tradingview-screener
ยท v1.1.0
Screen markets across 6 asset classes using TradingView data. API pre-filters + pandas computed signals. YAML-driven strategies.
H:4 D:1 A:0 C:1
โ ๏ธ Hazard Flags
EXEC CODE_EXEC FS_READ_WORKSPACE FS_DELETE
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
Unauthorized tool use: MCP_SYS_CRITICAL_ACCESS high
Mitigation: Avoid accessing system directories unless absolutely necessary.
Command injection risk: COMMAND_INJECTION_USER_INPUT, COMMAND_INJECTION_EVAL, MCP_SCRIPT_TAGS critical
Mitigation: Validate and sanitize all user inputs before using in commands
Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION low
Mitigation: Provide clear, detailed description of skill functionality
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:tradingview-screener:1.1.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T02:40:32.780Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "tradingview-screener",
"version": "1.1.0",
"format": "agent_skill",
"description": "Screen markets across 6 asset classes using TradingView data. API pre-filters + pandas computed signals. YAML-driven strategies.",
"publisher": "ClawHub",
"source": {
"channel": "local"
},
"artifact": {
"sha256": "ac68ab6d0dbcee60240f4197c9e57513153610c4261be7ccd5184d42fb41532a",
"hash_method": "files_sorted"
}
},
"capabilities": {
"execution": {
"can_exec_shell": true,
"can_exec_code": true,
"privilege_level": "user",
"can_install_deps": false,
"can_persist": false
},
"filesystem": {
"reads_workspace": true,
"reads_user_home": false,
"reads_system": false,
"writes_workspace": false,
"writes_user_home": false,
"writes_system": false,
"can_delete": true
},
"network": {
"egress": "none",
"ingress": false
},
"credentials": {
"reads_env_vars": false,
"reads_credential_files": false,
"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": [],
"content_types": [
"general"
]
},
"hazards": {
"hdac": {
"H": 4,
"D": 1,
"A": 0,
"C": 1
},
"flags": [
"EXEC",
"CODE_EXEC",
"FS_READ_WORKSPACE",
"FS_DELETE"
],
"custom_flags": [
{
"code": "FILE_DELETE",
"name": "File Deletion",
"description": "Can delete files in: scripts/tests/test_signal_engine.py"
},
{
"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": "COMMAND_INJECTION",
"name": "Command Injection Risk",
"description": "COMMAND_INJECTION_USER_INPUT, COMMAND_INJECTION_EVAL, MCP_SCRIPT_TAGS: User input used in command substitution - potential injection risk"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 4 security patterns (5 vendored rule hits). Review recommended."
},
"rationale": {
"H": "H4: Critical: Privilege escalation or malware detected",
"D": "D1: Limited data access",
"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": "Command injection risk: COMMAND_INJECTION_USER_INPUT, COMMAND_INJECTION_EVAL, MCP_SCRIPT_TAGS",
"severity": "critical",
"mitigation": "Validate and sanitize all user inputs before using in commands"
},
{
"risk": "Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION",
"severity": "low",
"mitigation": "Provide clear, detailed description of skill functionality"
}
],
"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": "install.sh",
"file_path": "install.sh"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "_meta.json",
"file_path": "_meta.json"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/screen.py",
"file_path": "scripts/screen.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/screener_constants.py",
"file_path": "scripts/screener_constants.py"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/signal_engine.py",
"file_path": "scripts/signal_engine.py"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "scripts/signal_types.py",
"file_path": "scripts/signal_types.py"
},
{
"evidence_id": "EV:file-7",
"type": "file_excerpt",
"title": "scripts/tests/__init__.py",
"file_path": "scripts/tests/__init__.py"
},
{
"evidence_id": "EV:file-8",
"type": "file_excerpt",
"title": "scripts/tests/test_screen.py",
"file_path": "scripts/tests/test_screen.py"
},
{
"evidence_id": "EV:file-9",
"type": "file_excerpt",
"title": "scripts/tests/test_signal_engine.py",
"file_path": "scripts/tests/test_signal_engine.py"
},
{
"evidence_id": "EV:file-10",
"type": "file_excerpt",
"title": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "COMMAND_INJECTION_USER_INPUT [MEDIUM] install.sh:5: SCRIPT_DIR=\"$(cd \"$(dirname \"$0\")\" && pwd)\"",
"file_path": "install.sh"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] install.sh:1: #!/usr/bin/env bash",
"file_path": "install.sh"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "COMMAND_INJECTION_EVAL [CRITICAL] scripts/signal_types.py:92: Uses df.eval() which is sandboxed to DataFrame operations.",
"file_path": "scripts/signal_types.py"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "MCP_SCRIPT_TAGS [HIGH] SKILL.md:23: skills/tradingview-screener/.venv/bin/python3 skills/tradingview-screener/script",
"file_path": "SKILL.md"
}
]
}