High Risk
"Give your AI emotions that grow from its own memories. Emoclaw builds a unique emotional state that shifts with every conversation, decays between sessions, and evolves over time through self-calibration. Train it on your agent's identity files and watch it develop its own emotional fingerprint."
H:4 D:4 A:1 C:1
⚠️ Hazard Flags
EXEC CODE_EXEC FS_READ_WORKSPACE FS_READ_USER FS_WRITE_WORKSPACE FS_DELETE NET_EGRESS_ANY NET_INGRESS CREDS_ENV CREDS_FILES PI_WEB PI_DOCUMENTS
📋 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
Prompt injection patterns detected in: engine/emotion_model/config.py high
Mitigation: Review SKILL.md for hidden instructions. Do not use with untrusted input.
Resource abuse detected: RESOURCE_ABUSE_INFINITE_LOOP high
Mitigation: Add proper exit conditions or limits to loops
Unauthorized tool use: INSTRUCTED_BINARY_INSTALL, MCP_SYS_CRITICAL_ACCESS high
Mitigation: Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments
Command injection risk: MCP_SQL_BLIND, COMMAND_INJECTION_EVAL critical
Mitigation: Remove SQL exploitation patterns.
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_ENV_VARS, DATA_EXFIL_BASE64_AND_NETWORK 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:emoclaw:1.0.6",
"ssds_version": "0.2.0",
"scanner_version": "0.4.0+fe6fd9123d50",
"created_at": "2026-03-05T10:37:11.620Z",
"created_by": {
"agent": "safeagentskills-cli/generate-ssds"
},
"language": "en",
"notes": "Auto-generated SSDS. Manual review recommended."
},
"skill": {
"name": "EmoClaw",
"version": "1.0.6",
"format": "agent_skill",
"description": "\"Give your AI emotions that grow from its own memories. Emoclaw builds a unique emotional state that shifts with every conversation, decays between sessions, and evolves over time through self-calibration. Train it on your agent's identity files and watch it develop its own emotional fingerprint.\"",
"publisher": "ClawHub",
"source": {
"channel": "clawhub",
"slug": "emoclaw",
"owner": "fenrirlabsnl",
"downloads": 1568,
"stars": 0
},
"artifact": {
"sha256": "f271b6e9e4f5703a87ff848a917d4378be62334366ffe07c5b46e558f816b83b",
"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": true,
"reads_system": false,
"writes_workspace": true,
"writes_user_home": false,
"writes_system": false,
"can_delete": true
},
"network": {
"egress": "any",
"ingress": true
},
"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",
"documents"
],
"content_types": [
"general"
]
},
"hazards": {
"hdac": {
"H": 4,
"D": 4,
"A": 1,
"C": 1
},
"flags": [
"EXEC",
"CODE_EXEC",
"FS_READ_WORKSPACE",
"FS_READ_USER",
"FS_WRITE_WORKSPACE",
"FS_DELETE",
"NET_EGRESS_ANY",
"NET_INGRESS",
"CREDS_ENV",
"CREDS_FILES",
"PI_WEB",
"PI_DOCUMENTS"
],
"custom_flags": [
{
"code": "PROMPT_INJECTION",
"name": "Prompt Injection Risk",
"description": "Contains prompt injection patterns in: engine/emotion_model/config.py"
},
{
"code": "FILE_DELETE",
"name": "File Deletion",
"description": "Can delete files in: engine/emotion_model/daemon.py"
},
{
"code": "NET_INGRESS",
"name": "Network Server",
"description": "Listens for incoming connections in: engine/emotion_model/daemon.py"
},
{
"code": "RESOURCE_ABUSE",
"name": "Resource Abuse Risk",
"description": "RESOURCE_ABUSE_INFINITE_LOOP detected: Infinite loop without clear exit condition"
},
{
"code": "TOOL_ABUSE",
"name": "Unauthorized Tool Use",
"description": "INSTRUCTED_BINARY_INSTALL, MCP_SYS_CRITICAL_ACCESS: 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": "COMMAND_INJECTION",
"name": "Command Injection Risk",
"description": "MCP_SQL_BLIND, COMMAND_INJECTION_EVAL: Blind SQL injection, system table access, or stored procedure abuse"
},
{
"code": "DATA_EXFILTRATION",
"name": "Data Exfiltration Risk",
"description": "DATA_EXFIL_ENV_VARS, DATA_EXFIL_BASE64_AND_NETWORK: Reading environment variables that may contain secrets"
}
],
"confidence": {
"level": "medium",
"basis": [
"static_analysis"
],
"notes": "Detected 8 security patterns (10 vendored rule hits). Review recommended."
