seQure Ground-Truth™ Available Now as Behavioral Defense Layer for Mythos-Class Cyber Threats

AI-native platform is designed to detect unknown, machine-speed attack behavior in under one second — without relying on signatures, rules, IOCs, or pre-labeled attack data

MIAMI--(BUSINESS WIRE)--seQure, an Entanglement, Inc. company, today announced the expanded availability of Ground-Truth™, an AI-native behavioral cybersecurity platform built to detect unknown and autonomous attack behavior before early signals become enterprise-scale breaches.

Ground-Truth™ is available now for qualified on-premises and cloud deployments, including Oracle Cloud Infrastructure deployment options. The platform is designed for Fortune 100 and Global 2000 enterprises, service providers, governments, financial institutions, and critical infrastructure operators that need a behavioral defense layer engineered for the speed, sovereignty, and scale demands of the AI-era threat environment. Oracle announced in 2025 that governments and enterprises could deploy Ground-Truth on OCI across public, government, sovereign, and dedicated cloud regions, with automated detection of novel threats and vulnerabilities in under one second.

The release comes during what many security leaders are now calling the Mythos moment: the point at which frontier AI has made vulnerability discovery, exploit development, and attack-chain automation materially faster than legacy, human-speed defense models were built to handle.

The question is no longer whether attackers will gain access to AI-speed cyber capability. The question is whether defenders can detect and act before the attack chain completes.

On April 7, Anthropic announced Project Glasswing and Claude Mythos Preview, describing Mythos as its most capable model yet for coding and agentic tasks and saying the model had already identified thousands of zero-day vulnerabilities across critical infrastructure. Anthropic’s technical write-up said Mythos Preview was capable of identifying and exploiting zero-day vulnerabilities in every major operating system and every major web browser when directed to do so, and that most of the vulnerabilities it found remained under responsible disclosure.

The issue has already moved from technical debate to board-level and regulatory concern. CBS News and Reuters reported that Treasury Secretary Scott Bessent and Federal Reserve Chair Jerome Powell convened top bank CEOs to discuss cybersecurity risks posed by Mythos and similar AI models. Reuters also reported that Anthropic limited access to Mythos and that the Treasury-hosted meeting was intended to ensure banks understood the risks and were taking steps to defend their systems.

“Mythos-type attacks represent new superpowers for attackers, Ground-Truth™ is the kryptonite to defend against it. Cybersecurity teams have now entered a world where the first signal may not be a known exploit, malware family, IOC, or policy violation,” said Jason Turner, Chairman of seQure. “The first signal may simply be behavior that does not belong or is designed to look normal. Ground-Truth™ was built for this moment. Rules describe what has already been seen. Ground-Truth™ learns what normal looks like, then identifies what changed.”

What Changed With Mythos

Mythos-class cyber risk is not defined by one model or one vendor. It is defined by a new operational reality: AI systems that can reason across complex software, identify weaknesses, chain steps together, adapt to failed attempts, and accelerate work that previously required elite human expertise.

That changes the defender’s clock.

Traditional security stacks were built for a slower world — one where attackers repeated patterns, signatures could be written, indicators of compromise could be circulated, and human analysts had time to investigate alerts manually. In a Mythos-class environment, waiting for a known exploit name, IOC, malware hash, or manually written rule is not a strategy. It is a delay.

“When the exploit is unknown, behavior becomes the evidence,” Turner said. “Whether the adversary uses a zero-day, stolen credentials, legitimate administrative tools, AI agents, or a multi-step autonomous attack chain, the method is secondary. The behavior is the signal.”

Built for the First Abnormal Move

Ground-Truth™ uses unsupervised behavioral models to learn what normal looks like across protocols, identities, network and VPC flows, endpoints, cloud activity, applications, logs, and graph context. It then scores live behavior against those baselines in real time, turning the first meaningful deviation into a high-confidence signal.

That approach is designed for the specific gaps exposed by Mythos-class threats:

Unknown exploit paths are met with detection that does not require the exploit to have a name.

Living-off-the-land activity is met with behavioral analysis that can surface legitimate tools being used illegitimately.

Autonomous chaining and agent-driven attack paths are met with real-time anomaly clustering across identity, network, endpoint, application, and cloud telemetry.

High-volume alert floods are met with behavioral compression designed to separate operational noise from true changes in risk.

Human-speed response queues are met with sub-second detection and routing into the tools security teams already use.

Proven at Scale

Ground-Truth™ is not a future roadmap. It is deployed technology built for high-scale environments where unknown threats are operational realities.

