{"schema_version":"0.9.0","id":"LR-2026-0245","record_version":2,"title":"Self-taught hacker uses AI coding agent and autonomous penetration-testing system to breach 90+ companies and steal 8.2 million records","verification":{"human_verified":false,"method":"automated_gate","auto_verified":true,"score":60.0,"score_breakdown":{"source_authority":12.1,"independent_corroboration":15.0,"implicated_party_confirmed":0.0,"citation_integrity":14.0,"specificity":3.0,"completeness":8.0,"unhedged_language":4.86},"checks":{"schema_valid":true,"every_field_cited":true,"quotes_verbatim":true,"source_fetched":true,"distinct_incident":true,"dates_plausible":true,"sources_agree":true,"source_describes_incident":true,"severe_backed_by_source":true,"record_integrity":true},"gate_version":"gate-2026-10-18.7","cross_check_model":null,"cross_check_agreement":null,"duplicate_of":null,"verified_by":null,"verified_at":"2026-10-26","extraction_run_id":null},"system":{"model_name":null,"model_version":null,"developer":"unknown","harness":"AI coding agent and an autonomous AI penetration testing system","tools_granted":[],"permissions_scope":null,"autonomy_level":"full-auto","guardrails_present":[],"deployment_context":"unknown","tier":null,"lifecycle_stage":null,"integration_type":"agentic_with_tools","intended_use":"autonomous AI penetration testing system","safeguard_state":null,"production_intended":null},"event":{"date_occurred":"2025-09-01","date_occurred_precision":"month","date_disclosed":"2026-10-26","incident_class":"security_compromise","failure_class":null,"agent_involved":true,"secondary_failure_classes":[],"trigger":"unknown","duration":null,"detection_method":"victim","summary":"A cybercrime ring allegedly used AI tools to hack over 90 entities including hospitals, private academies and businesses, stealing 8.2 million pieces of personal data and internal records from September last year until recently. Police said 38 targets suffered losses and the group demanded a combined 360 million won. Seven suspects were identified, and the 32-year-old ringleader was referred to prosecution.","tags":[],"date_detected":null,"near_miss":false,"root_cause":null,"root_cause_detail":null,"failure_class_detail":null,"responsible_party":"third_party","adversarial_actor":"external_attacker","input_provenance":null,"time_to_contain":null,"operations_paused":null,"remediation":null,"precursor_events":null},"impact":{"direct_loss_usd":null,"remediation_hours":null,"records_exposed":8200000,"third_parties_affected_count":38,"severity":"major","severity_because":"major: More than 90 businesses were hacked and 8.2 million personal records stolen, with 38 companies reporting losses.","harm_class":["privacy","financial","third_party_security"],"affected_description":"\"more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses\"; a funeral services provider lost 1.22 million records; data on minors was taken from private academies","protected_class_involved":null,"data_categories_exposed":["pii"],"loss_range_usd":null,"reversibility":null,"downstream_exposure_count":null},"evidence":{"sources":[{"url":"https://en.sedaily.com/society/2026/10/26/self-taught-hacker-used-ai-to-steal-82-million-records","publisher":"news search (Google News index)","date":"2026-10-26","type":"press","title":"Self-Taught Hacker Used AI to Steal 8.2 Million Records, Police Say","archived_url":null,"attachment":"first_report"},{"url":"https://www.koreatimes.co.kr/southkorea/law-crime/20261026/cybercrime-ring-busted-over-ai-powered-data-theft-targeting-hospitals-businesses","publisher":"news search (Google News index)","date":"2026-10-26","type":"press","title":"Cybercrime ring busted over AI-powered data theft targeting hospitals, businesses - The Korea Times","archived_url":null,"attachment":"fingerprint"}],"per_field_confidence":{"system.harness":"C","system.integration_type":"D","system.intended_use":"C","system.autonomy_level":"D","system.developer":"D","system.deployment_context":"D","event.date_occurred":"C","event.near_miss":"D","event.responsible_party":"D","event.adversarial_actor":"C","event.agent_involved":"C","event.detection_method":"D","event.incident_class":"D","event.summary":"D","event.date_disclosed":"A","event.trigger":"D","impact.records_exposed":"C","impact.third_parties_affected_count":"C","impact.harm_class":"C","impact.affected_description":"C","impact.data_categories_exposed":"C","impact.severity":"D","context.denominator_available":"D","context.country":"C","impact.severity_because":"D"},"field_citations":{"system.harness":[{"source_index":0,"quote":"Early on A operated website vulnerability scanning tools directly, but later used an AI coding agent and an autonomous AI penetration testing system to breach 60 companies in just over 40 days, from Aug. 31 to the 13th of this month."}],"system.intended_use":[{"source_index":0,"quote":"The autonomous AI penetration testing system A used in the crimes was found to be the same tool used in a recent personal data breach in the financial sector."}],"system.integration_type":[{"source_index":0,"quote":"Early on A operated website vulnerability scanning tools directly, but later used an AI coding agent and an autonomous AI penetration testing system to breach 60 companies in just over 40 days, from Aug. 31 to the 13th of this month."