AI pentesting that proves real exploitable risk

Prancer is the AI-Native autonomous penetration testing platform. SwarmHack™ combines a deterministic execution core with optional frontier-model exploration across 100+ agent capabilities and 85 plugins. Where a scanner produces a list of maybes, Prancer captures the request that worked, the target output it returned, and the path an attacker would walk next.

Coverage across every surface

• Web applications — crawling, authentication testing and roughly 22 deep vulnerability scanners that exploit inline rather than reporting and stopping.
• APIs — REST and GraphQL discovery, OAuth/JWT/cookie/custom auth, BOLA and IDOR chains, mass assignment and business-logic abuse.
• Networks, Active Directory and Windows identity — 21+ capabilities across anonymous discovery, credential production, authenticated re-enumeration, lateral movement and domain dominance.
• Cloud, containers and CI/CD — AWS, Azure and GCP misconfiguration to IAM pivot, IMDSv2 abuse, Docker escape, exposed kubelet and Jenkins paths.
• Secure Service Edge, ZTNA and GenAI egress — 23 validation capabilities that test whether the control actually blocks, not whether the policy says it should.
• RoboSec, IoT, code and Infrastructure-as-Code — 9 robotics/IoT capabilities plus white-box analysis correlated with runtime exploitability.

Autonomous, not automated

Automated scanners replay a fixed script. Autonomous penetration testing plans, acts, observes and re-plans. A GOAP A* planner selects and orders actions deterministically; when an action fails the swarm re-plans rather than aborting. Shared swarm state means a credential found on a web host becomes an Active Directory pivot seconds later — the pivot chains that human red teams find, produced continuously.

Frontier Models Attack Validation

Anthropic, OpenAI and sovereign AI. Frontier-model attack validation combines a deterministic core with optional LLM-assisted exploration under one evidence gate.

Mythos combines a deterministic core with optional LLM-assisted exploration under one evidence gate. Versioned playbooks and GOAP A* plans provide reproducible, air-gap-ready execution without requiring a model. When model assistance is enabled, leading frontier models can explore beyond fixed playbooks, and a model router sends workloads to the most appropriate eligible model.

Prancer is an Anthropic-verified vendor. Frontier Models Attack Validation runs in the customer environment and supports open-weight, privately hosted models and sovereign-AI environments. The predictive engine can be disabled; the evidence gate cannot. No Critical finding is published without captured target output. US Patent 11,843,627 B2.

Evidence, not theory

Every finding is graded Exploited, Observed, AttackPathIdentified or Simulated. Critical severity is reserved for proven evidence, and an "Exploited" label without captured target output is downgraded automatically — so version-match guesses never masquerade as exploitation. Findings reach the published report only when they carry a crown jewel or are genuinely Exploited, which is why triage queues shrink instead of growing.

Reporting your auditors and your SIEM both accept

Outputs ship as OCSF 1.1.0 JSON, interactive HTML attack graphs, Markdown, and DOT/Cytoscape/Neo4j graph exports, with compliance rollups for PCI DSS 4.0, NIST CSF 2.0, OWASP Top 10 2021, SOC 2, HIPAA, ISO 27001:2022, DORA and NIS2.

Proven in a live-fire lab

A 200-host AWS engagement produced 18 application surfaces, 45 findings, 19 Exploited and 13 Critical — unauthenticated web RCE to service credentials to host root to IAM credential holder, with zero cloud-native attack detections raised. Read the full engagement writeup.

Explore the platform

SwarmHack engine · Agentic pentesting · Active Directory · Cloud & containers · SSE validation · RoboSec · API security · Enterprise · MSP platform · Documentation · Book a demo.