The underlying Entanglement anomaly-detection technology was evaluated through U.S. Army CRADA work. Public reporting from Groq stated that Entanglement’s Groq-based approach achieved 72 million inferences per second and demonstrated potential to reach 120 million inferences per second across key workloads.

Oracle’s 2025 announcement said Ground-Truth can help automate detection of threats and vulnerabilities, reduce event alerts by 90 percent, support rule-free AI-powered operations, process up to 20TB of data per day, and integrate through APIs with existing security stacks across corporate networks, IoT, SCADA, and operational technology environments.

In one multibillion-dollar satellite-network environment, seQure reports that Ground-Truth™ detected a sophisticated zero-day attack that evaded the existing security stack while reducing approximately 130,000 daily alerts into 60 actionable signals.

“The result is not another dashboard,” Turner said. “Security teams do not need more noise. They need a control layer that compresses detection, triage, and response below the attacker’s loop.”

No Rip-and-Replace

Ground-Truth™ sits above and beside the existing security stack. The platform ingests telemetry from network and VPC flows, cloud trails, endpoint systems, identity platforms, logs, data lakes, applications, protocols, and custom codecs. It then publishes high-confidence action streams into the tools security teams already operate, including SIEM, SOAR, EDR, dashboards, ticketing systems, playbooks, automated-response workflows, and agentic AI security operations.

The platform is designed to help organizations extend existing investments rather than replace them. It provides the behavioral intelligence layer that legacy rule- and signature-based tools were not architected to deliver on their own.

For CISOs, Ground-Truth™ helps close the post-Mythos detection gap. For boards, it supports a defensible AI-era cyber-readiness posture. For operators, it turns overwhelming alert volume into actionable behavioral evidence.

30-Day Behavioral Readiness Assessment for Mythos-Class Threats

In response to the immediate threat environment, seQure is opening a limited number of 30-Day Behavioral Readiness Assessments for Mythos-Class Threats for qualified enterprises, financial institutions, public-sector agencies, cloud operators, service providers, and critical infrastructure organizations.

The assessment is designed to move organizations from uncertainty to operational readiness in four steps:

Days 0–3: Identify crown-jewel systems, critical applications, priority data sources, and high-risk IT, OT, cloud, and identity pathways.

Days 4–10: Connect flows, logs, endpoint, identity, application, and cloud telemetry into the Ground-Truth™ behavioral engine.

Days 11–20: Establish live behavioral baselines and route clustered anomalies into existing SOC workflows.

Days 21–30: Run a Mythos-class readiness exercise and report detection speed, triage quality, alert reduction, and response-cycle compression to executive leadership and the board.

“The worst time to learn what normal behavior looks like is during an attack,” Turner said. “Organizations that establish behavioral baselines now will be in a stronger position to know what changed when AI-speed threats emerge.”

The assessment is designed to answer four board-level questions:

1. Can we detect a Mythos-class attacker without knowing the exploit first?
2. Can we see legitimate tools being used illegitimately?
3. Can we reduce hundreds of thousands of alerts into what actually matters?
4. Can we move from detection to action at machine speed?

A Board-Level Readiness Issue

Ground-Truth™ gives organizations a way to establish that posture now — before the next unknown exploit, before the next autonomous attack chain, and before leadership is forced to ask why the enterprise was still defending at human speed.

The Mythos moment made AI-speed cyber risk visible. Treasury and the Federal Reserve made it board-level. Ground-Truth™ gives institutions a way to act.

Availability

Ground-Truth™ is available now for qualified on-premises and cloud deployments.

seQure is currently accepting qualified organizations for a limited number of 30-Day Behavioral Readiness Assessments for Mythos-Class Threats.

For more information or to begin the assessment, visit www.sequre.ai.

About seQure

seQure, an Entanglement company, delivers AI-era behavioral network and cybersecurity solution for Fortune 100 / Global 200, Governments, Service Providers, Data Centers, and Critical Infrastructure organizations facing machine-speed threats. Its flagship platform, Ground-Truth™, uses unsupervised behavioral baselines, high-dimensional correlation, graph context, and real-time inference to detect unknown threats without depending on signatures, rules, indicators of compromise, or pre-labeled attack data.

Ground-Truth™ is designed to ingest broadly, detect in real time, and publish high-confidence actions into the security tools enterprises already operate. DCAP is its Data Center Awareness Platform designed to detect the most sophisticated cross-domain threats faced by data centers through the convergence OT, IoT, and IT.