The Future of Security is Agentic: Building Infrastructure Secure From and For AI Agents

For decades, most security programs have followed the same rhythm: conduct an annual penetration test, run periodic audits, patch vulnerabilities after they are reported, and add controls around a network perimeter.

That approach is no longer enough for modern AI infrastructure. Applications change daily. Dependencies change constantly. APIs, models, tools, and agent workflows introduce new paths through which data can be accessed, or actions can be performed.

At the same time, attackers can use AI agents to scan systems faster, automate reconnaissance, test many attack paths at once, and adapt their techniques as environments change. A security program that only evaluates risk periodically cannot keep pace with an attack surface that evolves continuously.

At Lamatic.ai, we build agentic infrastructure that is secure in two directions:

Strong security requires depth. Rather than relying on a single tool or a once-a-year assessment, Lamatic combines specialist security, compliance, and testing partners with controls built into our own engineering workflows.

Vanta helps automate the operational work behind compliance programs such as SOC 2, ISO 27001, HIPAA, and GDPR. Instead of manually collecting screenshots and evidence before an audit, we use continuous monitoring to identify controls that drift out of compliance before they become audit or customer issues.

For Lamatic, compliance automation supports security rather than replacing it. It gives the team an ongoing view of device posture, access-control coverage, policy acknowledgment, vendor reviews, and evidence collection. This helps turn compliance from a periodic documentation exercise into a continuously measured operating practice.

What this enables:

Aikido provides application-security coverage across the software development lifecycle. It helps identify issues in source code, third-party dependencies, infrastructure-as-code, containers, cloud configuration, and running applications.

This matters because a vulnerability can enter a system in many ways. It may be introduced through a code change, a vulnerable open-source package, an exposed cloud service, a misconfigured Terraform resource, or a container image. A unified platform helps us see these risks in context and prioritize the issues most relevant to the services we operate.

What we use this layer to detect:

Independent assurance is important because internal teams can become accustomed to their own assumptions and operating patterns. Prescient Assurance supports independent security and compliance validation, helping verify that our controls are designed, documented, and operating as intended.

External review adds rigor to our security program. It challenges our evidence, tests our processes, and provides customers with greater confidence that Lamatic’s security posture is evaluated beyond internal claims.

Traditional penetration tests are useful, but they are point-in-time assessments. When the application changes, the test scope can quickly become outdated.

HackerOne’s agentic pentesting model combines autonomous testing capacity with human security expertise. AI agents can continuously explore known attack paths and environmental changes, while experienced security researchers validate the impact of significant findings and help distinguish real risk from noise.

This provides a stronger offensive-security loop:

Security should not be something added before release. It needs to be part of how software is planned, written, reviewed, tested, deployed, and monitored.

Every code change can introduce security consequences. A new endpoint may expose information, an authorization check may be missed, a dependency may introduce a known vulnerability, or a small configuration change may accidentally broaden access.

Lamatic uses automated and agent-assisted review to continuously examine code changes. These agents look beyond simple keyword matching: they evaluate patterns, data flows, permissions, and the security implications of a change in context.

AI review does not replace engineering judgment. Instead, it acts as an always-on additional reviewer that can flag risky patterns early, before code reaches production. Engineers remain accountable for reviewing findings, validating their relevance, and making the final design decisions.

Agent-assisted review focuses on:

A secure development process needs enforceable checkpoints. Security gates prevent code from being promoted when it fails critical security requirements.

At Lamatic, automated checks run throughout the CI/CD pipeline. Developers receive feedback while the change is still small and easy to fix, rather than discovering a problem after it has been deployed to production.

Our security gates include:

Production is not the first place where security checks happen. It is the last place a validated change is allowed to go.

A traditional penetration test is a snapshot. It is valuable, but it cannot represent the security state of a fast-moving platform for an entire year or quarter.

Agentic pentesting makes offensive testing continuous. Autonomous agents can map authorized attack surfaces, replay relevant tests after a deployment, look for new exposure caused by configuration changes, and test newly disclosed vulnerabilities against the current environment.

Every automated finding still needs prioritization. We combine continuous machine-scale testing with human validation to ensure security teams focus on vulnerabilities that are practical, impactful, and relevant to customers.

Continuous testing helps us:

Static analysis is fast and reliable for detecting known insecure patterns. It is an essential part of secure software delivery, but it does not always understand why a feature exists or whether a sequence of valid actions creates a business-logic vulnerability.

Agentic analysis adds contextual reasoning. It can evaluate how data moves through an application, how identity and permission checks are used across services, and whether a user could perform an action that their role should not permit.

Together, these layers provide broader coverage:

Not every critical CVE is equally dangerous. A CVSS 9.8 vulnerability in a library you don't use or a code path that's never executed poses little real risk. At Lamatic, we use CVE exploitability analysis to separate theoretical severity from actual exploitability in our environment.

Our approach:

We combine automated dependency scanning, static analysis, and threat intelligence with human judgment from engineers who understand our codebase and architecture. The result is faster response to real threats and informed risk decisions on everything else.

Customer data is the most sensitive part of an AI infrastructure platform. Our approach assumes that no request, service, identity, or environment should receive more access than it needs.

This is the foundation of zero trust: verify explicitly, use least privilege, and limit the duration and scope of access.

We separate development, staging, and production environments so that experimentation and testing do not expose production systems or customer data.

Environment separation limits blast radius. A mistake in development should not provide a path to production data or infrastructure.

