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| name: graphstrike | |
| version: "1.0.0" | |
| description: > | |
| RL environment for detecting coordinated fake account rings in social networks. | |
| An AI detective agent must identify all 10 members of a coordinated fake | |
| account gang before they evade detection. Three difficulty levels with | |
| increasing network size, decoys, and real-time evasion events. | |
| author: OpenENV Hackathon | |
| tags: | |
| - social-network | |
| - fraud-detection | |
| - graph | |
| - rl | |
| - fake-account-detection | |
| # ── Server configuration ────────────────────────────────────────────────────── | |
| server: | |
| dockerfile: Dockerfile | |
| port: 7860 | |
| environment_variables: | |
| PORT: "7860" | |
| HOST: "0.0.0.0" | |
| WORKERS: "1" | |
| # ── Task definitions (each has a grader) ───────────────────────────────────── | |
| tasks: | |
| - name: easy | |
| description: "50 accounts, 10 fakes, no evasion, 30 steps" | |
| max_steps: 30 | |
| grader: | |
| endpoint: /grader | |
| score_range: [0.0, 1.0] | |
| win_threshold: 0.815 | |
| win_conditions: | |
| recall: 0.8 | |
| precision: 0.7 | |
| formula: > | |
| if recall >= 0.8 and precision >= 0.7: | |
| score = 0.55 + 0.20*recall + 0.15*precision + 0.10*efficiency | |
| else: | |
| score = 0.30*recall + 0.10*precision | |
| - name: medium | |
| description: "200 accounts, 10 fakes + 20 decoys, 1 evasion event, 50 steps" | |
| max_steps: 50 | |
| grader: | |
| endpoint: /grader | |
| score_range: [0.0, 1.0] | |
| win_threshold: 0.815 | |
| win_conditions: | |
| recall: 0.8 | |
| precision: 0.7 | |
| formula: > | |
| if recall >= 0.8 and precision >= 0.7: | |
| score = 0.55 + 0.20*recall + 0.15*precision + 0.10*efficiency | |
| else: | |
| score = 0.30*recall + 0.10*precision | |
| - name: hard | |
| description: "1000 accounts, 10 fakes + 50 decoys, 4 evasion events, 80 steps" | |
| max_steps: 80 | |
| grader: | |
| endpoint: /grader | |
| score_range: [0.0, 1.0] | |
| win_threshold: 0.868 | |
| win_conditions: | |
| recall: 0.9 | |
| precision: 0.8 | |
| formula: > | |
| if recall >= 0.9 and precision >= 0.8: | |
| score = 0.55 + 0.20*recall + 0.15*precision + 0.10*efficiency | |
| else: | |
| score = 0.30*recall + 0.10*precision | |
| # ── Action schema ───────────────────────────────────────────────────────────── | |
| action_schema: | |
| action_type: | |
| type: string | |
| enum: [inspect, investigate_network, flag, unflag, submit] | |
| account_id: | |
| type: string | |
| description: "Required for all actions except submit" | |
| # ── Score range ─────────────────────────────────────────────────────────────── | |
| score_range: [0.0, 1.0] | |
| grader_formula: > | |
| if recall >= win_recall and precision >= win_precision: | |
| score = 0.55 + 0.20*recall + 0.15*precision + 0.10*efficiency | |
| else: | |
| score = 0.30*recall + 0.10*precision | |