Aaryanova works with engineering teams at design time — threat modelling systems before they ship, and securing AI features before they reach production. Senior practitioners embedded in your architecture decisions, not auditors reviewing them afterwards.
Deep specialisation in the design-stage security work that determines whether everything downstream is manageable or expensive.
Threat modelling for LLM and ML systems: prompt injection, data exfiltration through model outputs, agent permission boundaries, and supply chain risk in model dependencies. Assessed against the OWASP LLM Top 10 and NIST AI RMF, delivered as findings your engineers can act on this sprint.
Structured threat modelling using STRIDE, PASTA, and attack trees — run as a working session with your engineering team, not a document delivered over the wall. You get a living model your team can maintain, plus the capability to run the next one yourselves.
Architecture review and security requirements that land in backlogs rather than slide decks. Reusable design patterns for authentication, API security, and secrets management, integrated into your SDLC so security checks happen on every release.
Design-stage work rarely stays in its lane. These come up in most engagements and are included where relevant.
Threat modelling is not a tick-box exercise — it is a structured conversation between security and engineering that surfaces the real risks in your systems before they are built, not after they are breached.
We map your system: assets, data flows, trust boundaries, entry points, and actors. Architecture diagrams are built or validated with your engineering team.
Using STRIDE, PASTA, or attack trees as appropriate, we enumerate threats at each component and data flow — prioritised by likelihood and impact.
For each threat, we assess existing controls, identify gaps, and recommend specific, costed countermeasures aligned to your engineering roadmap.
We revisit threat models as your system evolves — threat modelling is a living artefact, not a one-time deliverable.
Security is most effective — and cheapest — when built in from the start. We work alongside your architects and engineers at design time, not after the fact.
We assess proposed or existing architectures against security principles — least privilege, defence-in-depth, zero trust — and identify structural weaknesses before build.
Translating threat models and compliance obligations into clear, developer-readable security requirements that land in backlogs, not slide decks.
Defining reusable security patterns — authentication, encryption, API security, secrets management — that developers can implement consistently across your estate.
Hands-on secure coding training, code review support, and security champions programmes that shift security left sustainably.
Embedding security gates, SAST/DAST tooling, and dependency scanning into your CI/CD pipeline so security checks happen automatically on every release.
Designing data minimisation, consent flows, and retention controls into your systems from day one — meeting GDPR obligations without retrofitting.
Cloud environments introduce shared responsibility, dynamic infrastructure, and complex identity relationships that on-premise security thinking doesn't map cleanly onto. We bring cloud-native security expertise to AWS, Azure, and GCP.
Continuous assessment of your cloud configuration against CIS Benchmarks and provider best-practice frameworks — with prioritised findings, not raw dumps.
Right-sizing IAM roles and policies, eliminating over-privileged service accounts, and implementing Just-In-Time access across cloud environments.
Secrets management, encryption key governance, and data classification controls — ensuring sensitive data is protected at rest and in transit.
Building detection rules, log pipelines, and response playbooks tailored to cloud-native threat vectors including credential abuse and lateral movement.
Every engagement follows a structured methodology — grounded in your environment, not a generic playbook.
We are practitioners first — not a checkbox factory.
Our consultants have built and broken real systems — not just written reports about them.
Every engagement ends with clear, prioritised, actionable recommendations — not a 200-page document no one reads.
Strategy through to implementation. We stay engaged until the risk is actually reduced, not just documented.
Deep experience in AWS, Azure, and GCP security — not retrofitted on-premise thinking.
We understand AI risks from both sides — securing your AI deployments and defending against adversaries who weaponise AI to attack you.
We've worked with clients across financial services, healthcare, critical infrastructure, technology, and the public sector.
We leave your team more capable — embedding knowledge, not dependency, in every engagement.
A European payments startup was rebuilding its core ledger and payout service ahead of an FCA authorisation milestone. The engineering team of around forty had strong product velocity but no formal security design process — security review happened at pen-test time, weeks after architecture was frozen. Two previous releases had required costly rework when auth flaws surfaced late.
We ran a structured threat model against the proposed architecture before implementation began. Working sessions with the platform and payments teams mapped assets, data flows, and trust boundaries, then enumerated threats at each boundary using STRIDE, with attack trees for the payout authorisation path specifically. Every finding was assessed against existing controls, prioritised by likelihood and impact, and translated into security requirements written as backlog tickets rather than report recommendations.
The model surfaced design-stage risks that would not have been visible to a post-build penetration test — including a trust boundary assumption in the reconciliation service that would have allowed a compromised internal service to initiate payouts without secondary authorisation. Mitigations were folded into the build rather than retrofitted. The team now maintains the threat model themselves and re-runs it each time the payout path changes.
Client details anonymised at their request. Reference available on request under NDA.
Most engagements begin with one of these. Each has a defined deliverable and a fixed fee, so you know what you're committing to before we start.
One LLM or ML feature assessed against the OWASP LLM Top 10. Delivered as a prioritised findings report plus a working session with your engineers.
Enquire →One product or service modelled end to end. Delivered as a maintainable threat model, prioritised risks, and costed mitigations mapped to your roadmap.
Enquire →A set block of hours for design review, architecture questions, and advisory as your systems evolve. For teams shipping continuously.
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