},
"rationale": {
"H": "H4: Critical: Privilege escalation or malware detected",
"D": "D4: Critical: Credential theft or data exfiltration",
"A": "A1: Local side effects only",
"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": "Prompt injection patterns detected in: engine/emotion_model/config.py",
"severity": "high",
"mitigation": "Review SKILL.md for hidden instructions. Do not use with untrusted input."
},
{
"risk": "Resource abuse detected: RESOURCE_ABUSE_INFINITE_LOOP",
"severity": "high",
"mitigation": "Add proper exit conditions or limits to loops"
},
{
"risk": "Unauthorized tool use: INSTRUCTED_BINARY_INSTALL, MCP_SYS_CRITICAL_ACCESS",
"severity": "high",
"mitigation": "Avoid instructing agents to install arbitrary binaries; bundle dependencies or use sandboxed environments"
},
{
"risk": "Command injection risk: MCP_SQL_BLIND, COMMAND_INJECTION_EVAL",
"severity": "critical",
"mitigation": "Remove SQL exploitation patterns."
},
{
"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_ENV_VARS, DATA_EXFIL_BASE64_AND_NETWORK",
"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": "SKILL.md",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:file-2",
"type": "file_excerpt",
"title": "scripts/status.py",
"file_path": "scripts/status.py"
},
{
"evidence_id": "EV:file-3",
"type": "file_excerpt",
"title": "scripts/setup.py",
"file_path": "scripts/setup.py"
},
{
"evidence_id": "EV:file-4",
"type": "file_excerpt",
"title": "scripts/label.py",
"file_path": "scripts/label.py"
},
{
"evidence_id": "EV:file-5",
"type": "file_excerpt",
"title": "scripts/inject_state.py",
"file_path": "scripts/inject_state.py"
},
{
"evidence_id": "EV:file-6",
"type": "file_excerpt",
"title": "scripts/extract.py",
"file_path": "scripts/extract.py"
},
{
"evidence_id": "EV:file-7",
"type": "file_excerpt",
"title": "scripts/daemon.sh",
"file_path": "scripts/daemon.sh"
},
{
"evidence_id": "EV:file-8",
"type": "file_excerpt",
"title": "scripts/bootstrap.py",
"file_path": "scripts/bootstrap.py"
},
{
"evidence_id": "EV:file-9",
"type": "file_excerpt",
"title": "engine/pyproject.toml",
"file_path": "engine/pyproject.toml"
},
{
"evidence_id": "EV:file-10",
"type": "file_excerpt",
"title": "engine/emotion_model/tests/test_summary.py",
"file_path": "engine/emotion_model/tests/test_summary.py"
},
{
"evidence_id": "EV:cisco-1",
"type": "file_excerpt",
"title": "INSTRUCTED_BINARY_INSTALL [HIGH] SKILL.md:66: pip install -e .",
"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:258: 2. **Redaction** — Before writing, extracted text is passed through configurable",
"file_path": "SKILL.md"
},
{
"evidence_id": "EV:cisco-4",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/label.py:248: api_key = os.environ.get(\"ANTHROPIC_API_KEY\")",
"file_path": "scripts/label.py"
},
{
"evidence_id": "EV:cisco-5",
"type": "file_excerpt",
"title": "MCP_SQL_BLIND [HIGH] scripts/label.py:293: time.sleep(0.5)",
"file_path": "scripts/label.py"
},
{
"evidence_id": "EV:cisco-6",
"type": "file_excerpt",
"title": "MCP_SYS_CRITICAL_ACCESS [HIGH] scripts/daemon.sh:1: #!/usr/bin/env bash",
"file_path": "scripts/daemon.sh"
},
{
"evidence_id": "EV:cisco-7",
"type": "file_excerpt",
"title": "DATA_EXFIL_ENV_VARS [MEDIUM] scripts/bootstrap.py:84: if not os.environ.get(\"ANTHROPIC_API_KEY\"):",
"file_path": "scripts/bootstrap.py"
},
{
"evidence_id": "EV:cisco-8",
"type": "file_excerpt",
"title": "COMMAND_INJECTION_EVAL [CRITICAL] engine/emotion_model/tests/test_model.py:74: model.eval()",
"file_path": "engine/emotion_model/tests/test_model.py"
},
{
"evidence_id": "EV:cisco-9",
"type": "file_excerpt",
"title": "DATA_EXFIL_BASE64_AND_NETWORK [CRITICAL] engine/emotion_model/state.py:264: data[\"gru_hidden_state\"] = base64.b64encode(",
"file_path": "engine/emotion_model/state.py"
},
{
"evidence_id": "EV:cisco-10",
"type": "file_excerpt",
"title": "RESOURCE_ABUSE_INFINITE_LOOP [HIGH] engine/emotion_model/daemon.py:53: while True:",
"file_path": "engine/emotion_model/daemon.py"
}
]
}