Cybersecurity & AI Security

Understand your exposure. Take the right action.

Digital products and operations depend on applications, infrastructure and increasingly connected AI systems. ALD Labs provides specialist security assessment, testing and implementation to help identify weaknesses and strengthen the controls around them.

We work with organisations preparing products for market, responding to customer requirements and strengthening established environments. Scope is agreed around your systems, business priorities and security objectives.

Request a security assessment Explore the approach

Connected security coverage

Assess the system
around the AI.

AI security sits alongside application, cloud and infrastructure security. The assessment follows the connections in your environment.

AI, models & connected tools

Inputs · LLM integrations · MCP · tool permissions

Applications & APIs

Web · mobile · thick clients · application workflows

Cloud, containers & infrastructure

Hosting · configurations · servers · networks

Across the environmentData exposure · Access controls · Remediation & validation

Security testing

Application security and penetration testing

Assess applications and APIs for vulnerabilities through manual expertise and appropriate tooling. Testing can cover web applications, APIs, mobile applications and thick-client applications.

Application security activities can also include static application security testing (SAST), dynamic application security testing (DAST) and software composition analysis (SCA), examining source code, running applications and third-party dependencies respectively.

Engagements can include technical findings, executive summaries, remediation guidance and revalidation, as agreed in scope.

Infrastructure vulnerability assessment and penetration testing

Assess security weaknesses across servers, network devices, firewalls, routers, switches, internal environments and external attack surfaces. Coverage reflects the environment's size, complexity and criticality.

Cloud and container security

Identify vulnerabilities, configuration weaknesses and security gaps across cloud environments, containerised applications, infrastructure configurations and application hosting environments.

AI, LLM and MCP security

AI-enabled applications introduce additional considerations around inputs, information access and connected tools. These need to be assessed alongside the security of the underlying application and infrastructure.

Specialist assessment can cover:

AI applications and large language model integrations.
Prompt and input handling.
Sensitive-data exposure.
AI-connected APIs and tools.
MCP integrations.
Access and permission controls.
AI-enabled application workflows.

This coverage is relevant to customer-facing products, internal systems and business-critical workflows using AI.

Red teaming

Red-team engagements simulate adversarial activity against agreed objectives. The approach is selected around the organisation's environment and risk profile, with activities and rules of engagement defined before work begins.

Methodologies may draw on a structured attack lifecycle, the Cyber Kill Chain or MITRE ATT&CK, as appropriate to the agreed engagement.

Security implementation

DevSecOps implementation

Integrate security activities into software delivery. Scoped work can include SAST, DAST and SCA implementation, software bills of materials, container and CI/CD security, vulnerability management, security dashboards, and defect and remediation workflows.

Infrastructure security implementation

Support targeted improvements through vulnerability management, logging and monitoring, security architecture, control implementation and security validation.

Implementation engagements follow an agreed sequence of assessment, design, implementation and validation.

Connect security with product delivery

For an AI or digital product, security requirements can be considered during planning, relevant controls incorporated into development, and agreed testing conducted before release.

For organisations implementing AI through our Incubator, specialist security work can address the selected application's integrations, permissions, data exposure and supporting environment. Testing and implementation are scoped to the actual solution.

A defined process

Understand and scope. Establish your objectives, environment and the systems and activities included.

Assess. Conduct the agreed work using appropriate manual and automated techniques.

Prioritise. Evaluate findings in the context of their potential security and business impact.

Address. Provide remediation recommendations and carry out implementation work where included.

Revalidate. Retest remediated findings where this forms part of the engagement.

Reporting for decision-makers and technical teams

Depending on scope, deliverables may include an executive security summary, detailed technical findings, supporting evidence, vulnerability prioritisation, remediation recommendations, a technical discussion and revalidation results.

We agree the deliverables before work begins so your leadership and technical teams understand what they will receive.

Start a conversation

What needs assessment in your organisation?

Tell us about the application, environment, customer requirement or AI initiative in front of you. We will help determine the appropriate security scope.

Request a security assessment