Key Capabilities
Everything you need to build production-grade solutions
LLM & Generative AI Security
Prompt injection and jailbreak risk analysis. Output filtering and safety guardrails. Secure prompt and context design. Abuse prevention strategies.
AI Threat Modeling
Threat mapping across AI pipelines. Identification of high-risk attack vectors. Security design reviews before production deployment.
Secure AI Architecture Reviews
End-to-end AI system audits. Model access control and isolation strategies. Secure inference and data handling practices.
AI Data Security & Privacy
Training and inference data risk assessment. Sensitive data exposure prevention. Privacy-preserving AI design guidance.
AI Security Testing
Adversarial testing of AI systems. Simulation of real-world attack scenarios. Validation of safety controls under stress.
Standards & Framework Alignment
OWASP Top 10 for LLM Applications. NIST AI Risk Management Framework. Secure-by-design AI principles applied pragmatically.
Our Process
A predictable process built for high-quality delivery
AI Risk Assessment
Identify where your AI system can fail, be exploited, or leak sensitive data.
Threat Modeling & Design Controls
Design safeguards directly into prompts, pipelines, APIs, and system architecture.
Security Testing & Validation
Test AI behavior under adversarial and edge-case scenarios.
Production Readiness Review
Ensure AI systems are safe to deploy, scale, and operate.
Technologies We Use
Production-tested tools and frameworks
Use Cases
Our services support
Design-Time Security Reviews
Secure AI systems before production deployment
Production AI Audits
Assess and harden existing AI applications
Embedded AI Security Support
Ongoing guidance as models, prompts, and workflows evolve
Why Choose Procedure for AI Security Services
Companies choose Procedure because
Companies choose Procedure because:
- Engineering-led AI security, not theory
- Experience securing real production AI systems
- Deep understanding of LLM behavior and failure modes
- Focus on business risk, not fear-based selling
- Pragmatic framework alignment (OWASP, NIST AI RMF)
Outcomes from recent engagements
Testimonials
Trusted by engineering leaders
“What started with one engineer nearly three years ago has grown into a team of five, each fully owning their deliverables. They've taken on critical core roles across teams. We're extremely pleased with the commitment and engagement they bring.”
Why Quality Matters
Poor engineering costs you
Data Breaches
AI systems can leak training data and sensitive information
Reputational Damage
Jailbreaks and misuse erode user trust
Legal Liability
AI security failures expose companies to regulatory risk
Business Disruption
Exploited AI systems require emergency fixes
Premium development is an investment in
Frequently Asked Questions
Before AI systems reach users, data, or production environments. Early security prevents costly failures later.