PlotAI eval vulnerability

The impact of CVE-2025-1497 is severe. An attacker exploiting this vulnerability can execute arbitrary Python code on the affected system. This grants them complete control, allowing for data exfiltration, system modification, and potentially, lateral movement within the network. The vulnerability's ease of exploitation, coupled with the potential for complete system takeover, makes it a high-priority concern. The PlotAI documentation notes that the vulnerable line is commented out, but enabling the software requires explicitly accepting this risk, highlighting the severity of the issue.

Organizations utilizing PlotAI for LLM-powered applications, particularly those running the software in production environments or on systems with sensitive data, are at significant risk. Users who have enabled the vulnerable feature by uncommenting the code are especially vulnerable.

• python / application: Monitor PlotAI logs for suspicious Python code execution attempts.

import os
import subprocess

def execute_command(command):
    try:
        result = subprocess.check_output(command, shell=True, stderr=subprocess.STDOUT, text=True)
        print(result)
    except subprocess.CalledProcessError as e:
        print(f"Error: {e}")

# Example usage (replace with actual log analysis)
# if 'malicious_code' in log_file_content:
#    execute_command('whoami')

• python / system: Check for unusual processes running with Python interpreter, especially those originating from PlotAI directories.

Get-Process | Where-Object {$_.Path -like "*plotai*" -and $_.ProcessName -notlike "python.exe"}

• generic web: Monitor web server access logs for requests containing suspicious LLM prompts or payloads.

1. 2025-03-10Disclosure

   disclosure

1. 已保留2025-02-20
2. 发布日期2025-03-10
3. 修改日期2025-10-03
4. EPSS 更新日期2026-04-02

The primary mitigation for CVE-2025-1497 is to immediately upgrade PlotAI to version 0.0.7 or later. This version includes the necessary validation to prevent arbitrary code execution. If upgrading is not immediately feasible, consider temporarily disabling the feature that utilizes LLM-generated output, although this will impact functionality. Thoroughly review the PlotAI codebase for any other instances of unvalidated LLM output. After upgrading, confirm the fix by attempting to inject malicious Python code through the LLM interface and verifying that it is properly sanitized.