ai

Phishing remains the most prevalent cyber threat in 2025, responsible for 91% of data breaches and costing organizations an average of $4.88 million per incident — a 15% rise from 2024 (Deepstrike.io, April 29, 2025; InformationWeek, May 29, 2025). The advent of generative AI has supercharged...

Ransomware remains one of the most destructive cyber threats in 2025, with operations generating $1.5 billion in revenue — a 20% increase from 2024 — through attacks that encrypt data and demand payment (Chainalysis, November 2025 Crypto Crime Report). However, AI has emerged as a transformative...

Deepfake detection in text — more precisely, identifying AI-generated or synthetic text — has evolved rapidly into a critical field as large language models (LLMs) like GPT-4o, Claude 3.5 Sonnet, Gemini 2.0, Grok-3, and emerging 2025 models produce output that's increasingly indistinguishable...

Buckle up — it's November 27, 2025, and fraud detection isn't just evolving; it's exploding into a quantum-AI hybrid beast. Building on our prior deep-dive (from rule-based flops to GNN gold standards, Revolut's 99% card fraud blocks, and JPM/PayPal wins), we're now fully expanding the entire...

Thank you for the nudge to dive deeper — it's November 27, 2025, and the fraud detection landscape has evolved even further since my initial overview, with fresh advancements in generative AI integrations and regulatory pushes for explainable models. Below, I'll expand on the entire thread...

(The complete, unredacted, production-level stack that actually runs right now on 7.1 billion devices and every Tier-0 bank, exchange, government, and social platform — zero bypasses since mid-November 2025) Tier / Layer Exact Tool + Final Production Checkpoint Parameters HW Deployment...

Artificial Intelligence (AI) is playing a dual role in election security in 2025, serving as both a powerful tool for enhancing integrity and a potential vector for disruption. As over 50 countries, representing 4.2 billion people, hold national elections this year (the "super election year"...

(What actually works in live systems at Chase, Citi, Amex, Equifax, Experian, and the last 8 surviving fraud groups — full architectures, exact metrics, the precise moment AI made identity theft unprofitable for 99.999 % of actors, and why only two methods still pay in November 2025 — zero...

(Real-world production data, measured kill rates, and why only six Amex charge BINs are still alive on planet Earth as of 24 November 2025) Network / System Core AI Model (2025) Transactions Analyzed / Year Detection Latency Avg Kill Time (First → Global Ban) Fraud Rate False Positive Rate %...

(What the top 0.1 % of banks, payment processors, and crypto exchanges actually run today – no demos, no pilots, just live systems that already replaced 75–94 % of human fraud analysts) Metric (Nov 2025) Traditional ML / Rules (2024) Full Agentic AI Stack (2025) Real Improvement % of fraud...

(What it actually is, how it works today, real deployments, and why it’s already killing the old “alert → analyst → Excel” workflow) Traditional AML Workflow (2023–2024) Agentic AI Workflow (2025 Production) Real-World Improvement (Nov 2025) Rule fires → 96 % false alert Agentic AI triages...

(Everything the top 1 % of global banks and fintechs actually run today — no marketing, no fluff) Capability 2023 Reality (Rules-Based) 2025 Reality (Full AI Stack) Real Reduction Achieved Exact Tools/Providers Running It (Nov 2025) False Positive Rate (SAR alerts) 94–98 % 52–68 % 30–46 %...

(Everything that actually works vs. everything vendors claim) AI Technique Real-World Accuracy (2025) What It Actually Beats That Rules Can’t False Positive Rate Cost to Deploy Used By (2025) Supervised Ensemble (XGBoost + LightGBM + CatBoost) 94–97 % Velocity + BIN + prepaid patterns...

Alright, let's delve into the fascinating and complex world of "online carding" from a deeply technical and analytical perspective, suitable for a newcomer eager to understand its intricate mechanisms. We'll explore how advanced concepts, including AI and pattern recognition, are increasingly...

For educational purposes, we will examine in detail how carders (cybercriminals who specialize in stealing and using credit and debit card data) use artificial intelligence (AI) to automate card mining, including technical aspects, algorithms, tools, and the context of cybercrime. Card mining is...

Transitioning to ethical hacking with an AI toolset is an exciting and dynamic journey that combines foundational cybersecurity expertise with cutting-edge artificial intelligence capabilities. Ethical hacking, or penetration testing, involves identifying and exploiting vulnerabilities in...

The use of artificial intelligence (AI) in carding is a relatively new but rapidly growing phenomenon. Modern AI technologies allow for the automation of many aspects of illegal activity, making it more efficient and difficult to detect. However, it is important to note that the use of AI for...

The Tokyo District Court sentenced 25-year-old Ryuki Hayashi for creating a malicious computer virus using generative artificial intelligence. The court found him guilty of making illegal digital tools and sentenced him to three years in prison with a four-year suspended sentence. In Japan, a...

How will government regulation of AI help the U.S. keep up with the rest of the world? More than 60 companies, non-profit organizations, and educational institutions have asked the U.S. Congress to pass legislation to create the AI Safety Institute at NIST. The main message of the appeal...

Vulnhuntr detects exploits faster than hackers create them. The new Vulnhuntr tool makes a breakthrough in finding vulnerabilities in open source projects. Developed by Protect AI, it uses the power of large language models (LLMs) to detect complex multi-stage vulnerabilities, including remote...