LLM Penetration Testing

Blacklock maps the LLM application architecture, model provider, prompt structure, input and output channels, API routes, data flows, user roles, document ingestion points, memory components and retrieval logic.

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We review prompt leakage exposure, verbose errors, sensitive output risks, weak tenant isolation, unsafe plugin design and public information that may assist an attacker.

Blacklock performs automated cloud security checksacross AWS, Azure and GCP services using a combination of licensed, open-sourceand custom tools.

For AWS, this may include tools such as Prowler,ScoutSuite, AWS Security Hub and custom audit scripts. Checks are aligned withCIS AWS Foundations, AWS Well-Architected Framework and AWS best practices.

For Azure, checks focus on identity, governance,networking, compute, storage, databases, key management, Defender posture,policy assignments and monitoring configuration.

For GCP, checks focus on organisation policy, IAMpermissions, service accounts, VPC firewall rules, public storage exposure,encryption, key management, logging, monitoring, Security Command Centerfindings and workload configuration.

Blacklock consultants manually test the LLM applicationusing adversarial prompts, multi-turn attack chains and indirect injectiontechniques.

Testing includes attempts to override instructions,extract system prompts, disclose sensitive data, manipulate retrieved context,bypass guardrails, trigger unsafe outputs, exploit weak access controls andabuse connected APIs or tools.

Blacklock delivers clear reports with executivesummary, technical findings, proof of concept, evidence, risk rating, impactand remediation recommendations.

Blacklock can support ongoing security assurance bycontinuously scanning LLM endpoints. Recurring scanning helps identify newvulnerabilities as the LLM application changes. Results can be reviewed in theBlacklock dashboard and used to support remediation, governance, compliance andrelease readiness.