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cs.CR updates on arXiv.org

An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense QSignAI: Quantum-Randomness-Seeded Identity Signatures at the Intersection of AI for Science and Science for AI A Standardized Ontology for Intent-Based Security Management in Autonomous Networks Code as a Weapon: A Consensus-Labeled Prompt Bank for Measuring Coding-Model Compliance with Malicious-Code Requests Cordyceps: Covert Control Attacks on LLMs via Data Poisoning SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness Mechanistic origins of catastrophic forgetting: why RL preserves circuits better than SFT? Red-Teaming Agent Execution Contexts: Open-World Security Evaluation on OpenClaw From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents Vendor-Conditioned Contrastive Learning for Predicting Organizational Cyber Threat Targets Anomaly Detection in XML-Structured SOAP Messages Using Tree-Based Association Rule Mining A Formal Calculus for International Relations Computation and Evaluation On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis Moving Target Defense for Web Applications using Bayesian Stackelberg Games A Mathematical Trust Algebra for International Nation Relations Computation and Evaluation A First Attempt to Cloud-Based User Verification in Distributed System Some Experimental Issues in Financial Fraud Detection: An Investigation Using Data Analytics to Detect Anomalous States in Vehicles On the Differential Privacy of Bayesian Inference Building and Measuring Privacy-Preserving Predictive Blacklists Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification Security Games with Ambiguous Beliefs of Agents Generating and Exploring S-Box Multivariate Quadratic Equation Systems with SageMath Private Disclosure of Information in Health Tele-monitoring Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review Implicit Contextual Integrity in Online Social Networks Phishing Detection in IMs using Domain Ontology and CBA - An innovative Rule Generation Approach Detecting fraudulent activity in a cloud using privacy-friendly data aggregates The Application of Differential Privacy for Rank Aggregation: Privacy and Accuracy An Evasion and Counter-Evasion Study in Malicious Websites Detection Hybrid Epidemics - A Case Study on Computer Worm Conficker A Self-Adaptive Network Protection System An Argumentation-Based Framework to Address the Attribution Problem in Cyber-Warfare Protecting Privacy through Distributed Computation in Multi-agent Decision Making Using Neural Network to Propose Solutions to Threats in Attack Patterns A Utility-Theoretic Approach to Privacy in Online Services Intrusion Detection using Continuous Time Bayesian Networks A DDoS-Aware IDS Model Based on Danger Theory and Mobile Agents Mining Malware Specifications through Static Reachability Analysis Subjective Logic Operators in Trust Assessment: an Empirical Study GOTCHA Password Hackers! On estimating total time to solve SAT in distributed computing environments: Application to the SAT@home project POMDPs Make Better Hackers: Accounting for Uncertainty in Penetration Testing Les POMDP font de meilleurs hackers: Tenir compte de l'incertitude dans les tests de penetration Automated Attack Planning Penetration Testing == POMDP Solving? Attack Planning in the Real World An Algorithm to Find Optimal Attack Paths in Nondeterministic Scenarios A Fuzzy Logic Based Certain Trust Model for E-Commerce Predicting Network Attacks Using Ontology-Driven Inference Semantic Matching of Security Policies to Support Security Experts A formalization of re-identification in terms of compatible probabilities A trust-based security mechanism for nomadic users in pervasive systems Intrusion Detection on Smartphones Obesity Heuristic, New Way On Artificial Immune Systems Secured Wireless Communication using Fuzzy Logic based High Speed Public-Key Cryptography (FLHSPKC) Mining Permission Request Patterns from Android and Facebook Applications (extended author version) Building a Chaotic Proved Neural Network Detecting Danger: The Dendritic Cell Algorithm Detecting Anomalous Process Behaviour using Second Generation Artificial Immune Systems Outrepasser les limites des techniques classiques de Prise d'Empreintes grace aux Reseaux de Neurones Building Computer Network Attacks ToLeRating UR-STD The DCA:SOMe Comparison A comparative study between two biologically-inspired algorithms Real-Time Alert Correlation with Type Graphs Performance Evaluation of DCA and SRC on a Single Bot Detection Behavioural Correlation for Detecting P2P Bots Malicious Code Execution Detection and Response Immune System inspired by the Danger Theory Integrating Real-Time Analysis With The Dendritic Cell Algorithm Through Segmentation Integrating Innate and Adaptive Immunity for Intrusion Detection Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm Further Exploration of the Dendritic Cell Algorithm: Antigen Multiplier and Time Windows Detecting Bots Based on Keylogging Activities Detecting Danger: Applying a Novel Immunological Concept to Intrusion Detection Systems Detecting Motifs in System Call Sequences Dendritic Cells for SYN Scan Detection Detecting Botnets Through Log Correlation DCA for Bot Detection Cooperative Automated Worm Response and Detection Immune Algorithm Cryptographic Implications for Artificially Mediated Games Differentially Private Empirical Risk Minimization An Immune Inspired Network Intrusion Detection System Utilising Correlation Context An Immune Inspired Approach to Anomaly Detection Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS Artificial Dendritic Cells: Multi-faceted Perspectives AIS for Misbehavior Detection in Wireless Sensor Networks: Performance and Design Principles The Role of Self-Forensics in Vehicle Crash Investigations and Event Reconstruction Beyond Nash Equilibrium: Solution Concepts for the 21st Century From Qualitative to Quantitative Proofs of Security Properties Using First-Order Conditional Logic Danger Theory: The Link between AIS and IDS? Dempster-Shafer for Anomaly Detection The Danger Theory and Its Application to Artificial Immune Systems ANTIDS: Self-Organized Ant-based Clustering Model for Intrusion Detection System Analyzing and Improving Performance of a Class of Anomaly-based Intrusion Detectors Soft Constraint Programming to Analysing Security Protocols A Method for Clustering Web Attacks Using Edit Distance Encoding a Taxonomy of Web Attacks with Different-Length Vectors
Layered Binary Templating: Efficient Detection of Compiler- and Linker-introduced Leakage
Martin Schwarzl, Erik Kraft, Daniel Gruss · 2022-08-03 · via cs.CR updates on arXiv.org

Cache template attacks demonstrated automated leakage of user input in shared libraries. However, for large binaries, the runtime is prohibitively high. Other automated approaches focused on cryptographic implementations and media software but are not directly applicable to user input. Hence, discovering and eliminating all user input side-channel leakage on a cache-line granularity within huge code bases are impractical. In this paper, we present a new generic cache template attack technique, LBTA, layered binary templating attacks. LBTA uses multiple coarser-grained side channel layers as an extension to cache-line granularity templating to speed up the runtime of cache templating attacks. We describe LBTA with a variable number of layers with concrete side channels of different granularity, ranging from 64 B to 2MB in practice and in theory beyond. In particular the software-level page cache side channel in combination with the hardware-level L3 cache side channel, already reduces the templating runtime by three orders of magnitude. We apply LBTAs to different software projects and thereby discover data deduplication and dead-stripping during compilation and linking as novel security issues. We show that these mechanisms introduce large spatial distances in binaries for data accessed during a keystroke, enabling reliable leakage of keystrokes. Using LBTA on Chromium-based applications, we can build a full unprivileged cache-based keylogger. Our findings show that all user input to Chromium-based apps is affected and we demonstrate this on a selection of popular apps including Signal, Threema, Discord, and password manager apps like passky. As this is not a flaw of individual apps but the framework, we conclude that all apps that use the framework will also be affected, i.e., hundreds of apps.