标签：#cybersec

South Korean authorities issued the record-breaking fine following a data breach that affected over 30 million customers.

Cross-border purchasing platforms commonly use marketing tactics such as coupons, registration points, order rebates, and spend-based discounts to acquire new users and boost engagement. However, public promotions are prime targets for “wool hunters” (fraudsters) who exploit batch account registration, fake orders, malicious order spamming, and combined discount abuse to drain platform benefits, causing direct financial losses. Most purchasing systems lack dedicated event risk controls, making them highly vulnerable to batch exploitation as soon as a promotion goes live. This not only leads to financial losses but also crowds out genuine user benefits and distorts campaign effectiveness. This article details Taocarts’ comprehensive anti-fraud risk control framework, which uses multi‑dimensional behavior detection, rule‑based blocking, and account risk assessment to accurately distinguish real users from malicious exploiters, ensuring fair and controllable marketing activities. First, we identify common malicious exploitation scenarios and system vulnerabilities in cross‑border platforms: Batch account registration – Using new‑user exclusive coupons and registration points to harvest benefits repeatedly. Fake order placement and cancellation – Repeatedly claiming limited‑time discounts or rebates by placing and then canceling orders. Multiple accounts from the same device/IP – Spamming orders to consume activity quotas. Illegal discount stacking – Violating platform rules by combining multiple coupons or point deductions. Activity volume manipulation – Generating fake orders to earn activity rewards or points, creating false engagement data. Traditional systems have no risk rules and cannot detect batch operations or abnormal behavior, leading to wasted marketing spend and campaigns that actually lose money. Taocarts builds a fine‑grained anti‑exploit rule engine based on four dimensions: user behavior, device information, network characteristics, and order data, ena

Most people studying for Security+ use practice questions the wrong way. They take a 90 question set, score a 74, feel bad, take another set the next day, score a 76, and call that progress. Two weeks later the number has barely moved and they have no idea why. The score is the least useful thing a practice exam gives you. What you actually want is a map of what you do not know yet. Here is the approach that worked for getting through SY0-701 without burning out on endless question sets. Start cold, on purpose Before you study a single domain, take a full practice exam and do not look anything up. It will feel bad. That is the point. A cold score tells you where you actually stand, not where your notes say you should be. SY0-701 is split into five domains, and they are not weighted evenly: 1.0 General Security Concepts (12%) 2.0 Threats, Vulnerabilities, and Mitigations (22%) 3.0 Security Architecture (18%) 4.0 Security Operations (28%) 5.0 Security Program Management and Oversight (20%) Domain 4 alone is more than a quarter of the exam. If you bomb Security Operations and ace General Concepts, splitting your time evenly between them is a mistake. A cold diagnostic shows you that split in about an hour. If you want one to start with, there is a free diagnostic exam at secplusmastery.com/diagnostic that breaks your result down by domain so the holes are easy to see. Review the wrong answers, and the right ones too This single habit moved my scores more than anything else: for every question I missed, I wrote down why each wrong option was wrong, not just why the correct one was correct. Security+ loves distractors that are real terms used in the wrong context. A question about a control that prevents an attack will offer you a control that detects one, and a control that corrects after the fact, all as plausible answers. If you only learn that the answer was C, you learn nothing you can reuse. If you learn that B was a detective control and the scenario asked for a p

