🚨 Incident Response Agent Specification¶

🎯 Purpose¶

The Incident Response Agent automates the detection, classification, containment, and resolution of security incidents and operational anomalies within the ConnectSoft AI Software Factory. It executes containment playbooks, coordinates cross-agent response workflows, and produces comprehensive post-incident reports for compliance and continuous improvement.

It operates as the first responder when security breaches, anomalous behaviors, or SLA violations are detected — ensuring that incidents are contained rapidly, documented thoroughly, and resolved systematically.

It ensures that no incident goes undetected, uncontained, or undocumented across the platform.

🧭 Role in the Platform¶

The Incident Response Agent sits at the heart of the Security and Compliance cluster, bridging real-time alerting with structured response workflows.

Factory Layer	Agent Role
Security	Executes containment actions and coordinates with Security Engineer
Compliance	Generates post-incident reports and evidence for regulatory review
Observability	Consumes alerts and anomalies from monitoring systems
Operations	Coordinates with Alerting/Incident Manager and SLO/SLA Compliance
DevOps & Delivery	Triggers emergency patches and hotfix deployments when needed

📊 Position Diagram¶

flowchart TD

  subgraph Detection & Alerting
    A[Alerting / Incident Manager Agent]
    B[Observability Engineer Agent]
    C[SLO/SLA Compliance Agent]
  end

  subgraph Security & Compliance
    D[Incident Response Agent]
    E[Security Engineer Agent]
  end

  subgraph Operations
    F[HumanOpsAgent]
    G[DevOps Engineer Agent]
  end

  A --> D
  B --> D
  C --> D
  D --> E
  D --> F
  D --> G
  E --> D

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The Incident Response Agent receives signals from alerting and observability systems, executes structured response playbooks, and coordinates remediation with security and operations teams.

📋 Triggering Events¶

Event	Source	Description
`security_breach_detected`	Security Engineer / WAF / SIEM	Confirmed or suspected security breach requires immediate response
`anomaly_alert_triggered`	Observability / Anomaly Detector	Unusual pattern detected in traffic, errors, or resource usage
`sla_breach_occurred`	SLO/SLA Compliance Agent	Service-level agreement violation requiring incident classification
`intrusion_attempt_detected`	Network Security / IDS	Intrusion detection system triggered on suspicious activity
`data_exfiltration_suspected`	DLP / Security Monitoring	Potential unauthorized data access or transfer detected

📌 Responsibilities¶

🔧 Core Responsibilities¶

✅ 1. Automated Incident Detection and Classification¶

Receive and correlate alerts from multiple detection sources
Classify incidents by type, severity, and scope:
Security: breach, intrusion, data leak, privilege escalation
Operational: SLA violation, service degradation, cascading failure
Compliance: policy violation, audit finding, regulatory trigger
Assign severity levels: SEV1 (critical) through SEV4 (informational)

incident_classification:
  id: INC-2025-0842
  type: security_breach
  severity: SEV1
  scope: multi-service
  affected_services: [AuthGateway, UserService]
  affected_environments: [production]
  detection_source: waf_alert
  classification_confidence: 0.95

✅ 2. Containment Playbook Execution¶

Select and execute appropriate containment playbook based on incident type
Playbooks are pre-defined, version-controlled, and trace-linked
Actions may include:
Network isolation of affected services
Token revocation and session invalidation
Traffic rerouting to safe fallback
Temporary RBAC lockdown
Service scaling down or pod termination

✅ 3. Incident Coordination and Communication¶

Notify relevant agents and human operators in real-time
Maintain incident timeline with all actions, decisions, and state changes
Coordinate parallel workstreams: containment, investigation, communication
Provide status updates at defined intervals during active incidents

✅ 4. Evidence Collection and Preservation¶

Capture logs, traces, metrics, and configuration snapshots at incident time
Preserve evidence chain-of-custody for forensic analysis
Store evidence artifacts in tamper-proof storage with trace linkage
Generate evidence summary for post-incident review

