Reference
The terms that run what matters.
A plain-language, bilingual glossary of the cybersecurity and AI terms that come up in board rooms and RFPs — searchable, citable, and always free.
- Zero Trust
- A security model that trusts no user, device, or network by default — every request is authenticated, authorized, and continuously verified, assuming any segment may already be compromised.
- Agentic AI
- AI systems that can plan and take multi-step actions toward a goal — calling tools, querying data, and making decisions — rather than only generating a single response.
- Multi-Factor Authentication (MFA)
- Requiring two or more independent proofs of identity (e.g. password + phone code) so a stolen password alone can't grant access.
- Least Privilege
- Granting each user, service, or process only the minimum access it needs to do its job — limiting the damage if it's compromised.
- Microsegmentation
- Dividing a network into small, isolated zones so that a breach in one area can't move laterally to reach the rest.
- DDoS
- A Distributed Denial-of-Service attack floods a system with traffic from many sources to overwhelm it and force downtime.
- Ransomware
- Malware that encrypts an organization's data and demands payment for the key — increasingly paired with stealing data to add extortion pressure.
- Phishing
- Fraudulent messages that trick people into revealing credentials or running malware, often by impersonating a trusted sender.
- EDR
- Endpoint Detection and Response — software on laptops and servers that detects suspicious behavior and lets teams investigate and contain threats.
- SIEM
- Security Information and Event Management — a platform that aggregates logs across systems to correlate events, detect threats, and support investigations.
- SOC
- Security Operations Center — the team and tooling that monitor, detect, and respond to security threats around the clock.
- Incident Response
- The planned process for detecting, containing, eradicating, and recovering from a security incident — and learning from it afterward.
- Attack Surface
- The total set of points where an attacker could try to enter or extract data — every exposed app, account, device, and integration.
- Encryption at Rest & in Transit
- Protecting data both while stored (at rest) and while moving across networks (in transit) so it's unreadable if intercepted or stolen.
- Large Language Model (LLM)
- An AI model trained on vast text to understand and generate language — the engine behind chat assistants and many agentic systems.
- Retrieval-Augmented Generation (RAG)
- A technique that grounds an AI model's answers in your own documents or data retrieved at query time — improving accuracy and reducing hallucinations.
- Prompt Injection
- An attack where malicious instructions hidden in inputs or documents trick an AI system into ignoring its rules or leaking data.
- Hallucination
- When an AI model produces confident but false or fabricated information — a key risk to control in regulated, high-stakes use.
- KYC
- Know Your Customer — the regulated process of verifying a customer's identity to prevent fraud, money laundering, and illicit financing.
- AML
- Anti-Money Laundering — the controls and monitoring that detect and report attempts to disguise the origins of illicit funds.
- GDPR
- The EU's General Data Protection Regulation — sets strict rules for handling personal data, with fines up to 4% of global revenue or €20M.
- LFPDPPP
- Mexico's federal data-protection law for private parties, governing how personal data is collected, used, and safeguarded, with penalties for breaches.
Want help putting this into practice?
Our team can assess your environment and build the roadmap with you — from first pilot to full rollout.
Book a consultation