Independent AI Adversarial Testing
Find Where Your AI System fails Before Someone Else Does
Independent adversarial testing for AI systems, helping identify vulnerabilities and produce evidence for risk reduction, governance, and EU AI Act readiness.
Trusted Methodology, Recognised Frameworks
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- [ PyRIT ]
Testing is carried out using recognised adversarial testing approaches and open-source tools.
The EU AI Act Has Shifted The
Burden of Proof
By 2 August 2026, high-risk AI systems under Annex III must meet the EU AI Act's robustness obligations. They need documented evidence, not assurances. The companies that prepare early write the playbook for everyone else.
- 01
Documentation, Not Declarations
Annex IV expects technical documentation that maps directly to the system's design, training data, and risk controls.
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Adversarial Testing, Not Self-Attestation
Internal teams and platform vendors can run scans. They cannot give an external, independent view of how a model, agent, or workflow fails under attack.
- 03
Speed, Matched to Deployment Cycle
Teams need a focused assessment that returns findings and structured documentation in days, on the timeline the business is already running.
Initial Assessment Offer
AI System Robustness Assessment
One AI system. Independent adversarial testing. A report your auditor can use.
We assess one AI system or workflow to identify vulnerabilities across the areas most likely to create security, safety, or compliance risk. The engagement includes scoped review, targeted adversarial testing, prioritised findings, remediation guidance, and a structured report designed to support more confident deployment.
Coverage
What We Test, Layer by Layer
We assess more than the model. We look across the layers that shape how an AI system behaves in production: prompts, guardrails, agents, tools, data, integrations, dependencies, and runtime controls.
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AI Application & Guardrail Security
Assess the application layer around the model, including prompts, input handling, output controls, guardrails, and orchestration logic. This helps identify weaknesses that could lead to prompt injection, jailbreaks, unsafe outputs, or policy bypass.
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Agentic & Tool-Use Security
Assess agents, tool connections, permissions, memory, and multi-step workflows. This helps uncover how autonomous or semi-autonomous systems can be manipulated, escalated, or misused when interacting with external tools, data, and actions.
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Model & Data Security
Assess the model and data layer for adversarial weaknesses, including poisoning, data leakage, inversion, membership inference, extraction, and bias exploitation. Focused on the security and robustness of the core intelligence layer itself.
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AI Supply Chain & Runtime Security
Assess the wider AI system across third-party components, APIs, dependencies, deployment controls, logging, authentication, rate limiting, and runtime monitoring. This helps expose risk across the environments and infrastructure supporting production AI.
Differentiation
Why Teams Choose Provion
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Independent Assessment
External, objective testing, with no model vendor, no cloud allegiance, and no platform to upsell.
- No infrastructure conflict
- No vendor allegiance
- Auditable, open-source testing stack
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EU AI Act Readiness
Testing and documentation aligned to requirements, expectations and logic shaping the EU AI Act.
- Adversarial robustness testing as evidence
- Annex IV technical documentation logic
- Article 72 post-market monitoring logic
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Focussed
DeliveryFrom kickoff to final report in days. From report to remediation in the next sprint, not the next quarter.
- Fixed scope and fixed timeline
- Remote delivery by default
- Structured outputs from day one
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Technical
DepthHands-on adversarial testing across modern AI systems, from core models to agentic workflows.
- Tooling: Garak, Giskard, Promptfoo, PyRIT
- Frameworks: OWASP ASI, MITRE ATLAS, ETSI EN 304 223
- Coverage: LLM-based systems and multi-step agentic workflows
Process
From Scoping Call to Signed Report
A focused assessment process designed to produce useful findings and structured documentation quickly.
- 01
Scoping Call
We define the AI system or workflow to be assessed, confirm objectives and identify access requirements.
- 02
System Review
We review the system architecture, use case, prompts, model setup, guardrails, integrations, data flows, and relevant controls.
- 03
Adversarial Testing
We test the system across applicable risk areas, including prompt attacks, guardrail bypass, agent/tool misuse, data exposure, and runtime weaknesses.
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Findings & Remediation
We document vulnerabilities, evidence, severity, likely impact, and practical remediation recommendations.
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Final Report
You receive a structured report designed for technical teams, security leaders, and governance stakeholders.
Typical engagements are scoped around one AI system or workflow. Final timeline depends on system complexity, access, and assessment depth.
Built for Teams Deploying AI Where Failure Matters
For teams designing, deploying, or managing AI systems and workflows. We help you understand real-world failure modes before wider rollout.
For teams responsible for understanding how AI systems can be manipulated, misused, or exposed through prompts, agents, integrations, and runtime infrastructure.
For stakeholders who need structured evidence, reporting, and documentation to support internal assurance, auditability, and EU AI Act readiness.
AI, Product & Technical Owners
For teams designing, deploying, or managing AI systems and workflows. We help you understand real-world failure modes before wider rollout.
Security & Risk Leaders
For teams responsible for understanding how AI systems can be manipulated, misused, or exposed through prompts, agents, integrations, and runtime infrastructure.
Compliance, Legal & Governance
For stakeholders who need structured evidence, reporting, and documentation to support internal assurance, auditability, and EU AI Act readiness.
Built by 
Provion is an independent AI security and adversarial testing service from Protokol, a European technology company with experience building trust infrastructure for emerging technologies. Protokol has worked across blockchain infrastructure, Digital Product Passports, EU-aligned innovation projects, and regulated technology environments.
This background gives us a practical understanding of how new technology becomes auditable, documented, and deployable while regulatory expectations are still forming. With AI, we see the same pattern emerging: organisations need independent testing, structured evidence, and clear documentation before systems can be deployed with confidence.
- EBSI
Contributor to European Commission blockchain infrastructure programmes.
- Digital Product Passport
Production solutions delivered ahead of ESPR enforcement.
- Horizon Europe
Participant in EU-funded research consortia on auditable systems.
Request an Independent AI Robustness Assessment
Book a short scoping call and we'll help you define what to assess, what access is needed, and what evidence would be most useful for your AI security, governance, and compliance teams.