Spyderbat Echo · Cloud Detection & Response for Linux and Kubernetes

Echo: The First AI SOC Platform Purpose-Built for Linux and Kubernetes. From Kernel to Verdict.

Runtime detection and response for Linux, Kubernetes and cloud, with AI agents that run your Level 1 and Level 2 security operations. Echo's eBPF agent records every process and connection as it happens. With that full context, Echo's AI catches what other tools miss, screens out false positives, stops attacks in progress, and sends your team only what needs their attention.

Last 24 HoursSpyderbat's Own Environment
The Power of Echo
Events recorded260.4M
↓ causal graph · signals · traces · prioritize
Cases for AI triage8.4K
↓ L1 AI triage agent → L2 AI analysis agent
Verdicts for a person1
Trusted by Security Teams At
NTT DataRakuten MobileWilliam BlairAGTEcoGobierno de Río NegroLatinex
Cloud Security Startup of the Year · CyberSecurity Breakthrough Awards

For SOC teams, CISOs, telecom operators, IBM Power shops, MDRs, MSSPs, government, and anyone who has to prove what happened.

Why Context Matters

Your Analysts Live in Noise. Echo Starts From the Whole Story.

A SOC analyst's day is thousands of alerts, most of them false positives, each a fragment to piece together from logs and consoles. Echo doesn't start from alerts. It starts from the complete causal chain, so there is nothing to piece together and nothing to guess.

An Analyst's Queue Today

14:02HIGHSuspicious outbound connection · ip-10-0-3-17
14:02MEDProcess anomaly · web-7f9c
14:03LOWDNS request to rare domain
14:03HIGHSuspicious outbound connection · ip-10-0-3-17
14:04MEDSensitive file access · /etc/*
… 2,316 more in queue

❑Are these related? Who started it? Which pod? Was it a routine release? An analyst has to piece it together by hand, and an AI reading the same alerts has to guess.

What Echo Reads

user contractor-17 (ssh, 13:58) └ kubectl exec web-7f9c · ns prod └ nginx worker pid 4127 └ bash -i ! shell from web server ├ dns rare-domain.example ├ connect 203.0.113.44:4444 └ open /etc/shadow ! credential access 5 alerts → 1 trace · risk 8.6 · 0 gaps

✓The same activity, recorded as it happened and linked by cause and effect. Echo reasons over facts, and you can check each one.

AI models are becoming a commodity. Complete, causal runtime data is not.

The Vision

An AI Is Only as Good as Its Data.

The Insight

Traditional security tools see only part of the picture, leading to missed attacks, false positives, and immense work for incident response. With complete, audit-quality ground truth data, linked by cause and effect, an AI can automatically work out what actually happened.

The Vision

Turn that insight into a real-time system that gathers the data, links it by cause, identifies suspicious activity, and uses AI to decide whether it is malicious.

The Hard Part

Record every process, connection, and file access across thousands of hosts in an enterprise, link it into a massive graph that captures context around events, and store it for 90 days, keeping host CPU consumption under 2%.

The Models

Use cost-effective, local AI models that understand Linux, Kubernetes and cloud systems to do expert SOC analysis.

Now: Echo

The first AI SOC Platform to realize the vision.

No Signal Switched Off

Other Tools Turn Signals Off So Humans Can Keep Up. Echo Keeps Them On.

An attack rarely starts with the damage. After initial access, which may come through a known exploit, a zero-day with no signature, or quietly abused credentials, attackers look around. They run reconnaissance, escalate privileges, set up persistence and make small lateral moves. Only later do they act on their objectives.

Detections for that middle stretch exist, but they are noisy and hard to tune, so SOC teams turn them off or learn to ignore them. Most tools catch an attack at the front door, if the exploit is known, or at the end, when the damage is already under way.

Signals only overwhelm a SOC when people have to read them. Echo's AI agents review every one with full causal context, keep the middle-stage signals on, and link them into one trace, so Echo can respond before the attacker reaches their goal.

