figma
ยท v2.1.0
Professional Figma design analysis and asset export. Use for extracting design data, exporting assets in multiple formats, auditing accessibility compliance, analyzing design systems, and generating comprehensive design documentation. Read-only analysis of Figma files with powerful export and reporting capabilities.
โ ๏ธ Hazard Flags
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
๐ Containment
Level: maximum
- LOG_ACTIONS: Audit trail for all actions
โก Risks
Mitigation: Review SKILL.md for hidden instructions. Do not use with untrusted input.
Mitigation: Remove SQL exploitation patterns.
Mitigation: Provide clear, detailed description of skill functionality
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:figma:2.1.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T01:53:55.412Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "figma",
"version": "2.1.0",
"format": "agent_skill",
"description": "Professional Figma design analysis and asset export. Use for extracting design data, exporting assets in multiple formats, auditing accessibility compliance, analyzing design systems, and generating comprehensive design documentation. Read-only analysis of Figma files with powerful export and reporting capabilities.",
"publisher": "ClawHub",
"source": {
"channel": "local"
},
"artifact": {
"sha256": "5f13dc9bb54501c835f950061ea08b4fabb74207aeb7b0841086fff67a6f626a",
"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": true,
"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",
"documents"
],
"content_types": [
"general"
]
},
"hazards": {
"hdac": {
"H": 4,
"D": 4,
"A": 1,
"C": 1
},
"flags": [
"FS_READ_WORKSPACE",
"FS_READ_USER",
"FS_WRITE_WORKSPACE",
"NET_EGRESS_ANY",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB",
"PI_DOCUMENTS"
],
"custom_flags": [
{
"code": "PROMPT_INJECTION",
"name": "Prompt Injection Risk",
"description": "Contains prompt injection patterns in: scripts/accessibility_checker.py"
},
{
"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_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": "A1: Local side effects only",
"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": "Prompt injection patterns detected in: scripts/accessibility_checker.py",
"severity": "high",
"mitigation": "Review SKILL.md for hidden instructions. Do not use with untrusted input."
},
{
"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_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": "_meta.json",
"file_path": "_meta.json"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "scripts/accessibility_checker.py",
"file_path": "scripts/accessibility_checker.py"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/export_manager.py",
"file_path": "scripts/export_manager.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/figma_client.py",
"file_path": "scripts/figma_client.py"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/style_auditor.py",
"file_path": "scripts/style_auditor.py"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/export_manager.py:11: import aiohttp",
"file_path": "scripts/export_manager.py"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "MCP_SQL_BLIND [HIGH] scripts/export_manager.py:272: time.sleep(0.5)",
"file_path": "scripts/export_manager.py"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/figma_client.py:11: import requests",
"file_path": "scripts/figma_client.py"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/figma_client.py:30: access_token=access_token or os.getenv('FIGMA_ACCESS_TOKEN')",
"file_path": "scripts/figma_client.py"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "MCP_SQL_BLIND [HIGH] scripts/figma_client.py:49: time.sleep(self.config.rate_limit_delay)",
"file_path": "scripts/figma_client.py"
},
{
"evidence_id": "EV:cisco-6",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
}
]
}