The Risks
What Can Go Wrong With Unsecured AI?
Prompt Injection Attacks
Attackers manipulate your AI to leak data, bypass controls, or execute unintended actions.
Sensitive Data Exposure
Your LLM reveals customer PII, internal documents, API keys, or proprietary information.
System Prompt Leakage
Competitors or attackers extract your proprietary prompts, revealing business logic.
Jailbreaks & Safety Bypass
Users bypass safety controls to generate harmful, illegal, or reputation-damaging content.
Compliance Failures
EU AI Act violations, SOC 2 gaps, or industry-specific regulations breached.
Uncontrolled Costs
Attackers or bugs cause runaway API bills through resource exhaustion attacks.
What We Do
AI Security Services
AI Red Teaming & Penetration Testing
We attack your AI systems before real attackers do.
- Prompt injection testing (direct & indirect)
- Jailbreak and safety bypass attempts
- System prompt extraction attacks
- Data exfiltration scenarios
- Abuse vector identification
LLM Security Architecture Review
Security review of your AI system design, before or after launch.
- Model access control & isolation
- API security & credential management
- Third-party model integration risks
- Input validation & output filtering
- Logging, monitoring & audit trails
AI Threat Modeling
Map every way your AI system can be attacked.
- Attack surface identification
- Threat actor profiling
- Risk prioritization by business impact
- Security control gap analysis
- Mitigation roadmap
AI Data Security & Privacy
Prevent your AI from leaking what it shouldn't.
- PII leakage detection & prevention
- Training data exposure risks
- Model memorization assessment
- Data extraction attack testing
- Privacy-preserving design guidance
Compliance & Framework Alignment
Get your AI systems audit-ready.
- OWASP Top 10 for LLMs (2025)
- EU AI Act compliance assessment
- NIST AI Risk Management Framework
- ISO/IEC 42001 alignment
- Industry-specific: Healthcare, Finance
Ongoing AI Security Support
Security isn't one-time. We stay with you.
- Embedded security for AI teams
- Security review before releases
- AI incident response
- Continuous monitoring setup
- Team training on secure AI dev
How We Work
From Assessment to Remediation
Scope
Understand your AI system, tech stack, and threat model. Define assessment boundaries.
Assess
Red team tests, architecture review, code analysis. Find vulnerabilities before attackers do.
Report
Clear findings with severity ratings, proof-of-concept exploits, and remediation guidance.
Fix
Help implement fixes or verify your team's remediations. Retest to confirm closure.
Is This For You?
Who We Work With
Good Fit
- ✓Teams deploying LLMs to production (not just experimenting)
- ✓Companies with compliance requirements (healthcare, finance, enterprise)
- ✓Startups about to raise or facing security due diligence
- ✓Teams that got burned by an AI security incident
- ✓Engineering teams building AI-powered products
Not a Fit
- ✕Just exploring AI with no production plans
- ✕Looking for a checkbox audit (we do real testing)
- ✕Need generic cybersecurity (we specialize in AI)
- ✕Want theoretical consulting without hands-on work
Frequently Asked Questions
AI systems have unique attack vectors, including prompt injection, jailbreaks, data leakage through model outputs, and system prompt extraction, that traditional security testing doesn't cover. We specialize in these AI-specific risks.
Related Expertise
Let's Find the Gaps Before Attackers Do
Book a 30-minute call to scope your AI security assessment.
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