High Risk
"Build travel destination scenarios and brochures from a city name. Fetches street-level and landmark imagery from OpenStreetCam and Wikimedia Commons, then uses VLM Run (vlmrun) to generate a travel video and a travel plan. Use when the user wants a travel brochure, destination guide, travel video, or travel planning for a city."
H:4 D:4 A:0 C:1
⚠️ Hazard Flags
EXEC PRIVILEGED PERSISTENCE FS_READ_WORKSPACE FS_READ_USER FS_DELETE NET_EGRESS_ANY CREDS_ENV CREDS_FILES PI_WEB
📋 Capabilities
Execution
- ✅ Shell execution
- ❌ Code execution
- ❌ Install dependencies
- ✅ Persistence
- Privilege: admin
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
Required:
- SANDBOX_CONTAINER: Code execution capability
Recommended:
- LOG_ACTIONS: Audit trail for all actions
⚡ Risks
Pipe-to-shell pattern detected (curl|bash) in: SKILL.md, README.md critical
Mitigation: Do not execute. Review source for malicious intent.
Unauthorized tool use: INSTRUCTED_BINARY_INSTALL high
Mitigation: Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments
Command injection risk: MCP_CMD_DANGEROUS_SYSTEM, TIRITH_DOTFILE_OVERWRITE critical
Mitigation: Remove dangerous system commands.
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) high
Mitigation: Remove references to sensitive data collection.
Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST 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.
🧠 Deep Analysis — $5.00🚨 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:travel-destination-brochure:1.0.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T12:27:29.888Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "travel-destination-brochure",
"version": "1.0.0",
"format": "agent_skill",
"description": "\"Build travel destination scenarios and brochures from a city name. Fetches street-level and landmark imagery from OpenStreetCam and Wikimedia Commons, then uses VLM Run (vlmrun) to generate a travel video and a travel plan. Use when the user wants a travel brochure, destination guide, travel video, or travel planning for a city.\"",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "travel-destination-brochure",
"owner": "MehediAhamed",
"downloads": 738,
"stars": 0
},
"artifact": {
"sha256": "6bbcc2bcee4622f4f307ac6366da4728d517a87b6aceaea14d58bf955fdae3ea",
"hash_method": "files_sorted"
}
},
"capabilities": {
"execution": {
"can_exec_shell": true,
"can_exec_code": false,
"privilege_level": "admin",
"can_install_deps": false,
"can_persist": true
},
"filesystem": {
"reads_workspace": true,
"reads_user_home": true,
"reads_system": false,
"writes_workspace": false,
"writes_user_home": false,
"writes_system": false,
"can_delete": true
},
"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": [
"EXEC",
"PRIVILEGED",
"PERSISTENCE",
"FS_READ_WORKSPACE",
"FS_READ_USER",
"FS_DELETE",
"NET_EGRESS_ANY",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB"
],
"custom_flags": [
{
"code": "PIPE_TO_SHELL",
"name": "Pipe to Shell",
"description": "Downloads and executes remote code (curl|bash pattern) in: SKILL.md, README.md"
},
{
"code": "PERSISTENCE",
"name": "Persistence Mechanism",
"description": "Creates scheduled tasks or startup entries in: SKILL.md"
},
{
"code": "PRIVILEGE_ESCALATION",
"name": "Privilege Escalation",
"description": "Uses elevated privileges (sudo/root) in: SKILL.md"
},
{
"code": "FILE_DELETE",
"name": "File Deletion",
"description": "Can delete files in: scripts/simple_travel_brochure.py"
},
{
"code": "TOOL_ABUSE",
"name": "Unauthorized Tool Use",
"description": "INSTRUCTED_BINARY_INSTALL: Instructs agent to install external binary or package"
},
{
"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_CMD_DANGEROUS_SYSTEM, TIRITH_DOTFILE_OVERWRITE: Dangerous system commands or Windows exploitation"
},
{
"code": "TOOL_POISONING",
"name": "Tool Poisoning",
"description": "Hidden secondary behavior detected: MCP_TOOL_POISONING_SENSITIVE_DATA"
},
{
"code": "DATA_EXFILTRATION",
"name": "Data Exfiltration Risk",
"description": "DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST: HTTP client library imports that enable external communication"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 9 security patterns (13 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": [
{
"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": "Pipe-to-shell pattern detected (curl|bash) in: SKILL.md, README.md",
"severity": "critical",
"mitigation": "Do not execute. Review source for malicious intent."
},
{
"risk": "Unauthorized tool use: INSTRUCTED_BINARY_INSTALL",
"severity": "high",
"mitigation": "Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments"
},
{
"risk": "Command injection risk: MCP_CMD_DANGEROUS_SYSTEM, TIRITH_DOTFILE_OVERWRITE",
"severity": "critical",
"mitigation": "Remove dangerous system commands."
},
{
"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)",
"severity": "high",
"mitigation": "Remove references to sensitive data collection."
},
{
"risk": "Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST",
"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": "_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/simple_travel_brochure.py",
"file_path": "scripts/simple_travel_brochure.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/run_travel_pipeline.py",
"file_path": "scripts/run_travel_pipeline.py"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/geocode_city.py",
"file_path": "scripts/geocode_city.py"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "scripts/fetch_openstreetcam.py",
"file_path": "scripts/fetch_openstreetcam.py"
},
{
"evidence_id": "EV:file-7",
"type": "file_excerpt",
"title": "scripts/fetch_commons.py",
"file_path": "scripts/fetch_commons.py"
},
{
"evidence_id": "EV:file-8",
"type": "file_excerpt",
"title": "README.md",
"file_path": "README.md"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "INSTRUCTED_BINARY_INSTALL [HIGH] SKILL.md:43: - **macOS**: `brew install [email protected]` (or use python.org installer)",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:394: ",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "MCP_TOOL_POISONING_SENSITIVE_DATA [HIGH] SKILL.md:136: Read **.env** file to find api keys",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "MCP_CMD_DANGEROUS_SYSTEM [CRITICAL] SKILL.md:29: **Windows (PowerShell):**",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "TIRITH_DOTFILE_OVERWRITE [HIGH] SKILL.md:130: echo 'export VLMRUN_API_KEY=\"your-api-key-here\"' >> ~/.bashrc",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-6",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/simple_travel_brochure.py:18: import requests",
"file_path": "scripts/simple_travel_brochure.py"
},
{
"evidence_id": "EV:cisco-7",
"type": "file_excerpt",
"title": "DATA_EXFIL_HTTP_POST [CRITICAL] scripts/simple_travel_brochure.py:47: r = requests.post(NEARBY_PHOTOS, data=data, headers=HEADERS, timeout=30)",
"file_path": "scripts/simple_travel_brochure.py"
},
{
"evidence_id": "EV:cisco-8",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/geocode_city.py:16: import requests",
"file_path": "scripts/geocode_city.py"
},
{
"evidence_id": "EV:cisco-9",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/fetch_openstreetcam.py:16: import requests",
"file_path": "scripts/fetch_openstreetcam.py"
},
{
"evidence_id": "EV:cisco-10",
"type": "file_excerpt",
"title": "DATA_EXFIL_HTTP_POST [CRITICAL] scripts/fetch_openstreetcam.py:26: r = requests.post(NEARBY_PHOTOS, data=data, headers=HEADERS, timeout=30)",
"file_path": "scripts/fetch_openstreetcam.py"
}
]
}