Security & Red-Teaming
LLM agents fail in unexpected ways. A model that clears every accuracy benchmark can still leak PII under adversarial pressure, hallucinate financial figures at the edge of its training distribution, or be coerced into crossing a regulatory line by a sufficiently crafted multi-turn prompt. Standard unit tests don't catch this. A disciplined adversarial programme does.
TestML's red-teaming service is built around your specific deployment's threat model, not a generic checklist of known exploits. Since 2022, our team has evaluated 340+ enterprise LLM pipelines across legal, financial, medical, and insurance verticals. We deliver written findings within 72 hours of environment access.
What Gets Tested
The attack surface of an enterprise LLM agent extends well past simple jailbreak attempts. Our proprietary adversarial test suites cover five primary categories:
- Prompt injection: Direct and indirect injection across multi-agent chains, where a downstream agent is manipulated via a poisoned tool call or retrieved document.
- Regulatory boundary violations: Inputs designed to push the agent into output that breaches GDPR, HIPAA, or sector-specific rules. We test refusal logic, not just the final response.
- Hallucination exploits: Targeted sequences that elicit confident but fabricated answers in high-stakes factual domains — case citations, clinical data, contract terms, financial figures.
- System prompt extraction: Attacks aimed at surfacing confidential instructions embedded in the agent's context window.
- Instruction override and role confusion: Multi-turn sequences that gradually erode the model's stated behavioural constraints across a conversation.
Each category maps to real failure modes observed across the 340+ pipelines we have evaluated.
How the Process Works
David Park, our Head of Evaluation Science, built adversarial test suites for three Fortune 500 LLM rollouts before joining TestML. That field experience is now encoded into a repeatable, auditable framework rather than living in one person's head.
Access to your environment is scoped and time-boxed before work begins. Your data stays within the agreed perimeter throughout. Within 72 hours of access, you receive a written report covering: attack vectors attempted, success rate per category, severity ratings calibrated to your regulatory context, and concrete remediation steps for each finding.
The output is not a dashboard export or an automated scan summary. It is a practitioner-grade document you can hand to a compliance officer, a legal team, or a board. Every finding is reproducible and evidence-backed.
What Clients Have Found
Sarah Moran, Head of LLM Platforms at a European investment bank, ran a red-team engagement ahead of the go-live of an internal document summarisation agent. TestML found three regulatory boundary violations the bank's internal QA had not surfaced. The deployment was held, patched, and retested. It shipped clean.
Tom Rigby, VP of AI Engineering at a global insurance carrier, used TestML's red-teaming alongside continuous drift detection to roll out claims-processing agents across seven markets. Zero compliance incidents post-launch.
The pattern is consistent across both engagements: test adversarially before production, monitor rigorously after.
Compliance and Data Handling
TestML is SOC 2 Type 2 certified. Engagements are structured to meet GDPR and HIPAA requirements, with on-premise test execution available where data residency rules prohibit cloud-side access. Every engagement includes a data processing agreement scoped to the specific work.
If your security or legal team has requirements around access controls, audit logging, or data destruction at engagement close, raise them at the scoping stage. Custom perimeter configurations are not an exception — they are a standard part of how we work with regulated clients.
For questions about data handling before you commit to an engagement, reach out via our contact page.
Stop guessing about your agent's failure modes. Book a technical review and get written red-team findings in 72 hours.