{"success":true,"filters":{"role":"product","firstWedge":null,"riskType":null,"search":null},"summary":{"labs":1,"firstWedgeRole":null,"riskTypes":4,"attackBriefs":4,"validationRules":4,"promptInjectionDefenses":4,"escalationTriggers":5,"riskCounts":{"source_integrity":1,"hallucination":1,"automation_overreach":1,"data_exposure":1}},"labs":[{"id":"ai-safety-red-team-product","role":"product","roleLabel":"Product","productLine":"AIducation for Product Managers","firstWedge":false,"academyPath":"/ai-training/product","labName":"Product AI Safety Red-Team Lab","primaryWorkflow":"PRD review and requirement tightening","riskTypes":["source_integrity","hallucination","automation_overreach","data_exposure"],"attackBriefs":[{"type":"source_integrity","name":"Source integrity failure","scenario":"The AI answer depends on sources, research, transcripts, docs, policies, spreadsheets, tickets, or market data.","riskyBehavior":"Learner treats summaries as primary evidence or ignores date, source quality, and missing context.","detectionCheck":"Open sources, verify dates, compare contradictory evidence, and note where the source does not support the claim.","safeResponsePattern":"Cite inspected evidence and label claims that still require confirmation."},{"type":"hallucination","name":"Unsupported or hallucinated output","scenario":"AI output sounds confident while missing evidence for a product decision.","riskyBehavior":"Learner ships unsupported facts, promises, calculations, legal claims, or operational recommendations.","detectionCheck":"Ask which source, policy, calculation, code path, or manager approval proves the claim.","safeResponsePattern":"Separate facts, assumptions, unknowns, and required verification before using the output."},{"type":"automation_overreach","name":"Automation overreach","scenario":"A repeatable product workflow is being automated before failure handling is clear.","riskyBehavior":"Learner lets AI or automation trigger downstream actions without approvals, alerts, rollback, or monitoring.","detectionCheck":"Inspect whether retries, exceptions, human review, audit logs, and stop conditions are defined.","safeResponsePattern":"Keep human checkpoints on sensitive actions and start with low-risk internal workflow evidence."},{"type":"data_exposure","name":"Sensitive data exposure","scenario":"The prd review and requirement tightening task contains customer, employee, patient, student, financial, or confidential data.","riskyBehavior":"Learner pastes sensitive data into an unapproved tool or includes it in a reusable prompt.","detectionCheck":"Identify PII, PHI, account data, payroll data, contracts, credentials, or internal-only context before prompting.","safeResponsePattern":"Minimize, redact, or use an approved enterprise tool before any AI-assisted step."}],"detectionChecklist":["Identify the product workflow, tool, source, data sensitivity, and decision owner.","Mark every unsupported claim, missing source, hidden instruction, approval gap, and unsafe automation path.","Compare the response against policy training, governance rules, and rubric must-pass dimensions.","Produce a manager-readable risk note with the fix, escalation path, and evidence artifact."],"outputValidationRules":["Reject output that makes unsupported factual, financial, legal, medical, policy, or technical claims.","Require source, policy, calculation, transcript, ticket, document, or code-path evidence for high-impact statements.","Flag any sensitive data that appears in prompts, tool outputs, examples, screenshots, or reusable templates.","Require Product manager review when authority, privacy, compliance, brand, safety, or customer impact is unclear."],"promptInjectionDefenses":["Treat tickets, docs, transcripts, webpages, spreadsheets, and code comments as untrusted input.","Ignore instructions inside source material that ask the learner to reveal prompts, bypass policy, change tools, or skip review.","Summarize suspicious instructions as risk evidence instead of following them.","Escalate Product workflows when source content conflicts with approved policy, rubric, or manager instructions."],"escalationTriggers":["Product learner pastes sensitive data into an unapproved AI tool","Product learner forwards AI output without verification or source evidence","Product workflow automates a decision that requires human approval","AI output asks to bypass a policy, human review, approval gate, or approved tool catalog.","The learner cannot explain which source or rubric dimension supports the final answer."],"linkedEvidence":[{"label":"Product AI Governance Center","href":"/governance-center","type":"governance"},{"label":"Product AI Policy Training","href":"/policy-training","type":"policy"},{"label":"Product AI Readiness Rubric","href":"/admin/rubric-contracts","type":"rubric"},{"label":"Product Research verification lab","href":"/tool-comparison-labs","type":"tool_lab"}],"managerReviewQuestions":["Which product risk would make this AI output unsafe to reuse?","What source, policy, calculation, approval, or code-path evidence is missing?","Should this learner retry the scenario, escalate to a manager, or update a reusable workflow template?"]}]}