Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Security threats don’t announce themselves. They can slip in through vulnerabilities in your code, hide in third-party libraries, and exploit gaps that your team hasn’t had time to patch yet. That’s why application threat detection isn’t just a nice-to-have; it’s the foundation of a modern security program.

If you’ve deployed your first AI agent, then you must have given it access to your CRMs, ticketing systems, and your cloud storage. This AI agent is programmed to run 24/7, make decisions, call external APIs, and trigger actions (without a human in the loop). Now, answer these questions: If you cannot answer these questions, then you have an agentic AI identity issue. Traditional Identity and Access Management (IAM) was built for service accounts with static API keys and users with usernames.

Artificial intelligence is rapidly transforming how organizations approach cybersecurity. However, much of the debate still centers on the same old question: will AI eventually replace security analysts? In reality, the question is no longer whether AI will replace analysts, but how it can amplify their performance and redefine their role within the SOC.

An attacker republished the entire @mastra npm scope on June 17, 2026, slipping a single malicious dependency into 143 packages and counting, including @mastra/core, which pulls roughly 4 million downloads a month and has hundreds of dependent projects. The injected dependency, easy-day-js, is a dayjs lookalike whose install hook disables TLS verification, downloads a second-stage payload from a raw IP address, and runs a cross-platform cryptocurrency stealer in the background.

Frontier AI is poised to change cybersecurity faster than most organizations can adapt. It’s accelerating vulnerability discovery, which puts new pressure on security teams to handle more vulnerabilities, in less time, with workflows built for much slower technology. The primary challenge of the frontier AI era is not the increase in vulnerabilities. It’s understanding which exposures are most critical and how to address them before adversaries target them.

India’s data protection landscape is changing. With the Digital Personal Data Protection Act bringing new compliance obligations to the fore, businesses across the country are being forced to think more...

AI models that generate code are also the best at exploiting it. Here’s why independent verification, not the model itself, is the only trustworthy answer. This month, the US government ordered Anthropic to suspend access to its most capable models, Mythos 5 and the newly released Fable 5, for all foreign nationals, citing national security. The trigger was a single reported jailbreak that let one of those models slip past its own guardrails on cybersecurity tasks.

Businesses must never store CVV/CVC codes, full magnetic stripe data, or PINs under any circumstances. For PANs that must be retained, use AES-256 encryption with hardware security modules (HSMs) or, better yet, replace card data entirely with tokens via a PCI-DSS-compliant third-party vault. This removes raw card data from your environment and reduces your compliance scope from SAQ D (hundreds of controls) to SAQ A (as few as 22 controls).

The Cybersecurity Maturity Model Certification (CMMC) is a Department of Defense (DoD) framework made to ensure organizations handling federal information maintain adequate cybersecurity controls. While CMMC is often associated with government agencies and defense contractors, research universities involved in DoD-funded projects may also need to protect Controlled Unclassified Information (CUI) like research data and technical specifications.

Most security teams aren’t naive to the growing risk in their environment, but because of high event volume and asset visibility gaps, emerging risk dynamics have become increasingly challenging to act on. Arctic Wolf’s latest State of the Cybersecurity Attack Surface report puts real data behind the challenge.