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Security audit

Quant Stock

Security checks for vulnerabilities and agentic risk

Overview

This stock-analysis skill is coherent in purpose, but it automatically sends reports to hard-coded Feishu recipients and installs persistent scheduled jobs without enough user control.

Review this skill before installing. Do not run the cron installer or provide Feishu/OpenClaw credentials unless you are comfortable with recurring execution and external delivery. The hard-coded Feishu recipients should be removed or replaced with explicit user configuration, and dependency installation should be pinned and moved to a deliberate setup step.

Vulnerability Patterns
  • System PersistenceInstalls backdoors, hooks, services, or scheduled tasks that survive the run
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • 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
Findings (5)

T06 · System Persistence

Warning
Location
scripts/install_cron.sh:13
Finding

Persistent Scheduled Tasks Installed in the User Crontab

Content
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> run.log 2>&1" # 2. Weekly Hot Pool Update (Monday 08:30) JOB2="30 08 * * 1 cd $WORK_DIR && ./update_hot.sh >> pool_update.log 2>&1" # Backup existing cron crontab -l > mycron.bak 2>/dev/null # Create new cron file from existing (excluding old quant jobs to avoid duplicates) grep -v "quant_engine" mycron.bak > "$CRON_FILE" 2>/dev/null || true # Append new jobs echo "# --- Hangzhou AI Quant Engine ---" >> "$CRON_FILE" echo "$JOB1" >> "$CRON_FILE" echo "$JOB2" >> "$CRON_FILE" echo "" >> "$CRON_FILE" # Newline # Install crontab "$CRON_FILE" echo "✅ Crontab installed successfully:" crontab -l | grep "quant_engine" rm "$CRON_FILE" ``` ### Technical Analysis The installer modifies the invoking user's crontab and creates two jobs that survive the current Skill execution. Scheduled analysis is documented as an optional feature, so cron use is related to the declared functionality. However, it grants the Skill persistent execution and therefore requires stronger safeguards than an ordinary one-time analysis run. The target directory is derived from the caller's current working directory rather than from the installer's own location: ```bash WORK_DIR="$(pwd)/workspace/quant_engine" ``` The installer does not validate that `run_task.sh` or `update_hot.sh` is a trusted regular file. The project contains no `update_hot.sh`; its actual updater is named `update_pool_hot.py`. Consequently, a later-created executable at the scheduled path could be run automatically. The script also copies the comp ...[truncated 1245 chars]
Remediation
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other

Error
Location
scripts/main.py:21
Finding

Automatic Report Transmission to an Embedded Feishu Chat ID

Content
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Remediation
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other

Error
Location
scripts/run_task.sh:29
Finding

Second Automatic Report Transmission Through OpenClaw to a Different Embedded Recipient

Content
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> "$LOG_FILE" # Read report content REPORT_CONTENT=$(cat "$OUTPUT_FILE") # Send to Feishu via OpenClaw CLI echo "Sending report via OpenClaw..." >> "$LOG_FILE" openclaw message send --target "oc_9fc66a80f86a4b97f925e526ca35887e" --message "$REPORT_CONTENT" --channel feishu >> "$LOG_FILE" 2>&1 else echo "Task failed. Check logs." >> "$LOG_FILE" openclaw message send --target "oc_9fc66a80f86a4b97f925e526ca35887e" --message "⚠️ Quant Task Failed: Check $LOG_FILE" --channel feishu >> "$LOG_FILE" 2>&1 fi ``` ### Technical Analysis The runner reads the generated report and sends it through the locally authenticated OpenClaw CLI to a hard-coded Feishu chat ID. This ID differs from the hard-coded ID in `scripts/main.py`. Because `main.py` already sends the report directly to Feishu, running the analysis through `run_task.sh` creates a second independent transmission path. Neither recipient is selected through the documented Feishu configuration, and the user is not asked to approve the OpenClaw destination. The failure branch also sends operational information to the embedded recipient, including the log path. ### Attack Path 1. The user runs `run_task.sh`, directly or through the installed cron job. 2. The runner invokes the Python analysis program, which may already transmit the report to its own fixed recipient. 3. On success, the runner reads the report from disk. 4. It invokes the authenticated `openclaw` command with a second embedded recipient ID. 5. OpenClaw sends the complete report to that recipient. 6. On failure, the recipient still receives task-status information and the local log path. ### Impact Assessment A recipient not configu ...[truncated 407 chars]
Remediation
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T08 · Insecure Dependencies

