Microsoft is set to officially launch Security Copilot, its advanced generative AI assistant tailored for cybersecurity professionals, on April 1. This release will mark its general availability worldwide, supporting multiple languages and broad geographic regions. Unlike traditional subscription models, Security Copilot will adopt a capacity-based pricing strategy, billed monthly through a new metric called the Security Compute Unit (SCU), priced at $4 per hour.
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Security Copilot is built on an extraordinary foundation of security insights. It leverages the analysis of 78 trillion security signals that Microsoft processes every day, supplemented with intelligence from external security entities, including the National Security Agency (NSA). This immense data foundation enables the AI assistant to deliver sophisticated threat detection, analysis, and response capabilities.
In addition to Microsoft’s baseline data, customers have the option to further train and tailor Security Copilot using their own proprietary security data. This flexibility allows organizations to customize the AI assistant’s responses and capabilities to their specific environments and security needs.
From Private Testing to Public Availability
Originally announced in March 2023, Security Copilot has been accessible to select enterprises through Microsoft’s Early Access Program since October 2023. During this private, paid testing phase, the tool demonstrated particular strength in areas such as summarizing security incidents, analyzing impact, reverse engineering malicious scripts, and providing guided incident response recommendations.
As it moves into general availability, Microsoft expects these core functionalities to be the primary drivers of value for security teams across industries.
Multiple Access Points: Standalone and Embedded Experiences
Security Copilot can be accessed in two primary ways: through an immersive standalone portal designed specifically for the assistant, and via embedded experiences integrated directly into Microsoft’s broader security ecosystem. This includes integration with Defender XDR, Sentinel, and Defender Threat Intelligence, among others. Notably, the pricing remains consistent whether customers choose to use the standalone portal or the embedded options.
Azure as the Backbone for Security Copilot
A key requirement for using Security Copilot is having an Azure environment in place. Organizations will provision Azure resources to run the workloads necessary to power Security Copilot. The tool is designed to seamlessly integrate with whatever mix of Microsoft security solutions a company currently uses, ranging from a few to many.
Moreover, Microsoft is actively collaborating with third-party security vendors as well as internal teams—such as Entra ID, Intune management, and Purview compliance—to expand Security Copilot’s reach by embedding it within various security products and services.
What to Expect on Pricing: Understanding the Security Compute Unit
When it comes to estimating costs, Microsoft acknowledges the complexity involved. Because Security Copilot usage can vary widely depending on the types of queries, scripts, and incident workflows, there is no simple conversion between the number of SCUs consumed and the number of customer queries.
A Microsoft spokesperson explained that each prompt and task varies in resource demand. Some workflows may be brief and straightforward, while others could involve lengthy script reverse engineering or complex multi-step incident analysis. These differences directly impact SCU consumption.
To help customers manage costs and usage, Security Copilot includes an in-product dashboard that tracks SCU usage in real time, enabling organizations to monitor patterns and adjust their capacity accordingly.
As a general guideline, Microsoft recommends provisioning approximately three SCUs per hour when starting out with Security Copilot.
Differentiation from Other Microsoft Copilot Pricing Models
Security Copilot’s consumption-based pricing contrasts with other Microsoft Copilot offerings. For instance, Copilot for Microsoft 365 is available for a fixed monthly fee of $30 per user (before discounts), making Security Copilot’s pricing model uniquely tied to actual usage.
Microsoft is still finalizing the full pricing strategy for Security Copilot and anticipates making further clarifications soon.
Analyst Insights: The Road Ahead for Security Copilot
Wes Miller, an analyst at Directions on Microsoft, commented on Security Copilot’s debut, stating, “This represents an intriguing initial step, but the service will need to evolve continually to meet the demands of managing Microsoft’s ever-expanding security landscape.”
Miller also noted that many customers might expect features like those offered by Security Copilot to come included in their existing subscriptions, given Microsoft’s historical practice of charging premium fees for advanced security tools.
As cybersecurity threats grow increasingly sophisticated, tools like Microsoft Security Copilot promise to offer security teams more powerful and AI-driven assistance. By launching with a capacity-based pricing model, Microsoft is giving organizations the flexibility to scale usage and costs according to their needs. With broad language support, multi-platform access, and deep integration into Microsoft’s security stack, Security Copilot is positioned to become a vital component in modern cybersecurity operations.
