Amazon Product Search Api Skill

· v0.1.0

High Risk

This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request: 1. Search for products related to [keyword]; 2. Find best-selling items from [brand]; 3. Monitor product prices and availability on Amazon; 4. Extract product listings for market research; 5. Collect product ratings and review counts for competitive analysis; 6. Find specific products with a maximum count of [number]; 7. Search Amazon in [language] for localized results; 8. Track monthly sales estimates for [brand] products; 9. Gather product URLs and titles for a product catalog; 10. Scan Amazon for "Best Seller" tags in a specific category; 11. Monitor shipping and delivery information for [brand] items; 12. Build a structured dataset of Amazon search results.

H:4 D:4 A:0 C:1

⚠️ Hazard Flags

NET_EGRESS_ANY CREDS_ENV PI_WEB

📋 Capabilities

Execution

❌ Shell execution
❌ Code execution
❌ Install dependencies
❌ Persistence
Privilege: user

Filesystem

❌ Read workspace
❌ Write workspace
❌ Read home
❌ Write home
❌ Read system
❌ Delete

Network

Egress: any
❌ Ingress

Credentials

✅ Environment vars
❌ Credential files
❌ Browser data
❌ Keychain

Actions

❌ send messages❌ post public❌ purchase❌ transfer money❌ deploy❌ delete external

🔒 Containment

Level: maximum

Recommended:

LOG_ACTIONS: Audit trail for all actions

⚡ Risks

Resource abuse detected: RESOURCE_ABUSE_INFINITE_LOOP high

Mitigation: Add proper exit conditions or limits to loops

Command injection risk: MCP_SQL_BLIND high

Mitigation: Remove SQL exploitation patterns.

Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION low

Mitigation: Provide clear, detailed description of skill functionality

Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST, DATA_EXFIL_ENV_VARS critical