✅ 5. Post-Incident Reporting¶

Generate comprehensive post-mortem reports including:
Timeline of events
Root cause analysis (preliminary and final)
Impact assessment (services, tenants, data)
Containment actions taken
Remediation recommendations
Lessons learned and preventive measures
Emit PostMortemGenerated event for knowledge management

✅ 6. Continuous Improvement Integration¶

Feed incident patterns into vulnerability management
Update containment playbooks based on lessons learned
Contribute to security policy refinement
Track mean time to detect (MTTD) and mean time to resolve (MTTR)

📊 Responsibilities and Deliverables¶

Responsibility	Deliverable
Incident classification	`incident-report.json` with type, severity, scope
Containment execution	`containment-playbook.json` with executed actions and results
Evidence preservation	Evidence artifacts stored with chain-of-custody metadata
Post-incident reporting	`post-mortem.md` with timeline, RCA, and recommendations
Metrics tracking	MTTD, MTTR, incident frequency dashboards

📤 Output Types¶

Output Type	Format	Description
`incident-report`	JSON	Structured incident record with classification and status
`containment-playbook`	JSON	Executed playbook with actions, timestamps, and outcomes
`post-mortem`	Markdown	Comprehensive post-incident analysis with RCA and recommendations
`evidence-bundle`	Archive	Collected logs, traces, configs, and metrics at incident time

🧾 Example `incident-report` Output¶

{
  "incident_id": "INC-2025-0842",
  "trace_id": "trace-incident-0842",
  "type": "security_breach",
  "severity": "SEV1",
  "status": "contained",
  "detected_at": "2025-06-10T03:15:22Z",
  "contained_at": "2025-06-10T03:18:45Z",
  "affected_services": ["AuthGateway", "UserService"],
  "affected_environments": ["production"],
  "detection_source": "waf_alert",
  "containment_actions": [
    "network_isolation_authgateway",
    "token_revocation_all_sessions",
    "traffic_reroute_to_maintenance"
  ],
  "investigating_agents": [
    "incident-response-agent",
    "security-engineer-agent"
  ],
  "agent": "incident-response-agent"
}

🧾 Example `containment-playbook` Output¶

{
  "incident_id": "INC-2025-0842",
  "playbook_id": "PB-SEC-001-network-isolation",
  "playbook_version": "2.1.0",
  "steps": [
    {
      "action": "isolate_network",
      "target": "AuthGateway",
      "status": "completed",
      "executed_at": "2025-06-10T03:16:01Z",
      "duration_ms": 2340
    },
    {
      "action": "revoke_tokens",
      "scope": "all_active_sessions",
      "status": "completed",
      "executed_at": "2025-06-10T03:16:45Z",
      "duration_ms": 1890
    },
    {
      "action": "enable_maintenance_mode",
      "target": "production_ingress",
      "status": "completed",
      "executed_at": "2025-06-10T03:17:30Z",
      "duration_ms": 1200
    }
  ],
  "overall_status": "containment_successful",
  "agent": "incident-response-agent"
}

🔄 Process Flow¶

flowchart TD
    A[Alert / Breach Signal Received] --> B[Classify Incident Type + Severity]
    B --> C[Select Containment Playbook]
    C --> D[Execute Containment Actions]
    D --> E[Collect and Preserve Evidence]
    E --> F[Notify Agents + Human Operators]
    F --> G[Monitor Resolution Progress]
    G --> H{Incident Resolved?}
    H -- Yes --> I[Generate Post-Mortem Report]
    I --> J[Emit PostMortemGenerated + Close Incident]
    H -- No --> K[Escalate to Security Engineer + HumanOps]
    K --> G

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🪜 Step-by-Step Breakdown¶

Step	Action
1	Receive alert signal from detection source (SIEM, WAF, anomaly detector, SLA monitor)
2	Classify incident by type, severity, scope, and affected assets
3	Select appropriate containment playbook from the playbook registry
4	Execute containment actions (network isolation, token revocation, traffic rerouting)
5	Collect evidence: logs, traces, metrics, config snapshots at incident time
6	Notify Security Engineer, HumanOpsAgent, and affected service owners
7	Monitor ongoing resolution — track containment effectiveness and service recovery
8	On resolution: generate post-mortem with timeline, RCA, and recommendations
9	On escalation: hand off to human operators with full incident context

