Detecting Agentic AI Attacks Inside Your Network

Two complementary layers give you a signal early enough to matter, and clean enough to go straight to the top of the queue. One watches everything moving inside your network. The other plants assets only an intruder would touch.
Detecting Agentic AI Attacks Inside Your Network

Promotional Content · Hyprfire · Labyrinth · Solution Brief

Why You Need to Update Your Defences

Your defences are too slow against agentic AI attacks. Most security architecture assumes an intruder who moves at a human pace. Agentic AI changes that pace: it runs attacks concurrently, enumerates, tests what it finds, and goes deeper without pausing between steps. An intruder's decision time between one step and the next goes to zero. Your defences have to answer at that new pace.


Signature Updates and Manual Triage Are Too Slow

Signature updates take too long. A signature turns up after somebody else has already been hit. Against an AI agent that varies its behaviour on each attempt, no update cadence closes that gap.

Manual alert triage is noisy and slow. A queue works when the queue moves faster than the attacker. A queue is also one thing at a time, and an agent is not. It probes in parallel and never waits. You are answering a concurrent attacker with a serial process, and all you have left is a record of what happened.

Complementary Capabilities to Counter Agentic AI Attacks

There are two capabilities that complement each other:

  • Visibility of what is moving inside your network in real time, because that is where an agent does its work and it is the traffic almost nobody watches.
  • High-confidence, genuine alerts you can prioritise without spending forty minutes proving them.

Hyprfire covers visibility. Labyrinth covers genuine alerts.

Hyprfire Watches the Traffic Itself

Hyprfire's Firebug is a managed network detection and response (NDR) service that watches the traffic between your systems, the east-west or lateral traffic. It uses statistical analysis, not a rulebook, to monitor that traffic. It does not require deep packet inspection and reads only metadata, so it works on encrypted traffic too. It baselines your environment within hours once set up, then flags what departs from that baseline. An AI agent moving laterally does not need to be recognised as a known threat. It only has to look unusual for your network.

Read the full article: Monitor Internal Network Traffic with Firebug, Including Encrypted Traffic

Labyrinth Makes the Network Answer Back

Labyrinth plants decoys across your network: machines that look like file servers, credentials that look valid, documents that look worth taking. They are indistinguishable from the real assets around them. No legitimate traffic has any reason to touch one. No scoring, no thresholds, just a high-signal, low-noise alert if one is touched. With decoys in place, the speed and thoroughness of an agent's reconnaissance become a liability to it.

Read the full article: When Faking It Produces High-Signal, Low-Noise Security Alerts

Why You Want Both Hyprfire and Labyrinth

Running both gives you two independent signals that push an alert straight to the top of the queue.

  • Hyprfire tells you that something in your environment is behaving out of the ordinary across your internal network traffic.
  • Labyrinth tells you that something just touched an asset only an intruder would touch, at a specific host, at a specific time.

The speed and thoroughness that make an autonomous AI agent hard to stop are the same qualities that walk it into a decoy and into the network record. These tools are not specific to AI. They work on human threats too: an insider accessing areas they shouldn't, or an intruder using stolen credentials to look around. A tripped decoy means activity where there should be none, and unusual traffic looks unusual whoever is generating it.

A Quick Word on the Standards

Detection obligations in Australia assume you can see inside your own environment.

None of these prescribe a product, so it is up to you to determine the best solution for your environment.

Where to Start

Ask how long an intruder could move inside your network before anything flagged it. If the answer is days, or you cannot say, that is the gap these two layers close.

Contact OneDot61

Hyprfire website

Labyrinth website

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