Security and Resilience in Autonomous Vehicles: A Proactive Design Approach

Autonomous vehicles AVs promise efficient, clean and cost-effective transportation systems, but their reliance on sensors, wireless communications, and decision-making systems makes them vulnerable to cyberattacks and physical threats. This chapter presents novel design techniques to strengthen t...

The threat hunter’s gambit

Welcome to this week's edition of the Threat Source newsletter. " Study hard what interests you the most in the most undisciplined, irreverent and original manner possible." ― Richard Feynman " I had discovered that learning something, no matter how complex, wasn't hard when I had a reason to wan...

Towards Resilient Intrusion Detection in CubeSats: Challenges, TinyML Solutions, and Future Directions

CubeSats have revolutionized access to space by providing affordable and accessible platforms for research and education. However, their reliance on Commercial Off-The-Shelf COTS components and open-source software has introduced significant cybersecurity vulnerabilities. Ensuring the cybersecuri...

Model Context Protocol Threat Modeling and Analyzing Vulnerabilities to Prompt Injection with Tool Poisoning

The Model Context Protocol MCP has rapidly emerged as a universal standard for connecting AI assistants to external tools and data sources. While MCP simplifies integration between AI applications and various services, it introduces significant security vulnerabilities, particularly on the client...

Cyber-Resilient Digital Twins: Discriminating Attacks for Safe Critical Infrastructure Control

Industrial Cyber-Physical Systems ICPS face growing threats from cyber-attacks that exploit sensor and control vulnerabilities. Digital Twin DT technology can detect anomalies via predictive modelling, but current methods cannot distinguish attack types and often rely on costly full-system...

Ransomware and Artificial Intelligence: A Comprehensive Systematic Review of Reviews

This study provides a comprehensive synthesis of Artificial Intelligence AI, especially Machine Learning ML and Deep Learning DL, in ransomware defense. Using a "review of reviews" methodology based on PRISMA, this paper gathers insights on how AI is transforming ransomware detection, prevention,...

PT-2026-24949

In Progress Flowmon ADS versions prior to 12.5.5 and 13.0.3, a vulnerability exists whereby an adversary with access to Flowmon monitoring ports may craft malicious network data that, when processed by Flowmon ADS and viewed by an authenticated user, could result in unintended actions being...

Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing

In modern transportation networks, adversaries can manipulate routing algorithms using false data injection attacks, such as simulating heavy traffic with multiple devices running crowdsourced navigation applications, to mislead vehicles toward suboptimal routes and increase congestion. To addres...

ProvAgent: Threat Detection Based on Identity-Behavior Binding and Multi-Agent Collaborative Attack Investigation

Advanced Persistent Threats APTs pose critical challenges to modern cybersecurity due to their multi-stage and stealthy nature. While provenance-based detection approaches show promise in capturing causal attack semantics, current threat provenance practices face two paradoxical issues: 1 expert...

AegisUI: Behavioral Anomaly Detection for Structured User Interface Protocols in AI Agent Systems

AI agents that build user interfaces on the fly assembling buttons, forms, and data displays from structured protocol payloads are becoming common in production systems. The trouble is that a payload can pass every schema check and still trick a user: a button might say "View invoice" while its...

Vulnerability fixed in Juniper Junos OS Evolved

Juniper has fixed a vulnerability in Junos OS Evolved Specifically for PTX Series devices. The vulnerability is in the On-Box Anomaly detection framework of Junos OS Evolved that runs on PTX Series devices. The cause is an incorrect assignment of permissions that allows unauthenticated remote...

EUVD-2026-8693

An Incorrect Permission Assignment for Critical Resource vulnerability in the On-Box Anomaly detection framework of Juniper Networks Junos OS Evolved on PTX Series allows an unauthenticated, network-based attacker to execute code as root. The On-Box Anomaly detection framework should only be...

PT-2026-21964

Name of the Vulnerable Software and Affected Versions Juniper Networks Junos OS Evolved on PTX Series versions prior to 25.4R1-S1-EVO, 25.4R2-EVO, and 26.2R1-EVO Description A critical issue exists in Juniper Networks Junos OS Evolved, specifically within the On-Box Anomaly Detection framework on...

Integrating Advanced API Security with Imperva Gateway Environment

As APIs power the majority of modern web applications, implementing robust API security is no longer optional - it’s a critical necessity for data protection. This guide explores how to seamlessly integrate API gateway security into your Imperva on-premises environment to mitigate OWASP Top 10...

Evasion of IoT Malware Detection Via Dummy Code Injection

The Internet of Things IoT has revolutionized connectivity by linking billions of devices worldwide. However, this rapid expansion has also introduced severe security vulnerabilities, making IoT devices attractive targets for malware such as the Mirai botnet. Power side-channel analysis has...

Next-Generation Cyberattack Detection with Large Language Models: Anomaly Analysis across Heterogeneous Logs

This project explores large language models LLMs for anomaly detection across heterogeneous log sources. Traditional intrusion detection systems suffer from high false positive rates, semantic blindness, and data scarcity, as logs are inherently sensitive, making clean datasets rare. We address...

KRONE: Hierarchical and Modular Log Anomaly Detection

Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions with clear boundaries, this structure is lost when they are stored as flat sequences. As a result, state-of-the-art methods risk missing true dependencies...

Reference-Free EM Validation Flow for Detecting Triggered Hardware Trojans

Hardware Trojans HTs threaten the trust and reliability of integrated circuits ICs, particularly when triggered HTs remain dormant during standard testing and activate only under rare conditions. Existing electromagnetic EM side-channel-based detection techniques often rely on golden references o...

Semantic-Aware Advanced Persistent Threat Detection Using Autoencoders on LLM-Encoded System Logs

Advanced Persistent Threats APTs are among the most challenging cyberattacks to detect. They are carried out by highly skilled attackers who carefully study their targets and operate in a stealthy, long-term manner. Because APTs exhibit "low-and-slow" behavior, traditional statistical methods and...

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...