AI Infrastructure Pentest
Our security research team simulates real-world attacks against your AI-powered applications, LLM integrations, and agentic infrastructure to find exploitable weaknesses before an attacker does.
Simulated AI Attacks
A penetration test from our seasoned professionals will give you an attacker’s perspective on your AI system implementation.
- Identify exploitable prompt injection, guardrail bypass, and tool manipulation vulnerabilities
- Receive a detailed report with proof-of-concept attack demonstrations
- Receive remediation recommendations your engineering team can act on immediately
- Receive a complimentary re-test after implementing fixes
Custom Scoped, Custom Quoted
All of our services are custom scoped and custom quoted because no two AI environments are exactly the same. All we need is some general information to get started.
What We Test
Prompt Injection and Guardrail Evasion
We attempt to override your AI’s system instructions, extract its internal configuration, and bypass safety controls through direct and indirect prompt manipulation. Whether your application runs on a commercial or open-source model, we test how the integration layer handles adversarial inputs.
MCP and Tool Integration Security
If your AI connects to external tools, data sources, or APIs, we test the trust boundaries between your agent and those connected systems. This includes tool call hijacking, privilege escalation through chained tool access, and unauthorized data access through manipulated tool descriptions.
RAG Pipeline Poisoning
For applications using retrieval-augmented generation, we test whether adversarial content injected into the knowledge base or retrieved documents can manipulate the AI’s output, steer it toward harmful responses, or exfiltrate data through retrieval channels.
Agentic Workflow Exploitation
For AI systems that plan, reason, and execute multi-step actions, we assess whether an attacker can hijack the agent’s goals, escalate its permissions, or manipulate its decision-making through adversarial inputs embedded in the data it processes.
AI Infrastructure Security
Beyond the model layer, we test the surrounding deployment: API authentication and rate limiting, session management, data handling, model endpoint exposure, environment network segmentation, and the security of the infrastructure itself.
Benefits
A Hacker’s Perspective on AI
Get an outside perspective on your AI risk posture from the lens of an attacker targeting your language models, integrations, and agentic workflows.
Go Beyond Traditional AppSec
Assess attack vectors that traditional web application pentests and vulnerability scanners are not built to detect. AI introduces a fundamentally different attack surface.
Proactive Remediation
Identify and fix AI-specific vulnerabilities before they are exploited in production, reported by researchers, or flagged during a compliance review.
Trusted Security Advisers
NopSec has performed manual penetration testing and red-teaming engagements across infrastructure, applications, wireless, mobile, social engineering, and VoIP since 2008. Our CTO and Head of Security Research have published original research on LLM applications in cybersecurity and are well-known in the industry.
NopSec is trusted by companies such as
SOC 2 Type II Compliant
Find the Weaknesses Before an Attacker Does
Every AI environment is different. Tell us about yours and we will scope a test.