Diving Deeper Into Microsoft Security Copilot’s Capabilities
Following the initial launch of Microsoft Security Copilot as a capacity-based service, it is essential to explore the core features and underlying technologies that empower this AI assistant to revolutionize cybersecurity workflows. Security Copilot is designed not only to reduce the burden on security professionals but also to augment their abilities by synthesizing vast amounts of security data and delivering actionable intelligence in real time.
How Security Copilot Analyzes and Summarizes Security Incidents
One of Security Copilot’s primary strengths lies in its ability to quickly digest complex security incidents and present concise, clear summaries. When security teams face alerts, investigations often start with an overwhelming amount of raw data — logs, threat intelligence feeds, system alerts, and historical context. Security Copilot uses its generative AI engine to automatically analyze this multifaceted data, generating narratives that explain what happened, when it happened, and the potential impact on the organization.
This summarization capability dramatically accelerates incident triage by enabling security analysts to gain situational awareness without sifting through countless disparate sources manually. The AI assistant highlights key attack vectors, affected assets, and indicators of compromise, allowing responders to prioritize effectively.
Incident Impact Analysis and Prioritization
Beyond summarizing incidents, Security Copilot assesses the potential impact of security events on an organization’s overall risk posture. Using its access to Microsoft’s vast repository of threat intelligence and contextual data, it evaluates factors such as the sensitivity of targeted assets, the scope of compromise, and the likelihood of lateral movement or data exfiltration.
This contextual analysis helps security teams prioritize response efforts, focusing resources on the most critical threats. By automating this assessment, Security Copilot reduces human error and supports a more strategic approach to cybersecurity operations.
Script Reverse Engineering: Understanding Malicious Code Quickly
Security analysts often face the challenge of dissecting malicious scripts or binaries to understand attacker techniques. Security Copilot incorporates advanced reverse engineering capabilities that can analyze scripts, breaking down complex code into understandable language.
This function helps security teams identify the purpose of suspicious scripts, detect embedded malicious payloads, and understand attacker tactics without requiring manual, time-intensive code analysis. The AI assistant can explain the steps the script performs, aiding in faster containment and remediation.
Guided Incident Response: From Detection to Resolution
An essential aspect of Security Copilot’s value proposition is its ability to guide analysts through the incident response process. Leveraging its understanding of industry best practices and Microsoft’s security frameworks, Security Copilot provides step-by-step recommendations for containment, investigation, and remediation actions tailored to the specific incident.
For example, if the assistant detects a ransomware attack, it might advise isolating affected endpoints, preserving evidence, and notifying stakeholders, all while suggesting the optimal tools and commands available within the Microsoft security ecosystem.
This guided approach empowers less experienced analysts while enabling seasoned professionals to operate more efficiently.
Integration With Microsoft Security Ecosystem
Security Copilot’s effectiveness is amplified by its deep integration with Microsoft’s suite of security products. By connecting seamlessly with Defender XDR (Extended Detection and Response), Sentinel, and Defender Threat Intelligence, Security Copilot consolidates telemetry and threat intelligence into a unified view.
This integration facilitates smoother workflows, as analysts can invoke the AI assistant’s capabilities directly within the tools they use daily, without switching contexts. The consistent user experience across platforms ensures adoption and maximizes the assistant’s utility.
Flexible Deployment Options: Standalone Portal and Embedded Experiences
Security Copilot offers flexible access models to suit diverse organizational needs. Users can interact with the AI through a dedicated standalone portal, providing a rich, immersive interface optimized for in-depth investigations and scenario analysis.
Alternatively, the assistant is embedded within existing Microsoft security tools, enabling contextual support as analysts navigate alerts, dashboards, and reports. This dual-access approach ensures that Security Copilot fits naturally into established security operations workflows.
Customization and Training With Customer Data
While Security Copilot benefits from Microsoft’s massive global security telemetry, it also offers the ability for customers to train the model on their own data. This customization capability enhances the assistant’s relevance and precision by incorporating organizational-specific threat indicators, policies, and incident histories.
For instance, an enterprise can feed historical incident logs, proprietary threat intelligence, and internal security policies into Security Copilot, enabling it to generate insights tailored to their unique environment.
This extensibility positions Security Copilot as a living, adaptive tool that grows with the organization’s security maturity.