🤝 Collaboration Patterns¶

📥 Upstream Inputs From¶

Agent	Input
Alerting / Incident Manager Agent	Alert signals with severity, source, and preliminary triage
Observability Engineer Agent	Anomaly detections, metric spikes, trace anomalies
SLO/SLA Compliance Agent	SLA breach notifications requiring incident classification
Security Engineer Agent	Security policy context and hardening baselines

📤 Downstream Consumers¶

Agent	Output Consumed
Security Engineer Agent	Incident details for deeper investigation and policy updates
HumanOpsAgent	Escalation alerts and incident status updates
DevOps Engineer Agent	Emergency patch triggers and hotfix deployment requests
Knowledge Management Agent	Post-mortem reports for organizational learning
Vulnerability Management Agent	Vulnerability records from incident-discovered exploits

🔁 Event-Based Communication¶

Event	Trigger	Consumed By
`IncidentDeclared`	Incident classified and registered	Security Engineer, HumanOpsAgent
`ContainmentExecuted`	Playbook actions completed	Observability Agent, HumanOpsAgent
`IncidentEscalated`	Containment insufficient, human action needed	HumanOpsAgent, Security Engineer
`IncidentResolved`	Incident fully resolved and verified	Release Manager, SLO/SLA Compliance Agent
`PostMortemGenerated`	Post-incident report completed	Knowledge Management, Vulnerability Management

🧩 Collaboration Sequence¶

sequenceDiagram
    participant Alert as Alerting Agent
    participant IR as Incident Response Agent
    participant SecEng as Security Engineer Agent
    participant HumanOps as HumanOpsAgent
    participant KM as Knowledge Management Agent

    Alert->>IR: Security Breach Detected
    IR->>IR: Classify + Select Playbook
    IR->>IR: Execute Containment
    IR->>SecEng: Emit IncidentDeclared
    IR->>HumanOps: Notify with Status Update
    IR->>IR: Collect Evidence + Monitor
    IR->>KM: Emit PostMortemGenerated

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🧠 Memory and Knowledge¶

📌 Short-Term Memory (Execution Scope)¶

Field	Purpose
`incident_id`	Unique identifier for the active incident
`trace_id`	Links incident to originating alert and system trace
`containment_state`	Current status of playbook execution
`evidence_collection_state`	Tracks which evidence artifacts have been collected
`notification_log`	Records all notifications sent during incident lifecycle

💾 Long-Term Memory (Persistent)¶

Memory Type	Purpose
Incident Registry	All incidents with full lifecycle state and audit trail
Playbook Registry	Version-controlled containment playbooks indexed by incident type
Evidence Archive	Tamper-proof storage of incident evidence bundles
Post-Mortem Repository	All post-incident reports with RCA and recommendations
MTTD/MTTR Metrics Store	Historical detection and resolution time metrics

📚 Knowledge Base¶

Knowledge Area	Description
Incident Classification Taxonomy	Type, severity, and scope definitions with classification rules
Containment Playbooks	Pre-defined response strategies per incident type
Escalation Policies	When and how to escalate based on severity and containment outcome
Evidence Collection Procedures	What to capture, how to preserve, chain-of-custody requirements
Post-Mortem Templates	Structured templates for timeline, RCA, impact, recommendations
Regulatory Notification Rules	When incidents require regulatory or customer notification

✅ Validation¶

Category	Checks Performed
Classification Accuracy	Incident type and severity match alert signals and evidence
Playbook Completeness	All required containment steps executed and verified
Evidence Integrity	Evidence artifacts collected with timestamps and chain-of-custody
Notification Compliance	All required stakeholders notified within policy-defined windows
Post-Mortem Quality	Report includes timeline, RCA, impact, actions, and prevention plan
Resolution Verification	Incident root cause addressed and recurrence prevention confirmed

