Cobalt
SpartanX vs Cobalt
See how SpartanX's autonomous AI agents outscale Cobalt's researcher-dependent model
Feature-by-Feature Comparison
| Category | SpartanX | Cobalt |
|---|---|---|
| Core Vision | Agentic AI Security Workforce, autonomous AI agents continuously testing and fixing across the entire stack. | Human-led, AI-powered PTaaS, vetted expert pentesters augmented by AI for on-demand engagements. |
| Mission Focus | Full lifecycle automation: discover → validate → prioritize → fix → simulate attacks → report. | On-demand penetration testing with fast launch times and human expertise at its core. |
| Scope of Coverage | Code → Infra → Cloud → APIs → LLMs → Continuous Red-Team. | Web, API, mobile, AI/LLM, network, cloud, red team, broad but human-gated. |
| Automation Level | Multi-agent AI, fully autonomous from discovery to fix and compliance report. | AI automates recon; humans conduct the core testing. Hybrid, not autonomous. |
| Scalability | Horizontal scaling, agents run across unlimited assets simultaneously. | Scalability gated by availability of Cobalt Core researcher community. |
| Testing Model | Continuous 24/7, agents run on every change, every commit. | Project-based engagements, launched on demand, credit-based pricing. |
| Remediation Capability | Auto-generates code fixes + Pull Requests into developer repos. | 50% faster remediation claimed, but fixing is still manual by development teams. |
| Report Speed | First findings in hours, auto-generated throughout testing. | 2.6x faster than traditional pentesting, but still report-delivery model. |
| Offensive Security | Fully autonomous AI Red-Team agents with no human bottleneck. | Elite human researchers with AI-assisted recon, not truly autonomous. |
| Human Dependency | Human-in-the-loop for approvals and governance only, not for testing execution. | Human researchers required for all meaningful test execution. |
| Knowledge Intelligence | Ontology-driven Knowledge Graph linking vulns ⇔ MITRE ATT&CK ⇔ business impact ⇔ compliance. | Decade of proprietary exploit intelligence built from human tester data. |
| DevSecOps Integration | Deep CI/CD and developer workflow integration, PRs auto-created. | Limited DevSecOps integration; engagement-based model doesn't fit CI/CD cadence. |
| Compliance Reporting | Auto-generates ISO 27001, PCI-DSS, HIPAA, NIST, GDPR, DORA, SOX reports. | SOC 2, HIPAA, PCI compliance testing available within engagement scope. |
| Multi-Tenant / MSSP Ready | Native multi-tenant architecture for MSSPs. | 1,500+ customers served; no native MSSP multi-tenant architecture. |
| AI / LLM Security | Dedicated AI/LLM red-team module with autonomous exploitation. | LLM pentesting available as an emerging engagement type, human-led. |
| Cost Model | Continuous coverage, no per-test gating. | Credit-based model, costs accumulate per engagement. |
| Outcome Speed | Detection → Auto-Fix → Report in minutes, 24/7. | Engagement launch in 24 hours, findings in days, fix cycle weeks. |
| Market Positioning | AI Security Workforce, autonomous, continuous, full stack. | Pioneer of PTaaS, human expertise on demand, AI-assisted. |
| Ideal Users | CISOs, AppSec leads, DevSecOps engineers, MSSPs. | AppSec teams, compliance teams, developers needing structured engagements. |
SpartanX Key Advantages
Human-dependent, scalability limited by researcher availability
Fully autonomous AI agents with no human bottleneck
Project-based, not continuous
24/7 continuous testing on every commit and build
No auto-remediation
Auto-PR generation with validated code fixes
Credit-based cost model accumulates per engagement
Continuous coverage model, no per-test gating
AI limited to recon augmentation
AI agents conduct full attack chains autonomously
No DevSecOps or CI/CD integration
Native developer workflow integration
No MSSP multi-tenant architecture
Native multi-tenant platform for service providers
Human tester fatigue and availability windows
AI agents run 24/7 with no off switch