Azure as the Foundational Platform for Security Copilot
Running Security Copilot requires Azure infrastructure, which provides the scalable, secure environment necessary to process vast amounts of data in real time. Organizations will allocate Azure resources to host their Security Copilot workloads, leveraging Azure’s global footprint to ensure low latency and compliance with regional data regulations.
Azure also facilitates seamless integration with Microsoft’s security portfolio and third-party tools, enabling a connected defense posture.
The Role of Security Compute Units (SCUs) in Pricing and Capacity Planning
Security Copilot’s pricing is based on Security Compute Units (SCUs), a novel capacity metric designed to reflect the computational resources consumed by AI-powered security operations. Unlike traditional fixed licensing models, SCUs provide a flexible framework that scales with actual usage.
Every query, script analysis, or incident summary performed by Security Copilot consumes a variable amount of SCU capacity depending on complexity and duration. This model ensures organizations pay proportionally to their usage while gaining access to powerful AI capabilities.
The in-product dashboard enables continuous monitoring of SCU consumption, allowing teams to optimize provisioning and control costs proactively.
Comparing Security Copilot’s Pricing Model to Other Microsoft Copilots
Microsoft’s other Copilot products, such as Copilot for Microsoft 365, follow a subscription-based pricing model with fixed fees per user. Security Copilot’s capacity-based approach reflects the distinct nature of security workflows, where usage intensity fluctuates widely based on threat environment and operational demands.
This differentiation acknowledges the need for flexible, consumption-driven pricing in the evolving cybersecurity landscape.
Preparing Organizations for Security Copilot Adoption
Successfully adopting Security Copilot requires thoughtful planning and readiness across several dimensions:
- Azure Infrastructure: Ensuring sufficient Azure capacity to host workloads is fundamental.
- Data Integration: Preparing relevant security data and integrating existing security tools for seamless AI assistant interaction.
- Training and Change Management: Equipping security teams to leverage the assistant effectively through training and workflow adjustments.
- Cost Management: Establishing SCU monitoring and provisioning processes to optimize spending.
Early adopters will gain significant operational efficiencies and enhanced threat detection capabilities, positioning themselves well against emerging cyber threats.
The Future Trajectory of Security Copilot and AI in Cybersecurity
As AI technologies continue to evolve, Security Copilot represents a pivotal step toward more intelligent, automated security operations centers (SOCs). Microsoft is expected to expand its capabilities, incorporating advanced machine learning models, broader integrations, and enhanced automation features.
Over time, Security Copilot could evolve from an assistive tool to a proactive partner in threat hunting, predictive analytics, and autonomous response, further transforming the cybersecurity landscape.
Analyst Perspectives on Security Copilot’s Potential
Industry experts recognize the promise of Security Copilot while emphasizing the need for ongoing innovation. Wes Miller from Directions on Microsoft highlights that although Security Copilot currently offers compelling functionalities, it will need continuous refinement to keep pace with the growing complexity of cyber threats and Microsoft’s expanding security ecosystem.
Security professionals also note that while AI-driven tools can dramatically improve efficiency, human expertise remains critical in interpreting AI outputs and making strategic decisions.
Security Copilot’s Role in Modern Cyber Defense
Microsoft Security Copilot, with its advanced AI capabilities, flexible deployment, and capacity-based pricing, is poised to reshape how organizations approach cybersecurity. By automating complex tasks like incident summarization, impact analysis, and script reverse engineering, it frees security teams to focus on high-value strategic activities.
Its integration within Microsoft’s security portfolio and extensibility through customer data customization make it a versatile asset for enterprises aiming to enhance their security posture efficiently and effectively.
As organizations prepare to adopt Security Copilot, understanding its capabilities, deployment requirements, and pricing model is crucial for maximizing its benefits and ensuring a successful transition to AI-augmented security operations.
The Strategic Implications of Microsoft Security Copilot for Organizations
With Security Copilot entering general availability as a capacity-based service, organizations must consider the broader strategic impact of integrating AI-driven security tools into their cybersecurity posture. This final part explores how Security Copilot fits into the evolving security landscape, the challenges and opportunities it presents, and how enterprises can future-proof their defenses.
