CVE-2026-5974 Overview
A command injection vulnerability has been identified in FoundationAgents MetaGPT, an AI-powered multi-agent framework used for software development automation. The vulnerability exists in the Bash.run function within the metagpt/tools/libs/terminal.py library, allowing remote attackers to inject and execute arbitrary operating system commands. This flaw enables attackers to potentially compromise systems running MetaGPT by manipulating input that is passed to shell execution functions without proper sanitization.
Critical Impact
Remote attackers can execute arbitrary OS commands on systems running vulnerable versions of MetaGPT, potentially leading to complete system compromise, data exfiltration, or lateral movement within the network.
Affected Products
- FoundationAgents MetaGPT versions up to and including 0.8.1
- Systems utilizing the metagpt/tools/libs/terminal.py library
- Deployments with network-accessible MetaGPT instances
Discovery Timeline
- April 9, 2026 - CVE-2026-5974 published to NVD
- April 9, 2026 - Last updated in NVD database
Technical Details for CVE-2026-5974
Vulnerability Analysis
This vulnerability is classified as CWE-77 (Improper Neutralization of Special Elements used in a Command), commonly known as Command Injection. The vulnerable component is the Bash.run function located in metagpt/tools/libs/terminal.py, which processes user-supplied input and passes it to the underlying operating system shell for execution.
The flaw arises from insufficient input validation and sanitization before shell command execution. When untrusted data reaches the Bash.run function, attackers can embed shell metacharacters or command separators to break out of the intended command context and execute arbitrary commands with the privileges of the MetaGPT process.
The network attack vector means exploitation can occur remotely without requiring local access to the target system. No authentication or user interaction is required for exploitation, making this vulnerability particularly dangerous in exposed deployments.
Root Cause
The root cause of CVE-2026-5974 is the lack of proper input sanitization in the Bash.run function within the terminal library. User-controlled input is passed directly to shell execution mechanisms without escaping shell metacharacters such as semicolons (;), pipes (|), backticks (`), or command substitution syntax ($()). This allows attackers to chain additional commands or redirect execution flow.
Attack Vector
The attack can be executed remotely over the network. An attacker can craft malicious input containing shell metacharacters that, when processed by the Bash.run function, will execute attacker-controlled commands on the underlying system. The exploitation does not require authentication or user interaction, making it accessible to unauthenticated remote attackers.
The vulnerability has been documented in GitHub Issue #1931 and a fix has been proposed via Pull Request #1940. The project maintainers were notified early through the pull request but have not yet responded to address the security concern.
Detection Methods for CVE-2026-5974
Indicators of Compromise
- Unexpected process spawning from MetaGPT-related processes, particularly shell commands containing pipe characters, semicolons, or command chaining operators
- Outbound network connections from MetaGPT processes to suspicious IP addresses or domains
- Unusual file system modifications or new files created in system directories by MetaGPT user context
- Log entries showing malformed or suspicious input patterns passed to terminal functions
Detection Strategies
- Monitor system process trees for child processes spawned by MetaGPT that include shell interpreters (bash, sh, cmd) with suspicious arguments
- Implement application-level logging to capture all inputs passed to the Bash.run function and alert on shell metacharacter patterns
- Deploy endpoint detection rules to identify command injection patterns such as ; whoami, | nc, or $() command substitution in process arguments
- Review MetaGPT application logs for error messages indicating command execution failures that may signal exploitation attempts
Monitoring Recommendations
- Enable enhanced logging for the MetaGPT terminal module to capture all command execution requests
- Configure SIEM rules to correlate MetaGPT process activity with unusual system command execution
- Implement network segmentation monitoring to detect unexpected outbound connections from MetaGPT deployment environments
How to Mitigate CVE-2026-5974
Immediate Actions Required
- Identify all deployments of MetaGPT version 0.8.1 and earlier in your environment
- Restrict network access to MetaGPT instances using firewall rules or network segmentation
- Review and audit any external input sources that could reach the vulnerable Bash.run function
- Consider temporarily disabling or isolating MetaGPT deployments until a patch is available
Patch Information
As of the last update, the vendor has not released an official patch for this vulnerability. A community-contributed fix is available via Pull Request #1940. Organizations should monitor the MetaGPT GitHub repository for official security updates and patch releases. Additional technical details are available through VulDB entry #356528.
Workarounds
- Implement network-level access controls to restrict who can interact with MetaGPT instances
- Deploy a web application firewall (WAF) or input validation layer to filter shell metacharacters before they reach the application
- Modify the terminal.py file locally to implement input sanitization using shell escaping functions such as shlex.quote() in Python
- Run MetaGPT in a sandboxed or containerized environment with minimal privileges to limit the impact of successful exploitation
# Example: Network isolation using iptables
# Restrict MetaGPT to internal network only
iptables -A INPUT -p tcp --dport 8080 -s 10.0.0.0/8 -j ACCEPT
iptables -A INPUT -p tcp --dport 8080 -j DROP
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