Imagine you lose your work laptop on a commute. It holds 3 years of customer PII, internal product roadmaps, and access keys to your company's cloud infrastructure. Without full disk encryption enabled, anyone who finds the device can access every file in 10 minutes or less with a free bootable USB tool. With encryption enabled? They'll never access your data, even if they brute-force the password for decades. Per IBM's 2025 Cost of a Data Breach Report, organizations that use encryption save significantly on breach costs compared to teams that skip encryption. As cyber threats grow more sophisticated, and quantum computing edges closer to breaking legacy cryptographic standards, encryption is no longer an optional add-on—it's a core requirement for every digital system. This guide breaks down everything you need to know about data encryption, from core concepts to 2026's latest post-quantum developments, with actionable best practices for teams of all sizes. Table of Contents Core Concepts of Data Encryption How Does Data Encryption Work? Key Data Encryption Algorithms (2026 Approved & Deprecated) Encryption for All 3 Data States: At Rest, In Transit, In Use Real-World Data Encryption Use Cases Encryption Standards & Compliance Regulations Data Encryption Best Practices Common Encryption Mistakes to Avoid 2024-2026 Encryption Trends & Future Developments Conclusion & Key Takeaways References Core Concepts of Data Encryption Data encryption is a cryptographic process that converts human-readable plaintext into unreadable scrambled ciphertext using mathematical algorithms and secret keys. Only authorized parties with the correct decryption key can reverse the process to recover the original plaintext. Core Benefits of Encryption Encryption provides three non-negotiable security properties: Confidentiality : Only authorized users can access sensitive data Authentication : Verifies the origin of encrypted data Integrity : Confirms encrypted data has not been tampered w

The update brings a low-latency profile, speeds up search, and patches hundreds of flaws.

“Defenders cannot afford to take weeks to patch,” one Cybersecurity and Infrastructure Security Agency official warned on Wednesday.

North Korean hackers posing as remote IT workers and recruiters remain a major threat to U.S., European, and Asian companies, accounting for about half of all attacks over the past 12 months.

Cybersecurity researchers are complaining that Anthropic's new model Fable has guardrails that are too strict for any cybersecurity work.

ServiceNow is used by thousands of enterprises to automate their internal processes, but says several customers had data accessed because of a security bug.

Check Point said hackers broke into dozens of organizations by exploiting a VPN bug in several of its products used across the government.

Anthropic is releasing Claude Fable 5, its first Mythos-class model available to the public. The model comes with guardrails that block responses in high-risk areas like cybersecurity and biology.

Anthropic is releasing Claude Fable 5, its first Mythos-class model available to the public. The model comes with guardrails that block responses in high-risk areas like cybersecurity and biology.

Your EDR sees everything. Process launches, thread injections, DLL loads, filesystem writes. It has eyes inside the kernel — little hooks that fire before anything consequential happens, passing information up to the agent, letting it decide whether to block or alert. Now imagine something reaches into that kernel and quietly removes the hooks. No crash. No blue screen. No alert. The EDR process is still running, the dashboard still shows healthy, but the inputs it depends on are just gone. This is part of windows internals I've been exploring — understanding how systems actually behave under the hood, not just how tools interact with them. That's not a Windows bug. That's a trust problem. BYOVD doesn't exploit Windows — it exploits trust. Ring 0 vs Ring 3 — The Boundary That Matters Windows splits execution into privilege levels. Your applications, your malware, your EDR agent — they all run in Ring 3, user mode. The kernel runs in Ring 0. In my previous posts, I focused on how processes and execution work from an attacker's perspective. This goes one layer deeper — into the kernel where those assumptions start to break. This isn't just organizational. The CPU enforces it. Ring 3 code cannot directly read kernel memory. It cannot call kernel functions. Every interaction goes through a controlled interface — syscalls — and the kernel decides whether to honor each request. This is why typical malware stays loud. It has to use syscalls. Syscalls can be intercepted and monitored. At Ring 0, security tools are just data structures. Get code running in the kernel and those data structures become writable. The callback tables EDRs rely on, the hook registrations, the minifilter stack — all of it is reachable, readable, modifiable. A Quick Personal Note on Why This Boundary Matters Early on when I was messing around with kernel concepts, I tried doing something simple from user mode — reading a memory address that I knew belonged to a kernel structure. The kind of thing th

Microsoft shut down dozens of GitHub code repositories for Azure and AI coding tools after a reported hack.

