Stop hoping your AI is secure. Start knowing.
Continuous adversarial validation for AI systems. RAP tests your defenses the way real attackers think — so you can fix vulnerabilities before they become breaches.
Root Access Protection is a continuous AI security validation service that uses real adversary methodology and disciplined tradecraft to test whether your AI defenses would stop what attackers actually do — not just what tools assume.
At its core, RAP operates as an adversary-informed tradecraft engine that captures and operationalizes observed attacker methodology under disciplined rules of engagement.
What AI Adversary Pentesting Is Not
We are not a checkbox auditor.
Compliance frameworks are necessary but insufficient. We test whether your AI can be compromised, not whether you've filled in the right forms.
We are not a prompt fuzzer.
Running random inputs at your model isn't adversary simulation. Real attackers chain techniques, persist, and adapt.
We are not a runtime guardrail vendor.
Those products filter outputs. We probe whether those filters would stop a determined attack chain — before production.
We are not an annual assessment.
Point-in-time snapshots don't reflect how fast AI attack surfaces evolve. We validate continuously.
Why Traditional Security Fails AI
The Problem
Annual pentests are theater. Point-in-time assessments are stale before the ink dries. As AI agents become autonomous, the gap between your perceived security and reality is widening.
Checklists aren't enough
Compliance checkboxes don't stop determined adversaries. OWASP LLM Top 10 coverage is table stakes — you need to test against attack chains, not just individual techniques.
Attackers move faster
New jailbreaks drop daily. Your annual audit cycle leaves you exposed for months. The gap between attacker innovation and defender validation is measured in weeks, not years.
Agentic Complexity
Autonomous agents introduce goal hijacking, tool misuse, memory poisoning, and cascading failures. Attack surfaces that traditional scanners can't even model.
EU AI Act: June 2, 2026
High-risk AI systems and GPAI models with systemic risk must demonstrate adversarial testing and conformity assessment. Penalties reach €20M or 4% of worldwide turnover.
Adversarial Testing
Document and perform model evaluations including adversarial testing
Conformity Evidence
Prove your AI is "accurate, robust, and secure" with audit trails
Continuous Monitoring
Ongoing risk management, not just point-in-time snapshots
RAP provides audit-ready evidence that proves you've tested — not just documented — your AI security posture.
Evidence, Not Belief
RAP compresses the time between attacker innovation and defender validation. We utilize MITRE ATLAS-aligned methodology to simulate real-world threats.
Continuous Validation
Not just a snapshot. Ongoing testing against 100K+ evolving threats, ensuring your defenses adapt as fast as the attackers do.
Agentic AI Security
Specifically targeting OWASP Top 10 for Agentic Apps. We validate against Memory Poisoning, Cascading Failures, Goal Hijacking, and Tool Misuse.
Compliance Ready
Maps directly to EU AI Act & NIST AI RMF requirements. Generate audit-ready reports that prove conformity, not just claim it.
Evidence-Based
Actionable remediation, not just a PDF report. We provide the kill chain evidence so engineering knows exactly what to fix.
OWASP Coverage
Measured. Not Claimed.
RAP validates against all three canonical OWASP AI security frameworks with custom adversary reasoning — not checkbox scans. Every percentage is backed by active probe evidence.
Framework Coverage Rate
Probe Depth by Category
Every bar represents custom adversary reasoning probes — not generic fuzzing. Categories sorted by depth within each framework.
Combined OWASP Coverage
| Framework | Categories | Active Probes | Static / Advisory | Not Testable | Coverage |
|---|---|---|---|---|---|
| LLM Top 10(2025) | 10 | 5 | 2 | 3 | 83% |
| MCP Top 10(2025) | 10 | 7 | 3 | 0 | 70% |
| Agentic AI Top 10(2026) | 10 | 7 | 1 | 2 | 88% |
| Combined | 30 | 19 | 5 | 6 | 79% |
Scope by Design
RAP's coverage reflects deliberate methodology, not gaps in capability. Categories outside active testing fall into three principled boundaries:
Categories like Unbounded Consumption map directly to denial-of-service vectors. Executing these against live systems violates responsible disclosure norms and rules of engagement. RAP will never run destructive availability attacks against your infrastructure.
Categories involving social engineering and human judgment manipulation operate outside the scope of automated adversary probes. These are assessed through engagement-specific manual tradecraft and advisory guidance.
Some categories require direct access to training pipelines, embedding APIs, or model internals that sit outside typical engagement boundaries. RAP addresses these through architecture review and static advisory when client access permits.
MITRE ATLAS Alignment
OWASP defines what to test. MITRE ATLAS defines how attackers think. RAP maps every probe to ATLAS tactics and techniques — 15 tactics, 66 techniques, and 33 real-world case studies — ensuring adversary reasoning reflects observed attacker behavior, not theoretical checklists.
Service Schema
How the Engagement Works
A structured approach to AI security validation, aligned with our core service methodology.
Inputs
- • AI System Access (API or Interface)
- • System Instructions / Prompts
- • Whitebox or Blackbox target
- • Compliance requirements (EU AI Act, NIST AI RMF)
Activities
- • Prompt Injection & Jailbreaking
- • Agentic Goal Hijacking
- • Tool Misuse Testing
- • RAG Knowledge Poisoning
- • System Prompt Leakage
- • MITRE ATLAS mapping
Outputs
- • Validated kill chains
- • Reproduction steps
- • Compliance conformity evidence
- • Engineering remediation guidance
- • Board-ready summary
Cadence
- • On-demand assessment
- • Continuous validation subscription
- • Monthly/Quarterly reporting cycles
- • Regression testing after changes
Competitive Differentiation
Why RAP, Not Them
The AI security market is crowded with overlapping claims. Here's how RAP is different.
Vs. Automated Red Teaming
"Minutes not months" sounds great — but speed without depth is theater. Automation finds bugs. Adversary Reasoning finds kill chains. We test how attackers actually think, not just run scripts.
Vs. Runtime Protection
Guardrails claim high detection rates against known attacks. We test whether new attack chains — the ones that bypass guardrails — would compromise your AI. Proactive validation, not reactive filtering.
Vs. Manual Pentesting
Expert judgment is irreplaceable. But annual snapshots are stale before the ink dries. RAP delivers continuous validation at machine speed with human oversight. Don't wait weeks for results.
Vs. Platform Players
Platforms consolidate tools. RAP delivers outcomes. We provide a validated security posture against real-world threats, continuously. Not another dashboard to manage.
Close the Gap.
Ready to see how actual adversaries view your AI infrastructure? Join the waitlist for priority access or book a discovery call.