[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71F9DD95FAP2KNDK8E04YSC":3,"skill-same:01M71F9DD95FAP2KNDK8E04YSC":93},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":66,"commitSha":67,"skillDirectory":68,"forksCount":14,"repositoryHtmlUrl":69,"repositoryHomepageUrl":6,"ownerHtmlUrl":70,"ownerBlogUrl":6,"ownerDescription":71,"updatedAt":72,"install":73,"resources":86},"01M71F9DD95FAP2KNDK8E04YSC","static-analysis-yara-analyze",null,"Persistent YARA rule lifecycle management with PostgreSQL backend. Create, test, optimize, and manage YARA rules derived from IOCs, memory patterns, and binary analysis. Integrates with yara_rule_generator, yara_rule_optimizer, and yara_rule_tester hooks across sessions.","DCx7C5\u002Fai-marketplace","DCx7C5","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42419559?v=4","01M71C01G2AZV3NTNGWAWSHJPP","DC","01M71C01GQW6G50S2BYMS7PP3E",0,"MIT","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fmalware\u002Fstatic-analysis\u002Fyara\u002Fanalyze\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"static analysis yara analyze","analysis","analyze","static analysis","yara","static","read","optimize","create","postgresql","mitre-attack","across","optimizer","websearch","Bash","yara-rules","hooks","memory","static-analysis","shared","2026-11-10 10:12:30",false,"---\nname: static-analysis-yara-analyze\ndescription: Persistent YARA rule lifecycle management with PostgreSQL backend. Create, test, optimize, and manage YARA rules derived from IOCs, memory patterns, and binary analysis. Integrates with yara_rule_generator, yara_rule_optimizer, and yara_rule_tester hooks across sessions.\nmodel: sonnet\nmaxTurns: 20\ntools:\n  - Read\n  - Write\n  - Bash\n  - Glob\n  - Grep\n  - WebSearch\nskills:\n  - shared-memory\n  - threats\u002Fmitre-attack-mapper\ntags:\n- malware\n- static-analysis\n- yara\n- yara-rules\nmitre_attack:\n- T1027\nnist_csf: []\ncapec: []\n---\n\n# YARA Rules Skill — Persistent Rule Lifecycle Management\n\n**Purpose:** Store, retrieve, test, and optimize YARA rules across sessions using the PostgreSQL backend.\n\n---\n\n## Database Schema\n\n### Table: `yara_rules`\n\n```sql\nSELECT column_name, data_type, is_nullable\nFROM information_schema.columns\nWHERE table_name = 'yara_rules'\nORDER BY ordinal_position;\n```\n\n| Column                    | Type                   | Description                                                              |\n|---------------------------|------------------------|--------------------------------------------------------------------------|\n| `id`                      | integer PK             | Auto-increment                                                           |\n| `rule_id`                 | varchar(100) UNIQUE    | Stable ID, e.g. `YARA-20260407-0001`                                     |\n| `name`                    | varchar(255)           | Rule name as in `.yar` file                                              |\n| `description`             | text                   | Human-readable purpose                                                   |\n| `author`                  | varchar(255)           | Generating agent or operator                                             |\n| `tags`                    | jsonb                  | `[\"rootkit\", \"ebpf\", \"persistence\"]`                                     |\n| `rule_text`               | text                   | Full YARA source                                                         |\n| `rule_file_path`          | varchar(500)           | Relative path on disk                                                    |\n| `status`                  | varchar                | `draft \u002F tested \u002F active \u002F false_positive \u002F retired \u002F optimized`         |\n| `source`                  | varchar                | `ioc_derived \u002F memory_pattern \u002F binary_analysis \u002F manual \u002F threat_intel` |\n| `severity`                | varchar                | `info \u002F low \u002F medium \u002F high \u002F critical`                                  |\n| `confidence`              | varchar                | `low \u002F medium \u002F high \u002F confirmed`                                        |\n| `mitre_techniques`        | jsonb                  | `[\"T1055\", \"T1014\"]`                                                     |\n| `mitre_tactics`           | jsonb                  | `[\"defense_evasion\", \"persistence\"]`                                     |\n| `ioc_source_ids`          | jsonb                  | IOCEntry.ioc_id values that generated this rule                          |\n| `generated_by_session_id` | FK → forensic_sessions | Session that created the rule                                            |\n| `project_id`              | FK → forensic_projects | Owning project                                                           |\n| `last_tested_at`          | timestamptz            | When last tested                                                         |\n| `test_target`             | varchar(500)           | Last scanned artifact\u002Fpath                                               |\n| `test_hits`               | integer                | True-positive hits from last run                                         |\n| `test_false_positives`    | integer                | FPs from last run                                                        |\n| `test_notes`              | text                   | Tester notes                                                             |\n| `optimization_notes`      | text                   | Optimizer notes                                                          |\n| `performance_score`       | float                  | 0.0–1.0 (higher = better)                                                |\n| `created_at`              | timestamptz            | Auto                                                                     |\n| `updated_at`              | timestamptz            | Auto                                                                     |\n\n### Table: `yara_test_runs`\n\n| Column             | Type                   | Description                             |\n|--------------------|------------------------|-----------------------------------------|\n| `run_id`           | varchar(100) UNIQUE    | e.g. `RUN-20260407-001`                 |\n| `rule_id`          | FK → yara_rules        | The rule being tested                   |\n| `session_id`       | FK → forensic_sessions | Session running the test                |\n| `target_path`      | varchar(500)           | Scanned path                            |\n| `hits`             | integer                | TP count                                |\n| `false_positives`  | integer                | FP count                                |\n| `scan_duration_ms` | integer                | Scan time                               |\n| `raw_output`       | text                   | Raw `yara` CLI stdout                   |\n| `verdict`          | varchar(50)            | `pass \u002F fail \u002F fp_heavy \u002F inconclusive` |\n| `run_at`           | timestamptz            | Auto                                    |\n\n---\n\n## Standard Workflows\n\n### 1 — Save a Generated Rule to DB\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nINSERT INTO yara_rules (\n    rule_id, name, description, rule_text,\n    status, source, severity, confidence,\n    mitre_techniques, tags, author\n) VALUES (\n    'YARA-$(date +%Y%m%d)-$(shuf -i 1000-9999 -n1)',\n    'Suspicious_LD_PRELOAD',\n    'Detects LD_PRELOAD injection strings in ELF binaries and memory dumps',\n    'rule Suspicious_LD_PRELOAD {\n    meta:\n        description = \\\"LD_PRELOAD injection indicator\\\"\n        severity = \\\"high\\\"\n    strings:\n        \\$s = \\\"LD_PRELOAD\\\" ascii wide nocase\n        \\$p = \\\"\u002Fetc\u002Fld.so.preload\\\" ascii\n    condition:\n        any of them\n}',\n    'draft', 'memory_pattern', 'high', 'medium',\n    '[\\\"T1574.006\\\"]', '[\\\"persistence\\\",\\\"privilege_escalation\\\"]',\n    'memory-analyst'\n) RETURNING rule_id, name, status;\n\"\n```\n\n### 2 — List Active Rules for Current Project\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nSELECT rule_id, name, severity, confidence, status, test_hits,\n       array_to_string(tags::text[], ',') AS tags\nFROM yara_rules\nWHERE status IN ('active', 'tested', 'optimized')\nORDER BY severity DESC, confidence DESC;\n\"\n```\n\n### 3 — Test a Rule and Record Results\n\n```bash\n# Run YARA against a target\nRULE_FILE=\"\u002Ftmp\u002Fcybersec-current.yar\"\nTARGET=\"\u002Fproc\"                         # or a memory dump, binary, etc.\n\n# Export rule from DB to file\npsql -U cybersec -d cybersec_forensics -t -c \\\n    \"SELECT rule_text FROM yara_rules WHERE rule_id = 'YARA-20260407-1234';\" \\\n    > \"$RULE_FILE\"\n\n# Run test (requires root for \u002Fproc)\nHITS=$(yara -r \"$RULE_FILE\" \"$TARGET\" 2>\u002Fdev\u002Fnull | wc -l)\n\n# Record test run\npsql -U cybersec -d cybersec_forensics -c \"\nINSERT INTO yara_test_runs (run_id, rule_id, target_path, hits, verdict, raw_output)\nSELECT 'RUN-$(date +%Y%m%d%H%M%S)',\n       id, '$TARGET', $HITS,\n       CASE WHEN $HITS > 0 THEN 'pass' ELSE 'inconclusive' END,\n       ''\nFROM yara_rules WHERE rule_id = 'YARA-20260407-1234';\n\nUPDATE yara_rules\nSET last_tested_at = NOW(),\n    test_hits = $HITS,\n    test_target = '$TARGET',\n    status = CASE WHEN $HITS > 0 THEN 'tested' ELSE status END\nWHERE rule_id = 'YARA-20260407-1234';\n\"\n```\n\n### 4 — Promote Rule to ACTIVE\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nUPDATE yara_rules\nSET status = 'active', confidence = 'high', updated_at = NOW()\nWHERE rule_id = 'YARA-20260407-1234'\n  AND test_hits > 0\n  AND test_false_positives = 0;\n\"\n```\n\n### 5 — Export All Active Rules to a Single .yar Bundle\n\n```bash\npsql -U cybersec -d cybersec_forensics -t -c \\\n    \"SELECT rule_text FROM yara_rules WHERE status = 'active' ORDER BY severity DESC;\" \\\n    > .