Ten core terms that come up constantly in cybersecurity and AI security work, defined in plain language with a link to where each one is covered in more depth on this site.

  • OWASP
    Open Web Application Security Project. A nonprofit that maintains the widely-used OWASP Top 10 — a ranked list of the most critical web application security risks (injection, broken access control, security misconfiguration, and others) — used as a baseline for security assessments and secure development. — Web & API Security Assessment (service) →
  • RAG (Retrieval-Augmented Generation)
    An architecture that connects a language model to an external knowledge source — typically a vector database — so it retrieves relevant documents before generating an answer, grounding responses in real data instead of relying only on what the model memorized during training. — RAG Security (service) →
  • Prompt Injection
    An attack where untrusted input (a message, a document, a tool's output) manipulates a language model into ignoring its original instructions or taking an unintended action. Direct injection comes from user input; indirect injection is hidden inside content the model retrieves or processes. — Prompt Injection and LLM Security (article) →
  • Zero Trust
    A security model built on "never trust, always verify": no user, device, or system is trusted by default, even inside the network perimeter. Access is granted per-request based on identity and context, not network location, and re-verified continuously rather than once at login. — Zero Trust Architecture (article) →
  • AI Agent
    A system that uses a language model to plan and take actions — calling tools, querying data, executing multi-step tasks — rather than only generating a single text response. Security-relevant because agents can take real actions, which makes permission boundaries and human-approval gates for consequential steps essential. — AI Agent Security (service) →
  • SIEM (Security Information and Event Management)
    A platform that aggregates logs and security events from across an organization's systems, correlates them, and surfaces alerts — the operational backbone for detecting and investigating incidents at scale. — Security Audits (service) →
  • SOC (Security Operations Center)
    The team and function responsible for continuously monitoring, detecting, and responding to security incidents — whether that's a dedicated internal team, a managed service, or a single analyst wearing that hat at a small organization. — SOC Analyst Field Notes (article) →
  • Threat Hunting
    Proactively searching for signs of compromise that automated detection missed, rather than waiting for an alert — working from a hypothesis about attacker behavior and looking for evidence that confirms or rules it out. — Threat Analysis (lab section) →
  • Vector Database
    A database optimized for storing and searching high-dimensional embeddings (numeric representations of text, images, or other content) by similarity rather than exact match — the retrieval engine underneath most RAG systems (e.g. pgvector, Pinecone, Qdrant). — RAG Security (service) →
  • Data Protection
    The practices and legal obligations around how personal data is collected, stored, used, and secured — in Kenya, governed primarily by the Data Protection Act (KDPA) and enforced by the Office of the Data Protection Commissioner (ODPC). — Kenya Data Protection Act Developer Checklist (article) →