{ "id": "AIBD-0178", "title": "India's DoT disconnects over 82 lakh mobile connections flagged by its AI facial-recognition tool ASTR", "summary": "DoT's indigenous ASTR tool matches subscriber photos to find connections taken by one person under different names; a Rajya Sabha reply (August 2025) counts more than 82 lakh disconnected after fai...", "date_observed": "2025-08-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Department of Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "category": "general benefit", "unexpected": false, "purpose": "Analyze, identify and weed out fake, forged and non-bonafide mobile connections to curb cyber crime.", "system": "ASTR, AI and facial recognition powered Solution for Telecom SIM Subscriber Verification", "model_version": null, "developer": "Department of Telecommunications, Government of India", "deployer": "Department of Telecommunications with telecom service providers", "location": null, "domain": "Telecom-enabled cyber financial fraud", "segment": "SIM subscriber verification", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Disconnection counts are aggregates. No measured reduction in fraud losses is documented." }, { "group": "organizational", "depth": null, "reason": "DoT and operators report disconnections and blacklisting without an evaluated outcome." } ], "ai_role": { "status": "assessed", "statement": "DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases." }, "evidence": [ { "kind": "press release", "citation": "Press Information Bureau, Ministry of Communications, written reply in Rajya Sabha by Dr Pemmasani Chandra Sekhar, 7 August 2025", "title": "Telecom-Related Cyber Frauds and Safety Measures", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153524", "date": "2025-08-07", "written_by": "makers", "quote": "disconnected more than 82 lakhs such connections through ASTR after they failed reverification" }, { "kind": "press release", "citation": "Press Information Bureau Chennai, release issued by M. Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. The Hans India, 9 October 2026.", "title": "Govt disconnects over 82 lakh fraudulent mobile connections via ASTR", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "date": "2026-10-09", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "model_version": null, "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "model_version": null, "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "model_version": null, "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] }, "paired_incident": null, "headline": "India's DoT disconnects over 82 lakh connections flagged by ASTR", "metric": "disconnected more than 82 lakh connections through ASTR after they failed re-verification", "comparator": null, "later": { "status": "persisted", "date": "2026-10-09", "note": "Minister of State Pemmasani restated at the India Mobile Congress that over 82 lakh fraudulent connections had been disconnected through ASTR.", "quote": "India has disconnected over 82 lakh fraudulent mobile connections through the Artificial Intelligence and Facial Recognition powered Telecom SIM Subscriber Verification (ASTR) tool, Union Minister of State for Communications and Rural Development Dr Chandra Sekhar Pemmasani said on Friday.", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Department_of_Telecommunications; https://en.wikipedia.org/wiki/Department_of_Telecommunications", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Department of Telecommunications.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, a registry entry and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0178", "catalog_version": "1.0.0", "source_fingerprint": "0ee3171393b93d69f5590e3a237ee805a460dd658fb47df72b475010d5019a9c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0178-source-0001", "AIBD-0178-source-0002", "AIBD-0178-source-0003", "AIBD-0178-source-0004", "AIBD-0178-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Department of Telecommunications, Government of India", "deployer": "Department of Telecommunications with telecom service providers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "DoT describes ASTR as an indigenous AI and big-data analytic tool. 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ASTR.", "quote": "India has disconnected over 82 lakh fraudulent mobile connections through the Artificial Intelligence and Facial Recognition powered Telecom SIM Subscriber Verification (ASTR) tool, Union Minister of State for Communications and Rural Development Dr Chandra Sekhar Pemmasani said on Friday.", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0178" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources 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Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Disconnection counts are aggregates. No measured reduction in fraud losses is documented." }, { "group": "organizational", "reason": "DoT and operators report disconnections and blacklisting without an evaluated outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Analyze, identify and weed out fake, forged and non-bonafide mobile connections to curb cyber crime." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Analyze, identify and weed out fake, forged and non-bonafide mobile connections to curb cyber crime." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-07", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Department_of_Telecommunications; https://en.wikipedia.org/wiki/Department_of_Telecommunications", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Department of Telecommunications.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Department_of_Telecommunications; https://en.wikipedia.org/wiki/Department_of_Telecommunications", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Department of Telecommunications.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Telecom-enabled cyber financial fraud", "segment": "SIM subscriber verification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau, Ministry of Communications, written reply in Rajya Sabha by Dr Pemmasani Chandra Sekhar, 7 August 2025", "title": "Telecom-Related Cyber Frauds and Safety Measures", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153524", "date": "2025-08-07", "written_by": "makers", "quote": "disconnected more than 82 lakhs such connections through ASTR after they failed reverification" }, { "kind": "press release", "citation": "Press Information Bureau Chennai, release issued by M. Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. The Hans India, 9 October 2026.", "title": "Govt disconnects over 82 lakh fraudulent mobile connections via ASTR", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "date": "2026-10-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0178-source-0001", "AIBD-0178-source-0002", "AIBD-0178-source-0003", "AIBD-0178-source-0004", "AIBD-0178-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau, Ministry of Communications, written reply in Rajya Sabha by Dr Pemmasani Chandra Sekhar, 7 August 2025", "title": "Telecom-Related Cyber Frauds and Safety Measures", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153524", "date": "2025-08-07", "written_by": "makers", "quote": "disconnected more than 82 lakhs such connections through ASTR after they failed reverification" }, { "kind": "press release", "citation": "Press Information Bureau Chennai, release issued by M. Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. The Hans India, 9 October 2026.", "title": "Govt disconnects over 82 lakh fraudulent mobile connections via ASTR", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "date": "2026-10-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "DoT's indigenous ASTR tool matches subscriber photos to find connections taken by one person under different names; a Rajya Sabha reply (August 2025) counts more than 82 lakh disconnected after fai...", "account": "The Department of Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ASTR, AI and facial recognition powered Solution for Telecom SIM Subscriber Verification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Department of Telecommunications, Government of India" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "India's DoT disconnects over 82 lakh mobile connections flagged by its AI facial-recognition tool ASTR", "headline": "India's DoT disconnects over 82 lakh connections flagged by ASTR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0ee3171393b93d69f5590e3a237ee805a460dd658fb47df72b475010d5019a9c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Department of Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }