Break your defenses
before attackers do.

STRATEGOS is the LLM mission planner at ARES's core. It builds a directed acyclic attack graph from SCOUT's recon output, schedules cluster tasks with dynamic concurrency across all 76 sub-agents, enforces per-phase token budgets, and detects failure loops — recovering without operator intervention. Game-theory optimized target selection (Nash equilibrium) ensures the highest-value attack paths are pursued first.

• DAG task scheduler with cycle and stall detection
• Dynamic concurrency — 76 sub-agents in parallel
• Nash equilibrium target prioritization
• Cross-session learning: prior campaign findings inform the next

SENTINEL is ARES's safety layer. It enforces your Rules of Engagement file for every agent action — blocking attacks on out-of-scope targets, enforcing timing windows, and halting on policy violation. Operators choose an autonomy level from L0 (manual approval per action) to L5 (fully autonomous within ROE). Air-gap deployment is supported; no data leaves the network without operator approval.

• L0–L5 autonomy spectrum — operator-controlled
• Rules of Engagement enforcement for every action
• Kill switch: full campaign abort in <5 seconds
• gVisor-sandboxed tool execution — host isolation guaranteed

Every potential finding passes through CRUCIBLE's 4-stage pipeline before being accepted: Stage 1 schema validation, Stage 2 cross-agent deduplication, Stage 3 evidence grading (L1 weak indication → L4 confirmed PoC), Stage 4 LLM reflector veto. Nothing is reported below ≥0.85 confidence. SCRIBE then generates structured findings with 70+ remediation templates matched to your stack.

• 4-stage pipeline — every finding before acceptance
• ≥0.85 confidence gate with LLM reflector veto
• Evidence graded L1 (indication) to L4 (confirmed PoC)
• 70+ remediation templates matched to your stack

A Series B payments startup operating across multiple markets asks Phalanxia to assess their payment reconciliation API ahead of a SOC 2 audit. The autonomous agents discover an IDOR vulnerability allowing any authenticated merchant to access another merchant's transaction records. The finding is validated with proof-of-concept evidence and a code-level fix is generated within the same run. The development team deploys the patch within 24 hours.

• Critical IDOR in reconciliation endpoint
• 30+ findings surfaced in first engagement
• Audit evidence package generated automatically

An electronic health records platform serving hundreds of clinics integrates Phalanxia into GitHub Actions to run an assessment on every release candidate. Within the first 90 days, the pipeline catches a broken access control flaw in the patient record export feature — a vulnerability that survived three prior manual pentests because it only manifested under specific role-combination conditions that automated tooling routinely tests.

• Broken access control in export workflow
• Flaws caught before reaching production
• Findings missed by previous manual engagements

A high-volume e-commerce operator commissions an attack surface discovery run before a major platform migration. Phalanxia's discovery module maps dozens of previously undocumented API endpoints and identifies forgotten staging environments still connected to production databases. Jira tickets with remediation code are created automatically, and every critical finding is closed within 48 hours using the generated patches.

• Undocumented API endpoints enumerated
• Staging environments exposed to production
• Auto-generated remediation code, Jira handoff