Context retrieval layer for AI agents across users' applications. Search and retrieve context from Airweave collections. Airweave indexes and syncs data from user applications to enable optimal context retrieval by AI agents. Supports semantic, keyword, and agentic search. Use when users ask about their data in connected apps (Slack, GitHub, Notion, Jira, Confluence, Google Drive, Salesforce, Linear, SharePoint, Stripe, etc.), need to find documents or information from their workspace, want answers based on their company data, or need you to check app data for context to complete a task.
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: Provide clear, detailed description of skill functionality
Mitigation: Clearly document which sensitive services are accessed and why; use minimal required permissions
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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:airweave:1.0.1",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T10:40:01.162Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "Airweave",
"version": "1.0.1",
"format": "agent_skill",
"description": "Context retrieval layer for AI agents across users' applications. Search and retrieve context from Airweave collections. Airweave indexes and syncs data from user applications to enable optimal context retrieval by AI agents. Supports semantic, keyword, and agentic search. Use when users ask about their data in connected apps (Slack, GitHub, Notion, Jira, Confluence, Google Drive, Salesforce, Linear, SharePoint, Stripe, etc.), need to find documents or information from their workspace, want answers based on their company data, or need you to check app data for context to complete a task.",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "airweave",
"owner": "lennertjansen",
"downloads": 1550,
"stars": 0
},
"artifact": {
"sha256": "65993c93f53c6e01cd6ff6151a2b0225a7966acc1fd0c2ad8f47852ddd6288e1",
"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": 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": 2,
"D": 4,
"A": 0,
"C": 1
},
"flags": [
"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": "DATA_EXFILTRATION",
"name": "Data Exfiltration Risk",
"description": "INSTRUCTED_SENSITIVE_SERVICE_ACCESS, DATA_EXFIL_NETWORK_REQUESTS: Instructs agent to access sensitive services (email, calendar, contacts, drive)"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 2 security patterns (3 vendored rule hits). Review recommended."
},
"rationale": {
"H": "H2: Filesystem writes or ingress 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": "Data exfiltration patterns: INSTRUCTED_SENSITIVE_SERVICE_ACCESS, DATA_EXFIL_NETWORK_REQUESTS",
"severity": "high",
"mitigation": "Clearly document which sensitive services are accessed and why; use minimal required permissions"
}
],
"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/search.py",
"file_path": "scripts/search.py"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "INSTRUCTED_SENSITIVE_SERVICE_ACCESS [HIGH] SKILL.md:3: description: Context retrieval layer for AI agents across users' applications. S",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/search.py:34: from urllib.request import Request, urlopen",
"file_path": "scripts/search.py"
}
]
}