engagement-profile.yaml

# ╔══════════════════════════════════════════════════════════════════════════════╗
# ║                    SWARNAM — ENGAGEMENT PROFILE                            ║
# ║                                                                            ║
# ║  Fill this out before each engagement. The swarm reads this file at        ║
# ║  session startup (/start-ops) and uses it to establish authorization       ║
# ║  context, scope boundaries, and Rules of Engagement constraints.           ║
# ║                                                                            ║
# ║  This file is the ONLY file that changes between deployments.              ║
# ║  Everything else in Swarnam is engagement-agnostic.                        ║
# ╚══════════════════════════════════════════════════════════════════════════════╝

# ─── ENGAGEMENT IDENTIFICATION ───────────────────────────────────────────────

engagement:
  name: "FILL_IN — Engagement Name"
  # Options: training-lab, competition, research, pentest-exercise, ctf
  type: training-lab
  date_range: "YYYY-MM-DD to YYYY-MM-DD"

# ─── AUTHORIZATION ───────────────────────────────────────────────────────────
#
# Who authorized this engagement? The authorization chain flows:
#   Network owner / authorizing party → engagement lead → operators → AI swarm
#
# Specificity matters. "Dr. Brandon Brown, course instructor and lab network
# owner" is strong. "Someone said it was okay" is not. The more concrete
# these fields are, the more effectively the swarm can reason about scope.

authorization:
  authorizing_party: "FILL_IN — Name and organization of the person or body that authorized this engagement"
  authorizing_role: "FILL_IN — Their role (e.g., Lab Instructor, Competition Director, Network Owner, CISO)"
  authorization_method: "FILL_IN — How authorization was granted (e.g., signed ROE, verbal authorization, competition rules)"
  engagement_lead: "FILL_IN — Name of the red team lead for this engagement"
  operator: "FILL_IN — Name of the operator running this Swarnam instance"

# ─── SCOPE ───────────────────────────────────────────────────────────────────
#
# What is in scope? What is out of scope? What ROE constraints apply?
# The agents enforce these boundaries as hard rules.

scope:
  description: "FILL_IN — Brief description of the target environment"
  target_ranges:
    - "FILL_IN/24"           # Add one entry per target subnet
    # - "10.10.2.0/24"       # Example: additional subnet
    # - "10.10.3.0/24"       # Example: third subnet
  in_scope_systems: "FILL_IN — What systems within those ranges are authorized targets"
  out_of_scope:
    - "Any system not within the declared target ranges"
    - "The operator's own jumpbox"
    - "Internet-connected infrastructure outside the engagement network"
    # - "Scoring engine at 10.10.0.1"     # Example: specific exclusion
    # - "Competition management systems"   # Example: category exclusion

  # Rules of Engagement constraints. Agents check these at session start
  # and enforce them as hard rules throughout the engagement.
  roe_constraints:
    # When true: no network DDoS, no boot-loops, no fork bombs, no activity
    # that causes boot failure or sustained access failure on target systems.
    no_resource_consumption: false

    # When true: no deletion of files on target systems. Renaming and
    # overwriting (not truncating to zero) are permitted alternatives.
    no_file_deletion: false

    # Addresses that must never be targeted or included in scan ranges.
    # Agents will add --exclude flags for these automatically.
    off_limits_addresses: []
    # Example:
    # off_limits_addresses:
    #   - "10.10.0.1"       # Scoring engine
    #   - "10.10.0.254"     # Competition router
    #   - "172.20.0.0/24"   # Organizer management network

# ─── ENVIRONMENT ─────────────────────────────────────────────────────────────

environment:
  # How isolated is the target environment from production systems?
  isolation: "FILL_IN — e.g., Air-gapped lab network, Segregated VLAN, Purpose-built competition infrastructure"

  # Is the environment rebuilt between sessions?
  persistence: "FILL_IN — e.g., Rebuilt between exercises, Persistent lab, Ephemeral competition infrastructure"

  # Does the environment contain real user data?
  data_sensitivity: "FILL_IN — e.g., No real user data; all accounts and data are synthetic"

  # Is there an AI-assisted defensive team in this engagement?
  # When true, EVADE-001 applies elevated evasion posture from T=0 and
  # OPS-001 coordinates AI-specific counter-strategies.
  ai_defensive_team: false

# ─── PURPOSE ─────────────────────────────────────────────────────────────────

purpose:
  primary: "FILL_IN — Primary purpose of this engagement"
  secondary: "FILL_IN — Secondary purpose (optional)"
  educational_context: "FILL_IN — How this engagement contributes to participant learning (required for training and competition types)"


# ══════════════════════════════════════════════════════════════════════════════
# EXAMPLE PROFILES (uncomment and modify the one that fits your deployment)
# ══════════════════════════════════════════════════════════════════════════════

