LLM Security Research · Lateos
Structured prompt injection susceptibility testing across frontier and edge LLMs. Using the IPI Taxonomy to classify, quantify, and map attack surface to OWASP LLM categories. All findings follow responsible structural disclosure — no weaponized payloads published.
Overview
This research track assesses how well language models resist indirect prompt injection (IPI) — the class of attack where untrusted content in a model's context window attempts to redirect or override its operational behavior.
Each assessment runs a structured test harness against a target model. Tests are organized by IPI class (attack pattern) and delivery variant (direct, obfuscated, embedded), producing a quantified susceptibility rate against a reproducible taxonomy. Results are cross-referenced to the OWASP Top 10 for LLMs to give enterprise teams a compliance-mapped risk picture.
The goal is to give application developers and security teams architectural data — not exploit code. Knowing which attack classes a model resists vs. which it fails, and why, drives better middleware design, safer deployment patterns, and more informed model selection.
Methodology
All findings are published under a Structural Disclosure framework. This approach demonstrates technical validity through data flow analysis, architectural root cause identification, and abstract defensive unit-tests — without releasing the adversarial inputs themselves.
| Withheld | Disclosed Instead | Operational Impact |
|---|---|---|
| Exact adversarial tokens & specific prompt strings | Data flow diagrams — the path of untrusted input through model context windows and tool boundaries | Protects production applications while exposing the underlying logic flaw |
| Weaponized payloads that trigger tool bypasses or arbitrary execution | OWASP LLM mapping — categorization via standard frameworks (LLM01 through LLM10) | Provides enterprise context for compliance and internal risk auditing |
| Live exploit scripts automating model exploitation | Validation unit-tests — safe, abstract dummy patterns allowing teams to verify if their middleware intercepts the class | Positions the research as builder-oriented, directly assisting defensive engineering teams |
Custom Testing
If you are building on top of a language model and need a structured adversarial assessment before shipping, or want to validate that your defensive middleware holds up against the IPI taxonomy, custom engagements are available. Testing is conducted against your target model or deployment configuration, not a generic benchmark environment.
Each engagement runs the full IPI Taxonomy test suite — 21 attack classes across 3 delivery variants (direct, obfuscated, embedded). Coverage spans prompt injection, steganographic payloads, tool-description poisoning, multi-agent propagation, unauthorized action induction, RAG corpus attacks, and role-boundary bypass patterns.
The deliverable is a full structural disclosure report — the same format as the published assessments on this page. It quantifies susceptibility per class and severity tier, traces architectural root causes, maps findings to OWASP LLM Top 10, and provides immediately actionable mitigations for each failed class.