Artificial intelligence is changing how organizations approach cybersecurity. The latest development comes from Armadin, the AI-native cybersecurity company founded by Kevin Mandia, which has raised approximately $255.5 million in a new funding round.
The Series B investment brings Armadin’s total funding to approximately $445 million and places the company’s reported valuation above $2.5 billion.
The funding highlights growing investor and industry interest in a new approach to cybersecurity: using autonomous AI agents to continuously simulate the behavior of sophisticated attackers and identify security weaknesses that could realistically be exploited.
From Vulnerability Scanning to Attack Path Validation
Traditional vulnerability scanners can identify large numbers of potential weaknesses, but security teams often face the challenge of determining which findings represent genuine business risk.
Armadin is taking a different approach.
Its platform uses AI agents trained with experience from offensive security and red team operations to simulate attack activity across an organization’s digital environment.
Rather than stopping at vulnerability identification, the agents can attempt to connect weaknesses across different parts of an environment, including external systems, networks and cloud infrastructure.
The objective is to identify attack paths that are actually exploitable and provide security teams with more actionable information.
AI Agents Can Operate at Machine Speed
The scale of autonomous security testing is one of the most significant developments in this approach.
Armadin reported that it deployed 26,000 AI agents during a three day assessment of a customer environment. The agents performed approximately 17 million offensive actions and identified 38 validated attack paths.
These figures demonstrate the potential scale of AI assisted security testing.
Traditional penetration testing relies heavily on human expertise and scheduled assessments. Autonomous systems can potentially operate continuously and examine large environments at a much greater frequency.
That does not eliminate the need for human security professionals. Instead, it can change how their expertise is applied by allowing automated systems to perform repetitive reconnaissance and testing while experienced security teams focus on validation, remediation and strategic decisions.
Why Continuous Security Testing Matters
Modern enterprise environments are constantly changing.
Cloud workloads are added, applications are updated, identities change, APIs are deployed and new technologies are integrated into existing infrastructure.
A security assessment performed several months ago may not accurately represent the current attack surface.
Continuous offensive security can help organizations identify changes in exploitable risk as environments evolve.
Key areas that organizations should continuously evaluate include:
• Internet-facing applications and infrastructure
• Cloud environments and workloads
• APIs and application services
• Identity and access controls
• Network segmentation
• Endpoint security
• Active Directory environments
• Software supply chains
• Third party integrations
• AI systems and agentic applications
• IT and operational technology connections
The Rise of AI-Powered Attack Paths
The development also reflects a broader change in the cybersecurity threat landscape.
AI can reduce the time and resources required to perform reconnaissance, analyze vulnerabilities and identify relationships between security weaknesses.
This creates a challenge for defenders.
Security teams cannot rely exclusively on periodic assessments if adversaries are increasingly capable of operating continuously and automatically.
Organizations may therefore need to complement conventional vulnerability management with attack path analysis, adversarial testing and continuous validation.
Human Expertise Still Matters
Autonomous security does not mean removing cybersecurity professionals from the process.
AI systems need appropriate boundaries, monitoring and validation. Security teams must determine what systems can be tested, define acceptable testing conditions and ensure that automated activity does not disrupt production environments.
Armadin has described a layered safety approach involving restricted environments, policy enforcement and monitoring of agent activity. The company has also highlighted the importance of keeping human expertise involved in offensive security operations.
This is an important consideration for enterprises exploring autonomous security technologies.
The objective should be controlled automation, not unrestricted autonomous activity.
What This Means for Enterprise Security Teams
Organizations should begin preparing for a cybersecurity environment where both attackers and defenders can operate with increasing levels of automation.
Security leaders should consider:
Continuous attack surface monitoring
Maintain visibility into external assets, cloud resources, applications, APIs and connected infrastructure.
Attack path validation
Prioritize vulnerabilities based on whether they can realistically be chained into an attack that affects important business assets.
AI security testing
Evaluate AI applications, models, agents and supporting infrastructure for security weaknesses and unintended behavior.
Identity security
Monitor privileged accounts, authentication systems and pathways that could enable lateral movement.
