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CYBERSECURITY
LLM and AI application security
We secure your AI applications and systems: adversarial testing (red teaming), prompt injection mitigation and hardening of the model supply chain.
LLM and AI application security
LLM security matters when you need to protect applications that use language models from specific attacks, not a traditional network audit. Before selecting tools, we define the journeys, data and decisions that must remain under your company's control.
We work from Barcelona and Madrid and remotely with teams across Spain, Europe, LATAM and the United States. The process combines decision sessions, verifiable releases and documentation so progress stays visible.
We hand over code, repositories, configurations and documentation in accounts owned by your company. You can therefore audit, evolve or change supplier without relying on private access or licences.
We secure your AI applications and systems: adversarial testing (red teaming), prompt injection mitigation and hardening of the model supply chain. That is why we prioritise a maintainable, measurable solution ready to evolve without rebuilding its foundations.
THE CHALLENGE
The challenge of LLM security
language models open new attack paths
Sensitive data sent to the model
Employees paste confidential information into prompts without control. The data leaves the company without leaving a trace.
Hallucinations reaching the customer
The model confidently answers with invented or outdated information. The error spreads before it is detected.
Prompts manipulated by third parties
Prompt injection can make the model ignore its rules. An attacker conditions the system's responses.
APPROACH
How we fix protecting AI applications in production
We move forward with measurable decisions and releases that already add value.
Usage policy and allowed data
We define what information can enter each prompt and what stays blocked. The rules are applied at technical level.
Output validation barriers
We review each response before it reaches the end user or customer. The filter detects unauthorized content.
Instruction and context control
We separate the system from external inputs to neutralize injections. The model only acts within its limits.
Conversation logging and audit
We store interactions with traceability to review incidents. Each decision is documented and recoverable.
DELIVERABLES
What LLM security leaves ready
We deliver an operational foundation your team can govern and keep improving.
Internal LLM usage policy
Document with data limits, roles and responsibilities for the whole team.
Response validation layer
Filter that blocks or reviews sensitive outputs before delivery to the user.
Anti-injection configuration
Separation of system and external instructions applied over the production model.
Auditable interaction log
Traceability system with the full history of prompts and responses for audit.
TRUST
Technology applied to real operations
We apply AI security criteria aligned with the OWASP Top 10 for LLM and ENS where required.
- Scope, assumptions and risks visible before the project is committed.
- Integrations, permissions and data designed for real operations.
- Reviewable releases before the solution reaches the whole organisation.
- Code, configuration and documentation under your company's control.
FAQ
Questions about LLM security for business
Have a project in mind?
Tell us what you need around LLM security for business. We will help you turn it into a clear, viable delivery plan.
