CVE-2026-6603 Overview
A code injection vulnerability has been identified in ModelScope AgentScope up to version 1.0.18. The vulnerability exists within the execute_python_code and execute_shell_command functions located in the file src/AgentScope/tool/_coding/_python.py. This flaw allows attackers to inject and execute arbitrary code through manipulation of input parameters, potentially leading to unauthorized system access and data compromise.
Critical Impact
Remote attackers can exploit this vulnerability to execute arbitrary Python or shell commands on affected systems, potentially gaining unauthorized access to sensitive data and system resources.
Affected Products
- ModelScope AgentScope versions up to 1.0.18
- Systems utilizing the AgentScope _python.py module for code execution
- Deployments exposing AgentScope functionality to untrusted input
Discovery Timeline
- 2026-04-20 - CVE-2026-6603 published to NVD
- 2026-04-22 - Last updated in NVD database
Technical Details for CVE-2026-6603
Vulnerability Analysis
This vulnerability is classified as CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component), commonly known as code injection. The affected functions execute_python_code and execute_shell_command within AgentScope's coding module fail to properly sanitize user-supplied input before execution.
When an application built on AgentScope accepts external input that is passed to these execution functions, an attacker can craft malicious payloads that break out of intended execution contexts. The network-accessible attack surface combined with no authentication requirements means that any system exposing these functions to untrusted sources is at significant risk.
The exploit has been publicly disclosed, increasing the urgency for organizations to implement protective measures. Despite early notification, the vendor has not responded to disclosure attempts.
Root Cause
The root cause lies in insufficient input validation and sanitization within the execute_python_code and execute_shell_command functions. The code execution module does not properly neutralize special characters or validate input boundaries before passing user-controlled data to Python's execution environment or shell interpreters. This allows attackers to inject arbitrary commands that execute with the privileges of the AgentScope process.
Attack Vector
The vulnerability can be exploited remotely over the network. An attacker does not require authentication or user interaction to exploit this flaw. The attack involves:
- Identifying an AgentScope deployment that exposes the vulnerable code execution functionality
- Crafting a malicious payload containing injected code or shell commands
- Submitting the payload through the exposed interface
- The injected code executes within the context of the AgentScope application
The vulnerability exists in the _python.py module where user input is processed without adequate sanitization before being passed to execution functions. An attacker can craft input that escapes the intended execution context and runs arbitrary Python code or shell commands. Technical details and proof-of-concept information are available in the GitHub Gist PoC Resource.
Detection Methods for CVE-2026-6603
Indicators of Compromise
- Unexpected child processes spawned from AgentScope or Python interpreter processes
- Unusual network connections originating from systems running AgentScope
- Suspicious command-line arguments in process logs containing shell metacharacters or Python execution syntax
- Anomalous file system activity in directories accessible to the AgentScope process
Detection Strategies
- Monitor process execution chains for unexpected shell or Python subprocess spawning from AgentScope applications
- Implement application-level logging to capture all inputs to the execute_python_code and execute_shell_command functions
- Deploy network intrusion detection rules to identify malicious payloads targeting code execution endpoints
- Use endpoint detection and response (EDR) solutions to detect suspicious process behavior patterns
Monitoring Recommendations
- Enable verbose logging for all AgentScope deployments and forward logs to a centralized SIEM
- Implement runtime application self-protection (RASP) to detect code injection attempts
- Monitor for unexpected outbound connections from application servers
- Configure file integrity monitoring on systems running AgentScope to detect unauthorized modifications
How to Mitigate CVE-2026-6603
Immediate Actions Required
- Audit all deployments using ModelScope AgentScope version 1.0.18 and earlier
- Restrict network access to AgentScope deployments to trusted sources only
- Implement input validation at the application layer before passing data to AgentScope functions
- Consider disabling the execute_python_code and execute_shell_command functions if not required for business operations
Patch Information
At the time of publication, no official vendor patch is available. The vendor was contacted regarding this vulnerability but did not respond. Organizations should monitor the VulDB Vulnerability Entry and official ModelScope repositories for updates. In the absence of a patch, implementing compensating controls is essential.
Workarounds
- Deploy a web application firewall (WAF) with rules to filter potentially malicious code injection payloads
- Implement strict input validation using allowlists for any data passed to code execution functions
- Run AgentScope processes in isolated containers or sandboxed environments with minimal privileges
- Use network segmentation to limit the blast radius of potential exploitation
# Example: Restrict network access to AgentScope service using iptables
# Allow only trusted internal networks to access the AgentScope port
iptables -A INPUT -p tcp --dport 8080 -s 10.0.0.0/8 -j ACCEPT
iptables -A INPUT -p tcp --dport 8080 -j DROP
# Run AgentScope with reduced privileges
# Create a dedicated service account with minimal permissions
useradd -r -s /bin/false agentscope-svc
chown -R agentscope-svc:agentscope-svc /opt/agentscope
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

