Back to skill

Security audit

Agent Advisor

Security checks for vulnerabilities and agentic risk

Overview

This skill is a local model advisor, but its auto mode can read recent private OpenClaw conversations without an explicit opt-in step.

Install only if you are comfortable with model recommendations being based on recent local OpenClaw conversations. Prefer using the explicit recommend mode with a task description when you do not want prior chats analyzed, and review the local OpenClaw config access before using the security report.

Vulnerability Patterns
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (2)

T05 · Unauthorized Access and Privilege Escalation

Warning
Location
scripts/advisor.js:184
Finding

Broad Access to Private Agent Conversation History

Content
View full analysis
s.sessionId) .sort((a, b) => (b.updatedAt ?? 0) - (a.updatedAt ?? 0)) .slice(0, maxSessions) .map(s => s.sessionId); } catch { /* ignore */ } } // 若 sessions.json 没读到,扫描 .jsonl 文件 if (activeIds.length === 0) { try { const files = readdirSync(SESSIONS_DIR) .filter(f => f.endsWith('.jsonl') && !f.includes('.deleted')) .slice(0, maxSessions); activeIds = files.map(f => f.replace('.jsonl', '')); } catch { /* ignore */ } } const messages = []; for (const id of activeIds) { const filePath = join(SESSIONS_DIR, `${id}.jsonl`); if (!existsSync(filePath)) continue; try { const lines = readFileSync(filePath, 'utf8').split('\n'); let count = 0; for (const line of lines) { if (!line.trim()) continue; try { const event = JSON.parse(line); if ( event.type === 'message' && event.message?.role === 'user' && Array.isArray(event.message.content) ) { const text = event.message.content .filter(c => c.type === 'text') .map(c => c.text ?? '') .join(' '); if (text.trim()) { messages.push({ text, timestamp: ...[truncated 2334 chars]
Remediation
View remediation

T05 · Unauthorized Access and Privilege Escalation

Note
Location
scripts/advisor.js:424
Finding

Configuration Files Are Loaded Outside the Minimum Needs of Each Command

Content
View full analysis
Remediation
View remediation
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (6)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The trigger phrases are broad enough to match ordinary conversation about models or safety, which can cause the skill to activate unexpectedly. Because the skill can read recent session history and local configuration, overbroad triggering increases the chance of unintended access to sensitive contextual data or misleading recommendations when the user did not explicitly request this tool.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

The skill documentation says it will 'directly analyze' recent sessions, but it does not present a clear user-facing warning or consent step for reading the last 5 sessions' user messages. This creates a privacy risk because users may trigger model advice without realizing that historical conversation content will be accessed and summarized.

Content

No source excerpt is available for this finding.

Ssd 3

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The history-analysis feature traverses recent session files, extracts user-authored text, and surfaces derived signals such as top keywords and model recommendations without clear consent or minimization controls. In this skill context, the feature is explicitly designed to mine prior conversations, which increases the privacy risk because users may not expect old sessions to be repurposed for profiling or inference.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The auto/history analysis mode reads local session transcripts from prior conversations and derives recommendations from them without any consent prompt, disclosure, or opt-in boundary. Even though the data is local, prior user messages may contain sensitive prompts, secrets, or personal information, and this creates an unexpected privacy exposure within the skill context.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
85% confidence
Finding

The natural-language instructions, trigger phrases, and outputs are entirely specified in Chinese, and the skill does not indicate that users may interact in other languages or opt into this locale. Under the stated policy, a fixed language without user choice can be a locale-policy issue unless clearly justified as region-specific.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
95% confidence
Finding

The natural-language comments, labels, help text, and output strings are consistently Chinese-only, which imposes a specific language/locale without presenting an opt-in or alternative. The file does not document a justified region-specific constraint or offer the user a language choice.

Content

No source excerpt is available for this finding.