Penetration Testing

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Modern applications can expose critical business processes, sensitive data and APIs to users and external systems. A secure development framework does not remove the risk created by insecure implementation, misconfiguration or flaws in application logic.

Web application penetration testing combines automated tooling, custom testing and manual exploitation to find vulnerabilities across applications and APIs. It can be performed with authenticated or unauthenticated access, depending on the objectives of the assessment. 

Testing follows recognised practice, including OWASP methodologies, and is tailored to the architecture and business functionality of the application. Where vulnerabilities are found, we validate whether they can be exploited and assess the potential impact, rather than relying on scanner output alone.

Areas assessed

• Authentication and session management
• Authorisation, access control and privilege escalation
• Business logic and workflow vulnerabilities
• Input validation and injection
• Cross site scripting and other client-side vulnerabilities
• Sensitive data exposure
• API and web service security
• File and data handling
• Security misconfiguration
• Insecure components and dependencies
• Cloud and third-party integrations

Outcome: A clear view of the exploitable weaknesses in your applications and APIs, their potential business impact and the actions needed to fix them.

Network penetration testing evaluates your external and internal infrastructure by simulating the techniques an attacker could use to gain access and move through your environment.

Testing covers both perimeter security and internal infrastructure, combining reconnaissance, vulnerability discovery and manual exploitation to find weaknesses that could lead to compromise. It can be performed externally, internally or as an assumed breach scenario. 

This shows not only whether an initial compromise is possible, but what an attacker could potentially reach afterwards.

Scenario based testing can also answer specific questions about your environment. Could a compromised workstation reach sensitive systems? Do segmentation controls effectively isolate critical networks?

Areas assessed

• External attack surface and internet facing systems and services
• Internal network infrastructure, servers and endpoints
• Firewalls and network security devices
• VPN, remote access and remote administration services
• Network segmentation
• Authentication mechanisms
• Active Directory security
• Privilege escalation and lateral movement
• Vulnerable and misconfigured services
• Wireless networks, where required
• Device and security configuration, where included in scope

Outcome: Evidence of exploitable weaknesses and realistic attack paths across your infrastructure, helping you prioritise the controls and remediation that will have the greatest security impact.

Cloud environments bring a broad attack surface across identities, permissions, networking, workloads, APIs, storage and cloud native services.

Cloud penetration testing shows whether vulnerabilities or misconfigurations could allow an attacker to gain unauthorised access, escalate privileges, reach sensitive data or move between connected resources. Testing covers public cloud, hybrid environments and cloud connected infrastructure across platforms such as Microsoft Azure, Amazon Web Services and Google Cloud.

Scenario based testing can be used to answer specific security questions. Can one identity access another user's data? Can a network boundary be bypassed? Could a compromised account reach sensitive cloud resources?

Areas assessed

• Cloud configuration and security controls, measured against vendor recommendations and security benchmarks
• Identity and access management
• Privileged roles and excessive permissions
• Virtual networks, subnets, security groups and firewall rules
• Internet facing cloud services
• Storage and data exposure
• APIs and cloud management interfaces
• Virtual machines, cloud workloads and containers, where applicable
• SaaS and PaaS security
• Hybrid connectivity and trust relationships
• Infrastructure as Code, where applicable

Outcome: Evidence of where cloud weaknesses create genuine attack paths, with prioritised recommendations to strengthen identity, configuration, segmentation and access controls.

AI systems introduce attack surfaces that traditional application security testing does not fully address. LLMs, AI applications and agentic systems can interact with sensitive data, APIs, applications and external services, which creates new opportunities for manipulation and abuse.

AI penetration testing combines conventional techniques with AI specific security testing. Each assessment is shaped around the architecture, model, data flows, integrations and capabilities of the system in scope, because a generic set of prompts is not enough to assess a real deployment. Testing includes threat modelling, tailored attack scenarios and controlled exploitation. Where a vulnerability is found, we validate it and demonstrate its potential impact through an appropriate proof of concept.

Areas assessed

• AI system architecture and attack surface
• Prompt injection, jailbreaks and safeguard bypass
• System prompt and instruction disclosure
• Sensitive and proprietary data leakage
• Adversarial inputs, model manipulation and unintended behaviour
• AI capability abuse and misuse
• API and integration security
• RAG and connected knowledge sources
• AI agents and tool access
• Excessive permissions and delegated access
• External services and integrations
• Insecure handling of model outputs
• Security boundaries between AI systems and supporting applications

Outcome: A practical understanding of how your AI system could be manipulated, what information or capabilities could be exposed and whether weaknesses in the AI layer could become a pathway into connected systems or data.