Beyond the buzzword.
This is a real adversary.
Most tools bolt AI onto a scanner. SpartanX is The Ultimate Adversary™, built from the ground up: a coordinated swarm that reasons, adapts, and turns your security intent into validated outcomes, at machine speed and under human oversight and guardrails.
Agents that don't assist. They execute.
A scanner that uses AI to summarize results is still a scanner. A chatbot that answers CVE questions is still reactive. SpartanX was designed as something different: a platform where agents carry out the attack, under your control. That required solving three hard problems together.
Deep context
Precise reasoning
Coordinated action
An ontology-driven knowledge graph, not a generic LLM.
A generic model knows security in the abstract. It does not know that your payment gateway runs on a specific server, processes cardholder data, and connects to three downstream APIs. The OKEG (Ontology-driven Knowledge Enterprise Graph) fuses two knowledge systems into one intelligence layer every agent queries in real time.
Your enterprise context
A living map of your assets, repositories, applications, user roles, data flows, and the relationships between them. An agent sees a business-critical application processing sensitive data, not an isolated finding.
Decades of cyber domain knowledge
MITRE ATT&CK, CVEs, EPSS, CWE, OWASP, and compliance standards, encoded into a machine-readable graph agents query during every operation.
Why it matters: the OKEG turns generic AI into a context-aware expert, so an agent understands not just what a vulnerability is, but what it means for your business, who is affected, and what the real exploitation path looks like.
Every agent gets a mission briefing, not a prompt.
The difference between a useful AI and a hallucinating one is the quality of its instructions. Rather than asking a model "is this code vulnerable," the inference engine queries the OKEG to construct a multi-layered brief for every operation.
Every agent operates with the perspective of a senior security architect, producing standardized, precise outcomes at scale.
A hierarchy that mirrors an elite red team.
SpartanX does not rely on one model doing everything. It runs a hierarchy where agents specialize, coordinate, and collaborate, each operating at the level of expertise its task demands.
Offensive agents
Category Masters
Strategic coordinators that own an attack domain (web, mobile, API, network, cloud, identity, AI systems). They decompose objectives into campaigns and assign tasks.
Worker sub-agents
Tactical operators that execute multi-step sequences within a domain, chaining techniques, moving laterally, and escalating privilege.
Skill-specific micro-agents
Deep specialists that each master a single technique across the surfaces.
Supporting agents
- Ingest agents across 150+ security tools
- Data enrichment and threat intelligence
- Fix generation
- Compliance and audit-ready reporting
- PESS re-prioritization
- SOC analyst support
Never locked to one vendor's limits.
No single model excels at everything. SpartanX runs a multi-vendor, multi-modal proxy between its agents and the leading foundation models, and routes each task to the best model for the job. As new models emerge, the proxy integrates them, so the platform improves without re-training or manual updates.
Elite red-team intuition, captured once, applied forever.
The most dangerous gap in AI security tools is their inability to learn from creative human thinking. SpartanX captures it through the Attack Telemetry Hub, at the technique level, never your data.
Capture
Optimize
Verify
What makes it different
- Proprietary attack intelligence, not prompt engineering
- Compounding intelligence across engagements
- Human creativity preserved
- Defenses that adapt automatically when targets change
The learning is technique-level, so your findings, targets, and results stay isolated within your tenant.
See agentic AI in action.
Watch a coordinated swarm find, validate, and remediate exposure across your surface, with proof.