Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How AI Is Changing Both Cyberattacks and Cyber Defense

Artificial intelligence is changing cybersecurity because it gives both attackers and defenders more speed, scale, and flexibility. Attackers can use AI to write better messages, test code, scan targets, and move through stolen data faster. Security teams can use similar technology to detect odd behavior, sort alerts, and respond before a small incident becomes a serious breach. The biggest shift is not that AI replaces every hacker or every analyst. Work that once required hours, special training, or a larger team can now be assisted by software.

Why Traditional Security Fails Against AI Attacks | Fidelis Deception

AI-powered cyber attacks are evolving faster than traditional defenses can respond. Modern attackers use valid credentials, native tools, and AI-assisted reconnaissance to move through enterprise environments without triggering conventional security controls. Signature-based detection and behavioral analytics often struggle to detect these advanced intrusions before damage is done. In this video, discover how Fidelis Deception helps security teams detect and disrupt AI-accelerated attacks by turning attacker reconnaissance into immediate detection.

Why Unmanaged IoT Devices Create Hidden Security Gaps

Why did the seven-month dwell time inside that hospital surprise nobody on my team? A smart HVAC controller in a third-floor conference room sat on a US healthcare network for seven months. IT security had never inventoried it. The SOC had never seen its traffic. Within 72 hours of initial compromise, the attacker had pivoted to corporate systems and reached patient records. The final bill, as compiled in public breach reporting, lands at $12.4 million.

AI vs. AI: Fighting the Next Wave of Cyber Attacks with Ravid Circus

Recently our CMO, Tony Thompson, caught up with Seemplicity co-founder and CPO, Ravid Circus, in Paris to talk about the massive shift in the cybersecurity landscape caused by Claude Mythos. As AI research models like Claude Mythos hyper-scale the ability to identify vulnerabilities and weaponize exploits in minutes rather than months, traditional risk-based vulnerability management must evolve. In this video, you will learn.

Crowdsourced Chaos: The Evolution of NoName057(16) and Why DDoS Resilience Matters

According to Bitsight Threat Intelligence, NoName057(16) remains one of the most visible pro-Russian hacktivist groups conducting distributed denial-of-service (DDoS) attacks against countries and organizations perceived as supporting Ukraine. This matters because the risk can extend beyond direct business ties to Ukraine, and the group may also target organizations that do business with vendors, suppliers, partners, or service providers perceived as supporting Ukraine.

Miasma supply chain attack: malicious code found in @redhat-cloud-services npm packages

On June 1, 2026, researchers identified malicious code embedded in at least 32 package releases published under the @redhat-cloud-services npm namespace, a set of frontend components and API clients that power the Red Hat Hybrid Cloud Console. The compromised releases carry a preinstall script that runs an obfuscated payload the moment a package is installed, harvesting developer and cloud credentials and attempting to spread itself to other packages the victim can publish.

Miasma: Red Hat Cloud Services npm Packages Hit by a Mini Shai-Hulud-Style Campaign

On June 1, 2026, multiple npm packages in the @redhat-cloud-services scope were published with malicious versions. Each tarball ships a 4.1 MB obfuscated JavaScript file added to package.json as a preinstall hook. The hook runs a multi-stage loader that ends in a Bun-executed credential stealer hitting AWS, Azure, GCP, HashiCorp Vault, Kubernetes, GitHub Actions OIDC, npm, Bitwarden, and 1Password.

Types of AI Agent Attacks: A Security Team's Taxonomy

A security team running agents in production can already list the ways those agents get attacked: prompt injection, memory poisoning, tool abuse, model tampering, agent-to-agent coercion. The list is not the problem. The problem is that a security architect can recite all five and still not know which ones their detection stack will catch, because the way the field catalogs these attacks says nothing about whether the attack is catchable.