LLM Pentesting & Assessment
Find real LLM abuse paths: prompt injection, tool misuse, data exfiltration, and weak guardrails, before users or attackers do.
Offensive testing for Large Language Models and LLM-based applications.
Why teams engage us
LLM applications blur trust boundaries: a single crafted prompt can bypass intent, leak retrieval context, or trigger dangerous tool calls. Compliance teams ask for assurance; developers need specifics, not vague 'be careful with prompts.'
What we deliver
We test LLM-powered applications and APIs for jailbreak and policy bypass, indirect prompt injection (including via retrieved content), data leakage, insecure tool and MCP integrations, and authorization flaws in agent workflows. Assessment aligns with modern guidance such as OWASP LLM Top 10 themes. Reporting includes reproduction prompts (sanitized), root causes, and engineering fixes.
How we run it
- Scope: models, tools, retrieval sources, and sensitive data classes
- Abuse case catalog tailored to your deployment pattern
- Controlled adversarial probing with logging and safety stops
- Joint review with developers on mitigations
- Optional retest after guardrail updates
Outcomes you can expect
- Validated abuse cases with clear severity and blast radius
- Concrete control improvements: sandboxing, retrieval hygiene, tool authz
- Test cases for regression in CI where feasible
- Customer- and regulator-ready description of LLM risk posture
Why Evaluris
- •Deep focus on LLM and agentic systems, not generic web pentesting with a chat window.
- •Aligned to how modern RAG and tool-using agents are built.
- •Practical fixes your team can ship, not research-only critique.
Deliverables
- LLM-specific report
- Proof-of-concept
- Security recommendations
When it makes sense
- •LLM in production
- •Prompt injection and jailbreak risk
- •AI compliance
FAQ
Chatbot only vs full RAG stack?
We scope to your architecture. RAG introduces retrieval poisoning and context leakage risks that pure chatbots do not.
Will testing break production?
We prefer non-production mirrors. Production testing requires strict rate limits, content policies, and rollback.
MCP and tool integrations?
Yes. We review tool authentication, argument injection, and least-privilege boundaries for agent tool use.
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ViewReady to scope this engagement?
Tell us about your environment, timelines, and objectives, we will respond with a tailored proposal.