AI Application Penetration Testing

Blacklock maps the AI application architecture, exposed endpoints, LLM integrations, model providers, prompt flows, API routes, file upload points, retrieval sources, memory stores and agent components.

We assess system prompt disclosure risk, verbose errors, unsafe responses, exposed tool schemas, public documentation, leaked configuration details and data flows that may expose sensitive information.

Blacklock runs targeted automated checks across AI input vectors, including user prompts, uploaded files, API parameters, tool outputs and retrieved content.

Testing may include prompt injection suites, jailbreak pattern testing, harmful content checks, RAG poisoning simulation, tool schema fuzzing, rate limit review and API security scanning for authentication and authorisation weaknesses.

Blacklock consultants perform manual testing to identify exploitable AI application risks. Testing includes direct and indirect prompt injection, jailbreak attempts, data exfiltration, unsafe output handling, access control bypass, business logic abuse, tool misuse and model behaviour manipulation.

Where the application integrates with APIs, databases, documents or business systems, we test whether the AI layer can be used to trigger unauthorised actions or expose sensitive data.

Blacklock provides actionable reports for executive, technical and remediation audiences. Reports include attack narratives, evidence, proof of concept, business impact, severity, affected components and prioritised remediation guidance.

Blacklock can support ongoing security assurance by continuously scanning AI application endpoints. Recurring scanning helps identify new vulnerabilities as the AI application changes. Results can be reviewed in the Blacklock dashboard and used to support remediation, governance, compliance and release readiness.