Identity is the starting point for security. Before a person, service, or agent can access a resource, Lamatic verifies who or what is making the request and whether that identity has a legitimate reason to perform the action.

Our access-control model includes:

Encryption protects data while it is moving, stored, and accessed. We use multiple layers because no single control should be responsible for protecting sensitive information.

Just-in-time decryption is especially important for agentic systems. An agent should not receive a permanent decrypted dataset simply because it has a valid task. It should receive only the data and access required for the specific approved action.

Security includes what happens to data after it has been created. We define how information is stored, retained, recovered, accessed, and deleted.

Technology alone does not create a secure organization. Security also depends on how people make decisions, how quickly teams respond, and whether responsibilities are clear.

Every employee completes annual security awareness training. The goal is practical behavior, not checkbox compliance.

Training covers phishing and social engineering, secure handling of customer information, password and device hygiene, incident reporting, secure development expectations, and privacy obligations. We reinforce that security concerns should be reported early, even when the impact is uncertain.

A plan that has never been tested is only a document. Lamatic runs quarterly disaster recovery and incident response exercises to validate people, tooling, escalation paths, communications, and recovery procedures.

Exercises may simulate data-exfiltration attempts, ransomware, a cloud-provider outage, compromised credentials, DDoS events, or service failures. Each exercise produces lessons, follow-up actions, and owners so that our response capabilities improve over time.

Security researchers play an important role in improving the security of the broader ecosystem. Our Vulnerability Disclosure Program provides a responsible path for researchers to report potential issues.

We aim to acknowledge reports quickly, triage them transparently, and provide clear remediation expectations based on severity. A good disclosure program creates a constructive relationship with researchers and gives Lamatic another channel for discovering issues before they can be abused.

Not every vulnerability carries the same risk. We use severity-based service-level objectives to ensure the highest-risk issues receive the fastest attention.

These targets guide prioritization, but active exploitation, customer impact, and business context can always accelerate response.

Corporate devices are part of the security perimeter. A compromised laptop can bypass otherwise strong cloud controls through stolen sessions, source code access, or credential theft.

All corporate endpoints are enrolled in Mobile Device Management (MDM). This supports consistent requirements for full-disk encryption, supported operating-system versions, screen-lock policies, remote wipe, approved software, and jailbreak or root detection.

Automation gives us speed and consistency. Human review adds context, accountability, and judgment.

The combination is intentional: agents detect and analyze at machine speed, while people decide, prioritize, and remain accountable for outcomes.

Secure AI infrastructure requires more than secure code. The platform must also protect the way services run, communicate, store data, and respond to malicious traffic.

Lamatic uses serverless microservices, including Cloudflare Workers and DigitalOcean Cloud Functions, to separate responsibilities into smaller services with explicit interfaces and limited permissions.

This architecture can reduce operational risk when implemented carefully. Services can scale automatically, execution is often short-lived, and each component can be assigned a dedicated identity with only the permissions it needs. A compromise in one service should not automatically become unrestricted access across the environment.

Core principles:

For sensitive workloads, infrastructure isolation may need to go beyond logical access controls. Dedicated tenant-isolated infrastructure can provide separate compute, storage, network, database, and encryption boundaries for a customer or workload.

This option reduces shared-resource exposure, simplifies customer security reviews, and supports strict data-separation requirements. It is particularly valuable for organizations operating in regulated environments or handling highly sensitive data.

Security cannot be effective if critical actions are invisible. Lamatic instruments services with OpenTelemetry (OTEL) to provide end-to-end traces across distributed systems.

Observability helps us understand how a request moved through services, where an authorization decision occurred, which tool an agent invoked, and what data-access operation was attempted. These signals support reliability engineering, security monitoring, incident response, and auditability.

Security-relevant telemetry includes:

Public-facing applications need edge protection before malicious traffic reaches internal services. We use layered controls because attacks range from simple credential-stuffing attempts to sophisticated application-layer DDoS campaigns.

Audit logs establish accountability. They record who performed an action, what action occurred, where it originated, and when it happened. These records support investigations, customer assurance, and detection of unusual patterns.

Intrusion detection adds another layer by analyzing network, host, application, and identity signals for behavior that may indicate compromise. Alerts are routed through defined severity and escalation paths so the right people can investigate quickly.

Some customers need stronger control over how long data remains available. For eligible workloads, Lamatic can provide Zero Data Retention (ZDR) options that minimize or eliminate persistence beyond the active session or approved processing window.

Depending on the configuration, ZDR can include ephemeral processing, reduced logging, no storage of prompts or outputs, and destruction of session-specific encryption material after use. Exact behavior is defined by the product configuration and customer agreement.

AI agents can take actions, use tools, process inputs, and interact with external systems. That makes the agent runtime a critical security boundary.

Lamatic runs agents in isolated container sandboxes with explicit constraints. A sandbox limits what an agent can access and do, even if its instructions, tool inputs, or dependencies behave unexpectedly.

Sandbox controls include:

The goal is to ensure that an agent can perform its intended task without receiving unrestricted access to the host, network, data plane, or other tenants.

Traditional security is often reactive and periodic. Agentic security is designed for a world where software, infrastructure, agents, and threats all change continuously.

Agentic security does not mean handing security decisions entirely to AI. It means using agents responsibly to make security continuous, scalable, and context-aware—while keeping humans accountable for high-impact decisions.

At Lamatic.ai, we are building more than an AI platform. We are building infrastructure designed to protect customers as the threat landscape becomes more autonomous.

Want to learn more about Lamatic.ai’s approach to agentic security?