{"adaptive_threat_observation_containment_concept":{"deception_sandbox":{"automatic_learning_authority":false,"production_return_path":false,"purpose":"Observe suspicious behavior and attack-path choices without exposing productive authority.","synthetic_only":true},"laws":["UNKNOWN_IS_NOT_MALICIOUS","OBSERVATION_IS_NOT_AUTHORITY","ATTACK_OBSERVATION_BECOMES_CANDIDATE_INTELLIGENCE_ONLY","SANDBOX_HAS_NO_AUTHORITY_PATH_BACK_TO_PRODUCTION","NO_REAL_CUSTOMER_DATA_OR_PRODUCTION_CREDENTIALS_IN_DECEPTION_DOMAIN"],"response_classes":["OBSERVE_ONLY","CONTAIN_OR_ISOLATE","HARD_CUT"],"stages":["OBSERVE","CLASSIFY_AUTHORIZED_EXPECTED_ANOMALOUS_UNKNOWN","RISK_BOUND_RESPONSE","CONTROLLED_DECEPTION_REDIRECTION","ISOLATED_OBSERVATION_SANDBOX","ATTACK_PATH_EVIDENCE","GAP_CANDIDATE","CONTAIN_OR_HARD_CUT_WHEN_AUTHORIZED","GLOBAL_LAST_GOOD_RECOVERY_WHEN_APPLICABLE","REOBSERVE","QUALIFY_BEFORE_LEARN"],"state":"CAPABILITY_FAMILY_CANDIDATE_UNIMPLEMENTED_AS_END_TO_END_SECURITY_PRODUCT"},"atlas_interpretation":{"classification":"ATLAS_SYSTEMIC_INTERPRETATION_NOT_EXTERNAL_FACT","legacy_boundary":"Legacy implementations are not preserved as authority. Relevant behaviour, data meaning, rules and capabilities are observed and qualified before composition into the ATLAS system landscape.","statement":"A grown digital landscape can contain poorly understood boundaries, legacy assumptions and authority gaps. Machine-speed actors may search those seams faster than human operators can reason about them."},"authority":false,"decision":"PUBLIC_PROJECTION_OF_FACTORY_V868_CONCEPT_AUTHORITY_NO_DEFENSIVE_EFFECT_CLAIM","existing_factory_primitives":[{"id":"FAILED_CLOSE_AUTHORITY_BOUNDARIES","state":"EXISTING_PRIMITIVE_NOT_CYBER_DEFENSE_EFFECT"},{"id":"GAR_CAS_EVIDENCE_BINDING","state":"EXISTING_PRIMITIVE_NOT_CYBER_DEFENSE_EFFECT"},{"id":"GLOBAL_LAST_GOOD_AND_ROLLBACK","state":"EXISTING_PRIMITIVE_NOT_GENERAL_ATTACK_RECOVERY_CLAIM"},{"id":"QUARANTINE_REPLAY_AND_REOBSERVATION","state":"EXISTING_PRIMITIVE_NOT_GENERAL_ATTACK_CONTAINMENT_CLAIM"},{"id":"NETWORK_SCOPE_SEPARATION","state":"EXISTING_PRIMITIVE_NOT_IDS_IPS_CLAIM"}],"promotion_boundary":"NO_CLAIM_THAT_ATLAS_CURRENTLY_DETECTS_REDIRECTS_CONTAINS_OR_ROLLS_BACK_REAL_AGENTIC_ATTACKS; NO_CLAIM_OF_UNIVERSAL_SECURITY; CONCEPT_REQUIRES_IMPLEMENTATION_AND_ATTACK_RED_TEAM_RECEIPTS_BEFORE_EFFECT_PROMOTION","published_at":"2026-09-05","schema":"atlas.public.digital_threat_intelligence.v1.machine.json","security_product_inheritance_rule":{"required_declarations":["THREAT_MODEL","AUTHORITY_BOUNDARIES","OBSERVATION_SURFACES","CONTAINMENT_OPTIONS","RECOVERY_BOUNDARY","DATA_PRESERVATION_BOUNDARY","EVIDENCE_STATUS","EXTERNAL_EFFECT_STATUS"],"rule":"SECURITY_RELEVANT_PRODUCTS_MUST_FAIL_CLOSE_WHERE_AUTHORITY_OR_EFFECT_IS_UNPROVEN","scope":"ATLAS_AND_ALL_SECURITY_RELEVANT_PRODUCTS"},"source_observations":[{"date":"2026-07-27","id":"microsoft-2026-07-27","observation_de":"Microsoft beschreibt autonome Systeme, die kontinuierlich denken, sich anpassen und handeln können, und fordert Security, die fortlaufend wahrnimmt, schlussfolgert und mit Maschinengeschwindigkeit handelt.","observation_en":"Microsoft describes autonomous systems that can reason, adapt, and operate continuously, and argues that security must continuously perceive, reason, and act at machine speed.","publisher":"Microsoft","url":"https://blogs.microsoft.com/blog/2026/07/27/rethinking-security-for-the-age-of-ai/"},{"date":"2026-08-20","id":"ncsc-2026-08-20","observation_de":"Das britische NCSC fordert, Kontrollen und Annahmen bei agentischer KI laufend zu überprüfen und den Autonomiegrad am tatsächlichen Risiko auszurichten.","observation_en":"The UK NCSC says controls and assumptions for agentic AI should be reviewed continuously and autonomy should remain proportionate to actual risk.","publisher":"UK NCSC","url":"https://www.ncsc.gov.uk/blogs/managing-the-cyber-risk-of-agentic-ai"},{"date":"2026-08-04","id":"ncsc-2026-08-04","observation_de":"Das NCSC warnt, dass Erkennung allein nach einem Vorfall nicht genügt, und fordert Echtzeit-Aufsicht sowie klare Reaktionspläne für unerwartetes Verhalten.","observation_en":"The NCSC warns that detection alone after an incident is insufficient and calls for real-time oversight and clear response plans for unexpected behaviour.","publisher":"UK NCSC","url":"https://www.ncsc.gov.uk/news/ncsc-statement-in-response-to-recent-incidents-resulting-from-frontier-ai-evaluations"},{"date":"2026-09-01","id":"owasp-acs-2026-09-01","observation_de":"Der OWASP Agent Control Standard fordert, Agenten inspizierbar, nachvollziehbar und instrumentierbar zu machen und ihr Verhalten zur Laufzeit kontrollieren zu können.","observation_en":"The OWASP Agent Control Standard calls for agents to be inspectable, traceable, instrumentable, and controllable at runtime.","publisher":"OWASP GenAI Security Project","url":"https://genai.owasp.org/resource/agent-control-standard-acs/"}],"status":"CURRENT_ANALYSIS_CONCEPT_NOT_PRODUCT_SECURITY_CLAIM","topic_id":"agentic_ai_and_machine_speed_attack_surface_2026_09","updated_at":"2026-09-05","version":"V868","semantic_discovery_v871":"/cyber-threat-semantic-discovery-v871.machine.json"}