Transforming Security Operations Centers with AI Assistance
Security Operations Centers (SOCs) have traditionally relied on skilled analysts manually parsing alerts, logs, and threat intelligence to identify and respond to cyber threats. This process is labor-intensive, error-prone, and increasingly overwhelmed by the volume and complexity of attacks.
Security Copilot represents a paradigm shift, introducing AI as a force multiplier that enhances SOC efficiency. By automating routine tasks—such as incident summarization and script analysis—it reduces alert fatigue and shortens response times. Analysts are empowered to focus on strategic decision-making rather than mundane data wrangling.
Moreover, the assistant’s guided response recommendations enable less experienced staff to operate at higher levels, democratizing cybersecurity expertise across teams.
Enhancing Threat Hunting and Proactive Defense
Beyond reactive incident response, Security Copilot opens new avenues for proactive threat hunting. By continuously synthesizing global and organizational data, the AI assistant can surface subtle anomalies, emerging attack patterns, and indicators of compromise that might escape human detection.
This proactive stance is crucial as adversaries adopt increasingly sophisticated techniques. Security Copilot’s ability to analyze complex data at scale positions organizations to detect threats earlier, reducing dwell time and potential damage.
Bridging Skill Gaps in the Cybersecurity Workforce
A chronic challenge facing cybersecurity teams worldwide is the shortage of skilled professionals. Recruiting and retaining top talent is costly and competitive.
Security Copilot helps alleviate this pressure by augmenting human capabilities, enabling smaller or less experienced teams to maintain robust defenses. By handling complex analyses and offering actionable guidance, the AI assistant reduces dependency on scarce expert resources.
This augmentation can improve job satisfaction by allowing analysts to engage in higher-value tasks, supporting talent retention and development.
Integration Challenges and Considerations
Despite its promise, implementing Security Copilot is not without challenges. Organizations must ensure their existing security infrastructure is compatible and that workflows adapt to incorporate AI assistance effectively.
Key considerations include:
- Data Privacy and Compliance: Handling sensitive security data through an AI service requires careful attention to compliance with regulations such as GDPR, HIPAA, and others. Azure’s compliance certifications help, but organizations must manage data governance prudently.
- Trust and Explainability: Analysts need to understand and trust the AI’s recommendations. Security Copilot’s ability to provide transparent explanations for its analyses and guidance is critical to adoption.
- Change Management: Incorporating AI tools requires cultural shifts within security teams, including training and adjustment of standard operating procedures to leverage AI outputs effectively.
Addressing these challenges upfront will maximize Security Copilot’s impact and minimize disruption.
Economic Impact and Return on Investment
Security Copilot’s capacity-based pricing introduces flexibility but also necessitates careful cost management. Organizations must monitor SCU consumption to optimize provisioning and avoid unexpected expenses.
However, the potential cost savings through improved efficiency, reduced incident impact, and better threat detection are significant. By decreasing the time and effort spent on investigations and remediation, Security Copilot can reduce operational expenses and limit financial losses from breaches.
Furthermore, the scalability of AI-powered security allows organizations to expand their security posture without proportionally increasing headcount or infrastructure investments.
Future Directions: Expanding AI’s Role in Cybersecurity
Microsoft is expected to continuously evolve Security Copilot, enhancing its intelligence, expanding integrations, and introducing new automation capabilities. Potential future developments include:
- Deeper Automation: Moving beyond guided response to automated mitigation for certain incident types.
- Cross-Platform Intelligence: Integrating data from broader cloud ecosystems and third-party security tools for a holistic view.
- Advanced Analytics: Leveraging predictive modeling and behavioral analytics to forecast threats before they manifest.
These enhancements will further embed AI into the fabric of cybersecurity, transforming how organizations defend themselves in an increasingly hostile digital environment.
Competitive Landscape and Market Position
Security Copilot enters a competitive market where numerous vendors are incorporating AI into their security solutions. Microsoft’s advantage lies in its comprehensive cloud infrastructure, extensive threat intelligence, and deep integration with widely used security products.
By offering a flexible, capacity-based pricing model and extensive customization options, Microsoft positions Security Copilot as an accessible yet powerful tool for enterprises of various sizes.
Organizations evaluating AI security assistants should consider factors such as integration ease, data privacy controls, AI model transparency, and total cost of ownership.
Best Practices for Maximizing Security Copilot’s Benefits
To fully leverage Security Copilot, organizations should adopt several best practices:
- Start Small and Scale: Begin with pilot deployments, monitor SCU usage, and gradually expand as teams gain confidence and workflows mature.
