Strategic Adversary Simulation Services for AI

Adversary simulation is a controlled security assessment that models how a motivated attacker would pursue a realistic objective, such as extracting sensitive data, taking over an AI agent, or reaching privileged systems. Rather than only listing isolated vulnerabilities, it tests attack paths, exploit chaining, and business impact. The result is evidence-based prioritization and remediation guidance for the defenses that matter most.

In cyber security, an adversary is a person, group, or automated capability that attempts to compromise a system, steal information, disrupt operations, or abuse access. In an assessment, the adversary is simulated by authorized security testers working within agreed rules. Their methods help organizations evaluate detection, prevention, access controls, and response readiness without exposing production systems to uncontrolled risk.

Penetration testing identifies and validates vulnerabilities within a defined scope, often emphasizing broad coverage and actionable technical findings. Adversary simulation starts with an attacker objective and tests whether weaknesses can be combined to achieve it. Vynox Security uses both approaches: penetration testing reveals exploitable issues, while adversarial scenarios demonstrate how an attacker could move through AI applications, agents, data stores, and infrastructure.

Vynox Security tests LLM applications, RAG pipelines, autonomous agents, model integrations, APIs, web applications, mobile applications, cloud workloads, and networks supporting AI products. Assessments can examine direct and indirect prompt injection, retrieval isolation, tool-call security, model extraction, IAM paths, secrets exposure, and workflow abuse. Scope is tailored to the architecture, deployment stage, and security or compliance objective.

Testing is planned with agreed scope, guardrails, and communication channels to minimize operational risk. Potentially destructive agent actions, such as record deletion or payment execution, are assessed in staging or sandbox environments. Production validation focuses on safe proof-of-concept methods wherever possible. Before testing begins, Vynox Security aligns on authorized targets, test windows, escalation contacts, and conditions that require an immediate pause.

Deliverables include an executive summary for leadership and detailed technical findings for engineering teams. Each validated issue includes evidence, reproduction steps, severity scoring, impact context, and stack-specific remediation guidance. Where relevant, reports map findings to OWASP LLM Top 10, SOC 2, ISO 27001, and EU AI Act evidence requirements. Vynox Security also provides retesting within scope to verify remediated issues.

Timing depends on the scope and objective. Focused AI and LLM penetration tests commonly take 5–7 business days, while RAG, agent, and model extraction assessments typically take 10–15 business days. Comprehensive AI red teaming, which includes threat modeling and multi-step adversarial scenarios, generally takes 3–5 weeks. A 30-minute discovery call establishes the appropriate scope and delivery timeline.

Yes. Vynox Security maps relevant findings and remediation evidence to SOC 2 and ISO 27001 control requirements, helping teams prepare for audits and customer security reviews. For high-risk AI systems, AI red teaming can support EU AI Act Article 15 adversarial-testing needs. This is security-testing evidence rather than a certification audit, but it gives assessors and stakeholders clear, structured documentation.