Secure Your AI Against Prompt Injection Attacks
Professional penetration testing for LLM applications. We identify vulnerabilities in your AI systems before malicious actors do—protecting your data, reputation, and users.
AI Systems Face Critical Security Risks
As AI adoption accelerates, so do sophisticated attacks targeting LLM vulnerabilities. Is your system protected?
Data Exfiltration
Attackers can extract sensitive training data, API keys, and confidential information through carefully crafted prompts.
System Jailbreaks
Bypass safety guardrails and content filters to make your AI generate harmful or inappropriate content.
Prompt Injection
Manipulate AI behavior by injecting malicious instructions that override original system prompts.
User Impersonation
Exploit context windows to impersonate users or administrators, gaining unauthorized access.
Comprehensive AI Security Testing
Our specialized pentesting services are designed specifically for modern LLM applications and AI agents.
Prompt Injection Testing
Comprehensive evaluation of your LLM application against direct and indirect prompt injection attacks.
- Multi-turn conversation attacks
- System prompt extraction attempts
- Context manipulation testing
- RAG poisoning analysis
Jailbreak Assessment
Rigorous testing of your AI guardrails and safety mechanisms against known and emerging jailbreak techniques.
- Safety filter bypass testing
- Role-play exploitation
- Token smuggling detection
- Output filtering validation
Security Hardening
Expert recommendations and implementation guidance to fortify your AI systems against attacks.
- Input validation strategies
- Output sanitization methods
- Architecture review & redesign
- Ongoing monitoring solutions
Our Security Testing Process
A systematic approach to uncovering and addressing AI security vulnerabilities.
Discovery
We analyze your AI architecture, data flows, and identify potential attack surfaces.
Testing
Our experts conduct manual and automated testing using the latest attack vectors.
Reporting
Receive detailed findings with severity ratings, proof-of-concepts, and evidence.