LLM security
- Prompt injection
- Indirect prompt injection
- System prompt exposure
- Sensitive information disclosure
- Insecure output handling
LINK AI Security Assessment
Know what your AI can expose. Before someone else does.
A structured, authorised technical assessment for organisations deploying AI-powered applications, LLMs, RAG architectures and AI agents. Tests are selected according to the architecture and the agreed scope.
The business problem
AI systems now sit on documents, customer data, tools and workflows. If access boundaries are weak, an attacker — or simply another user — can reach more than the product was meant to show. The assessment exists to make that exposure visible while you still control the conditions.
Who needs the assessment
- Founders and product teams shipping an AI-powered application.
- CTOs and engineering leaders connecting models to internal data or tools.
- CISOs and security leads who must brief a board on AI risk with evidence.
- Organisations in Morocco and internationally that are moving an AI system from development into production.
AI systems covered
- LLM and generative AI applications
- Chatbots and copilots with access to internal knowledge
- RAG systems and document retrieval pipelines
- AI agents with tools, APIs or workflow permissions
- AI features inside SaaS products
- Internal AI applications
Security domains tested
Applicable tests are chosen after the architecture is understood. The list is a catalogue, not a promise that every item will be executed on every system.
RAG security
- Document access control
- Cross-user and cross-tenant isolation
- Retrieval manipulation
- Document injection
- Unauthorised context retrieval
AI agent security
- Excessive permissions
- Tool misuse
- Unauthorised actions
- Insecure tool integrations
- Agent instruction manipulation
- Weak approval boundaries
Application and API security
- Authentication and authorisation
- API access controls
- Session management
- Insecure integrations
- Data exposure
How we work
Understand. Define. Test. Secure.
01
Understand
Understand the AI system, intended purpose, architecture, data, integrations and security concerns.
02
Define
Agree on written scope, objectives, exclusions, authorisation and rules of engagement.
03
Test
Conduct controlled, evidence-based technical testing within the agreed scope.
04
Secure
Deliver documented findings, technical evidence, impact analysis and prioritised remediation recommendations.
Testing begins only after written authorisation and an agreed scope.
What the client receives
- Executive summary
- Scope and methodology
- Reproducible findings
- Evidence and affected components
- Attack paths
- Severity and business impact
- Prioritised remediation roadmap
- Retest when contractually included
This is not a certification, a guarantee of security, or automatic regulatory compliance.
Flagship offer
LINK AI SECURITY ASSESSMENT
Know what your AI can expose. Before someone else does.
A structured, authorised technical assessment designed to identify exploitable weaknesses in AI-powered applications, LLMs, RAG architectures and AI agents.
A
AI Exposure Review
Initial structured discovery of an AI system’s architecture, access boundaries, data flows and potential security exposure. It is not a full penetration test.
- Who it is for
- Teams deploying or piloting an AI assistant, RAG system or agent who need a first technical picture of exposure.
- What is assessed
- Intended purpose, architecture, data categories, integrations, permissions and the most plausible exposure paths.
- What the client receives
- A written exposure map, priority concerns, and a recommendation on whether a full assessment is warranted.
- What is excluded
- Deep exploitation, guaranteed coverage of every attack class, certification, and any testing outside a written scope.
- How it begins
- A conversation. No production credentials. Testing only after written authorisation.
B
AI Security Assessment
A scoped technical assessment involving applicable attack scenarios, evidence collection, impact analysis and remediation recommendations. This is the primary flagship paid offer.
- Who it is for
- Founders, CTOs, CISOs and engineering leaders putting AI-powered products or internal systems into production.
- What is assessed
- The attack surfaces that apply to the agreed architecture: LLM, RAG, agents, application and API controls as relevant.
- What the client receives
- Executive summary, scope and methodology, reproducible findings, evidence, attack paths, severity, business impact and a prioritised remediation roadmap. Retest when contractually included.
- What is excluded
- Certification, a guarantee of security, automatic regulatory compliance, and unbounded testing.
- How it begins
- Written scope, objectives, exclusions, authorisation and rules of engagement.
C
AI Red Team Engagement
Deeper adversarial testing of complex AI systems, agent workflows, tool integrations and application-level attack paths. The scope must be agreed individually.
- Who it is for
- Organisations with multi-step agents, tool-using systems, or a higher-risk production deployment.
- What is assessed
- Chained attack paths across prompts, retrieval, tools, approvals and the surrounding application.
- What the client receives
- Evidence-backed findings, attack narratives, impact analysis and remediation ordered by risk. Deliverables are defined in the engagement letter.
- What is excluded
- Open-ended testing, production disruption outside the rules of engagement, and any implied certification.
- How it begins
- A scoping discussion to agree systems, environments, limits and authorisation.
Scope and authorisation
- Testing begins only after written authorisation and an agreed scope.
- The public form does not collect passwords, API keys, production credentials, patient information or confidential datasets.
- Technical evidence and access are agreed after qualification, never through the website form.
Questions
- Is this a penetration test of the whole company?
- No. It is a scoped assessment of agreed AI systems and the application surfaces around them. Broader infrastructure testing is a separate cybersecurity engagement.
- Do you certify the system afterwards?
- No. You receive findings and remediation guidance. We do not issue a security certification or a compliance badge.
- When does testing start?
- After both sides agree in writing on scope, objectives, exclusions, authorisation and rules of engagement.
- What if the system is still in development?
- An AI Exposure Review is often the right first step. A full assessment can be scoped against a staging environment.
- Do you publish client names or scores?
- No. Client identities and results are not listed on this website.