AI
AI systems influence decisions, automate workflows and interact with your business. When their boundaries fail, bad outputs can become real business consequences.
Risk — manipulation & misuse
CobaltSec / 2026
Secure your
AI / LLM / MCP.
We test AI applications, LLMs, agents and MCP integrations for vulnerabilities, unsafe behavior and unauthorized access.
Explore our services ↓Three layers.
One attack surface.
LLM
LLMs process your data, represent your business and generate answers users trust. Prompt injection, data leakage and hallucinations can turn that trust into an attack vector.
Risk — data & trust
MCP
MCP gives models access to tools, systems and data. When an AI can call real services, a successful attack can move beyond text and directly affect your infrastructure.
Risk — unauthorized execution
01 Sensitive data can leak through prompts, context, integrations or model outputs — sometimes in ways your users never see coming.
02 AI can confidently produce false or manipulated information, turning a model failure into a security, financial or operational problem.
03 AI agents can be manipulated into abusing their tools, accessing unauthorized resources or making destructive changes to production systems.
04 Employees can unintentionally expose credentials, source code, customer data or other sensitive information through AI services.
What
we attack.
01
AI Security Assessment
We assess your AI architecture, data flows, integrations and security controls to identify weaknesses before attackers do.
02
AI Red Teaming
We actively attack your AI systems to bypass security boundaries, extract sensitive data, abuse functionality and reach systems they should never touch.
03
LLM & Guardrail Pentesting
We test prompts, models and guardrails against prompt injection, data leakage, jailbreaks, policy bypasses and other adversarial techniques.
04
MCP Security Testing
We test Model Context Protocol servers, tools and integrations for broken authorization, excessive privileges, injection and dangerous attack paths.
05
AI Agent Security
We test autonomous agents and their tool access for privilege escalation, unsafe actions, excessive agency and manipulation.
06
AI Security Hardening
We help fix what we find by strengthening prompts, permissions, tool boundaries, data handling and the controls around your AI systems.
07
AI Security Retesting
We return after remediation and verify that vulnerabilities have actually been fixed and previously successful attacks no longer work.
08
AI Security Training
Practical security training for developers and employees covering prompt injection, sensitive data, AI misuse and secure AI development.
09
AI Security & Compliance Assessment
We assess your AI systems and processes against relevant security frameworks, regulations and internal requirements, then provide a clear remediation roadmap.
✦
Find the gaps
before attackers do.
Let's test your AI, break its boundaries, and show you what needs fixing.
Start a conversation ↗