CrowdStrike Launches Frontier Models for Cybersecurity, Created with NVIDIA

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CrowdStrike SafeMind, the first agentic system for defenders, built with NVIDIA Nemotron, protects more and costs less than generic frontier models

AUSTIN, Texas & LAS VEGAS--(BUSINESS WIRE)-- Fal.Con 2026 – CrowdStrike (NASDAQ: CRWD) today introduced CrowdStrike SafeMind, a family of purpose-built security models and harnesses from the CrowdStrike Cyber Superintelligence Lab. The SafeMind agentic system will operate natively in the CrowdStrike Falcon® platform. Trusted access for standalone models and harnesses will be part of the Project QuiltWorks program.

SafeMind – Delivering Cybersecurity’s First Agentic System Built for Defenders

Unlike frontier AI models, SafeMind runs as one system designed to deliver AI safety: an offensive model that finds the attack path, a defensive model that closes it, and the harnesses that operate both in the same loop.

SafeMind model training data comes from CrowdStrike Falcon sensor telemetry, the world’s largest pureplay cyber dataset and edge install base. Model training also includes CrowdStrike’s threat intelligence, Falcon Complete MDR event annotations, and fifteen years of incident response fieldwork, where human responders stopped breaches on the front lines. SafeMind launches with two distinct models, delivering unique security competencies:

• Red Tempest: Offensive red team model release, built for advanced attack scenarios, emulating AI adversaries.
• Blue Solano: Defensive blue team model release, built for protecting enterprise assets by deploying battle-tested measures that defenders use in real-life.

CrowdStrike builds the models using NVIDIA Nemotron open models in collaboration with NVIDIA, its AI design partner. The program also includes CoreWeave’s AI Cloud for training and inference.

SafeMind’s harnesses operationalize both the red and blue CrowdStrike models in a closed-loop system that continuously pits the models against each other to improve. The harnesses also work with frontier and open-source models, maximizing user choice and model preference while maintaining cost control. Frontier labs can tell a defender a risk exists. CrowdStrike goes beyond with the harnesses that can autonomously act on risk.

“The future of cybersecurity won’t be defined by AI that simply identifies threats, it will be defined by AI that defeats them,” said George Kurtz, CEO and founder of CrowdStrike. “SafeMind brings offensive and defensive models together in a system trained on CrowdStrike’s unique cyber data. It finds weaknesses, strengthens protection, and gets smarter with every cycle, advancing our mission to stop breaches at machine speed.”

“Cybersecurity in the age of AI will be a continuous contest between adversaries using AI to scale attacks and defenders using AI to expand detection and response. Cyber defense will be among the most compute-intensive applications of AI,” said Jensen Huang, founder and CEO of NVIDIA. “SafeMind combines NVIDIA Nemotron open models with CrowdStrike’s deep cybersecurity expertise, trusted security data, purpose-built agent harnesses, rigorous evaluations, and safeguards – creating a frontier agentic cybersecurity stack designed to operate at machine speed. Powered by NVIDIA accelerated computing, SafeMind makes AI a force multiplier for defenders.”

“The real test of AI is what it can do in production, at scale, when the stakes are highest. Few environments put that to the test more than cybersecurity,” said Michael Intrator, co-founder and chief executive officer, CoreWeave. “We’re proud to power SafeMind across training and inference as CrowdStrike puts specialized AI to work against real-world threats.”

What Evaluations Show

Compared to leading frontier models and open-source baselines, SafeMind delivers:

• 29% higher detection rate
• 6x faster end-to-end remediation
• 99% cost savings on detection and remediation

“Our models are the start of a new chapter for cyberdefense,” said Dr. Bartley Richardson, chief AI and autonomous systems officer at CrowdStrike. "With the models and harnesses together in a co-evolving agentic system, defenders can now act at machine speed. This is the foundation for the next decade of AI security, and CrowdStrike is the only company that owns the entire stack, from sensor to harness to model."

About CrowdStrike

CrowdStrike (NASDAQ: CRWD), a global cybersecurity leader, has redefined modern security with the world’s most advanced cloud-native platform for protecting critical areas of enterprise risk – endpoints and cloud workloads, identity and data.

Powered by the CrowdStrike Security Cloud and world-class AI, the CrowdStrike Falcon® platform leverages real-time indicators of attack, threat intelligence, evolving adversary tradecraft, and enriched telemetry from across the enterprise to deliver hyper-accurate detections, automated protection and remediation, elite threat hunting, and prioritized observability of vulnerabilities.

Purpose-built in the cloud with a single lightweight-agent architecture, the Falcon platform delivers rapid and scalable deployment, superior protection and performance, reduced complexity, and immediate time-to-value.

CrowdStrike: We stop breaches.

Learn more: https://www.crowdstrike.com/

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© 2026 CrowdStrike, Inc. All rights reserved. CrowdStrike and CrowdStrike Falcon are marks owned by CrowdStrike, Inc. and are registered in the United States and other countries. CrowdStrike owns other trademarks and service marks and may use the brands of third parties to identify their products and services.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260901951891/en/

Media Contact
Jake Schuster
CrowdStrike Corporate Communications
press@crowdstrike.com

Source: CrowdStrike

Key Terms

agentic system technical

An agentic system is an automated decision-making tool or software that acts independently to carry out tasks, set priorities, or make choices on behalf of people or organizations—think of it as a self‑driving assistant for business processes. Investors care because these systems can change costs, speed, and risk exposure: they can boost efficiency and revenue potential but also introduce operational errors, compliance issues, or liability that affect a company’s value.

frontier models technical

Frontier models are the most powerful and cutting-edge artificial intelligence systems, trained on massive amounts of data to perform complex tasks like generating text, analyzing images, or making predictions. For investors, they matter because they can create significant advantages or risks for companies — like a new industrial machine that radically boosts productivity or a costly, unproven technology that attracts regulatory scrutiny and high ongoing costs — affecting growth prospects, margins, and competitive position.

red team technical

A red team is an internal or external group that plays the role of an opponent to test a company’s plans, systems, or defenses by trying to find weaknesses before real threats do. Like a dress rehearsal where actors intentionally break the script to reveal problems, red-team exercises can cover cybersecurity attacks, regulatory or business-process failures, and other operational risks; for investors, their findings signal how well a company identifies and fixes vulnerabilities that could affect performance or reputation.

blue team technical

A blue team is the group within an organization responsible for defending its computer systems, networks, and data against cyberattacks. They monitor for threats, patch vulnerabilities, enforce security policies, and respond to incidents—like a building’s security staff who watch cameras, lock doors, and react to break-ins. Investors care because a strong blue team reduces the chance of breaches that can cause financial loss, operational disruption, regulatory fines, or reputational damage.

inference technical

Inference is the process of drawing a conclusion from available evidence or data, like a detective piecing together clues to form a likely story. For investors it matters because these judgments turn raw reports, test results, or market signals into expectations about future performance, risk, or regulatory outcomes—so how someone infers from the same facts can change investment decisions and valuation.