Security for a future where
attackers use frontier AI

Security used to mean patching servers, scanning for known issues, and hoping your controls held. That is no longer enough. As frontier models become more capable, attackers can use them to reason through your systems, identify misconfigurations, craft targeted exploits, and find paths into sensitive data faster than manual testing ever could.

Addbox helps businesses stay ahead by using the same generation of models defensively. We analyse your websites, applications, APIs, and data exposure points, then maintain periodic protection that is refreshed whenever major LLMs from OpenAI, Anthropic, Google, Meta, and others release new capabilities that could change the attack surface.

The new threat landscape

Attackers no longer rely only on scripted tools and known exploit lists. Frontier models can help them understand your stack, interpret error messages, chain vulnerabilities together, and adapt their approach in real time.

• Automated reasoning through application logic to find bypasses
• Faster discovery of exposed endpoints, credentials, and misconfigurations
• Targeted social engineering and phishing built from public information
• Analysis of source code, documentation leaks, and API behaviour
• Identification of data exposure paths that traditional scans miss
• Continuous adaptation as new model capabilities unlock new attack methods

The risk is not hypothetical. Each major model release can shift what is possible for both defenders and attackers. Businesses that only test once a year, or rely on last year's tooling, are defending against yesterday's threats.

Why traditional security is not enough

Conventional audits and automated scanners still matter, but they were built for a different era. They excel at known patterns, not novel reasoning against your specific environment.

• Annual pentests capture a point in time, not an evolving threat model
• Scanner results often miss business logic and contextual weaknesses
• Security teams are overwhelmed by alerts with limited prioritisation
• Cloud, SaaS, and AI integrations expand the surface area faster than reviews keep up
• Internal teams may not have access to the latest frontier models used by attackers
• Compliance checklists do not guarantee protection against AI-assisted exploitation

You need security that evolves at the same pace as the models driving the next wave of attacks.

Periodic protection with each model release

Our core approach is model-release protection: a structured review cycle tied to major frontier LLM updates across the leading providers. When capabilities change, so does the way systems can be probed, manipulated, or exposed.

With each cycle, we:

• Re-analyse your environment using the latest frontier models available
• Test for newly possible attack paths introduced by improved reasoning or tooling
• Review prior findings to confirm fixes hold under stronger adversarial analysis
• Update hardening recommendations, monitoring rules, and response playbooks
• Prioritise gaps by exploitability, data sensitivity, and business impact
• Deliver a clear report your leadership and technical teams can act on

This is not a one-off audit. It is ongoing protection designed for a world where the tools available to attackers improve several times a year.

What we analyse

We assess the places where AI-assisted attackers are most likely to find a way in, and where a successful breach would cause the most damage.

• Websites, web applications, and customer-facing portals
• APIs, integrations, and authentication flows
• Cloud infrastructure, access controls, and permission models
• Data exposure, storage practices, and backup visibility
• Third-party services, webhooks, and supply chain connections
• AI features in your own products, including prompt and data leakage risks
• Internal tools, admin panels, and privileged account pathways
• Monitoring gaps that would delay detection of a breach

The goal is to expose gaps before they are exploited, with practical fixes rather than theoretical risk registers that never get addressed.

How we use frontier models defensively

We use frontier LLMs as part of a disciplined security process, not as a replacement for expert judgement. Models help us explore attack paths, interpret complex systems, and stress-test assumptions at scale. Humans validate findings, eliminate false positives, and define remediation.

Our defensive use of AI includes:

• Multi-model analysis across major LLM providers to reduce blind spots
• Adversarial reasoning against application logic and access controls
• Review of code, configuration, and architecture for exploitable patterns
• Simulation of attacker workflows that combine reconnaissance and exploitation
• Prioritisation of findings based on real-world exploitability
• Clear remediation guidance your development team can implement

If attackers are using the best models available, your defences should be tested with the same standard.

What we cover

Model-release protection sits alongside the security fundamentals every business still needs. We help you build and maintain a complete programme, not just a report.

• Frontier model vulnerability analysis
• Periodic protection cycles aligned to major LLM releases
• Security audits and penetration testing
• Application, API, and infrastructure hardening
• SSL, access control, and configuration review
• Monitoring, alerting, and detection improvements
• Incident response planning and breach support
• Compliance guidance for GDPR, ISO, and sector-specific requirements
• Remediation support through our development team when needed

How it works

1. We scope your environment, data sensitivity, and existing security controls.
2. We run an initial frontier-model-assisted analysis to establish a baseline.
3. We deliver prioritised findings with clear remediation steps and ownership.
4. We support fixes, retesting, and hardening across your stack.
5. We repeat the analysis on each major frontier model release cycle.
6. We update protections, monitoring, and guidance as the threat landscape shifts.

Why Addbox?

Most security providers still sell annual scans and generic checklists. We built our approach for the reality that AI is now part of the attack toolkit.

Stay ahead of AI-assisted attacks

Working with Addbox on security means:

• Protection tested with the same class of models attackers are using
• Regular reassessment as frontier LLMs release new capabilities
• Faster discovery of gaps in applications, APIs, and data exposure
• Clear prioritisation so your team fixes what matters first
• Reduced risk of breach, downtime, and reputational damage
• Stronger confidence for customers, investors, and compliance reviews
• Security connected to development, AI strategy, and infrastructure work
• A partner that understands both offensive reasoning and practical remediation