- Invest in Training: Provide comprehensive training to ensure analysts understand how to interpret and act on AI-generated insights.
- Maintain Human Oversight: Use Security Copilot as an augmentation, not a replacement, preserving human judgment in critical decisions.
- Regularly Review and Tune: Continuously assess AI performance, update data inputs, and adjust provisioning to optimize effectiveness and cost.
- Foster Collaboration: Encourage collaboration between IT, security teams, and business units to align AI-driven security efforts with organizational objectives.
Embracing AI-Driven Cybersecurity with Security Copilot
Microsoft Security Copilot signifies a major step toward AI-enhanced cybersecurity, blending Microsoft’s unparalleled threat intelligence with advanced generative AI to empower security teams worldwide. Its launch as a capacity-based service democratizes access to cutting-edge AI capabilities, enabling organizations to respond to threats faster, smarter, and more efficiently.
While challenges remain, the strategic advantages offered by Security Copilot—ranging from improved incident response to bridging skill gaps—make it a compelling tool for modern cybersecurity operations.
As the cybersecurity landscape grows more complex and adversaries more sophisticated, embracing AI tools like Security Copilot will be essential for organizations striving to safeguard their digital assets and maintain resilience in the face of evolving threats.
The Road Ahead: Navigating the Future of AI in Cybersecurity with Microsoft Security Copilot
As Microsoft Security Copilot continues to make waves in the cybersecurity world, organizations must prepare for the evolving landscape where artificial intelligence plays an increasingly critical role. This final installment explores key future trends, the ethical challenges tied to AI-powered security, and strategic advice for integrating such technologies responsibly and effectively.
The Expanding Role of AI in Cybersecurity
Artificial intelligence is no longer a futuristic concept but a present-day necessity in cyber defense. Security Copilot represents a significant leap forward, combining generative AI with Microsoft’s extensive threat intelligence to support security teams in real time. But this is just the beginning of AI’s transformational journey in cybersecurity.
From Reactive to Predictive Security
Traditional cybersecurity often focuses on detecting and responding to threats after they occur. AI changes this paradigm by enabling predictive capabilities. Advanced machine learning models analyze historical data, network behaviors, and global threat patterns to forecast vulnerabilities and likely attack vectors before any breach happens. This proactive stance dramatically shortens the window of opportunity for adversaries.
Security Copilot, through continuous learning from trillions of daily security signals, is well-positioned to evolve into such a predictive tool, alerting teams to potential threats and vulnerabilities ahead of time. As AI models grow more sophisticated, organizations will increasingly rely on them to anticipate and preempt cyber incidents.
Automating Complex Response and Remediation
Beyond threat detection, AI will take on more autonomous roles in mitigating risks. Today, Security Copilot guides incident response with recommended actions and script reverse engineering. Tomorrow, AI systems could execute remediation steps automatically for well-understood threats, such as isolating compromised devices or deploying patches, reducing human workload and response times.
This progression toward automation will require careful oversight to balance speed with safety, ensuring AI actions do not inadvertently disrupt business operations.
Integrating Cross-Domain Intelligence
The cyber threat landscape increasingly intersects with physical security, insider threats, fraud, and compliance risks. Future AI-powered security solutions will integrate data across these domains to provide holistic threat intelligence. Microsoft’s extensive ecosystem, including Entra ID, Intune, and Purview, enables Security Copilot to serve as a central nervous system for security operations.
By correlating information across platforms and environments, organizations can detect complex, multi-vector attacks that may evade siloed defenses.
Ethical and Privacy Considerations in AI-Driven Security
Deploying AI in cybersecurity also raises vital ethical questions that organizations must address to build trust and ensure responsible use.
Safeguarding Data Privacy
Security Copilot processes massive volumes of sensitive security data, including internal organizational logs and external threat intelligence. Maintaining strict data privacy is paramount, especially given increasing regulatory scrutiny worldwide—from GDPR in Europe to CCPA in California.
Microsoft’s cloud infrastructure offers strong compliance certifications, but organizations must establish clear data governance policies, including data minimization, access controls, and audit trails, to prevent misuse or unauthorized access.
