Medium Risk
AI新闻自动获取与推送Skill v2.2。新增智能产品价值评分、高质量信源过滤、三级分类机制和人工反馈迭代。支持Tavily、Brave、RSS多新闻源聚合，无需API Key即可使用RSS源。当用户需要获取AI行业最新动态、自动化新闻推送、多源新闻聚合或智能内容过滤时触发此Skill。
H:3 D:4 A:0 C:1
⚠️ Hazard Flags
EXEC FS_READ_WORKSPACE 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: INSTRUCTED_BINARY_INSTALL high
Mitigation: Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments
Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION, SOCIAL_ENG_ANTHROPIC_IMPERSONATION 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_ENV_VARS, DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST critical
Mitigation: Minimize access to environment variables
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:ai-news-pusher-v2:2.2.2",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-14T02:25:50.566Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "AI News Pusher",
"version": "2.2.2",
"format": "agent_skill",
"description": "AI新闻自动获取与推送Skill v2.2。新增智能产品价值评分、高质量信源过滤、三级分类机制和人工反馈迭代。支持Tavily、Brave、RSS多新闻源聚合，无需API Key即可使用RSS源。当用户需要获取AI行业最新动态、自动化新闻推送、多源新闻聚合或智能内容过滤时触发此Skill。",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "ai-news-pusher",
"owner": "kern1x",
"downloads": 207,
"stars": 1
},
"artifact": {
"sha256": "e7da29c24432a69db686a7213f8fea3ff8cc3f579598d7029e3c9887b32980b5",
"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": true,
"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_WORKSPACE",
"FS_READ_USER",
"NET_EGRESS_ANY",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB"
],
"custom_flags": [
{
"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, SOCIAL_ENG_ANTHROPIC_IMPERSONATION: Skill description is too vague or missing"
},
{
"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_ENV_VARS, DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST: Reading environment variables that may contain secrets"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 4 security patterns (12 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: INSTRUCTED_BINARY_INSTALL",
"severity": "high",
"mitigation": "Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments"
},
{
"risk": "Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION, SOCIAL_ENG_ANTHROPIC_IMPERSONATION",
"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_ENV_VARS, DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_HTTP_POST",
"severity": "critical",
"mitigation": "Minimize access to environment variables"
}
],
"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/schedule_push.py",
"file_path": "scripts/schedule_push.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/push_to_feishu.py",
"file_path": "scripts/push_to_feishu.py"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/news_sources.py",
"file_path": "scripts/news_sources.py"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "scripts/news_scorer.py",
"file_path": "scripts/news_scorer.py"
},
{
"evidence_id": "EV:file-7",
"type": "file_excerpt",
"title": "scripts/news_manager.py",
"file_path": "scripts/news_manager.py"
},
{
"evidence_id": "EV:file-8",
"type": "file_excerpt",
"title": "scripts/fetch_ai_news.py",
"file_path": "scripts/fetch_ai_news.py"
},
{
"evidence_id": "EV:file-9",
"type": "file_excerpt",
"title": "scripts/data_storage.py",
"file_path": "scripts/data_storage.py"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "INSTRUCTED_BINARY_INSTALL [HIGH] SKILL.md:247: pip install feedparser requests",
"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": "SOCIAL_ENG_ANTHROPIC_IMPERSONATION [MEDIUM] SKILL.md:10: description: Anthropic API Key，用于LLM评分功能（可选，与OpenAI二选一）",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "MCP_TOOL_POISONING_SENSITIVE_DATA [HIGH] SKILL.md:14: description: Brave Search API Key，用于Brave新闻源（可选）",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/schedule_push.py:14: GATEWAY_TOKEN = os.environ.get('OPENCLAW_GATEWAY_TOKEN', '')",
"file_path": "scripts/schedule_push.py"
},
{
"evidence_id": "EV:cisco-6",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/push_to_feishu.py:10: import requests",
"file_path": "scripts/push_to_feishu.py"
},
{
"evidence_id": "EV:cisco-7",
"type": "file_excerpt",
"title": "DATA_EXFIL_HTTP_POST [CRITICAL] scripts/push_to_feishu.py:138: response = requests.post(",
"file_path": "scripts/push_to_feishu.py"
},
{
"evidence_id": "EV:cisco-8",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/news_sources.py:10: import requests",
"file_path": "scripts/news_sources.py"
},
{
"evidence_id": "EV:cisco-9",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/news_sources.py:31: self.api_key = api_key or os.environ.get('TAVILY_API_KEY')",
"file_path": "scripts/news_sources.py"
},
{
"evidence_id": "EV:cisco-10",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/news_scorer.py:72: return os.environ.get('OPENAI_API_KEY')",
"file_path": "scripts/news_scorer.py"
}
]
}