Find AI Vulnerabilities Before Attackers Do.
A comprehensive AI security audit that covers both AI-specific risks and traditional application security. From prompt injection to OWASP Top 10, tested by engineers who understand how AI systems actually break.
What We Test
Every AI security audit covers six core areas. We test the things that traditional security firms miss entirely.
LLM Red-Teaming
Adversarial testing of your large language models for jailbreaks, harmful outputs, and safety bypasses.
Prompt Injection Testing
Direct and indirect prompt injection attacks against your AI system to test input validation and guardrails.
RAG Pipeline Security
Testing retrieval-augmented generation pipelines for poisoning, context manipulation, and data leakage.
Agent Tool-Use Audit
Evaluating AI agents for unauthorized tool calls, privilege escalation, and unintended side effects.
AI Data Exfiltration
Testing whether attackers can extract training data, system prompts, or sensitive information from your models.
Model Supply Chain
Reviewing model provenance, dependency security, and third-party integration risks across your AI stack.
Our Process
From scoping to remediation, every AI security audit follows a structured process so you know exactly what to expect.
Scoping
We map your AI architecture: models, endpoints, data flows, RAG pipelines, and agent configurations. You get a fixed-price quote and a clear timeline.
Adversarial Testing
Our security engineers run targeted attacks against your AI systems and traditional infrastructure. Every finding is verified manually, not just flagged by a scanner.
Reporting
You receive a detailed report with severity ratings, proof-of-concept exploits, and a prioritized remediation roadmap. Plus an executive summary for leadership.
Remediation
We walk your team through every finding, answer questions, and provide hands-on guidance. Optional retesting confirms your fixes actually work.
Who This Is For
You are deploying AI in production and need to know it is secure. Maybe a customer asked for a security audit. Maybe your compliance team flagged AI as a risk. Maybe you just want to ship with confidence.
Our AI security audit service is built for companies that are actively using AI, not just planning to. We work with engineering teams directly, speak your language, and deliver findings you can act on immediately.
SaaS companies integrating LLMs into their products
Healthcare organizations deploying AI for clinical or operational use
Fintech companies using ML models for fraud detection or underwriting
Startups shipping AI features and needing security validation for customers
Enterprises adding AI copilots, chatbots, or automation agents
What You Get
Every AI security audit delivers actionable results, not a generic PDF full of scanner output.
Executive summary for leadership and board reporting
Technical report with every finding rated by severity
Proof-of-concept exploits demonstrating real impact
Prioritized remediation roadmap with effort estimates
60-minute walkthrough call with our security engineers
Optional retesting to verify your fixes are effective
Frequently Asked Questions
Common questions about our AI security audit service.
How long does an AI security audit take?
Most AI security audits take 2 to 4 weeks depending on the number of AI models, endpoints, and integrations in scope. A simple single-model audit can finish in under 2 weeks. Complex multi-agent systems with RAG pipelines and tool-use may take closer to 4 weeks. We provide a clear timeline during the scoping call.
What is included in an AI security audit?
Our AI security audit covers LLM red-teaming, prompt injection testing, RAG pipeline security review, agent tool-use auditing, data exfiltration testing, model supply chain analysis, and traditional application security testing (OWASP Top 10, API security, authentication, authorization). You get a detailed report with severity-rated findings and remediation guidance.
How much does an AI security audit cost?
Cost depends on the scope: the number of AI models, the complexity of your pipelines, and whether traditional infrastructure testing is included. We offer audits accessible to startups and SMBs, not just large enterprises. Book a scoping call and we will provide a fixed-price quote with no surprises.
How is an AI security audit different from a traditional penetration test?
A traditional penetration test focuses on network, web application, and infrastructure vulnerabilities. An AI security audit adds testing for AI-specific risks: prompt injection, jailbreaking, training data extraction, model inversion, agent manipulation, and RAG poisoning. BeyondScale covers both in a single engagement so nothing falls through the cracks.
What do I receive as deliverables after the audit?
You receive an executive summary, a detailed technical report with every finding categorized by severity (critical, high, medium, low, informational), proof-of-concept demonstrations for key vulnerabilities, a prioritized remediation roadmap, and a 60-minute walkthrough call with our security engineers. We also offer optional retesting after you apply fixes.
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