Real-time Threat Detection
Detect and disrupt adversaries before they reach their objective.
You can't prevent every breach. But you can prevent the breach from becoming a business-impacting attack.
Take the product tour- Detect behaviours.
- Trace the origin.
- Disrupt the attack.
- Automatically.
Prevention eventually fails. Nodal is built for what happens next.
Modern security stacks are built to prevent compromise. But prevention eventually fails: through stolen credentials, vulnerabilities found by AI, supply-chain compromise, or simply brute force. Nodal detects and protects against what happens immediately next.
The window between compromise and impact is shrinking.
Attackers no longer need to spend days manually navigating an environment in preparation for an attack. Attackers are increasingly using automation, living-off-the-land techniques and AI-assisted tooling to accelerate reconnaissance, lateral movement, collection, exfiltration and exploitation.
Why should it take days to correlate evidence, decide and act?
The traditional question
Can we prevent the breach?
The modern question
How quickly can we detect and contain an attacker once they are inside?
As attackers automate more of the intrusion lifecycle, the time available to detect, investigate and decide can shrink dramatically. Nodal is built for what happens after the breach, and for disrupting the attack.
Minutes to seconds.
We have collapsed response from minutes to seconds: from detection to the command-and-control channel cut, with no queue in between.
From signals to containment.
Nodal turns fragmented security signals into a single understanding of the attack, then acts on it.
01 · detect
Detect where security is often blind
Nodal analyses east-west activity between systems and correlates it with north-south traffic to find a wide range of suspicious behaviour. Its engine understands relationships between devices, connections, timing and attacker techniques, not isolated events.
02 · correlate
Correlate detections into one story
Single signals rarely tell the whole story, and fragmented detections fly under the radar because none of them reaches an alert threshold. Nodal combines its own device-level detections with activity across other devices and detections from your integrated tools, and consolidates them into a few investigation cases under one ticket.
03 · trace
Trace the origin of commands
When suspicious activity is detected, Nodal reconstructs at machine speed the communication paths behind it, across one or many internal devices, to find where the activity started and which systems are involved. The Nodal Agent, or a capable integrated EDR, adds process-level attribution that surfaces the whole attack pathway and its command-and-control infrastructure.
04 · disrupt
Disrupt the command-and-control
When a malicious path is identified, Nodal can safely and dynamically block the connection between the edge device and the external host, cutting the attacker's ability to run commands and take data out.
05 · contain
Contain the insider threat
If an edge block is not enough, or when the threat is already inside, Nodal monitors and contains continued activity across the identified devices.
06 · investigate
Investigate, report and improve resilience
Nodal's AI investigation agent analyses the detections, the history and the reconstructed attack chain to explain what happened and assess the threat, then gives the analyst next steps in one consolidated ticket, saving time when it matters most.
Turn low-level network signals into high-fidelity detections.
Nodal Probes and Agents analyze network activity at the edge and transform raw communication into security-relevant signals. Nodal's detection engine continuously correlates these signals across devices, connections and time, identifying behaviors such as network discovery, worm propagation, brute-force attempts, lateral movement, command-and-control, data staging, exfiltration and network impersonation.
01 · Signals
A probe reads packets at line rate
Traffic between devices becomes discrete network signals, each one small and on its own unremarkable.
02 · Behaviours
Rules corroborate signals through time
The rules engine takes in the stream of signals and connects them over time, following the loaded rules, into higher-fidelity behaviours.
- Outbound packet on a new flow, no reply
- TCP half-open to a new port
- High egress along a flow
- Session-like exchange between two endpoints
inferred by a proprietary pre-trained model
Illustrative: which signals feed which behaviour is set by the rules.
03 · Supporting
Surprise, per device
Behavioral detection is complemented by Nodal's per-device behavioral learning, which evaluates how surprising an event is for that specific device, providing additional context around expected and anomalous behavior.
04 · Supporting
Rules that model behaviour, not bytes
Nodal's proprietary detection language makes temporal correlation, entity relationships and behavioral chaining native to the detection engine, allowing complex attack sequences to be identified directly from streaming network activity or replayed packet captures. This enables Nodal to join weak signals into higher-fidelity behavioral detections and encode specialized detection logic for environments where generic rules are not enough.
| YARA | Nodal rules | |
|---|---|---|
| Input | YARA · A static blob: a file, memory image or process | Nodal rules · A live stream of network events, with source, destination and ports |
| Question | YARA · Does this artefact contain these byte or string patterns? | Nodal rules · Did these behaviours happen, in this order, within these time windows, between these hosts? |
| Time | YARA · None: the whole input is evaluated at once | Nodal rules · Central: counts within windows, sequences, debouncing, sliding windows |
| State | YARA · Stateless, per scan | Nodal rules · Stateful: per-host buffers, counts and sequences that can stay open for minutes |
| Correlation | YARA · A condition over string hits in one file | Nodal rules · Joins across events and hosts: a sweep tied to a later scan by the same source |
| Output | YARA · Match or no match, and which strings hit | Nodal rules · A raise naming which host played which role, with a weight and the evidence events |
| Typical use | YARA · Malware classification, IOC hunting, file triage | Nodal rules · Multi-step intrusions: reconnaissance, access, pivot, exfiltration |
YARA tells you a file is Cobalt Strike. A Nodal rule tells you host A swept the segment, port-scanned B ten minutes later, and that B is now relaying an interactive session onward.
The closer relative is YARA-L (Google SecOps), which also works over time across logs. Nodal rules stream in real time from a network tap or a PCAP replay, with raising entities and native chaining built into the language.
Once an attacker breaches the perimeter, the threat is effectively an insider threat, whether it is a human or an AI agent.
The network is the high ground.
Attacks from outside become insider threats.
- Observe east-west
- Detect
- Disrupt
An outside attack that gets through stops being an outside attack. It now operates as an insider, with insider access.
Explore the rest of the Nodal platform.
See it on your traffic
Watch CyberBrain reconstruct a live attack chain.
A 30-minute technical walkthrough on sanitised threat data — or a proof of concept in your own environment. No agents required to evaluate.