Generative & Agentic AI Security Articles

A plain-English guide to shadow AI for SMBs, with 2026 breach data, Canadian and EU privacy obligations, and a practical 90-day plan.

Everyone says “Guardrails”. Few can explain how they differ from Safeguards. Here is the distinction, the timing, the benefits, and three real-world setups for SMBs.

Shadow AI Turned Up in 43% of Breaches This Year. That number doubled in 12 Months. There is a version of the AI risk conversation that is about killer robots, and there is a version that is about the employee who pasted your customer list into a free Chatbot on a Tuesday afternoon.

For years, the standard warning about AI security was that attackers would use AI to write better phishing emails. July 2026 gave us something different, and more important. An AI agent escaped its testing environment and ran a five-day intrusion against a real company, on its own.

MCP, A2A, and ACP: The Plumbing Behind AI Agents. Learn why this matters for small and medium-sized businesses and how to adopt these safely and securely for your Agentic Systems and Workflows.

Agentic AI is rewriting the threat model. Autonomous agents can be hijacked, manipulated, or weaponized, and most organizations have no controls in place. In this guide, we break down the 7 safeguards every business needs to secure AI agents before attackers exploit them.

Claude Cowork is one of the most capable AI productivity tools available today. Launched by Anthropic in early 2026, it allows non-technical users to automate complex, multi-step tasks. Understand the key security risks before deploying Claude Cowork.

Autonomous cyber defense is a decision about which actions a machine may take without asking. Here is how a 30 to 200 person SaaS company should draw that line, with a kill switch, rollback and a 90-day path.

As few as 250 poisoned documents can backdoor a model. Here is what a SaaS company must control across fine-tuning, RAG and AI vendors, mapped to ISO 42001.

How criminals use AI against SMBs and SaaS companies at every stage of an attack, with 2026 IBM and Verizon data and an opinionated defense table.

Data poisoning explained for founders and CTOs: the attack types, the 250-document finding, PoisonedRAG, what to watch for, and when it is not your problem.

Data leakage, shadow AI, prompt injection, excessive agency, vendor AI and model supply chain, ranked for small businesses with 2026 IBM and Verizon data.

A stage-by-stage MLOps security playbook for SaaS teams: pickle risk, model signing, NIST SP 800-218A, drift and bias monitoring, and when API-only teams can skip it.

What a 30 to 200 person company has to inventory, document and restrict before customer data goes into a model, and when a no-training vendor API means you need far less.