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21/08/2026 4:44 pm
TL;DR: “AI security” still spans multiple disciplines without a shared operating vocabulary, while prompt injection has emerged as the common failure pattern across browser agents, coding agents, and MCP-connected systems, according to Impart. The practical divide is no longer detection alone but whether controls can stop unsafe actions before a request completes.
NHIMG editorial — based on content published by Impart: AI Security Still Doesn't Have a Shared Vocabulary. Prompt Injection Does
Questions worth separating out
Q: How should security teams govern AI agents that can choose tools at runtime?
A: Security teams should govern runtime agent choice as an access event, not as a simple application action.
Q: Why do prompt injections matter so much in AI security programmes?
A: They matter because they exploit a trust failure, not just a content issue.
Q: How do you know whether AI observability is actually reducing risk?
A: Look for evidence that the programme can stop unsafe actions, not only reconstruct them.
Practitioner guidance
- Define instruction boundary enforcement Classify which inputs an agent may read, which it may treat as instructions, and which must remain data only.
- Add runtime stop points before tool execution Require an allow, deny, or constrain decision at the point where an agent is about to call a tool.
- Scope MCP integrations to least privilege Treat each MCP server or connector as a privileged integration.
What's in the full article
Impart's full blog post covers the operational detail this post intentionally leaves for the source:
- How the vendor distinguishes AI gateways, AI firewalls, browser agent security, and MCP security in practice
- The specific runtime enforcement approach it argues is needed before a request completes
- Examples from Black Hat and Ai4 conversations that show how buyers are framing the problem
- The vendor’s own view of where visibility stops and blocking begins
👉 Read Impart's analysis of AI security vocabulary and prompt injection risk →
Prompt injection is the common AI security failure teams are missing?
Explore further
21/08/2026 5:04 pm
Prompt injection is the category’s shared failure mode, not just one more AI bug. The article is right to collapse browser agents, coding agents, and MCP-connected workflows into a single control problem. The delivery mechanism changes, but the underlying issue is the same: a system built to follow instructions cannot reliably separate instruction from untrusted content. That makes prompt injection the most citable security concept in this space, and it should be used as the anchor for policy design, red teaming, and architecture reviews.
A question worth separating out:
Q: What is the difference between monitoring AI behaviour and controlling it?
A: Monitoring tells you what happened after the fact. Controlling means the environment can prevent, limit, or redirect the action before it completes. In practice, that difference determines whether the organisation has a forensic capability or a true enforcement boundary for AI-driven workflows.
👉 Read our full editorial: AI security still lacks a shared vocabulary, but prompt injection does
