Advance_WAF_project_CS

WAFinity - Infinite Protection, Intelligent Detection WAFin...

Characterizing AI-Assisted Bot Traffic in Darknet Data: Implications for ICS and IIoT Security

The rise of automated scanning tools and AI assisted reconnaissance agents has significantly altered internet background traffic patterns, threatening the baseline assumptions underlying intrusion detection systems IDS deployed in critical infrastructure networks. This paper characterizes the...

When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications

Natural language interfaces to structured databases are becoming increasingly common, largely due to advances in large language models LLMs that enable users to query data using conversational input rather than formal query languages such as SQL. While this paradigm significantly improves usabili...

AI Native Asset Intelligence

Modern security environments generate fragmented signals across cloud resources, identities, configurations, and third-party security tools. Although AI-native security assistants improve access to this data, they remain largely reactive: users must ask the right questions and interpret...

Evaluating Tabular Representation Learning for Network Intrusion Detection

Classic Network Intrusion Detection Systems NIDS often rely on manual feature engineering to extract meaningful patterns from network traffic data. However, this approach requires domain expertise and runs counter to the widely adopted principle of modern machine learning and neural networks: tha...

Exploit for Improper Check for Unusual or Exceptional Conditions in Mozilla Firefox

🔐 PDFGuardian Pro - Advanced PDF.js Security Fortification Fra...

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...

API Security Based on Automatic OpenAPI Mapping

This paper presents Map Reduce Graph MRG, a novel unsupervised method for modeling and securing HTTP REST APIs. MRG learns API structure from real-world traffic without prior knowledge or labels, automatically generating OpenAPI-compliant documentation by reconstructing routes, methods, and...

DP-FlogTinyLLM: Differentially Private Federated Log Anomaly Detection Using Tiny LLMs

Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world settings, these logs are often distributed across multiple organizations and cannot be centralized due to privacy and security constraints. Existing...

Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining

Anomaly-based Intrusion Detection Systems IDSs ensure protection against malicious attacks on networked systems. While deep learning-based IDSs achieve effective performance, their limited trustworthiness due to black-box architectures remains a critical constraint. Despite existing explainable...

CVE-2026-5598

A flaw was found in Legion of the Bouncy Castle Inc. BC-JAVA core. A covert timing channel vulnerability, caused by non-constant time comparisons, risks the leakage of private keys in the FrodoKEM implementation. An unauthenticated, remote attacker can potentially exploit this timing discrepancy ...

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...

Security Bulletin: Vulnerabilities in urllib3, router, qs, cryptography, axios might affect IBM Storage Defender Sentinel Anomaly Scan Engine.

Summary IBM Storage Defender Sentinel Anomaly Scan Engine can be affected by vulnerabilities in urllib3, router, qs, cryptography, and axios. Vulnerabilities include allowing an attacker to cause cross-site scripting, input improper data, provide a public key point from a small order subgroup, an...

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...

Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain

Large language model LLM agents increasingly rely on third-party API routers to dispatch tool-calling requests across multiple upstream providers. These routers operate as application-layer proxies with full plaintext access to every in-flight JSON payload, yet no provider enforces cryptographic...

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...

Ransomware in 2025: Blending in is the strategy

Ransomware attacks aren't smash-and-grab anymore. They're built on access that already looks legitimate -- closer to positioning chess pieces than breaking the door down. That's the big trend that comes through in the ransomware data from the Talos 2025 Year in Review. Once attackers have initial...

Policy-Guided Threat Hunting: An LLM Enabled Framework with Splunk SOC Triage

With frequently evolving Advanced Persistent Threats APTs in cyberspace, traditional security solutions approaches have become inadequate for threat hunting for organizations. Moreover, SOC Security Operation Centers analysts are often overwhelmed and struggle to analyze the huge volume of logs...

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...