Know exactly how your AI breaks — in two weeks.
A fixed-scope, fixed-fee adversarial assessment of one production or near-production AI system: chatbot, copilot, or agent.
Challenge
Your teams shipped an LLM feature. Your board is asking if it's safe. Your auditors are asking how you'd prove it. Pen-test firms don't understand prompt injection, and AI vendors only test their own products. Meanwhile every week in production is a week of untested exposure.
Solution
Aynigma runs a structured adversarial assessment against your system using the same engine that powers our platform: automated attack probes across the OWASP LLM Top 10, agent tool-call risk review, and human-led exploitation of what the automation finds. You get a severity-ranked findings report, an executive readout, and a remediation roadmap — delivered inside two weeks, with an optional compliance gap analysis mapped to the frameworks your auditors actually use.
Key Capabilities
OWASP LLM Top 10 Coverage
Automated and human-led probes: prompt injection, jailbreaks, data leakage, system prompt extraction, and more
Agent & Tool-Call Risk Review
What your agents can touch, what they can be tricked into doing, and where a human should be in the loop
Compliance Gap Analysis
Findings mapped to SOC 2, ISO 27001, HIPAA, NIST AI RMF — plus NCA-ECC, PDPL, and SAMA guidance for Gulf enterprises
Executive Readout & Roadmap
A severity-ranked report your engineers can act on and a readout your leadership can take to the board
Business Outcomes
Board-Ready Evidence
A defensible answer to "is our AI safe?" — with findings, severity, and remediation status
Two-Week Turnaround
Fixed scope and fixed fee. No months-long consulting engagement
Actionable Remediation
Every finding comes with a concrete fix, not just a CVSS number
A Path to Continuous Coverage
Assessment findings flow straight into the Aynigma platform for continuous re-testing and runtime protection
Book your AI Security Assessment.
Tell us what you've deployed. We'll scope the assessment on a 30-minute call.