}],"system.autonomy_level":[{"source_index":0,"quote":"Early on A operated website vulnerability scanning tools directly, but later used an AI coding agent and an autonomous AI penetration testing system to breach 60 companies in just over 40 days, from Aug. 31 to the 13th of this month."}],"event.date_occurred":[{"source_index":0,"quote":"The group is accused of hacking the websites of private academies, hospitals, golf courses and universities over about 13 months from September last year through this month, taking personal data and internal corporate documents."}],"event.detection_method":[{"source_index":0,"quote":"Police opened the investigation in June after receiving a complaint from one of the victimized companies."}],"event.near_miss":[{"source_index":0,"quote":"Using the stolen information as leverage, they threatened the companies and actually collected 300,000 won (about $210) from one of them, while an attempt to extort a total of 360 million won (about $250,000) failed, the investigation found."}],"event.adversarial_actor":[{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"event.incident_class":[{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"event.agent_involved":[{"source_index":0,"quote":"Early on A operated website vulnerability scanning tools directly, but later used an AI coding agent and an autonomous AI penetration testing system to breach 60 companies in just over 40 days, from Aug. 31 to the 13th of this month."}],"event.responsible_party":[{"source_index":1,"quote":"Police have busted a cybercrime ring that allegedly stole over 8 million pieces of personal information from dozens of businesses by using artificial intelligence (AI), officials said Monday."}],"event.summary":[{"source_index":1,"quote":"Seven suspects allegedly stole 8.2 million pieces of personal data and other internal records from over 90 entities, including hospitals, private academies and businesses, until recently from September last year, according to the Seoul Metropolitan Police Agency."},{"source_index":1,"quote":"Of the targeted entities, 38 suffered losses, with the group demanding a combined 360 million won ($272,000) from them."},{"source_index":0,"quote":"Police opened the investigation in June after receiving a complaint from one of the victimized companies."},{"source_index":0,"quote":"Police seized a laptop, burner phones and a wireless router from A's residence and recovered the stolen personal data stored on them."}],"impact.records_exposed":[{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"impact.third_parties_affected_count":[{"source_index":1,"quote":"Of the targeted entities, 38 suffered losses, with the group demanding a combined 360 million won ($272,000) from them."}],"impact.harm_class":[{"source_index":0,"quote":"The group is accused of hacking the websites of private academies, hospitals, golf courses and universities over about 13 months from September last year through this month, taking personal data and internal corporate documents."},{"source_index":0,"quote":"Using the stolen information as leverage, they threatened the companies and actually collected 300,000 won (about $210) from one of them, while an attempt to extort a total of 360 million won (about $250,000) failed, the investigation found."},{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"impact.affected_description":[{"source_index":0,"quote":"One of the companies that lost the most personal data, a funeral services provider, had 1.22 million records taken, and the data stolen from private academies included personal information on minors."}],"impact.data_categories_exposed":[{"source_index":0,"quote":"The group is accused of hacking the websites of private academies, hospitals, golf courses and universities over about 13 months from September last year through this month, taking personal data and internal corporate documents."}],"impact.severity_because":[{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"context.country":[{"source_index":0,"quote":"The Seoul Metropolitan Police Agency's cyber investigation division said on the 26th that it had detained the ringleader, a 32-year-old identified as A, and referred him to prosecutors on charges of violating the Information and Communications Network Act, extortion and attempted extortion, while six accomplices are under investigation without detention."}],"impact.severity":[{"source_index":0,"quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims."}],"event.date_disclosed":[{"source_index":0,"quote":"published: 2026-10-26"}]},"notes_on_gaps":"Model name, version and developer are not stated by any source; the harness is described only generically as an AI coding agent plus an autonomous AI penetration testing system. No source states the agent's tools, permissions scope, guardrails, deployment context, safeguard state, or whether the model was meant for production. No source states a failure_class mechanism (the AI was the attacker's instrument, not a malfunctioning agent), so failure_class and secondary classes are omitted; root_cause is omitted because no source names what failed. No source states duration, time to contain, operations paused, remediation, precursor events, input provenance, or a disclosure date. Third-party count conflicts: source 0 says 15 companies reported damage, source 1 says 38 suffered losses; 