Ai Daily
· v1.2.0
AI 日报 - 自动抓取 LLM/Agent 领域热点信息,生成结构化中文简报。
H:4 D:4 A:0 C:1
⚠️ Hazard Flags
EXEC PRIVILEGED PERSISTENCE 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: admin
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.
Command injection risk: MCP_SCRIPT_TAGS high
Mitigation: Remove embedded script tags and encoded payloads.
Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION, SOCIAL_ENG_ANTHROPIC_IMPERSONATION low
Mitigation: Provide clear, detailed description of skill functionality
Data exfiltration patterns: DATA_EXFIL_NETWORK_REQUESTS, DATA_EXFIL_ENV_VARS 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:ai-daily:1.2.0",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-06T08:11:42.208Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "Ai Daily",
"version": "1.2.0",
"format": "agent_skill",
"description": "AI 日报 - 自动抓取 LLM/Agent 领域热点信息,生成结构化中文简报。",
"publisher": "unknown",
"source": {
"channel": "local"
},
"artifact": {
"sha256": "b27849e94357e4c37d29eb78c9fc5ec45abe4a90cd6d086fdac6d7b94057118e",
"hash_method": "files_sorted"
}
},
"capabilities": {
"execution": {
"can_exec_shell": true,
"can_exec_code": false,
"privilege_level": "admin",
"can_install_deps": false,
"can_persist": true
},
"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": 4,
"D": 4,
"A": 0,
"C": 1
},
"flags": [
"EXEC",
"PRIVILEGED",
"PERSISTENCE",
"FS_READ_WORKSPACE",
"FS_READ_USER",
"NET_EGRESS_ANY",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB"
],
"custom_flags": [
{
"code": "PERSISTENCE",
"name": "Persistence Mechanism",
"description": "Creates scheduled tasks or startup entries in: README.md, SKILL.md"
},
{
"code": "PRIVILEGE_ESCALATION",
"name": "Privilege Escalation",
"description": "Uses elevated privileges (sudo/root) in: README.md"
},
{
"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, SOCIAL_ENG_ANTHROPIC_IMPERSONATION: Skill description is too vague or missing"
},
{
"code": "COMMAND_INJECTION",
"name": "Command Injection Risk",
"description": "MCP_SCRIPT_TAGS: Script tags, VBScript, or encoded script data URIs"
},
{
"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 6 security patterns (9 vendored rule hits). Review recommended."
},
"rationale": {
"H": "H4: Critical: Privilege escalation or malware 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": "Command injection risk: MCP_SCRIPT_TAGS",
"severity": "high",
"mitigation": "Remove embedded script tags and encoded payloads."
},
{
"risk": "Social engineering indicators: SOCIAL_ENG_VAGUE_DESCRIPTION, SOCIAL_ENG_ANTHROPIC_IMPERSONATION",
"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": "README.md",
"file_path": "README.md"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "scripts/ai_daily.py",
"file_path": "scripts/ai_daily.py"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/generate.sh",
"file_path": "scripts/generate.sh"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/push-to-dingtalk.sh",
"file_path": "scripts/push-to-dingtalk.sh"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/test.sh",
"file_path": "scripts/test.sh"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "scripts/view.sh",
"file_path": "scripts/view.sh"
},
{
"evidence_id": "EV:file-7",
"type": "file_excerpt",
"title": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:file-8",
"type": "file_excerpt",
"title": "_meta.json",
"file_path": "_meta.json"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "DATA_EXFIL_NETWORK_REQUESTS [MEDIUM] scripts/ai_daily.py:13: import urllib.request",
"file_path": "scripts/ai_daily.py"
},
{
"evidence_id": "EV:cisco-2",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/ai_daily.py:264: self.tavily_api_key = os.environ.get('TAVILY_API_KEY', '')",
"file_path": "scripts/ai_daily.py"
},
{
"evidence_id": "EV:cisco-3",
"type": "file_excerpt",
"title": "MCP_SCRIPT_TAGS [HIGH] scripts/ai_daily.py:415: text = re.sub(r'<script[^>]*>.*?</script>', '', html, flags=re.DOTALL | re.IGNOR",
"file_path": "scripts/ai_daily.py"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/generate.sh:1: #!/bin/bash",
"file_path": "scripts/generate.sh"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/push-to-dingtalk.sh:1: #!/bin/bash",
"file_path": "scripts/push-to-dingtalk.sh"
},
{
"evidence_id": "EV:cisco-6",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/test.sh:1: #!/bin/bash",
"file_path": "scripts/test.sh"
},
{
"evidence_id": "EV:cisco-7",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/view.sh:1: #!/bin/bash",
"file_path": "scripts/view.sh"
},
{
"evidence_id": "EV:cisco-8",
"type": "file_excerpt",
"title": "SOCIAL_ENG_VAGUE_DESCRIPTION [LOW] SKILL.md:1: ---",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-9",
"type": "file_excerpt",
"title": "SOCIAL_ENG_ANTHROPIC_IMPERSONATION [MEDIUM] SKILL.md:61: - OpenAI, Anthropic, Google DeepMind, Meta AI, Mistral AI, Qwen, AWS ML",
"file_path": "SKILL.md"
}
]
}