What Gets Seen, Stage by Stage
Known exploitZero-day (no signature)Credential misuse
Blocked, if knownRead and linked
Account and host enumerationUnusual DNS lookupsPort scan from a pod
Switched off or ignoredRead and linked
sudo misusesetuid binary run
Switched off or ignoredRead and linkedEcho responds here
New cron jobModified system service
Switched off or ignoredRead and linked
SSH to a new hostkubectl exec into another pod
Switched off or ignoredRead and linked
Data leaving the networkCrypto minerRansomware
Alerted, damage under wayRead and linked
Most tools see the start and the end. The middle, where attackers spend most of their time, goes dark.Echo reads every stage and links the signals into one trace, so it can respond early in the attack. Illustrative · MITRE ATT&CK tactics
How Echo Works

Watching Every Event. Surfacing the Activity That Matters.

Echo is a real-time system, not a batch job. Each event updates the causal graph the moment it happens, and every stage after it runs continuously.

Pipeline Funnel · Last 24 Hours · Spyderbat's Own EnvironmentStreaming
64.2MProcesses
196.2MConnections
3.3KOther security tools
7.8MFlagged
247MNot flagged
4.8MTraces
2.3MNo trace
425KKnown-normal (your rules)
4.2MBelow thresholdKept, rescored if new activity connects
145KMatches a past benign case
8.4KCases
8.4KL1 AI triage agent
12L2 AI analysis agent
8.4KAuto-closed
1To a person
Hover a stage below to see where it happens.Collect · 260M eventsAll 260M events linked, flagged or not.Signals · 7.8M flaggedTraces · 4.8M tracesPrioritize · 8.4K casesL1 AI triage agent · 8.4K reviewedL2 AI analysis agent · 12 investigated → 1 to a person Hatched = set aside automatically, and kept
Last 24 Hours · Spyderbat's Own Environment
260.4M
Events recorded and causally linked
7.8M
Flagged as signals
4.8M
Linked into traces
8.4K
Cases reviewed by the L1 AI triage agent
12
Investigated by the L2 AI analysis agent
1
Verdicts for a person
1
Collect260M events
The eBPF agent records every process and connection on every workload. Echo adds findings from Kubernetes, the cloud and your other security tools.
2
Causal connectionsevery event linked
Each record is linked to what caused it and what it caused, the moment it arrives, across hosts and containers, no matter how much time passes between them.
3
Signals7.8M flagged
Behavior-based detections across users, processes, workloads and network activity are overlaid on the causal graph in real time. None are switched off to spare analysts.
4
Traces4.8M traces
Causally connected signals become one trace across processes, containers, nodes and identities. Traces are scored by risk and stay open for up to 90 days, so a later signal can still join an earlier one. You always know who did what, when and where.
5
Prioritize8.4K cases
Traces that match your known-normal rules or a past benign case are set aside. Low-risk traces are kept and rescored if new activity connects to them. The rest become cases.
6
L1 AI triage agent8.4K reviewed
Reviews every case. Closes what is benign, with its reasoning attached, and escalates the rest to the L2 AI analysis agent.
7
L2 AI analysis agent12 investigated → 1 to a person
Investigates in depth and delivers a finished, audit-ready case: verdict, assessed impact, recommendations and automated actions.
Automated L1 + L2

Level 1 and Level 2, Done. Your Team Starts at the Answer.

L1 AI triage agentReviews every case with Linux and Kubernetes attack expertise. Closes what is benign, with its reasoning attached. Escalates the rest to the L2 AI analysis agent.
L2 AI analysis agentInvestigates each escalation in depth, with the full telemetry for that case, and delivers a finished, audit-ready case.
Your teamReviews verdict and confidence, assessed impact, recommendations, automated actions taken or proposed, what Echo is unsure about, and the full causal trace behind every claim. Every case Echo closes is kept with its reasoning. Reopen any of them, overturn the verdict, and Echo learns from it.
CASE 20417 · prod-east · web-7f9cReverse Shell From Web Container
Needs your team
Verdict · confidence high

Malicious. contractor-17 opened an interactive shell inside web-7f9c through kubectl exec, connected out to an unrecognized host and tried to read /etc/shadow. No release or change ticket matches.