Cloud security validation
Regularly test cloud configurations, workloads, permissions and connectivity between environments.
Human oversight
Establish clear governance for automated security testing, including authorization, scope, monitoring and emergency controls.
Continuous remediation
Connect security findings with remediation workflows so that validated risks can be addressed quickly.
Industries That Can Benefit
The shift toward continuous and AI assisted security validation has relevance across industries with large and complex digital environments.
Financial Services
Banks, fintech companies, payment providers and investment organizations can use continuous security testing to assess digital banking platforms, APIs, cloud infrastructure, identity systems and critical applications.
Healthcare
Healthcare providers and technology companies can strengthen security around patient portals, healthcare applications, cloud environments, medical data systems and connected technologies.
Retail and E-commerce
Retailers can assess customer-facing applications, payment systems, APIs, cloud infrastructure and digital supply chains for exploitable attack paths.
Manufacturing
Manufacturers can evaluate enterprise networks, cloud platforms, connected systems and pathways between IT and operational technology environments.
Government
Government agencies can use continuous security validation to assess public-facing services, cloud environments, identity systems and critical infrastructure.
Technology and SaaS
Technology companies and SaaS providers can continuously test applications, APIs, cloud infrastructure, software dependencies and identity controls that support their platforms and customers.
The Broader Cybersecurity Shift
Armadin’s latest funding illustrates the growing investment in AI-native cybersecurity.
The company initially launched in March 2026 with approximately $189.9 million in combined seed and Series A funding. The latest round brings its reported total funding to approximately $445 million.
The development reflects a broader industry movement toward using AI not only to detect threats but also to actively test defenses.
As AI capabilities continue to develop, organizations will increasingly need to understand how their environments perform against automated and adaptive attack techniques.
Conclusion
The rise of AI-powered offensive security represents an important development in enterprise cybersecurity.
Vulnerability identification alone is often not enough. Organizations need to understand which weaknesses can be connected, exploited and used to reach valuable systems.
AI agents can potentially accelerate that process by continuously testing environments and validating attack paths at a scale that would be difficult to achieve through human-led assessments alone.
At the same time, autonomous security requires strong governance, controlled testing environments, human oversight and clear authorization.
The future of cybersecurity is likely to involve closer collaboration between experienced security professionals and AI systems that can continuously test, analyze and validate enterprise defenses.
Organizations that prepare for this shift can build a more proactive approach to identifying exploitable risk before real attackers discover it.
About COE Security
COE Security partners with organizations in financial services, healthcare, retail, manufacturing, and government to secure AI-powered systems and ensure compliance.
Our offerings include:
• AI-enhanced threat detection and real-time monitoring
• Data governance aligned with GDPR, HIPAA, and PCI DSS
• Secure model validation to guard against adversarial attacks
• Customized training to embed AI security best practices
• Penetration Testing (Mobile, Web, AI, Product, IoT, Network & Cloud)
• Secure Software Development Consulting (SSDLC)
• Customized CyberSecurity Services
COE Security also helps organizations strengthen their security posture through continuous vulnerability assessment, attack surface analysis, penetration testing, cloud security assessments, API security testing, identity security reviews, threat modeling, AI security assessments and adversarial testing.
For financial services and banking, COE Security can help assess digital banking applications, APIs, authentication systems, cloud environments and critical financial infrastructure.
For healthcare organizations, we help evaluate patient-facing applications, sensitive data environments, cloud infrastructure, connected systems and third party integrations.
For retail and e-commerce, we help secure payment applications, customer-facing platforms, APIs, cloud infrastructure and digital supply chains.
For manufacturing organizations, we help assess enterprise networks, connected technologies, cloud environments and IT and OT security boundaries.
For government organizations, we help strengthen public-facing applications, identity systems, cloud environments, infrastructure and security monitoring capabilities.
For technology and SaaS companies, we help identify vulnerabilities across applications, APIs, cloud environments, software dependencies, identity systems and AI-powered platforms.
As AI becomes increasingly integrated into cybersecurity and enterprise operations, COE Security helps organizations evaluate emerging risks while strengthening security, compliance and resilience.
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