Understanding how AI, information exposure and cryptographic change affect business risk, sensitive data and organisational resilience.
R2N Partner supports organisations in assessing technology-driven risks that sit between governance, fraud, information protection and long-term resilience. The focus is not traditional cybersecurity testing, but whether emerging technologies are creating exposures that management may not currently see or control.
Assessment of how employees and business functions use generative AI, what confidential or personal information may be exposed through prompts, uploads or connected tools, and where policy, process or control gaps create risk.
Design of practical safeguards for approved and shadow AI use, including data classification, usage rules, preventive controls, monitoring logic, alerting criteria and investigative response to suspected information disclosure.
Inventory and assessment of where cryptography is used across systems, applications, databases, backups, certificates, APIs and communications, considering algorithm suitability, key management, data sensitivity and required confidentiality periods.
Assessment of cryptographic exposure to future quantum capabilities, including long-lived sensitive data, public-key dependencies, harvest-now-decrypt-later scenarios, crypto-agility and prioritised migration planning.
A practical lifecycle for managing sensitive-information exposure through AI systems without treating every use case as a conventional cybersecurity problem.
Assess approved and shadow AI use, information flows, employee behaviours and exposure scenarios.
Prevent inappropriate disclosure through policy, data classification, configuration and proportionate technical guardrails.
Detect potentially sensitive prompts, uploads or behavioural patterns through monitoring and risk-based alerting.
Respond by reviewing events, determining what was exposed, understanding root cause and defining remediation.
Cryptographic adequacy depends not only on the algorithm in use, but also on what is being protected and for how long it must remain confidential.
Discover where encryption, digital signatures, certificates and public-key cryptography are used across the organisation.
Classify protected information by sensitivity, business criticality and required confidentiality or retention period.
Assess algorithms, protocols, key lengths, key management, certificate lifecycle and dependencies for adequacy and obsolescence risk.
Evaluate quantum exposure, including long-lived data and harvest-now-decrypt-later scenarios.
Define remediation priorities, crypto-agility requirements and a proportionate post-quantum migration roadmap.
Synthetic identity and AI-assisted onboarding fraud.
Deepfake-enabled impersonation and payment-authorisation fraud.
AI-enhanced business email compromise and social engineering.
Document manipulation, fabricated evidence and synthetic content.
Prompt-injection and unsafe AI workflows where they create fraud, information or governance risk.