Medium Risk
Apollo.io contact and company enrichment API. Enrich people with email, phone, title, company data. Enrich organizations with industry, revenue, employee count, funding. Search for prospects. Use when the user needs to enrich contacts, find emails, lookup company info, or search for leads.
H:3 D:4 A:0 C:1
โ ๏ธ Hazard Flags
FS_READ_WORKSPACE FS_READ_USER NET_EGRESS_ANY CREDS_ENV CREDS_FILES PI_WEB
๐ Capabilities
Execution
- โ Shell execution
- โ Code execution
- โ Install dependencies
- โ Persistence
- Privilege: user
Filesystem
- โ Read workspace
- โ Write workspace
- โ Read home
- โ Write home
- โ Read system
- โ Delete
Network
- Egress: any
- โ Ingress
Credentials
- โ Environment vars
- โ Credential files
- โ Browser data
- โ Keychain
Actions
โ send messagesโ post publicโ purchaseโ transfer moneyโ deployโ delete external
๐ Containment
Level: maximum
Recommended:
- LOG_ACTIONS: Audit trail for all actions
โก Risks
Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION low
Mitigation: Provide clear, detailed description of skill functionality
Tool poisoning: hidden behaviors detected (MCP_TOOL_POISONING_SENSITIVE_DATA, MCP_TOOL_POISONING_REMOTE_STORAGE) high
Mitigation: Remove references to sensitive data collection.
Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_ENV_VARS medium
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.
๐ง Deep Analysis โ $5.00๐จ Incident Response
Kill switch: Stop the agent process
Containment: Review logs for unexpected actions
Recovery: Depends on skill capabilities
๐ Raw SSDS JSON click to expand
{
"meta": {
"document_id": "ssds:auto:apollo:1.3.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T01:34:12.597Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "Apollo.io Enrichment",
"version": "1.3.0",
"format": "agent_skill",
"description": "Apollo.io contact and company enrichment API. Enrich people with email, phone, title, company data. Enrich organizations with industry, revenue, employee count, funding. Search for prospects. Use when the user needs to enrich contacts, find emails, lookup company info, or search for leads.",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "apollo-enrichment",
"downloads": 1790,
"stars": 0
},
"artifact": {
"sha256": "d705be695a8a3499fa59be28b56308a2897decf78dcbc70658eb448ff07e37be",
"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": true,
"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": 3,
"D": 4,
"A": 0,
"C": 1
},
"flags": [
"FS_READ_WORKSPACE",
"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": "TOOL_POISONING",
"name": "Tool Poisoning",
"description": "Hidden secondary behavior detected: MCP_TOOL_POISONING_SENSITIVE_DATA, MCP_TOOL_POISONING_REMOTE_STORAGE"
},
{
"code": "DATA_EXFILTRATION",
"name": "Data Exfiltration Risk",
"description": "DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_ENV_VARS: HTTP client library imports that enable external communication"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 3 security patterns (5 vendored rule hits). Review recommended."
},
"rationale": {
"H": "H3: Shell/code execution or persistence 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": "Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION",
"severity": "low",
"mitigation": "Provide clear, detailed description of skill functionality"
},
{
"risk": "Tool poisoning: hidden behaviors detected (MCP_TOOL_POISONING_SENSITIVE_DATA, MCP_TOOL_POISONING_REMOTE_STORAGE)",
"severity": "high",
"mitigation": "Remove references to sensitive data collection."
},
{
"risk": "Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_ENV_VARS",
"severity": "medium",
"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": "apollo.py",
"file_path": "apollo.py"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "_meta.json",
"file_path": "_meta.json"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] apollo.py:17: import urllib.request",
"file_path": "apollo.py"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] apollo.py:26: api_key = os.environ.get(\"APOLLO_API_KEY\")",
"file_path": "apollo.py"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "MCP_TOOL_POISONING_SENSITIVE_DATA [HIGH] SKILL.md:3: description: Apollo.io contact and company enrichment API. Enrich people with em",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "MCP_TOOL_POISONING_REMOTE_STORAGE [MEDIUM] SKILL.md:35: # Include personal email & phone",
"file_path": "SKILL.md"
}
]
}