AI is moving faster than security.
LLM agents shipping without auth checks. Public endpoints exposing backend logic. Prompt injection vulnerabilities in production. Teams prioritizing growth over security.
Only 24% of generative AI projects include any security component—even though 82% of leaders say secure AI is essential. — IBM Institute for Business Value, 2024
AI-native security testing.
We don't run generic scanners against your AI stack. We simulate real adversaries targeting LLM pipelines, agent workflows, and the infrastructure that supports them.
- Red team simulations tailored to LLM pipelines
- Threat modeling across agent workflows and APIs
- Adversary testing with zero-day mindset
- Prioritized remediation you can act on
Attack Surfaces Specific to LLM Systems
Prompt Injection
Direct injection through user inputs. Indirect injection via retrieved documents or external data. Jailbreaks that bypass system prompt restrictions.
Agent Workflow Exploitation
If your LLM can call tools, we test what happens when those tools are abused. Privilege escalation through agent actions. Chained operations that achieve unintended objectives.
RAG Pipeline Attacks
Data leakage through retrieval. Poisoning attacks against your knowledge base. Access control bypasses that expose documents users shouldn't see.
Data Exfiltration
Training data extraction. System prompt disclosure. PII leakage through model outputs. We find what your model knows that it shouldn't share.
API & Infrastructure
Authentication weaknesses. Rate limiting bypasses. Model endpoint enumeration. The traditional attack surface still matters.
Trust Boundary Analysis
Where does your system trust the model's output? What happens when that trust is misplaced? We map the boundaries and test what breaks when we cross them.
Flexible for Your Stage
Focused Assessment
One-time engagement focused on your AI stack, agents, and APIs. Find critical issues before launch.
Pre-funding or MVP validation
Full Security Test
Complete assessment of live AI systems. LLM pipelines, agent workflows, infrastructure, and APIs.
Production deployments
Continuous Testing
Regular assessments as your AI evolves. New features get tested. New attack techniques get applied.
Scaling teams
What you get.
Proof of Exploitation
Screenshots, payloads, step-by-step reproduction. Not theoretical risk—demonstrated impact.
Risk-Based Prioritization
Findings ordered by actual exploitability and business impact, not generic severity ratings.
Actionable Remediation
Specific fixes for your stack. Guidance that accounts for how your system is actually built.
Retest Included
Fix the issues, we verify the fixes. You shouldn't have to pay twice to confirm remediation worked.
Let's talk about your AI stack.
15-minute call to understand what you're building and what testing makes sense.