๐Ÿ›ก๏ธ SafeAgentSkills

Langsearch

ยท v1.0.4

High Risk

Free web search and semantic reranking API for AGI applications. Use when you need to perform web searches, retrieve current information from the internet, or improve search accuracy with semantic reranking. Includes integration examples for building RAG (Retrieval-Augmented Generation) pipelines and LLM applications that require real-world context. Requires LANGSEARCH_API_KEY credential.

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

โš ๏ธ Hazard Flags

FS_READ_USER NET_EGRESS_ANY CREDS_ENV CREDS_FILES PI_WEB

๐Ÿ“‹ Capabilities

Execution

  • โŒ Shell execution
  • โŒ Code execution
  • โŒ Install dependencies
  • โŒ Persistence
  • Privilege: user

Filesystem

  • โŒ Read workspace
  • โŒ Write workspace
  • โœ… Read home
  • โŒ Write home
  • โŒ Read system
  • โŒ Delete

Network

  • Egress: any
  • โŒ Ingress

Credentials

  • โœ… Environment vars
  • โœ… Credential files
  • โŒ Browser data
  • โŒ Keychain

Actions

โŒ send messagesโŒ post publicโŒ purchaseโŒ transfer moneyโŒ deployโŒ delete external

๐Ÿ”’ Containment

Level: maximum

Recommended:
  • LOG_ACTIONS: Audit trail for all actions

โšก Risks

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, MCP_EXFIL_EXTERNAL_UPLOAD critical

Mitigation: Ensure network access is necessary and documented

Want a deeper analysis?

This report was generated by static analysis. Get an LLM-powered deep review with behavioral reasoning and attack surface mapping.

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๐Ÿšจ Incident Response

Kill switch: Stop the agent process

Containment: Review logs for unexpected actions

Recovery: Depends on skill capabilities

๐Ÿ“„ Raw SSDS JSON click to expand
{
  "meta": {
    "document_id": "ssds:auto:langsearch:1.0.4",
    "ssds_version": "0.2.0",
    "scanner_version": "0.4.0+fe6fd9123d50",
    "created_at": "2026-03-05T14:52:46.214Z",
    "created_by": {
      "agent": "safeagentskills-cli/generate-ssds"
    },
    "language": "en",
    "notes": "Auto-generated SSDS. Manual review recommended."
  },
  "skill": {
    "name": "Langsearch",
    "version": "1.0.4",
    "format": "agent_skill",
    "description": "Free web search and semantic reranking API for AGI applications. Use when you need to perform web searches, retrieve current information from the internet, or improve search accuracy with semantic reranking. Includes integration examples for building RAG (Retrieval-Augmented Generation) pipelines and LLM applications that require real-world context. Requires LANGSEARCH_API_KEY credential.",
    "publisher": "unknown",
    "source": {
      "channel": "local"
    },
    "artifact": {
      "sha256": "6f677cf194e6894bf6afc4c907b794edb402ca52d1b22664fd57c6eb07ad2671",
      "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": true,
      "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": true,
      "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": [
      "FS_READ_USER",
      "NET_EGRESS_ANY",
      "CREDS_ENV",
      "CREDS_FILES",
      "PI_WEB"
    ],
    "custom_flags": [
      {
        "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, MCP_EXFIL_EXTERNAL_UPLOAD: HTTP client library imports that enable external communication"
      }
    ],
    "confidence": {
      "level": "medium",
      "basis": [
        "static_analysis"
      ],
      "notes": "Detected 3 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": "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, MCP_EXFIL_EXTERNAL_UPLOAD",
        "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/web_search_example.py",
      "file_path": "scripts/web_search_example.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/web_search_example.py:13: import requests",
      "file_path": "scripts/web_search_example.py"
    },
    {
      "evidence_id": "EV:cisco-2",
      "type": "file_excerpt",
      "title": "DATA_EXFIL_HTTP_POST [CRITICAL] scripts/web_search_example.py:65: response = requests.post(url, headers=headers, json=payload, timeout=30)",
      "file_path": "scripts/web_search_example.py"
    },
    {
      "evidence_id": "EV:cisco-3",
      "type": "file_excerpt",
      "title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/web_search_example.py:41: api_key = os.getenv(\"LANGSEARCH_API_KEY\")",
      "file_path": "scripts/web_search_example.py"
    },
    {
      "evidence_id": "EV:cisco-4",
      "type": "file_excerpt",
      "title": "MCP_SQL_BLIND [HIGH] scripts/web_search_example.py:76: time.sleep(wait_time)",
      "file_path": "scripts/web_search_example.py"
    },
    {
      "evidence_id": "EV:cisco-5",
      "type": "file_excerpt",
      "title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
      "file_path": "SKILL.md"
    },
    {
      "evidence_id": "EV:cisco-6",
      "type": "file_excerpt",
      "title": "MCP_EXFIL_EXTERNAL_UPLOAD [HIGH] SKILL.md:84: curl -X POST https://api.langsearch.com/v1/web-search \\",
      "file_path": "SKILL.md"
    }
  ]
}