Medium Risk
This skill should be used when the user asks to "enable semantic caching", "cache LLM responses", "reduce API costs", "speed up AI responses", "configure LangCache", "search the semantic cache", "store responses in cache", or mentions Redis LangCache, semantic similarity caching, or LLM response caching. Provides integration with Redis LangCache managed service for semantic caching of prompts and responses.
H:3 D:4 A:0 C:1
⚠️ Hazard Flags
EXEC FS_READ_USER NET_EGRESS_ANY CREDS_ENV CREDS_FILES PI_WEB
📋 Capabilities
Execution
- ✅ Shell execution
- ❌ Code execution
- ❌ Install dependencies
- ❌ Persistence
- Privilege: user
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
Unauthorized tool use: MCP_SYS_CRITICAL_ACCESS high
Mitigation: Avoid accessing system directories unless absolutely necessary.
Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION low
Mitigation: Provide clear, detailed description of skill functionality
Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS 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.
🧠 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:langcache:1.0.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T11:28:53.630Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "Langcache Semantic Caching for OpenClaw",
"version": "1.0.0",
"format": "agent_skill",
"description": "This skill should be used when the user asks to \"enable semantic caching\", \"cache LLM responses\", \"reduce API costs\", \"speed up AI responses\", \"configure LangCache\", \"search the semantic cache\", \"store responses in cache\", or mentions Redis LangCache, semantic similarity caching, or LLM response caching. Provides integration with Redis LangCache managed service for semantic caching of prompts and responses.",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "openclaw-langcache",
"owner": "manvinder01",
"downloads": 1313,
"stars": 0
},
"artifact": {
"sha256": "636be08278b413bf694a489ee85f3450c1c2e58e81e295d4355acca943b4b308",
"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": 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": 3,
"D": 4,
"A": 0,
"C": 1
},
"flags": [
"EXEC",
"FS_READ_USER",
"NET_EGRESS_ANY",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB"
],
"custom_flags": [
{
"code": "TOOL_ABUSE",
"name": "Unauthorized Tool Use",
"description": "MCP_SYS_CRITICAL_ACCESS: Access to critical system directories"
},
{
"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": "DATA_EXFIL_NETWORK_REQUESTS: HTTP client library imports that enable external communication"
}
],
"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": "Unauthorized tool use: MCP_SYS_CRITICAL_ACCESS",
"severity": "high",
"mitigation": "Avoid accessing system directories unless absolutely necessary."
},
{
"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",
"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": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/langcache.sh",
"file_path": "scripts/langcache.sh"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "examples/basic-caching.sh",
"file_path": "examples/basic-caching.sh"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "examples/agent-integration.py",
"file_path": "examples/agent-integration.py"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/langcache.sh:1: #!/usr/bin/env bash",
"file_path": "scripts/langcache.sh"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] examples/basic-caching.sh:1: #!/usr/bin/env bash",
"file_path": "examples/basic-caching.sh"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] examples/agent-integration.py:31: import httpx",
"file_path": "examples/agent-integration.py"
}
]
}