Overview
LLM Security, Not Just Prompt Testing
LLM products are a new kind of application: models, tools, retrieval, and business logic are tightly coupled. We test the full stack to prevent misuse, data leakage, and privilege escalation, then translate findings into practical engineering fixes.
Engagements cover assistants, copilots, RAG systems, agent workflows, and the surrounding application surface.
Why Atlan
Senior Operator-Led Teams
We operate a contractor-led model and provide consultant profiles for review and approval, allowing teams to be tailored to each engagement.
LLM Red Team + AppSec
We combine prompt-level attack testing with application security review to cover the real risk surface.
Research-Led Tradecraft
Turul GAN was NATO DIANA shortlisted and informs our advanced testing and tooling. Explore our R&D program.
Engagement Snapshot
Discovery & Scoping
- Map LLM use cases, data sources, and tools.
- Define access boundaries and safety constraints.
- Agree rules of engagement and success criteria.
Testing & Exploitation
- Prompt injection, jailbreaks, and tool abuse.
- RAG data exposure and retrieval boundary checks.
- Business logic abuse and privilege escalation.
Reporting & Remediation
- Risk-rated findings with evidence and fixes.
- Architecture hardening recommendations.
- Debrief and optional retest.
Methodology & Focus Areas
LLM Red Teaming Meets AppSec. We test model behavior, tool execution, and the surrounding application surface to uncover real-world compromise paths.
LLM Application Security Testing
Prompt injection, tool abuse, data exfiltration, retrieval manipulation, and guardrail bypass testing for production LLM applications.
LLM AppSec Review
Threat modelling, access control verification, RAG pipeline review, system prompt analysis, and evaluation of output filtering and monitoring.
Frontier Model Testing
Safety red teaming, misuse pathway discovery, and evaluation of jailbreak resilience, autonomy risks, and high-impact capability safeguards.
Model Evaluation & Governance
Evaluation harness design, red team scenario planning, policy testing, and reporting aligned to organisational risk governance.
Outcome Focus
Actionable LLM Risk Coverage
Findings are prioritized by exploitability and business impact, with clear guidance on guardrails, permissions, and architecture changes.
Case Study (Anonymised)
SaaS Platform with an AI Assistant at the Core
We assessed a multi-feature SaaS platform where an AI assistant was the primary interface for knowledge access and workflow automation.
- Used prompt injection and tool chaining to extract confidential data from connected sources.
- Identified business logic flaws that could have enabled cross-tenant access to customer data.
- Advised on architectural isolation between model runtime, tools, and data stores to reduce blast radius.
We delivered prioritized fixes, guardrail updates, and a validation retest plan.
Enquiries
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Contact Us
How can we help?
Whether you represent a corporate, a consultancy, a government or an MSSP, we’d love to hear from you. To discover just how our offensive security contractors could help, get in touch.