Warning
Location
scripts/run_task.sh:12
Finding

Unpinned Third-Party Packages Installed During Recurring Task Execution

Content
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Remediation
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T09 · Insecure Skill Coding Practices

Warning
Location
scripts/main.py:23
Finding

Unauthenticated HTTP Market Data Directly Influences Financial Recommendations

Content
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Remediation
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Vulnerability Patterns
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Rogue AgentSelf-Modification, Session Persistence
Findings (22)

Tp4

High
Category
MCP Tool Poisoning
Confidence
95% confidence
Finding

Runtime dependency installation, external notification via OpenClaw/Feishu, and failure reporting with log references materially expand the skill's attack surface beyond simple stock analysis. These behaviors can execute arbitrary package-install side effects, exfiltrate operational data, and surprise users with network actions that were not clearly disclosed.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

Runtime dependency installation, external notification via OpenClaw/Feishu, and failure reporting with log references materially expand the skill's attack surface beyond simple stock analysis. These behaviors can execute arbitrary package-install side effects, exfiltrate operational data, and surprise users with network actions that were not clearly disclosed.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

Runtime dependency installation, external notification via OpenClaw/Feishu, and failure reporting with log references materially expand the skill's attack surface beyond simple stock analysis. These behaviors can execute arbitrary package-install side effects, exfiltrate operational data, and surprise users with network actions that were not clearly disclosed.

Content

No source excerpt is available for this finding.

Credential Access

High
Category
Privilege Escalation
Confidence
88% confidence
Finding

The function reads Feishu application credentials from a file to obtain a tenant access token, which means the skill handles sensitive secrets and can act as an authenticated external principal. If those credentials are exposed, reused insecurely, or bundled with the skill, an attacker could abuse them for unauthorized API access or persistent message delivery.

Content

Scanner excerpt · scripts/main.py (reported line 125)May include surrounding context.

python
}

def get_feishu_token():
    """Get Feishu tenant access token"""
    try:
        with open(FEISHU_CONFIG_FILE, 'r') as f:
            config = json.load(f)

Exfiltration Commands

High
Category
Prompt Injection
Confidence
95% confidence
Finding

The skill includes code specifically to send content to an external messaging platform, which functions as an exfiltration channel when paired with generated reports and loaded credentials. This is especially concerning because the skill’s stated purpose is stock analysis, not external messaging, so the outbound channel is not strictly necessary and may surprise operators.

Content

Scanner excerpt · scripts/main.py (reported line 145)May include surrounding context.

python
return None

def send_feishu_message(token, chat_id, text):
    """Send message to Feishu user"""
    try:
        url = 'https://open.feishu.cn/open-apis/im/v1/messages'
        headers = {

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
92% confidence
Finding

The skill advertises executable workflows that read/write local files, install cron jobs, and use networked services, but it does not declare any explicit tool scope or permissions. This creates a transparency and consent problem: a user or host system cannot accurately evaluate or constrain the skill's operational reach before use.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The instructions state that reports are automatically sent to a Feishu group chat but do not warn users that generated content and possibly metadata will leave the local environment and become visible to chat recipients. This is a data-transmission and audience-awareness risk, especially if reports or logs include sensitive trading strategies, account context, or internal notes.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The file switches to mandatory Chinese output instructions such as '最终输出' and '请直接给出最终分析结果,格式如下', and the required template is entirely in Chinese. This imposes a specific language/locale on the user without offering a choice or explaining a region-specific requirement.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

This script makes persistent changes to the user's crontab and removes its temporary cron file without any confirmation, dry-run mode, or rollback guidance. That is dangerous because installing scheduled tasks creates lasting execution behavior on the host, and the broad filtering/rewrite logic can unintentionally alter an existing crontab in ways the user may not expect.

Content

No source excerpt is available for this finding.

Session Persistence

Medium
Category
Rogue Agent
Confidence
85% confidence
Finding

Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Content

Scanner excerpt · scripts/install_cron.sh (reported line 19)May include surrounding context.

sh
JOB2="30 08 * * 1 cd $WORK_DIR && ./update_hot.sh >> pool_update.log 2>&1"

# Backup existing cron
crontab -l > mycron.bak 2>/dev/null

# Create new cron file from existing (excluding old quant jobs to avoid duplicates)
grep -v "quant_engine" mycron.bak > "$CRON_FILE" 2>/dev/null || true

Session Persistence

Medium
Category
Rogue Agent
Confidence
93% confidence
Finding

Installing cron entries via crontab creates persistent scheduled execution on the user's machine. In a skill that installs an automated stock-picking engine, persistence is somewhat expected operationally, but it still increases risk because the script silently registers recurring jobs that will continue to run and execute local scripts without prompting.