❌ Failure Actions¶

Failure Type	Action
Containment action failed	Retry once, then escalate to HumanOpsAgent immediately
Evidence collection incomplete	Flag gap in post-mortem, attempt recovery from backup logs
Classification uncertain	Default to higher severity, request human triage
Notification delivery failed	Retry via alternate channel (Slack → Email → PagerDuty)
Playbook not found for type	Execute generic containment, escalate for custom response

🧩 Skills and Kernel Functions¶

Skill	Purpose
`IncidentClassifierSkill`	Classify incidents by type, severity, and scope from alert data
`PlaybookSelectorSkill`	Match incident type to appropriate containment playbook
`ContainmentExecutorSkill`	Execute playbook steps with status tracking and rollback capability
`EvidenceCollectorSkill`	Capture logs, traces, metrics, and config snapshots
`NotificationDispatcherSkill`	Send alerts to agents and human operators via multiple channels
`PostMortemGeneratorSkill`	Produce structured post-incident reports with RCA
`IncidentTimelineBuilderSkill`	Construct chronological event timeline for incident
`EscalationManagerSkill`	Manage escalation paths based on severity and containment status
`EventEmitterSkill`	Emit incident lifecycle events

📈 Observability Hooks¶

Span Name	Description
`incident.detect`	Incident detection and classification
`incident.contain.start`	Containment playbook execution begins
`incident.contain.action`	Individual containment action execution
`incident.evidence.collect`	Evidence collection operation
`incident.notify`	Stakeholder notification dispatch
`incident.resolve`	Incident resolution and closure
`incident.postmortem.generate`	Post-mortem report generation

Span Tags¶

incident_id, trace_id, severity, type
agent: incident-response-agent
status: detected | classified | contained | resolved | escalated
playbook_id, affected_services, mttd_ms, mttr_ms

🧠 Summary¶

The Incident Response Agent is the rapid-response coordinator of the ConnectSoft AI Software Factory. It ensures that:

🚨 Every incident is detected, classified, and contained within minutes
📋 Containment playbooks are executed automatically with full trace linkage
🔍 Evidence is preserved for forensic analysis and compliance
📝 Post-mortem reports drive continuous improvement and knowledge sharing
⏱️ MTTD and MTTR are tracked and optimized over time
🤝 Human operators are engaged at the right time with the right context

It transforms incident response from a chaotic, ad-hoc process into a structured, automated, trace-aware security operation — ensuring the platform's resilience and trustworthiness are maintained even under active threat.

🚨 Incident Response Agent Specification¶

🎯 Purpose¶

🧭 Role in the Platform¶

📊 Position Diagram¶

📋 Triggering Events¶

📌 Responsibilities¶

🔧 Core Responsibilities¶

✅ 1. Automated Incident Detection and Classification¶

✅ 2. Containment Playbook Execution¶

✅ 3. Incident Coordination and Communication¶

✅ 4. Evidence Collection and Preservation¶

✅ 5. Post-Incident Reporting¶

✅ 6. Continuous Improvement Integration¶

📊 Responsibilities and Deliverables¶

📤 Output Types¶

🧾 Example incident-report Output¶

🧾 Example containment-playbook Output¶

🔄 Process Flow¶

🪜 Step-by-Step Breakdown¶

🤝 Collaboration Patterns¶

📥 Upstream Inputs From¶

📤 Downstream Consumers¶

🔁 Event-Based Communication¶

🧩 Collaboration Sequence¶

🧠 Memory and Knowledge¶

📌 Short-Term Memory (Execution Scope)¶

💾 Long-Term Memory (Persistent)¶

📚 Knowledge Base¶

✅ Validation¶

❌ Failure Actions¶

🧩 Skills and Kernel Functions¶

📈 Observability Hooks¶

Span Tags¶

🧠 Summary¶

🧾 Example `incident-report` Output¶

🧾 Example `containment-playbook` Output¶