Our services
AI Application and Agent Security Testing
Traditional application testing does not cover every risk introduced by language models and AI agents. Apexagen assesses the application, its integrations and its safeguards to identify weaknesses before wider deployment.
Who this service is for
- Organisations preparing an AI application for production.
- Teams deploying customer-facing assistants or chatbots.
- Businesses connecting AI to internal documents and databases.
- Developers building AI agents that can call tools or APIs.
- Organisations using AI for higher-impact business processes.
- Teams responding to customer or internal assurance requirements.
What the service covers
Direct and indirect prompt injection
Test whether instructions supplied by users or contained in emails, documents and web content can override intended behaviour.
Sensitive-data exposure
Assess whether the application can reveal confidential data, system instructions, credentials or information belonging to other users.
Access and permission controls
Check whether users or agents can access functions and information outside their approved scope.
Tool and API misuse
Test whether connected tools can be invoked in unintended ways or with unsafe parameters.
Excessive agent autonomy
Assess whether the agent can perform sensitive actions without appropriate limits or human approval.
Unsafe output handling
Review whether unreliable or manipulated AI output can be passed directly into applications, scripts or business processes.
Memory and knowledge poisoning
Assess whether untrusted content can influence persistent memory or retrieved information.
Cost and resource abuse
Review controls intended to prevent uncontrolled model usage, repeated agent loops and unexpected consumption.
Logging and response readiness
Check whether suspicious activity can be detected, investigated and contained.
What you receive
- Confirmed testing scope and rules of engagement.
- Description of the test methods used.
- Findings supported by reproducible evidence.
- Business impact and severity assessment.
- Prioritised remediation recommendations.
- Management summary and technical report.
- Retesting of agreed findings where included in the scope.
How we deliver it
We agree on the target environment, authorised techniques, testing boundaries and escalation contacts before work begins. Testing is designed around the application’s actual functions, data access and connected tools.
Where an engagement includes activities regulated as cybersecurity testing in Singapore, the work will be performed with an appropriately licensed service provider. Delivery responsibilities will be confirmed during scoping.
Explore all AI security, governance and automation services.
FAQ
How is this different from conventional penetration testing?
Conventional testing focuses on infrastructure, applications and common security weaknesses. AI testing also examines model behaviour, prompt manipulation, agent permissions, connected tools and AI-specific data exposure.
Can testing be performed in production?
A non-production environment is generally preferred. Production testing may be considered when appropriate controls, approvals and limitations are agreed.
Does passing a test mean the AI system is completely secure?
No. Testing provides evidence about the system and scenarios assessed at that point in time. AI applications require continued monitoring and review as models, data and integrations change.
Deployed to Deliver
Scope an AI security test
Tell us how the application works, what it can access and where it will be deployed. We will define an appropriate testing scope.
Scope an AI security test