The messaging giant announced that it disrupted a phishing campaign targeting its users with NSO’s spyware.

The bill is expected to blanket-ban companies and startups from selling people's precise location data across the state.

From a massive DOGE data breach and the hacking of critical energy and water systems to the hack of an FBI surveillance system, here are the most damaging security incidents and data breaches of 2026.

June 7, 2026. Dennis Kim, ex-CEO of Cyworld, CEO of BetaLabs https://github.com/gameworkerkim/vibe-investing https://github.com/gameworkerkim/CYBER-THREAT-INTELLIGENCE-REPORT Prologue: Two Incidents That Shook South Korea in 2026 In early June 2026, a data breach exposed the personal information of 5 million users of TVING, the largest OTT service in South Korea. The leaked data was extensive: IDs, names, birth dates, gender, CI (connection information), DI (duplicate registration verification information), mobile phone numbers, emails, refund account numbers, passwords, and more. The parent company, CJ ENM, saw its stock price plummet 3.44% in a single day, and investigations by the Personal Information Protection Commission and KISA were launched. But behind this incident hid another shocking fact. TVING's GitHub repository had an AWS access token hardcoded and publicly exposed. It was a stark reminder that a single cloud private key accidentally committed by a developer can jeopardize an entire company's infrastructure. These two events seem like different stories on the surface. Yet here I want to ask one common question: Who protects our generative AI, our LLM systems? Part 1. The Age of Vibe Coding: Security Takes a Backseat Recently, natural language-based programming using LLMs, the so-called "Vibe Coding" trend, has exploded. Generative AI coding assistants dramatically accelerate development speed. But behind this speed lies serious security risks. According to Veracode's 2025 GenAI Code Security report, 45% of code generated by LLMs contained security vulnerabilities. More concerning, developers place excessive trust in AI outputs and show behavior patterns prioritizing speed over vulnerability verification. Kaspersky's 2025 report revealed even more shocking findings. A vulnerability in the popular AI development tool Cursor (CVE-2025-54135) allowed attackers to execute arbitrary commands on a developer's machine, and a vulnerability in the Claude Code a

AI Code Security: Claude's rsync Bugs; Europe's GNSS Interference & GPS Anomalies Today's Highlights This week in security, a deep dive explores how AI code generation might introduce new vulnerabilities, with analysis showing Claude increasing bugs in rsync. We also highlight two critical infrastructure concerns: a powerful GNSS interference source over Europe and the mysterious 'numbers station' broadcasts found on GPS frequencies. Did Claude increase bugs in rsync? (Hacker News) Source: https://alexispurslane.github.io/rsync-analysis/ This article presents an intriguing analysis of how large language models (LLMs) might inadvertently introduce bugs into software. Focusing on Claude's contributions to the widely used rsync utility, the author investigates code changes attributed to AI and compares them against human-written code. The study reveals instances where AI-generated code, while appearing plausible, introduced subtle yet significant defects, raising questions about the reliability of AI assistance in critical codebases. The implications extend beyond rsync , pointing to potential supply chain vulnerabilities if AI-generated code is not rigorously audited. This research highlights a new frontier for AI-specific security, emphasizing the need for developers to employ practical hardening guides and thorough review processes when integrating AI into their development workflows to prevent the unintentional introduction of new attack vectors. Comment: As a developer, seeing concrete examples of AI introducing bugs, even subtle ones, in a fundamental tool like rsync is a wake-up call. It's a reminder that AI-generated code requires diligent human review, especially when security or reliability is paramount, highlighting prompt engineering as a defensive technique. Tracing a powerful GNSS interference source over Europe (Hacker News) Source: https://arxiv.org/abs/2606.03673 Researchers have identified and traced a significant source of Global Navigation Satellite

IBM and two of its subsidiary companies were allegedly breached during the mid-2010s, which a lawsuit filed by a former cybersecurity executive accuses IBM of not disclosing and actively covering up.