Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Testing MiniMax M2.1 for AI Coding: The Results Might Surprise You

Jan 19, 2026 By Snyk In Snyk
Can "lesser-known" AI models actually keep up with the giants like Google, OpenAI, and Anthropic? In today’s video, we put MiniMax M2.1 to the ultimate test: building a production-ready, secure Node.js note-taking application from a single prompt. We’ll explore how to access MiniMax natively in the Windsurf IDE, walk through the debugging process for common errors (like environment variables and OS-specific dependencies), and perform a deep-dive security audit using Snyk. Stick around until the end to learn how to integrate MiniMax M2.1 into VS Code using OpenRouter.
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kroll

AI Strategy: Building a Future-Proof Framework

Jan 19, 2026 By Kroll In Kroll
Artificial intelligence (AI) adoption is fast becoming a strategic necessity for modern businesses. With adoption continuing at pace, a carefully considered strategy is essential for gaining or maintaining a competitive advantage, managing downside risk and addressing the continued regulatory, legal, ethical and operational complexities presented by AI.
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cloudflare

How we mitigated a vulnerability in Cloudflare's ACME validation logic

Jan 19, 2026 By Hrushikesh Deshpande In Cloudflare
On October 13, 2025, security researchers from FearsOff identified and reported a vulnerability in Cloudflare's ACME (Automatic Certificate Management Environment) validation logic that disabled some of the WAF features on specific ACME-related paths. The vulnerability was reported and validated through Cloudflare’s bug bounty program. The vulnerability was rooted in how our edge network processed requests destined for the ACME HTTP-01 challenge path (/.well-known/acme-challenge/*).
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trilio

Trilio Transform Automation: Complete Kubernetes Migration Solution

Jan 19, 2026 By Rodolfo Casas In Trilio
Kubernetes workloads comprise more than just container images—they encapsulate state, storage dependencies, service endpoints, and intricate metadata. A naive “lift and shift” approach that moves persistent data, manifest files, and images overlooks the crucial platform-specific configurations required for true application fidelity.
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safeaeon

8 Ways Organizations Reduce Exposure to Social Engineering Attacks

Jan 19, 2026 By SafeAeon Inc. In SafeAeon
It is not always malware or a sophisticated tool that results in cyber threats. Sometimes, this happens through a convincing email or a request that appears trustworthy. There have been occasions where attackers created a moment of urgency to lead someone into clicking, sharing, or approving without realizing the consequences. This is social engineering. Social engineering threats are becoming more dangerous.
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Ransomware, Bitcoin And Harsh Crypto Reality

Jan 19, 2026 By Razorthorn Security In Razorthorn
An estimated ninety eight percent of ransoms use cryptocurrency, with Bitcoin at the centre, which turns it into core infrastructure for extortion and fraud. The discussion questions positive impact, pointing to energy waste, slow transactions, fixed supply design and the likelihood of central banks adopting similar tech without those flaws.
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outpost 24

The 2026 Cybersecurity Threat Landscape: Persistent Adversaries, Repeatable Playbooks

Jan 19, 2026 By Lidia López Sanz In Outpost 24
As a threat intelligence team, our job is to separate noise from persistence in the cybersecurity threat landscape. In this article, we assess the threats most likely to remain and evolve through 2026 based on the threat actors, campaigns, and malware we have tracked and researched during the last year. Our work centers on tracking adversaries with a strong footprint in the underground ecosystem: forums, Telegram channels, data leak sites, and marketplaces where cybercriminals operate.
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protecto

Why Protecto Privacy Vault Is Ideal for Masking Structured Data

Jan 19, 2026 By Amar Kanagaraj In Protecto
Picture this. You’re a data engineer at a healthcare company with millions of patient records in Snowflake. HIPAA requires you to protect PII before sharing data with researchers or running analytics. So you tokenize the data. And your system catches fire. Your joins break. Your ETL pipelines fail. BI dashboards return wrong results. ML model training jobs crash. All because something fundamental changed about your data architecture.
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