AI Security Outcomes
Anonymized examples of AI security work: what we found, why it mattered, and how outcomes were measured.
Fintech: Prompt Injection in a Support Agent
A fintech's customer-support assistant could call internal tools to look up accounts. Our red team chained an indirect prompt injection through a support ticket to those tools, reaching data the agent should never have exposed.
We deployed an LLM firewall with input/output filtering, tightened tool-call authorization, and added retrieval access controls — closing every exploit path before the public launch.
Proven Results
Explore how we've helped organizations defend with AI and secure the AI they ship.
Health System: Clinical LLM Governance
Built a model inventory, PHI-leakage guardrails, and NIST AI RMF evidence for a clinical documentation assistant ahead of a board review.
Online Retailer: Shopping Assistant Abuse
Red-teamed a customer-facing shopping assistant for jailbreaks, content-safety bypasses, and coupon/pricing abuse before a seasonal campaign.
Manufacturer: ML Supply-Chain Review
Reviewed third-party model dependencies and training-data sources for a predictive-maintenance pipeline, prioritizing data-poisoning and integrity risks.
SaaS Platform: Agent & RAG Hardening
Hardened a multi-agent RAG product against prompt injection and data exfiltration, and mapped findings to the OWASP LLM Top 10 for customer security reviews.
Public Agency: EU AI Act Readiness
Helped an agency classify AI use cases by risk tier and document the controls and evidence needed for EU AI Act obligations.
Utility: Agentic SOC Rollout
Stood up AI-driven anomaly detection and agentic triage across identity and cloud telemetry for a utility modernizing its security operations.
Sectors Shipping AI
Deep expertise across industries deploying AI into sensitive, high-stakes environments.
Financial Services
Securing AI copilots, fraud models, and assistants under banking and PCI-DSS obligations.
Healthcare
Guardrails and governance for clinical LLMs and diagnostic models handling PHI.
Public Sector
NIST AI RMF alignment and EU AI Act readiness for agencies deploying AI.
Critical Infrastructure
Protecting ML-driven monitoring and automation across energy and utilities.
AI-Native SaaS
Red teaming and LLM firewalls for products built on agents and foundation models.
Manufacturing
ML supply-chain and data-integrity protection for industrial AI systems.
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