Addressing Bias and Ensuring Fairness
AI models learn from historical data, which can contain biases or inaccuracies. In cybersecurity, biased models might unfairly flag benign behaviors as threats or overlook subtle malicious activity in certain environments. Ongoing monitoring, testing, and model retraining are essential to detect and mitigate bias, ensuring fair and accurate threat detection.
Promoting Transparency and Explainability
Trust in AI-generated security insights depends on transparency. Analysts need to understand why Security Copilot recommends certain actions or labels events as suspicious. Explainable AI techniques that provide clear reasoning behind decisions help foster confidence and enable effective human oversight.
Maintaining Human Judgment and Oversight
While AI accelerates and enhances security operations, it must not replace human judgment. Analysts and security leaders remain critical for validating AI outputs, making strategic decisions, and handling ambiguous or high-impact scenarios. Organizations should cultivate a collaborative environment where AI augments rather than supplants human expertise.
Managing Organizational Change and Skill Development
Introducing Security Copilot involves more than just technology adoption; it requires shifts in culture, processes, and capabilities.
Upskilling Security Teams
AI-powered tools demand new skill sets. Security professionals need training on interpreting AI insights, understanding model limitations, and integrating AI into incident response workflows. Investing in ongoing education helps teams harness AI’s potential fully while avoiding overreliance or misuse.
Cultivating a Collaborative Culture
Successful AI adoption thrives in organizations that encourage collaboration between humans and machines. Security Copilot can act as a trusted assistant, but teams must adapt their workflows and communication to incorporate AI inputs seamlessly.
Executive Leadership and Governance
Leadership plays a vital role in championing AI security initiatives. Executives must allocate resources, set policies, and drive cultural acceptance. Establishing governance frameworks for ethical AI use, data privacy, and risk management is essential to sustainable success.
Strategic Recommendations for Adopting Security Copilot
Organizations looking to integrate Security Copilot or similar AI-driven security solutions can follow these best practices to maximize value and minimize risk.
Conduct a Readiness Assessment
Evaluate your current security infrastructure, data quality, and workforce skills to identify gaps before deployment. Understanding organizational maturity helps tailor the rollout plan and set realistic expectations.
Define Clear Use Cases
Pinpoint specific pain points where AI assistance can deliver quick wins—such as incident summarization, threat hunting, or automated script analysis. Focused pilots help demonstrate ROI and build stakeholder buy-in.
Start with Pilot Programs
Begin with limited deployments to gather real-world feedback, fine-tune configurations, and train staff. Iterative pilots reduce disruption and build confidence.
Monitor and Optimize Usage
Leverage Security Copilot’s usage dashboards to track SCU consumption, analyze workflows, and adjust capacity provisioning. Monitoring costs and performance enables efficient scaling.
Emphasize Human-AI Collaboration
Encourage teams to view Security Copilot as a partner. Develop SOPs that integrate AI recommendations with human decision-making, ensuring balanced responses.
Engage with Industry and Vendor Communities
Participate in security forums, Microsoft’s partner ecosystem, and industry groups to stay updated on best practices, threat intelligence, and product enhancements.
The Competitive Landscape and Microsoft’s Position
Security Copilot enters a crowded market of AI-enabled cybersecurity products from vendors like Palo Alto Networks, CrowdStrike, and IBM. Microsoft’s competitive edge lies in:
- Deep Integration: Tight coupling with Microsoft’s cloud and security stack provides seamless workflows.
- Extensive Threat Intelligence: Access to trillions of daily signals and global intelligence networks enriches AI models.
- Flexible Pricing: Capacity-based billing supports diverse organizational sizes and usage patterns.
- Customization: Customers can train Security Copilot on their own data for tailored insights.
These factors make Security Copilot a compelling option for organizations invested in Microsoft technologies seeking to elevate their security posture with AI.
Conclusion:
Microsoft Security Copilot signals a profound shift in how organizations defend themselves against cyber threats. By harnessing generative AI combined with vast security intelligence, it empowers teams to respond faster, think smarter, and operate more efficiently.
However, the journey to AI-driven security is complex and multifaceted. Success depends on ethical stewardship, human collaboration, continuous learning, and strategic planning.
As organizations navigate this new frontier, embracing tools like Security Copilot thoughtfully and responsibly will be key to building resilient defenses capable of withstanding today’s dynamic threat landscape—and tomorrow’s unknown challenges.