Characterizing Event-Themed Malicious Web Campaigns: A Case Study on War-Themed Websites

Cybercrimes such as online scams and fraud have become prevalent. Cybercriminals often abuse various global or regional events as themes of their fraudulent activities to breach user trust and attain a higher attack success rate. These attacks attempt to manipulate and deceive innocent people int...

CTEM's Core: Prioritization and Validation

Despite a coordinated investment of time, effort, planning, and resources, even the most up-to-date cybersecurity systems continue to fail. Every day. Why? It's not because security teams can't see enough. Quite the contrary. Every security tool spits out thousands of findings. Patch this. Block...

Adversarial Defense in Cybersecurity: a Systematic Review of GANs for Threat Detection and Mitigation

Machine learning-based cybersecurity systems are highly vulnerable to adversarial attacks, while Generative Adversarial Networks GANs act as both powerful attack enablers and promising defenses. This survey systematically reviews GAN-based adversarial defenses in cybersecurity 2021--August 31,...

Towards Adapting Federated and Quantum Machine Learning for Network Intrusion Detection: a Survey

This survey explores the integration of Federated Learning FL with Network Intrusion Detection Systems NIDS, with particular emphasis on deep learning and quantum machine learning approaches. FL enables collaborative model training across distributed devices while preserving data privacy-a critic...

Rain: Transiently Leaking Data from Public Clouds Using Old Vulnerabilities

Given their vital importance for governments and enterprises around the world, we need to trust public clouds to provide strong security guarantees even in the face of advanced attacks and hardware vulnerabilities. While transient execution vulnerabilities, such as Spectre, have been in the...

The API Battleground: Why APIs are the new frontline—and how to stop the stealthiest attacks

APIs used to be the quiet backstage crew that made apps feel magical. Now attackers have learned the script — they walk onstage, deliver perfectly polite lines, and walk off with the props. In H1 2025 Imperva observed 40,000+ API incidents across 4,000+ monitored environments , including an...

Adversarial Attacks against Automated Fact-Checking: a Survey

In an era where misinformation spreads freely, fact-checking FC plays a crucial role in verifying claims and promoting reliable information. While automated fact-checking AFC has advanced significantly, existing systems remain vulnerable to adversarial attacks that manipulate or generate claims,...

The Price of ‘Free’: How Nulled Plugins Are Used to Weaken Your Defense

The Wordfence Threat Intelligence Team has discovered a new malware campaign that highlights the hidden risks associated with "nulled plugins", or premium plugins that have been tampered with by third parties. This campaign is particularly concerning because it doesn't just infect websites: it...

Backdoor Attacks and Defenses in Computer Vision Domain: a Survey

Backdoor trojan attacks embed hidden, controllable behaviors into machine-learning models so that models behave normally on benign inputs but produce attacker-chosen outputs when a trigger is present. This survey reviews the rapidly growing literature on backdoor attacks and defenses in the...

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT continues to expose critical security vulnerabilities, necessitating the development of efficient and robust intrusion detection systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detectio...

Network-Level Censorship Attacks in the InterPlanetary File System

The InterPlanetary File System IPFS has been successfully established as the de facto standard for decentralized data storage in the emerging Web3. Despite its decentralized nature, IPFS nodes, as well as IPFS content providers, have converged to centralization in large public clouds...

Schrodinger'S Toolbox: Exploring the Quantum Rowhammer Attack

Residual cross-talk in superconducting qubit devices creates a security vulnerability for emerging quantum cloud services. We demonstrate a Clifford-only Quantum Rowhammer attack-using just X and CNOT gates-that injects faults on IBM's 127-qubit Eagle processors without requiring pulse-level...

Detecting Stealthy Data Poisoning Attacks in AI Code Generators

Deep learning DL models for natural language-to-code generation have become integral to modern software development pipelines. However, their heavy reliance on large amounts of data, often collected from unsanitized online sources, exposes them to data poisoning attacks, where adversaries inject...

Google Reveals UNC6395’s OAuth Token Theft in Salesforce Breach

A new advisory from Google and Mandiant reveals a widespread data breach in Salesforce. Learn how UNC6395 bypassed…...

Foe for Fraud: Transferable Adversarial Attacks in Credit Card Fraud Detection

Credit card fraud detection CCFD is a critical application of Machine Learning ML in the financial sector, where accurately identifying fraudulent transactions is essential for mitigating financial losses. ML models have demonstrated their effectiveness in fraud detection task, in particular with...

Researchers Uncover GPT-5 Jailbreak and Zero-Click AI Agent Attacks Exposing Cloud and IoT Systems

Cybersecurity researchers have uncovered a jailbreak technique to bypass ethical guardrails erected by OpenAI in its latest large language model LLM GPT-5 and produce illicit instructions. Generative artificial intelligence AI security platform NeuralTrust said it combined a known technique calle...

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...

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,...

Scattered Spider Hacker Arrests Halt Attacks, But Copycat Threats Sustain Security Pressure

Google Cloud's Mandiant Consulting has revealed that it has witnessed a drop in activity from the notorious Scattered Spider group, but emphasized the need for organizations to take advantage of the lull to shore up their defenses. "Since the recent arrests tied to the alleged Scattered Spider...

Can We End the Cat-And-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms

Anticipating emerging attack methodologies is crucial for proactive cybersecurity. Recent advances in Large Language Models LLMs have enabled the automated generation of phishing messages and accelerated research into potential attack techniques. However, predicting future threats remains...