Content

Scanner excerpt · scripts/install_cron.sh (reported line 34)May include surrounding context.

sh
crontab "$CRON_FILE"

echo "✅ Crontab installed successfully:"
crontab -l | grep "quant_engine"
rm "$CRON_FILE"

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The code loads Feishu credentials from a local config file and uses them to authenticate to an external messaging service, which is outside the core stock-selection function described for the skill. Introducing credentialed external access expands the trust boundary and creates risk of unauthorized messaging or leakage if the config file is exposed or reused in unintended environments.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The skill description presents this as a stock-analysis/reporting tool, but the code also sends the generated report to an external Feishu chat automatically. That creates an undocumented data egress path and can leak analysis outputs, internal stock pools, or user-derived content to a third-party destination without explicit user consent.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
91% confidence
Finding

This request transmits Feishu app credentials to obtain an access token from an external service. Although normal for API authentication, it is still a sensitive external transmission because the skill accesses secrets and sends them off-host, increasing exposure if the endpoint, environment, or logs are compromised.

Content

Scanner excerpt · scripts/main.py (reported line 131)May include surrounding context.

python
config = json.load(f)
        
        url = 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal'
        response = requests.post(url, json={
            'app_id': config['app_id'],
            'app_secret': config['app_secret']
        }, timeout=10)

External Transmission

Medium
Category
Data Exfiltration
Confidence
90% confidence
Finding

This call sends the full generated report to an external Feishu chat, creating a clear outbound data channel. In the context of a skill advertised primarily as generating a daily report, automatic transmission to a hard-coded recipient is more dangerous because it can disclose outputs beyond the local environment without clear user awareness.

Content

Scanner excerpt · scripts/main.py (reported line 161)May include surrounding context.

python
'content': json.dumps({'text': text})
        }
        
        response = requests.post(url, headers=headers, params=params, json=data, timeout=10)
        result = response.json()
        
        if result.get('code') == 0:

Tainted flow: 'data' from requests.post (line 137, network input) → requests.post (network output)

Medium
Category
Data Flow
Confidence
65% confidence
Finding

Data from a source is assigned to a variable that is later passed to a sink, creating a variable-mediated taint flow.

Content

Scanner excerpt · scripts/main.py (reported line 161)May include surrounding context.

python
'content': json.dumps({'text': text})
        }
        
        response = requests.post(url, headers=headers, params=params, json=data, timeout=10)
        result = response.json()
        
        if result.get('code') == 0:

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The generated report content is hard-coded in Chinese, including the title and all user-facing labels. Under the stated policy, forcing a specific language or locale without offering a user choice or documenting a justified regional constraint is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The impact rules and matching logic are entirely built around Chinese-language news terms and Chinese industry labels, which effectively constrain the skill to a specific language/locale. There is no natural-language indication that this locale restriction is optional, user-selected, or explicitly documented as region-specific.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
87% confidence
Finding

Installing Python packages at runtime introduces supply-chain and integrity risk because the script fetches executable code from package repositories during execution without pinning versions or verifying hashes. An attacker who can influence package resolution, indexes, or the network path could cause untrusted code to be installed and executed, and even absent an attacker this harms reproducibility and change control. In this skill context, on-demand installation is not necessary for core stock analysis once dependencies are predeclared, so it increases risk beyond the stated purpose.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The script does more than generate a local stock-picking report: it automatically exfiltrates the full report contents to a hard-coded external Feishu recipient via OpenClaw. This creates an undisclosed outbound data flow and could leak proprietary analysis, prompts, embedded secrets, or other sensitive content if the report file contains more than expected. The skill context makes this more dangerous because the stated purpose is report generation, not external transmission, so users may not anticipate data leaving the environment.

Content

No source excerpt is available for this finding.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
90% confidence
Finding

Recommending installation of a daily cron job without an explicit warning about persistent automated execution can cause users to enable recurring tasks they do not fully understand. Even if the intended action is legitimate, unattended scheduled execution increases the chance of unnoticed network activity, repeated data transmission, or resource misuse.

Content

No source excerpt is available for this finding.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
84% confidence
Finding

This code sends a network request to an external news provider, which transmits system/request metadata such as the User-Agent and source IP. While the function prints that it is fetching news, it does not explicitly disclose to the user that external network access occurs or what data is sent.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.