\u002Fcybersec-shared\u002Fyara-active-bundle.yar\n\necho \"Exported $(grep -c '^rule ' .\u002Fcybersec-shared\u002Fyara-active-bundle.yar) active rules\"\n```\n\n### 6 — Link Rule to IOC Source\n\n```bash\n# After generating from an IOCEntry\npsql -U cybersec -d cybersec_forensics -c \"\nUPDATE yara_rules\nSET ioc_source_ids = ioc_source_ids || '[\\\"IOC-2026-00123\\\"]'::jsonb\nWHERE rule_id = 'YARA-20260407-1234';\n\"\n```\n\n---\n\n## Rule Lifecycle\n\n```\nIOC discovered \u002F memory pattern found \u002F binary analyzed\n        │\n        ▼\nyara_rule_generator.py → INSERT INTO yara_rules (status='draft')\n        │\n        ▼\nyara_rule_tester.py    → INSERT INTO yara_test_runs\n                       → UPDATE yara_rules SET status='tested', test_hits=N\n        │\n        ▼\nyara_rule_optimizer.py → UPDATE yara_rules SET\n                             status='optimized',\n                             performance_score=0.95,\n                             optimization_notes='...'\n        │\n        ▼\nOperator promotes      → UPDATE yara_rules SET status='active'\n        │\n        ▼\nSession end sync       → Export active bundle → cybersec-shared\u002Fyara-active-bundle.yar\n```\n\n---\n\n## Integration with Agents\n\n- **@reverse-engineer** → generates rules from binary signatures via `yara_rule_generator.py`\n- **@memory-analyst** → generates rules from memory patterns and shellcode strings\n- **@hunter** → promotes rules after cross-validation, queries active bundle before scan\n\nWhen CYBERSEC-AGENT calls this skill, it should:\n1. Load `cybersec-shared\u002Fyara-active-bundle.yar` at investigation start\n2. After any binary\u002Fmemory finding, trigger `yara_rule_generator.py`\n3. Test new rules immediately with `yara_rule_tester.py`\n4. Promote confirmed rules via the SQL above\n5. At session end, re-export the active bundle\n\n---\n\n## Quick Stats Query\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nSELECT status, COUNT(*) as rules,\n       SUM(test_hits) as total_hits,\n       ROUND(AVG(performance_score)::numeric, 2) as avg_perf\nFROM yara_rules\nGROUP BY status\nORDER BY status;\n\"\n```\n\n","# YARA Rules Skill — Persistent Rule Lifecycle Management\n\n**Purpose:** Store, retrieve, test, and optimize YARA rules across sessions using the PostgreSQL backend.\n\n---\n\n## Database Schema\n\n### Table: `yara_rules`\n\n```sql\nSELECT column_name, data_type, is_nullable\nFROM information_schema.columns\nWHERE table_name = 'yara_rules'\nORDER BY ordinal_position;\n```\n\n| Column                    | Type                   | Description                                                              |\n|---------------------------|------------------------|--------------------------------------------------------------------------|\n| `id`                      | integer PK             | Auto-increment                                                           |\n| `rule_id`                 | varchar(100) UNIQUE    | Stable ID, e.g. `YARA-20260407-0001`                                     |\n| `name`                    | varchar(255)           | Rule name as in `.yar` file                                              |\n| `description`             | text                   | Human-readable purpose                                                   |\n| `author`                  | varchar(255)           | Generating agent or operator                                             |\n| `tags`                    | jsonb                  | `[\"rootkit\", \"ebpf\", \"persistence\"]`                                     |\n| `rule_text`               | text                   | Full YARA source                                                         |\n| `rule_file_path`          | varchar(500)           | Relative path on disk                                                    |\n| `status`                  | varchar                | `draft \u002F tested \u002F active \u002F false_positive \u002F retired \u002F optimized`         |\n| `source`                  | varchar                | `ioc_derived \u002F memory_pattern \u002F binary_analysis \u002F manual \u002F threat_intel` |\n| `severity`                | varchar                | `info \u002F low \u002F medium \u002F high \u002F critical`                                  |\n| `confidence`              | varchar                | `low \u002F medium \u002F high \u002F confirmed`                                        |\n| `mitre_techniques`        | jsonb                  | `[\"T1055\", \"T1014\"]`                                                     |\n| `mitre_tactics`           | jsonb                  | `[\"defense_evasion\", \"persistence\"]`                                     |\n| `ioc_source_ids`          | jsonb                  | IOCEntry.ioc_id values that generated this rule                          |\n| `generated_by_session_id` | FK → forensic_sessions | Session that created the rule                                            |\n| `project_id`              | FK → forensic_projects | Owning project                                                           |\n| `last_tested_at`          | timestamptz            | When last tested                                                         |\n| `test_target`             | varchar(500)           | Last scanned artifact\u002Fpath                                               |\n| `test_hits`               | integer                | True-positive hits from last run                                         |\n| `test_false_positives`    | integer                | FPs from last run                                                        |\n| `test_notes`              | text                   | Tester notes                                                             |\n| `optimization_notes`      | text                   | Optimizer notes                                                          |\n| `performance_score`       | float                  | 0.0–1.0 (higher = better)                                                |\n| `created_at`              | timestamptz            | Auto                                                                     |\n| `updated_at`              | timestamptz            | Auto                                                                     |\n\n### Table: `yara_test_runs`\n\n| Column             | Type                   | Description                             |\n|--------------------|------------------------|-----------------------------------------|\n| `run_id`           | varchar(100) UNIQUE    | e.g. `RUN-20260407-001`                 |\n| `rule_id`          | FK → yara_rules        | The rule being tested                   |\n| `session_id`       | FK → forensic_sessions | Session running the test                |\n| `target_path`      | varchar(500)           | Scanned path                            |\n| `hits`             | integer                | TP count                                |\n| `false_positives`  | integer                | FP count                                |\n| `scan_duration_ms` | integer                | Scan time                               |\n| `raw_output`       | text                   | Raw `yara` CLI stdout                   |\n| `verdict`          | varchar(50)            | `pass \u002F fail \u002F fp_heavy \u002F inconclusive` |\n| `run_at`           | timestamptz            | Auto                                    |\n\n---\n\n## Standard Workflows\n\n### 1 — Save a Generated Rule to DB\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nINSERT INTO yara_rules (\n    rule_id, name, description, rule_text,\n    status, source, severity, confidence,\n    mitre_techniques, tags, author\n) VALUES (\n    'YARA-$(date +%Y%m%d)-$(shuf -i 1000-9999 -n1)',\n    'Suspicious_LD_PRELOAD',\n    'Detects LD_PRELOAD injection strings in ELF binaries and memory dumps',\n    'rule Suspicious_LD_PRELOAD {\n    meta:\n        description = \\\"LD_PRELOAD injection indicator\\\"\n        severity = \\\"high\\\"\n    strings:\n        \\$s = \\\"LD_PRELOAD\\\" ascii wide nocase\n        \\$p = \\\"\u002Fetc\u002Fld.so.preload\\\" ascii\n    condition:\n        any of them\n}',\n    'draft', 'memory_pattern', 'high', 'medium',\n    '[\\\"T1574.006\\\"]', '[\\\"persistence\\\",\\\"privilege_escalation\\\"]',\n    'memory-analyst'\n) RETURNING rule_id, name, status;\n\"\n```\n\n### 2 — List Active Rules for Current Project\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nSELECT rule_id, name, severity, confidence, status, test_hits,\n       array_to_string(tags::text[], ',') AS tags\nFROM yara_rules\nWHERE status IN ('active', 'tested', 'optimized')\nORDER BY severity DESC, confidence DESC;\n\"\n```\n\n### 3 — Test a Rule and Record Results\n\n```bash\n# Run YARA against a target\nRULE_FILE=\"\u002Ftmp\u002Fcybersec-current.yar\"\nTARGET=\"\u002Fproc\"                         # or a memory dump, binary, etc.