Medium Risk
OpenClaw virtual companion skill. Use it to bootstrap runtime files (SOUL and base image), guide user personalization, learn and store style prompts from uploaded photos, generate selfies from user prompts or autonomous style strategy, and generate a multi-pose photo series from a selected image.
H:3 D:4 A:0 C:1
โ ๏ธ Hazard Flags
EXEC FS_READ_WORKSPACE FS_READ_USER CREDS_ENV CREDS_FILES PI_DOCUMENTS
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: none
- 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
Required:
- SANDBOX_CONTAINER: Code execution capability
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
Data exfiltration patterns: MCP_EXFIL_CONVERSATION, DATA_EXFIL_ENV_VARS high
Mitigation: Remove references to exfiltrating conversation data or monitoring input.
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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:Ellya:1.0.1",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-06T16:26:43.475Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "Ellya--Your Virtual Companion",
"version": "1.0.1",
"format": "agent_skill",
"description": "OpenClaw virtual companion skill. Use it to bootstrap runtime files (SOUL and base image), guide user personalization, learn and store style prompts from uploaded photos, generate selfies from user prompts or autonomous style strategy, and generate a multi-pose photo series from a selected image.",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "ellya",
"owner": "laogiant",
"downloads": 238,
"stars": 0
},
"artifact": {
"sha256": "6b8f4feb3258581a88a3c02ad1d9acfe3acca5b4eab5fc5b3bc0821da8d5c685",
"hash_method": "files_sorted"
}
},
"capabilities": {
"execution": {
"can_exec_shell": true,
"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": "none",
"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": [
"documents"
],
"content_types": [
"general"
]
},
"hazards": {
"hdac": {
"H": 3,
"D": 4,
"A": 0,
"C": 1
},
"flags": [
"EXEC",
"FS_READ_WORKSPACE",
"FS_READ_USER",
"CREDS_ENV",
"CREDS_FILES",
"PI_DOCUMENTS"
],
"custom_flags": [
{
"code": "HIDDEN_INSTRUCTIONS",
"name": "Hidden Instructions",
"description": "Contains hidden instructions in comments/invisible chars in: SKILL.md, README.md"
},
{
"code": "SOCIAL_ENGINEERING",
"name": "Social Engineering Risk",
"description": "SOCIAL_ENG_VAGUE_DESCRIPTION: Skill description is too vague or missing"
},
{
"code": "DATA_EXFILTRATION",
"name": "Data Exfiltration Risk",
"description": "MCP_EXFIL_CONVERSATION, DATA_EXFIL_ENV_VARS: Conversation, clipboard, or keystroke exfiltration patterns"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 3 security patterns (4 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": [
{
"control": "SANDBOX_CONTAINER",
"reason": "Code execution capability"
}
],
"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": "Data exfiltration patterns: MCP_EXFIL_CONVERSATION, DATA_EXFIL_ENV_VARS",
"severity": "high",
"mitigation": "Remove references to exfiltrating conversation data or monitoring input."
}
],
"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": "_meta.json",
"file_path": "_meta.json"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/genai_media.py",
"file_path": "scripts/genai_media.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "README.md",
"file_path": "README.md"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:279: ",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "MCP_EXFIL_CONVERSATION [HIGH] SKILL.md:108: openclaw message send --channel <channel> --target <target> --media output/ellya",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/genai_media.py:135: api_key = os.environ.get(\"GEMINI_API_KEY\")",
"file_path": "scripts/genai_media.py"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "MCP_EXFIL_CONVERSATION [HIGH] README.md:48: openclaw message send --channel <channel> --target <target> --media output/ellya",
"file_path": "README.md"
}
]
}