channel, an adversary can trigger the models safety reasoning to halt or disrupt...
Operationalising Information Security Management: A Procedural Framework Analysis of ISO/IEC 27001:2022 Implementation in a Financial-Technology Organisation
Organisations operating within information-intensive environments face intensifying pressure to formalise the governance of information security. The ISO/IEC 27001:2022 standard provides a globally recognised framework for establishing, implementing, maintaining, and continually improving an...
From Stateless Queries to Autonomous Actions: A Layered Security Framework for Agentic AI Systems
Agentic AI systems face security challenges that stateless large language models do not. They plan across extended horizons, maintain persistent memory, invoke external tools, and coordinate with peer agents. Existing security analyses organize threats by attack type prompt injection, jailbreakin...
ARIstoteles -- Dissecting Apple's Baseband Interface
Wireless chips and interfaces expose a substantial remote attack surface. As of today, most cellular baseband security research is performed on the Android ecosystem, leaving a huge gap on Apple devices. With iOS jailbreaks, last-generation wireless chips become fairly accessible for performance...
Architecture Matters for Multi-Agent Security
Multi-agent systems MAS, composed of networks of two or more autonomous AI agents, have become increasingly popular in production deployments, yet introduce security risks that do not arise in single-agent settings. Even if individual agents exhibit robust security, architectural decisions...
Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection
The global financial ecosystem confronts a critical asymmetry: while fraud syndicates operate as borderless, distributed networks, banking institutions remain constrained by regulatory data silos, limiting visibility into cross-institutional threat patterns under strict privacy laws such as GDPR...
Ghost in the Agent: Redefining Information Flow Tracking for LLM Agents
Autonomous Large Language Model LLM agents are increasingly deployed to conduct complex tasks by interacting with external tools, APIs, and memory stores. However, processing untrusted external data exposes these agents to severe security threats, such as indirect prompt injection and unauthorize...
listmonk Admin Authentication / Password Flow Security Assessment Module
This Metasploit auxiliary module is a web application security testing tool designed to evaluate authentication and password management logic in a Listmonk admin panel deployment...
Automation-Exploit: A Multi-Agent LLM Framework for Adaptive Offensive Security with Digital Twin-Based Risk-Mitigated Exploitation
The offensive security landscape is highly fragmented: enterprise platforms avoid memory-corruption vulnerabilities due to Denial of Service DoS risks, Automatic Exploit Generation AEG systems suffer from semantic blindness, and Large Language Model LLM agents face safety alignment filters and...
Libgcrypt 1.12.2
Libgcrypt is a general-purpose cryptographic library based on the code from GnuPG. It provides functions for all cryptographic building blocks: symmetric ciphers AES, DES, Blowfish, CAST5, Twofish, and Arcfour, hash algorithms MD4, MD5, RIPE-MD160, SHA-1, and TIGER-192, MACs HMAC for all hash...
MetInfo CMS 8.1 WeChat Module Vulnerability Detection Scanner
This Metasploit auxiliary module is a non-exploit vulnerability detection scanner designed to assess potential security weaknesses in the MetInfo CMS WeChat module, specifically related to weixinreply.class.php handling logic...
Joern 4.0.527
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...
NLTK Simple Random Input Fuzzer for Function Testing
This script is a basic fuzzing tool that generates random inputs strings containing letters, numbers, and special characters and feeds them into a target function to test its stability. It runs multiple iterations, monitors for exceptions or crashes, and counts how many errors occur during...
The Security Cost of Intelligence: AI Capability, Cyber Risk, and Deployment Paradox
Firms are deploying more capable AI systems, but organizational controls often have not kept pace. These systems can generate greater productivity gains, but high-value uses require broader authority exposure -- data access, workflow integration, and delegated authority -- when governance control...
Training a General Purpose Automated Red Teaming Model
Automated methods for red teaming LLMs are an important tool to identify LLM vulnerabilities that may not be covered in static benchmarks, allowing for more thorough probing. They can also adapt to each specific LLM to discover weaknesses unique to it. Most current automated red teaming methods a...
Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset
Android malware detectors built with machine learning often suffer from temporal bias: models are trained and evaluated without respecting apps' actual release times, inflating accuracy and weakening real-world robustness. We address this by constructing a time-stamped dataset of benign and...
Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations
This work proposes a structural approach to concept drift detection in malware classification using decision tree rulesets. Classifiers are trained across temporal windows on the EMBER2024 dataset, and drift is quantified by comparing extracted rule representations using feature importance,...
Apple Silicon Vulnerability Research — A18 Pro (MacBook Neo)
This is systematic security research targeting Apple's A18 Pro chip MacBook Neo / Mac17,5, the first A-series SoC shipped in a Mac laptop. The MacBook Neo is used as an authorized Apple Security Research Device SRD and doubles as a high-visibility proxy for iPhone 16 Pro research, since A18 Pro i...
Rosemary 1.0.4
Rosemary is a cross-platform transparent tunneling platform designed for network pivoting. Unlike traditional tools that rely on TUN/TAP interfaces or require per-application proxy configuration like proxychains, Rosemary intercepts traffic at the kernel level...
Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective
Machine learning-based malware detectors are increasingly vulnerable to adversarial examples. Traditional defenses, such as one-shot adversarial training, often fail against adaptive attackers who use reinforcement learning to bypass detection. This paper proposes a robust defense framework based...
GNU Privacy Guard 2.5.19
GnuPG the GNU Privacy Guard or GPG is GNU's tool for secure communication and data storage. It can be used to encrypt data and to create digital signatures. It includes an advanced key management facility and is compliant with the proposed OpenPGP Internet standard as described in RFC2440. As suc...
Keras 3.13.0 Bulk Generator for Large-Scale HDF5 Shape Test Models
This script is a parallel batch generator designed to create multiple .keras model files using a thread pool. Each file is generated with a predefined set of large tensor shapes intended for stress testing or memory-impact evaluation in HDF5/Keras workflows...
Rosemary 1.0.3
Rosemary is a cross-platform transparent tunneling platform designed for network pivoting. Unlike traditional tools that rely on TUN/TAP interfaces or require per-application proxy configuration like proxychains, Rosemary intercepts traffic at the kernel level...
Grav CMS Authenticated Scanner
This Python script is a safe, read-only scanner designed to detect whether a target running Grav CMS with its Admin plugin may be vulnerable to CVE-2025-50286, based purely on version analysis...