Module 2 Assignment: Threat likelihood and impact modeling#
Scenario#
You are advising a cyber risk committee prioritizing mitigation across assets with different exposure and business value. The stakeholders are: CISO, risk officer, system owner, auditor, and executive sponsor.
Task#
Answer the module question: How can AI support risk estimation?
Use the module lab and course readings to produce: cyber risk assessment package with scoring rationale, treatment plan, and executive dashboard focused on threat likelihood and impact modeling: Create a likelihood-impact model..
Required Evidence#
Define the decision or system boundary in one paragraph.
Identify the dataset, proxy data, or evidence source you used: synthetic asset risk records with exposure, vulnerability severity, control strength, threat activity, and business impact.
Compare at least two alternatives, baselines, policies, or designs.
Report one quantitative result or structured scoring table.
Explain two failure modes and one mitigation for each.
State what additional evidence would be required before real deployment.
Submission#
Submit the completed notebook plus a 900-1200 word memo. The memo must include clear headings for context, method, evidence, risks, recommendation, and open questions.
# Assignment workspace for Module 2: Threat likelihood and impact modeling
module = 2
decision = "How can AI support risk estimation?"
artifact = "cyber risk assessment package with scoring rationale, treatment plan, and executive dashboard focused on threat likelihood and impact modeling: Create a likelihood-impact model."
alternatives = [
{"option": "baseline_or_manual_process", "strength": "", "risk": "", "evidence": ""},
{"option": "ai_assisted_or_advanced_option", "strength": "", "risk": "", "evidence": ""},
]
recommendation = {
"decision": decision,
"recommended_option": "",
"minimum_evidence_before_pilot": [],
"monitoring_metric": "",
"rollback_trigger": "",
}
{"module": module, "artifact": artifact, "alternatives": alternatives, "recommendation": recommendation}
{'module': 2,
'artifact': 'cyber risk assessment package with scoring rationale, treatment plan, and executive dashboard focused on threat likelihood and impact modeling: Create a likelihood-impact model.',
'alternatives': [{'option': 'baseline_or_manual_process',
'strength': '',
'risk': '',
'evidence': ''},
{'option': 'ai_assisted_or_advanced_option',
'strength': '',
'risk': '',
'evidence': ''}],
'recommendation': {'decision': 'How can AI support risk estimation?',
'recommended_option': '',
'minimum_evidence_before_pilot': [],
'monitoring_metric': '',
'rollback_trigger': ''}}
Acceptance Criteria#
Your submission is complete only if another reviewer can reproduce your reasoning from the evidence you provide. You do not need production-grade data, but you must be explicit about proxy-data limits and what would change with real institutional data.