38 is written as the higher stated figure. Direct loss of $210 is the extortion actually collected; a further 360 million won (~$250,000) demand failed. Severity is major on many third parties and 8.2 million records; no single loss figure reaches the dollar bands. context.industry is left null because the victims span multiple sectors and the operator is a criminal group, not an industry operator. system.autonomy_level full-auto is classified from the description of the penetration-testing system as autonomous, not from a statement that no human watched the attacker's use. event.date_occurred: the source states the month only. event.trigger: human_misuse was classified, not stated; a trigger is never inferred, so it is unknown. impact.direct_loss_usd: the source gives 210 only as a bound ('about'); not stored as an exact count. system.tier: not set; no operator named and deployment_context is not a lab's. Sources disagree on impact.affected_description: [0] \"\\\"more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses\\\"; a funeral services provider lost 1.22 million records; data on minors was taken from private academies\", [1] \"over 90 entities, including hospitals, private academies and businesses; 38 suffered losses\"; impact.third_parties_affected_count: [0] \"15\", [1] \"38\". [aggregated by deepseek-chat, aggregate-2026-09-27.1, 2026-10-26] system.integration_type: classified from described behaviour. system.autonomy_level: a source states no person was in the loop while it ran (not: silence about a human is not a statement that none was there). system.developer: no source names the developer. system.deployment_context: no source states where it ran. event.near_miss: classified from described behaviour. event.responsible_party: third_party. event.detection_method: a source states the affected party noticed it first. event.incident_class: a source states an attacker, an injected instruction or a misused credential caused the system to act, or that the system's own boundary (sandbox, permissions, weights, accounts) was breached (not: an agent acting on a goal of its own with no external cause is agent_misalignment; a wrong action with no adversary and no breach is operational_error). event.summary: classified from described behaviour. event.trigger: no source states a cause. context.denominator_available: no denominator is available for this incident."},"context":{"industry":null,"org_size_band":null,"country":"KR","denominator_available":false,"denominator":null,"related_incident_ids":[],"systemic_exposure":null,"shared_model_id":null,"upstream_incident_id":null,"incident_evidence":null,"regulatory":null,"coverage":null},"narrative":{"steps":[{"step":"doing","text":"A cybercrime ring used an AI coding agent and an autonomous AI penetration-testing system to attack the websites of academies, hospitals, golf courses and universities, taking personal data and internal documents. The model and developer are not named.","quote":"Early on A operated website vulnerability scanning tools directly, but later used an AI coding agent and an autonomous AI penetration testing system to breach 60 companies in just over 40 days, from Aug. 31 to the 13th of this month.","source_index":0,"grade":"C"},{"step":"went_wrong","text":"The AI tools were used to breach more than 90 companies' websites and steal 8.2 million pieces of personal data, crossing the boundary of unauthorized access to victims' systems.","quote":"Police have arrested a group accused of using generative artificial intelligence to hack more than 90 businesses, including an affiliate of a large conglomerate as well as private academies, hospitals and golf courses, stealing 8.2 million pieces of personal data and demanding money from the victims.","source_index":0,"grade":"C"},{"step":"reached","text":"Data from over 90 businesses was taken, including 1.22 million records from a funeral services provider and minors' personal information from academies; victims were then threatened by email, calls and texts.","quote":"One of the companies that lost the most personal data, a funeral services provider, had 1.22 million records taken, and the data stolen from private academies included personal information on minors.","source_index":0,"grade":"C"},{"step":"caught","text":"Police opened an investigation in June after a complaint from one victimized company, then ran a comprehensive investigation as similar cases mounted nationwide.","quote":"Police opened the investigation in June after receiving a complaint from one of the victimized companies.","source_index":0,"grade":"C"},{"step":"done","text":"Police arrested the ringleader and accomplices, seized a laptop, burner phones and a wireless router, and recovered the stolen data; they plan to identify more victims and trace proceeds.","quote":"Police seized a laptop, burner phones and a wireless router from A's residence and recovered the stolen personal data stored on them.","source_index":0,"grade":"C"}],"model":"deepseek-chat","prompt_version":"aggregate-2026-09-27.1","extracted_at":"2026-10-26","source_urls":["https://en.sedaily.com/society/2026/10/26/self-taught-hacker-used-ai-to-steal-82-million-records","https://www.koreatimes.co.kr/southkorea/law-crime/20261026/cybercrime-ring-busted-over-ai-powered-data-theft-targeting-hospitals-businesses"]}}