Mitigation: Ensure network access is necessary and documented

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🚨 Incident Response

Kill switch: Stop the agent process

Containment: Review logs for unexpected actions

Recovery: Depends on skill capabilities

📄 Raw SSDS JSON click to expand

{
  "meta": {
    "document_id": "ssds:auto:amazon-product-search-api-skill:0.1.0",
    "ssds_version": "0.2.0",
    "scanner_version": "0.4.0+fe6fd9123d50",
    "created_at": "2026-03-05T12:02:36.556Z",
    "created_by": {
      "agent": "safeagentskills-cli/generate-ssds"
    },
    "language": "en",
    "notes": "Auto-generated SSDS. Manual review recommended."
  },
  "skill": {
    "name": "Amazon Product Search Api Skill",
    "version": "0.1.0",
    "format": "agent_skill",
    "description": "This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request: 1. Search for products related to [keyword]; 2. Find best-selling items from [brand]; 3. Monitor product prices and availability on Amazon; 4. Extract product listings for market research; 5. Collect product ratings and review counts for competitive analysis; 6. Find specific products with a maximum count of [number]; 7. Search Amazon in [language] for localized results; 8. Track monthly sales estimates for [brand] products; 9. Gather product URLs and titles for a product catalog; 10. Scan Amazon for \"Best Seller\" tags in a specific category; 11. Monitor shipping and delivery information for [brand] items; 12. Build a structured dataset of Amazon search results.",
    "publisher": "unknown",
    "source": {
      "channel": "local"
    },
    "artifact": {
      "sha256": "09804b20a7fdb03ee808ca81d28cdf3875c76c88c06e7f12689333a82f1b74a7",
      "hash_method": "files_sorted"
    }
  },
  "capabilities": {
    "execution": {
      "can_exec_shell": false,
      "can_exec_code": false,
      "privilege_level": "user",
      "can_install_deps": false,
      "can_persist": false
    },
    "filesystem": {
      "reads_workspace": false,
      "reads_user_home": false,
      "reads_system": false,
      "writes_workspace": false,
      "writes_user_home": false,
      "writes_system": false,
      "can_delete": false
    },
    "network": {
      "egress": "any",
      "ingress": false
    },
    "credentials": {
      "reads_env_vars": true,
      "reads_credential_files": false,
      "reads_browser_data": false,
      "reads_keychain": false
    },
    "services": [],
    "actions": {
      "can_send_messages": false,
      "can_post_public": false,
      "can_purchase": false,
      "can_transfer_money": false,
      "can_deploy": false,
      "can_delete_external": false
    },
    "prompt_injection_surfaces": [
      "web"
    ],
    "content_types": [
      "general"
    ]
  },
  "hazards": {
    "hdac": {
      "H": 4,
      "D": 4,
      "A": 0,
      "C": 1
    },
    "flags": [
      "NET_EGRESS_ANY",
      "CREDS_ENV",
      "PI_WEB"
    ],
    "custom_flags": [
      {
        "code": "RESOURCE_ABUSE",
        "name": "Resource Abuse Risk",
        "description": "RESOURCE_ABUSE_INFINITE_LOOP detected: Infinite loop without clear exit condition"
      },
      {
        "code": "SOCIAL_ENGINEERING",
        "name": "Social Engineering Risk",
        "description": "SOCIAL_ENG_VAGUE_DESCRIPTION: Skill description is too vague or missing"
      },
      {
        "code": "COMMAND_INJECTION",
        "name": "Command Injection Risk",
        "description": "MCP_SQL_BLIND: Blind SQL injection, system table access, or stored procedure abuse"
      },
      {
        "code": "DATA_EXFILTRATION",
        "name": "Data Exfiltration Risk",
        "description": "DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST, DATA_EXFIL_ENV_VARS: HTTP client library imports that enable external communication"
      }
    ],
    "confidence": {
      "level": "medium",
      "basis": [
        "static_analysis"
      ],
      "notes": "Detected 4 security patterns (6 vendored rule hits). Review recommended."
    },
    "rationale": {
      "H": "H4: Critical: Privilege escalation or malware detected",
      "D": "D4: Critical: Credential theft or data exfiltration",
      "A": "A0: No side effects detected",
      "C": "C1: General content"
    }
  },
  "containment": {
    "level": "maximum",
    "required": [],
    "recommended": [
      {
        "control": "LOG_ACTIONS",
        "reason": "Audit trail for all actions"
      }
    ],
    "uncontained_risk": "Risk level depends on manual review of actual capabilities."
  },
  "risks": {
    "risks": [
      {
        "risk": "Resource abuse detected: RESOURCE_ABUSE_INFINITE_LOOP",
        "severity": "high",
        "mitigation": "Add proper exit conditions or limits to loops"
      },
      {
        "risk": "Command injection risk: MCP_SQL_BLIND",
        "severity": "high",
        "mitigation": "Remove SQL exploitation patterns."
      },
      {
        "risk": "Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION",
        "severity": "low",
        "mitigation": "Provide clear, detailed description of skill functionality"
      },
      {
        "risk": "Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST, DATA_EXFIL_ENV_VARS",
        "severity": "critical",
        "mitigation": "Ensure network access is necessary and documented"
      }
    ],
    "limitations": [
      "Static analysis only - runtime behavior not verified"
    ]
  },
  "incident_response": {
    "kill_switch": [
      "Stop the agent process"
    ],
    "containment": [
      "Review logs for unexpected actions"
    ],
    "recovery": [
      "Depends on skill capabilities"
    ]
  },
  "evidence": [
    {
      "evidence_id": "EV:file-1",
      "type": "file_excerpt",
      "title": "scripts/amazon_product_search_api.py",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:file-2",
      "type": "file_excerpt",
      "title": "SKILL.md",
      "file_path": "SKILL.md"
    },
    {
      "evidence_id": "EV:file-3",
      "type": "file_excerpt",
      "title": "_meta.json",
      "file_path": "_meta.json"
    },
    {
      "evidence_id": "EV:cisco-1",
      "type": "file_excerpt",
      "title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/amazon_product_search_api.py:3: import requests",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:cisco-2",
      "type": "file_excerpt",
      "title": "DATA_EXFIL_HTTP_POST [CRITICAL] scripts/amazon_product_search_api.py:32: res = requests.post(f\"{API_BASE_URL}/run-task-by-template\", json=payload, header",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:cisco-3",
      "type": "file_excerpt",
      "title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/amazon_product_search_api.py:83: api_key = os.getenv(\"BROWSERACT_API_KEY\")",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:cisco-4",
      "type": "file_excerpt",
      "title": "RESOURCE_ABUSE_INFINITE_LOOP [HIGH] scripts/amazon_product_search_api.py:45: while True:",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:cisco-5",
      "type": "file_excerpt",
      "title": "MCP_SQL_BLIND [HIGH] scripts/amazon_product_search_api.py:63: time.sleep(10)",
      "file_path": "scripts/amazon_product_search_api.py"
    },
    {
      "evidence_id": "EV:cisco-6",
      "type": "file_excerpt",
      "title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
      "file_path": "SKILL.md"
    }
  ]
}