{
 "public_id": "AIR-2026-0274",
 "incident_id": "2026-10-south-korea-artex-ai-assisted-bank-campaign",
 "date_disclosed": "2026-10-06",
 "date_occurred": null,
 "title": "Suspected AI-assisted South Korean bank campaign exposed customer contact and borrowing records",
 "class": "in_the_wild",
 "attack_surface": "autonomous_ops",
 "initial_vector": "operator_misuse_ai_penetration_testing_tool",
 "agent_capability_abused": [
  "ai_assisted_vulnerability_scanning",
  "penetration_testing_tooling"
 ],
 "target_product": "ARTEX with unspecified large language models in a reported bank-intrusion campaign",
 "target_vendor": null,
 "autonomy_level": "assistant",
 "impact_realized": true,
 "impact_type": [
  "data_exfiltration"
 ],
 "blast_radius": "The October 16 account reports roughly 100,000 customer contact and borrowing records across at least 16 financial institutions; the October 11 investigation describes a narrower seven-institution scope",
 "cve": [],
 "taxonomy": {
  "mitre_atlas": [],
  "labels": [
   "regional_campaign",
   "backfill",
   "suspected_ai_assistance",
   "human_led_tool_use",
   "attribution_uncertain",
   "reported_customer_data_exposure"
  ],
  "owasp_asi": [
   "ASI02"
  ]
 },
 "defense_present": null,
 "defense_bypassed": null,
 "fix_shipped": null,
 "primary_sources": [
  "https://www.straitstimes.com/asia/east-asia/south-koreas-lee-says-ai-appears-to-have-been-used-in-bank-hacks",
  "https://www.straitstimes.com/asia/east-asia/ai-powered-attacks-on-south-korean-financial-sectors-linked-to-chinese-ddos-group-report",
  "https://www.straitstimes.com/asia/east-asia/millions-of-personal-records-in-japan-south-korea-exposed-amid-surge-in-ai-powered-cyberattacks"
 ],
 "verified_quote": "The police have launched a full-scale investigation into the hacking attacks against commercial banks that led to a breach of customers’ personal information, the Yonhap news agency reported on Oct 6.",
 "confidence": "medium",
 "notes": "October 6 is the first verified AI-related disclosure in the checked sources, not a claim to the earliest report worldwide: that Reuters account also mentions October 2 bank-attack reporting. The October 11 Korea Herald account and October 16 roundup add suspected ARTEX and LLM-assisted vulnerability scanning, including a reported DeepSeek role. The campaign therefore predates the weekly window and belongs in backfill. Attacks are described across late September and early October; there is no defensible single occurrence date. The later roundup reports roughly 100,000 contact and borrowing records at at least 16 institutions, while the October 11 investigation discusses seven institutions; their scopes are different and should not be reconciled into a fabricated total. Passwords, credit-card numbers and transaction histories were reportedly not compromised. Customer data exposure is reported as actual, but AI attribution and the operators' identities remain uncertain; automated scanning is not proof of an autonomous end-to-end breach. The campaign is coded as human-led use of AI output, with a debatable agency boundary. News syndication supplies the evidence, not a fetched regulator or forensic report. The Japanese incidents in the roundup lack per-case agent mechanisms and are not split into additional AI intrusions.",
 "risk_category": "privacy",
 "risk_secondary": [],
 "risk_subcategory": "Data Exfiltration via Context",
 "risk_sub_secondary": [],
 "ai_entity": "generative",
 "agency": "human_acted_on_output",
 "agency_debatable": true,
 "agency_reason": "Reporting attributes the intrusions to operators using ARTEX and LLM-assisted scanning, without showing an AI executing the breaches. Human-led use of output is the conservative stratum; automated scanning leaves agent_acted plausible but unproven without direct tool traces",
 "vector_family": "misuse",
 "vector_detail": "operator_misuse_ai_penetration_testing_tool",
 "guardrail_kind": [
  "unknown"
 ],
 "guardrail_outcome": "silent",
 "xrefs": {
  "aiid": [],
  "atlas": [],
  "cve": [],
  "ghsa": []
 },
 "primary_asi": "ASI02",
 "agent_framework": "unknown",
 "model_provider": "multiple",
 "model_name": "",
 "detection_mechanism": "unknown",
 "tool_access": "unknown",
 "financial_loss_band": "unknown",
 "eai_category": "data_exfiltration_channels",
 "eai_domain": "privacy",
 "eai_secondary": [],
 "eai_reason": "subcategory: Data Exfiltration via Context",
 "asi_curated": [],
 "asi_scope": "in_scope",
 "asi_provenance": "rule",
 "asi_reason": "ASI02 (impact=tool_misuse)",
 "submitted_by": "EAI Internal"
}