AI in cybersecurity
Navigating AI in cybersecurity with control.
Smart use of AI. Strong security foundations.
Attacks move faster than a purely manual security operation can investigate. We help organisations use AI to shorten the time from the first suspicious signal to a safe, informed response — under controls you agree, with people accountable for the outcome, and value shown in security measurements rather than AI terminology.
Where we help
- Expert guidance to adopt AI in cybersecurity securely, practically and with measurable value.
- Threat modelling and risk assessment to secure AI agents before design or deployment.
- Design and deployment of private, organisation-controlled AI chat solutions with governance controls.
- Optimise SOC operations by adopting and evaluating vendor AI agents safely.
- Design AI-enhanced security workflows that automate decisions, enrichment and response.
We help customers leverage AI to support humans in solving the most complex cybersecurity problems.
Why it matters
AI is rapidly changing how cybersecurity is designed, operated and governed.
Used well, AI can strengthen protection, improve decision-making and help organisations manage complexity at scale. Used poorly, it introduces new risks — reduced transparency, over-automation, data leakage and misplaced trust in algorithmic outcomes.
Most organisations are asking the same three questions: where does AI genuinely add security value, how can it be applied responsibly, and how do you stay in control? That is the conversation we have with you first — before any technology decision.
Securing the use of AI: end-to-end assessments of AI architectures and use cases, structured threat modelling, and practical hardening recommendations based on real-world experience — plus targeted threat hunting and validation where it is needed.
What we test for
- Prompt injection through documents, tickets, email and other untrusted input
- Data leakage through context windows, logs and third-party model providers
- Over-broad agent permissions to systems, APIs and mailboxes
- Autonomous actions taken without an audit trail or human approval
- Model, plugin and supply chain trust — where the model and its tools come from
AI agent security
We help you design, deploy and operate AI agents securely.
Whether the agent is one you build, one you buy or one we build with you, the same questions apply: what can it reach, what can it do on its own, and who can see what it did.
Agent security reviews & audits
Assess existing AI agent designs to identify security risks, data exposure and control gaps.
Threat modelling & pre-build risk assessment
Evaluate attack paths, misuse scenarios and governance risks before agents are developed or deployed.
Secure agent design & implementation
Support the design and deployment of agents that securely collect and analyse data from internal systems to assist operational teams.
Custom agent development & API integration
Design and build purpose-driven AI agents by securely integrating your APIs and data sources to deliver actionable insights.
Adoption of vendor AI agents
Optimise security and operational workflows by evaluating, adopting and governing third-party AI agents within existing platforms.
We hold our own agents to the same standard — our AI SOC agents run in parallel with Sciber analysts so quality is measured case by case. See our AI SOC agents →
Private AI
An assistant your organisation actually owns.
Staff will use AI whether or not it is sanctioned. We design and deploy private, organisation-controlled AI chat — running in your own tenant, on your own data, with the governance the business needs — so the useful work happens inside your boundaries instead of in a public tool.
Runs in your own tenant
A private assistant deployed inside your cloud tenant, under your identity provider, your network controls and your logging.
Your data stays yours
Prompts and documents are never used to train public models, with retention, residency and deletion set by you.
Access control and full audit
Who may use which model, on which data, with every prompt and response logged for review and investigation.
Connected to your systems
Approved integrations to the systems your teams actually use, so answers are grounded in your own information.
How we start
From first workshop to running capability.
- 01
Discovery workshop
Half a day with your team to map the use cases, the data involved and where AI genuinely adds value. You get a prioritised shortlist.
- 02
AI risk and threat model
Structured threat modelling of the chosen use cases against OWASP Top 10 for LLM Applications and MITRE ATLAS. You get findings and required controls.
- 03
Secure design and pilot
We design the architecture, guardrails and integrations, then run a contained pilot with real users and measured results.
- 04
Operate and improve
Controls, logging and review move into daily operations, and the use cases keep improving as the models and threats change.
Utilising AI in cyberdefence
AI that supports the analyst, never replaces the judgement.
Workflow automation
Design and build AI-enhanced security workflows that automate decisions, data processing and response actions across the estate, while keeping governance and human oversight. The value: repeatable work leaves the queue, and specialists keep capacity for the cases that need them.
AI-assisted detection & analysis
Apply AI to improve signal quality, set aside likely noise and identify patterns across large volumes of security telemetry. The value: fewer irrelevant escalations, and a lower chance that a weak signal is missed.
Investigation, enrichment & decision support
Accelerate investigations through automated enrichment, correlation and contextual analysis. The value: a shorter path from signal to a qualified response decision, and the same evidence gathered for every case whoever is on shift.
Threat intelligence & proactive defence
Process and correlate threat intelligence, identify emerging campaigns and support proactive hunting. The value: detection coverage designed to improve from each confirmed incident rather than standing still.
Why context matters
The same capable model makes better decisions with customer context
Without context
No asset, identity or case context
- Generic priority
- Manual review
- Higher uncertainty
With shared context
Shared customer context
- Correct priority
- Clear verdict
- Confident action
Sciber brings shared customer context into agentic triage.
AI usage and sovereignty
Your data, your boundaries, your control.
Sovereignty is a design decision rather than a checkbox exercise. We set the boundaries with you first, then choose the models and architecture that fit inside them.
Data access, residency & retention
Agree what AI may read, where that data is processed and how long it is kept — inside the geographic, legal and contractual boundaries that apply to you.
Model usage & permitted actions
Define guardrails for how AI services, models and agents may be used: access control, approval flows, acceptable use, and which actions AI may take on its own.
Model selection & deployment strategy
Support decisions around public, private and hybrid models, including tenant isolation, customer-managed keys and deployment aligned with sovereignty requirements.
We work against
EU AI ActNIS2OWASP Top 10 for LLM ApplicationsMITRE ATLASISO/IEC 42001Start with a workshop.
Half a day with your team is usually enough to see where AI adds real security value in your organisation — and where it should not be used at all. Detect. Respond. Evolve.