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Solvex Space
Web3 & EmergingLegal technology / AI2-week assessment plus retest

Securing a legal-tech LLM assistant before its enterprise launch

Series A legal-tech company, ~60 staff, LLM assistant over privileged documents

A legal-tech company was weeks from launching an LLM assistant that answers questions over clients' privileged documents — a product where one prompt injection could mean privileged material crossing a client boundary. An adversarial AI assessment proved the retrieval pipeline could be poisoned to exfiltrate context, drove architectural fixes, and left the team a red-team prompt suite to re-run on every model upgrade.

Representative engagement — the client is confidential, and the figures and the quoted comment illustrate typical outcomes for the work described.

Injection paths proven pre-fix
5
including document-borne indirect injection
Cross-matter leakage after architectural fixes
0 reproduced
on retest, against the same payloads
Red-team prompt suite delivered
120+ payloads
re-run on every model upgrade
OWASP LLM Top 10 categories covered
10/10
with per-category evidence

The challenge

  • The assistant retrieved from privileged legal documents, so context leakage across client matters was an existential product risk.
  • Enterprise law-firm prospects were asking security questions the team could not yet answer with evidence.
  • Guardrails had been tuned against casual misuse, never against a motivated adversary using indirect injection.

What we did

  • Attacked the assistant with direct, indirect and cross-user prompt injection, including payloads planted in uploaded documents the model would later retrieve.
  • Attempted system-prompt extraction, retrieval-context exfiltration and abuse of every tool the agent could call.
  • Reviewed the RAG pipeline's trust boundaries: embedding-store access controls, per-matter retrieval scoping and output handling.
  • Ran a threat-modelling workshop with the engineering team so the fixes were owned, not just prescribed.
  • Recommended architectural controls — retrieval scoping by matter, tool-call privilege boundaries, output filtering — and verified them on retest.

The outcome

  • Document-borne indirect injection could no longer steer the assistant across matter boundaries after the retrieval-scoping fix, confirmed on retest.
  • Findings mapped to the OWASP LLM Top 10 gave the sales team evidence-backed answers for enterprise security review.
  • The client's team re-runs the delivered prompt suite on every model and prompt change as a regression gate.
We thought our guardrails were solid because casual jailbreaks failed. They showed us what a motivated adversary does instead — and gave us the fixes that survive model upgrades.
CTO, Series A legal-tech companyIllustrative — composed to show the kind of feedback this work draws, not a quotation from a named client.
LLM Assistant Security Assessment | Case Study — Solvex Space