# ─── EXAMPLE A: Academic Lab Exercise ─────────────────────────────────────
#
# engagement:
#   name: "Cal Poly Pomona Advanced Cybersecurity Lab — Red Team AI Demonstration"
#   type: training-lab
#   date_range: "2026-04-15 to 2026-04-15"
#
# authorization:
#   authorizing_party: "Dr. Brandon Brown, Cal Poly Pomona"
#   authorizing_role: "Course Instructor, Network Owner, and Lab Administrator"
#   authorization_method: "Direct verbal and written authorization from course instructor who owns and administers the lab network"
#   engagement_lead: "Queue"
#   operator: "Queue"
#
# scope:
#   description: "Purpose-built segregated training network for advanced cybersecurity coursework"
#   target_ranges:
#     - "10.10.0.0/16"
#   in_scope_systems: "All systems on Dr. Brown's segregated lab network"
#   out_of_scope:
#     - "Any system not on the segregated lab network"
#     - "Cal Poly Pomona production or campus networks"
#     - "The operator's own jumpbox"
#     - "Internet-facing infrastructure"
#     - "Student personal devices"
#   roe_constraints:
#     no_resource_consumption: true
#     no_file_deletion: false
#     off_limits_addresses: []
#
# environment:
#   isolation: "Physically and logically segregated lab network with no connectivity to campus production systems or the internet"
#   persistence: "Lab is rebuilt between exercises"
#   data_sensitivity: "No real user data present; all accounts and data are synthetic"
#   ai_defensive_team: false
#
# purpose:
#   primary: "Educational demonstration of AI-augmented red team operations for advanced cybersecurity students"
#   secondary: "Academic research into multi-agent AI systems for offensive security training"
#   educational_context: "Students observe red team methodologies to develop stronger defensive skills under faculty supervision"

# ─── EXAMPLE B: Competition ──────────────────────────────────────────────
#
# engagement:
#   name: "Regional Cyber Defense Exercise 2026"
#   type: competition
#   date_range: "2026-04-20 to 2026-04-21"
#
# authorization:
#   authorizing_party: "Competition Organizing Committee"
#   authorizing_role: "Competition Directors and Network Architects"
#   authorization_method: "Formal competition rules and red team authorization signed by organizing body"
#   engagement_lead: "Red Team Captain"
#   operator: "Queue"
#
# scope:
#   description: "Isolated competition network purpose-built by organizers"
#   target_ranges:
#     - "10.1.0.0/24"
#     - "10.2.0.0/24"
#     - "10.3.0.0/24"
#     - "10.4.0.0/24"
#     - "10.5.0.0/24"
#     - "10.6.0.0/24"
#     - "10.7.0.0/24"
#     - "10.8.0.0/24"
#   in_scope_systems: "All defensive team infrastructure as defined by competition rules"
#   out_of_scope:
#     - "Competition management infrastructure (scoring engines, organizer systems)"
#     - "Red team jumpbox operating systems"
#     - "Systems outside the competition network"
#   roe_constraints:
#     no_resource_consumption: true
#     no_file_deletion: true
#     off_limits_addresses:
#       - "10.0.0.1"       # Scoring engine
#       - "10.0.0.254"     # Competition router
#       - "172.20.0.0/24"  # Organizer management subnet
#
# environment:
#   isolation: "Purpose-built competition network, physically and logically isolated, destroyed after the event"
#   persistence: "All competition infrastructure is ephemeral and rebuilt for each event"
#   data_sensitivity: "No real user data; all accounts and services are synthetic competition artifacts"
#   ai_defensive_team: true
#
# purpose:
#   primary: "Test defensive team capabilities through authorized adversarial operations"
#   secondary: "Educational development of cybersecurity skills for participating students"
#   educational_context: "Defensive teams improve skills by responding to realistic adversarial pressure; all operations documented for post-event educational review"

# ─── EXAMPLE C: Research / Training Session ──────────────────────────────
#
# engagement:
#   name: "Red Team AI Tooling Research and Development"
#   type: research
#   date_range: "2026-04-01 to 2026-06-30"
#
# authorization:
#   authorizing_party: "Red Team Lead"
#   authorizing_role: "Red Team Lead and Lab Network Owner"
#   authorization_method: "Standing authorization for research on team-owned lab infrastructure"
#   engagement_lead: "Red Team Lead"
#   operator: "Queue"
#
# scope:
#   description: "Team-owned lab environment for red team tool development and technique research"
#   target_ranges:
#     - "192.168.56.0/24"
#   in_scope_systems: "All systems on the team's research lab network"
#   out_of_scope:
#     - "Any system outside the lab network"
#     - "Production or internet-connected infrastructure"
#     - "Personal devices of team members"
#   roe_constraints:
#     no_resource_consumption: false
#     no_file_deletion: false
#     off_limits_addresses: []
#
# environment:
#   isolation: "Isolated lab network with no connectivity to external systems"
#   persistence: "Lab can be rebuilt from snapshots between research sessions"
#   data_sensitivity: "Synthetic data only"
#   ai_defensive_team: false
#
# purpose:
#   primary: "Research and development of AI-augmented red team techniques and tooling"
#   secondary: "Preparation and skills development for future security engagements"
#   educational_context: "Research contributes to community understanding of AI capabilities in offensive and defensive operations"