\n\n# Export rule from DB to file\npsql -U cybersec -d cybersec_forensics -t -c \\\n    \"SELECT rule_text FROM yara_rules WHERE rule_id = 'YARA-20260407-1234';\" \\\n    > \"$RULE_FILE\"\n\n# Run test (requires root for \u002Fproc)\nHITS=$(yara -r \"$RULE_FILE\" \"$TARGET\" 2>\u002Fdev\u002Fnull | wc -l)\n\n# Record test run\npsql -U cybersec -d cybersec_forensics -c \"\nINSERT INTO yara_test_runs (run_id, rule_id, target_path, hits, verdict, raw_output)\nSELECT 'RUN-$(date +%Y%m%d%H%M%S)',\n       id, '$TARGET', $HITS,\n       CASE WHEN $HITS > 0 THEN 'pass' ELSE 'inconclusive' END,\n       ''\nFROM yara_rules WHERE rule_id = 'YARA-20260407-1234';\n\nUPDATE yara_rules\nSET last_tested_at = NOW(),\n    test_hits = $HITS,\n    test_target = '$TARGET',\n    status = CASE WHEN $HITS > 0 THEN 'tested' ELSE status END\nWHERE rule_id = 'YARA-20260407-1234';\n\"\n```\n\n### 4 — Promote Rule to ACTIVE\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nUPDATE yara_rules\nSET status = 'active', confidence = 'high', updated_at = NOW()\nWHERE rule_id = 'YARA-20260407-1234'\n  AND test_hits > 0\n  AND test_false_positives = 0;\n\"\n```\n\n### 5 — Export All Active Rules to a Single .yar Bundle\n\n```bash\npsql -U cybersec -d cybersec_forensics -t -c \\\n    \"SELECT rule_text FROM yara_rules WHERE status = 'active' ORDER BY severity DESC;\" \\\n    > .\u002Fcybersec-shared\u002Fyara-active-bundle.yar\n\necho \"Exported $(grep -c '^rule ' .\u002Fcybersec-shared\u002Fyara-active-bundle.yar) active rules\"\n```\n\n### 6 — Link Rule to IOC Source\n\n```bash\n# After generating from an IOCEntry\npsql -U cybersec -d cybersec_forensics -c \"\nUPDATE yara_rules\nSET ioc_source_ids = ioc_source_ids || '[\\\"IOC-2026-00123\\\"]'::jsonb\nWHERE rule_id = 'YARA-20260407-1234';\n\"\n```\n\n---\n\n## Rule Lifecycle\n\n```\nIOC discovered \u002F memory pattern found \u002F binary analyzed\n        │\n        ▼\nyara_rule_generator.py → INSERT INTO yara_rules (status='draft')\n        │\n        ▼\nyara_rule_tester.py    → INSERT INTO yara_test_runs\n                       → UPDATE yara_rules SET status='tested', test_hits=N\n        │\n        ▼\nyara_rule_optimizer.py → UPDATE yara_rules SET\n                             status='optimized',\n                             performance_score=0.95,\n                             optimization_notes='...'\n        │\n        ▼\nOperator promotes      → UPDATE yara_rules SET status='active'\n        │\n        ▼\nSession end sync       → Export active bundle → cybersec-shared\u002Fyara-active-bundle.yar\n```\n\n---\n\n## Integration with Agents\n\n- **@reverse-engineer** → generates rules from binary signatures via `yara_rule_generator.py`\n- **@memory-analyst** → generates rules from memory patterns and shellcode strings\n- **@hunter** → promotes rules after cross-validation, queries active bundle before scan\n\nWhen CYBERSEC-AGENT calls this skill, it should:\n1. Load `cybersec-shared\u002Fyara-active-bundle.yar` at investigation start\n2. After any binary\u002Fmemory finding, trigger `yara_rule_generator.py`\n3. Test new rules immediately with `yara_rule_tester.py`\n4. Promote confirmed rules via the SQL above\n5. At session end, re-export the active bundle\n\n---\n\n## Quick Stats Query\n\n```bash\npsql -U cybersec -d cybersec_forensics -c \"\nSELECT status, COUNT(*) as rules,\n       SUM(test_hits) as total_hits,\n       ROUND(AVG(performance_score)::numeric, 2) as avg_perf\nFROM yara_rules\nGROUP BY status\nORDER BY status;\n\"\n```\n\n",{"name":5,"tags":49,"capec":51,"model":52,"tools":53,"skills":59,"maxTurns":62,"nist_csf":63,"description":7,"mitre_attack":64},[50,42,28,39],"malware",[],"sonnet",[54,55,38,56,57,58],"Read","Write","Glob","Grep","WebSearch",[60,61],"shared-memory","threats\u002Fmitre-attack-mapper",20,[],[65],"T1027","main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fmalware\u002Fstatic-analysis\u002Fyara\u002Fanalyze","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 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CommandLineEventConsumer, and permanent subscriptions in the WMI repository.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fpersistence\u002Fdetect\u002FSKILL.md",[],[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119],"services","detect","services wmi persistence detect","wmi","persistence","de","cm","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","cybersecurity","process-forensics",{"skillNo":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":126,"publishedAt":44},"01M71HAK6JTTTS229T17WJMMCG","services-wmi-exec-exploit","Perform lateral movement 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