AiStrike Resource Hub

Following the launch of our Detection Optimization capability at RSAC 2025, we want to share more about the broader vision behind it—and where AiStrike is headed next.

All alerts are not equal. Yet somehow, every alert becomes the SOC’s problem. Every day, SIEM and CNAPP tools flood the SOC with alerts — but take a closer look, and they generally fall into four categories:

I got this question last week from one of the largest financial institutions: “When you’re looking at millions of CSPM alerts, do you actually investigate them or just treat them as hygiene issues and assign them to the cloud team?” Honestly, it’s a fair question—and one a lot of teams are probably asking themselves.

AI SOC tools today seem fixated onspeed—how quickly they can investigate and how many issues they can call falsepositives. But at AiStrike, we’re taking a slightly different approach.

Security operations (SecOps) teams are under pressure like never before. Threats are evolving, attack surfaces are expanding, and skilled security talent is scarce. To fill the gaps, many organizations turn to Managed Security Service Providers (MSSPs)—but at a steep cost.

As cyber threats grow in complexity and volume, AI-driven Security Automation Solutions (AI SOC) have emerged to automate and accelerate threat investigation and response. These platforms leverage Agentic AI to analyze security signals, investigate anomalies, and automate swift actions. However, the efficacy, cost, and scalability of an AI SOC largely depend on how it ingests and processes security data.

The Software-as-a-Service (SaaS) model has dominated the cybersecurity industry for years, offering cloud-based platforms that provide security solutions as a service. Today, with the power of AI, this landscape is evolving. A new paradigm has emerged—Service-as-Software (SaaS 2.0). This shift is transforming how organizations think about security operations, automation, and scalability.

As we step into 2025, the cybersecurity landscape is growing increasingly complex, driven by the adoption of AI, advanced threats, and evolving geopolitical dynamics. Cybersecurity vendors such as Palo Alto Networks, Google, and others predict substantial challenges in addressing sophisticated attacks, AI-driven exploitation, and supply chain vulnerabilities. Here’s an in-depth look at the emerging threat trends and how AiStrike is well-prepared to combat these challenges.

The rapid advancement of artificial intelligence (AI), machine learning (ML), and generative AI is transforming the landscape of cybersecurity. Security Operations Centers (SOCs) need smarter, faster, and more efficient solutions to keep up with the scale and sophistication of modern cyber threats.

Guidelines for selecting the most suitable CMS for your project.

Exploring the advantages of utilizing a CMS for website management.

An overview of what a CMS is and its importance.

Global Software Design Company Leverages AiStrike to Investigate Cloud Alerts

This guide provides CISOs with a comprehensive understanding of how AI-driven automation can revolutionize cloud security operations, enhancing both efficiency and effectiveness.

In today's landscape of relentless cyber-attacks, organizations are facing increasing threats to their critical assets. Security detection tools like SIEM, XDR, and CNAPP generate vast volumes of alerts—often lacking sufficient context—leaving security teams overwhelmed with alert backlog. With limited resources and insufficient business context, prioritizing critical alerts that require immediate action becomes a significant challenge.

Cloud infrastructure today is the primary target for malicious actors. The risk of exposure of cloud assets continues to grow as organizations expand their cloud footprint and new cyberattacks targeting cloud infrastructure emerge.