Assessed impactContained to one pod. No lateral movement. Credential read attempted, no follow-on use seen.
Automated actions✓ Blocked 203.0.113.44
✓ Killed pod; cluster self-healed
Recommendations❑ Suspend contractor-17's cluster access
❑ Rotate the web-7f9c service-account token
What Echo is unsure aboutWhether contractor-17's credentials were stolen or used by the contractor directly.
Timeline2m 44s
Detected14:04:07
L1 AI triage14:04:31
L2 AI analysis14:05:40
Your team14:06:51
"It's like magic. Echo hands our analysts an audit-ready report backed by a complete dossier on the attacker activity."
SOC Manager, Fortune 500 financial services
From the Field

Five Days of Guessing With Other Tools. Minutes to Evidence With Spyderbat.

An overnight outage took a customer's Kubernetes cluster offline when TLS connections started failing. Splunk, Datadog and their EDR showed nothing useful. After five days of troubleshooting, and a contractor denying any change, DevOps escalated to security.

Within Minutes, Spyderbat Showed

✓The exact script that ran
✓The user who ran it
✓That it changed the system time
✓That it didn't follow approved instructions
✓A full execution timeline
"Spyderbat has distinct components that allow you to see things as they were, as they are, and how they should be."
Gestalt IT
"Spyderbat is an amazing option for companies looking for rich Kubernetes specific runtime protection."
James Berthoty, DevSecOps
Trusted by Security Teams At
What Only Echo Does

An AI SOC Platform That Owns Its Data and Acts on It.

Ground truth, owned

Kernel-Level Data You Control

Every user and system action, visualized and instantly replayable, for 90 days.

Stops attacks early

Caught While They Unfold

Insider abuse, misconfiguration, zero-days and known vulnerabilities, detected and answered while the attack is still unfolding.

Acts on its own

Guardrails and Automated Response

Learns each application's normal behavior and blocks drift. Built-in and custom actions block IPs or kill pods so the cluster self-heals.

Far fewer alerts

1 in 260 Million Reached a Person

That was one day in our own environment. Everything else was triaged, investigated or set aside automatically.

Private and Open

Your Data Stays Yours. Deploy Where You Want.

1
Echo never sends your data to public AI models.Every model it runs is private. Your data never leaves your Echo environment, whether that's the Spyderbat cloud, your private cloud or on-prem, and is never used to train models.
2
Any environmentRun Echo in the Spyderbat cloud, your private cloud, on-premise or air-gapped. RHEL, Ubuntu, Amazon Linux, Debian, Rocky and more, on x86, ARM and IBM Power.
3
Costs under controlSpyderbat built its own AI technology to keep your data private and your costs low, so reviewing every signal never turns into a runaway AI bill. Echo is priced per node, alongside the Spyderbat platform.
4
Open to your AIRaw and processed data through open access, to feed your own AI engines with the same ground truth Echo uses.
<2%CPU overhead from the eBPF agent
Minutesto install, on a cluster or a single host
SOC 2Type II certified
Purpose-Built

Echo Is the AI SOC Platform, Purpose-Built for Linux and Kubernetes.

Most security expertise, and most security tooling, grew up on Windows endpoints. Echo was built for the infrastructure modern businesses actually run on: Linux servers, the Kubernetes clusters built on them, and the cloud they run in.

Linux

Every Server, Bare Metal to Cloud

RHEL, Ubuntu, Amazon Linux, Debian, Rocky and more, on x86, ARM and IBM Power.

Kubernetes

Clusters, Pods and Control Plane

Follow an attack across VMs, pods, namespaces and nodes, back to the workload and the person or process that started it.

Cloud

AWS, Hybrid and Multi-Cloud

Runtime activity joined with cloud context such as IAM roles and tags.

AI workloads

The AI You're Putting Into Production

Model servers, agents and pipelines run on Linux and Kubernetes too. See every process, file and connection an agent touches.

Spyderbat

The Best Test Is Your Own Data.

1
InstallThe eBPF agent installs in minutes, on a cluster or a single host.
2
Watch it buildSee the causal graph of your workloads fill in, live.
3
Read Echo's first casesFinished investigations from your own environment.