CVE-2026-10566 in MetaGPT
Summary
by MITRE • 06/02/2026
A weakness has been identified in FoundationAgents MetaGPT up to 0.8.2. This affects the function Message.check_instruct_content of the file metagpt/schema.py. Executing a manipulation of the argument mapping can lead to deserialization. The attack is restricted to local execution. The exploit has been made available to the public and could be used for attacks. The project was informed of the problem early through an issue report but has not responded yet.
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Analysis
by VulDB Data Team • 06/02/2026
The vulnerability resides within FoundationAgents MetaGPT version 0.8.2 and earlier, specifically in the Message.check_instruct_content function located in metagpt/schema.py. This weakness represents a deserialization flaw that occurs when the system processes argument mapping manipulations, creating a potential attack vector through improper input handling. The vulnerability is classified as a local execution issue, meaning that malicious actors must already have access to the system to exploit it effectively. The nature of this flaw suggests it operates within the application's internal processing mechanisms rather than through external network interfaces, making it a more contained but still significant security concern.
The technical implementation of this vulnerability stems from insufficient validation of input parameters during the message processing workflow. When the Message.check_instruct_content function receives manipulated argument mappings, it fails to properly sanitize or validate these inputs before deserializing them, potentially allowing attackers to inject malicious payloads. This type of vulnerability commonly maps to CWE-502 in the Common Weakness Enumeration catalog, which specifically addresses deserialization of untrusted data. The flaw demonstrates poor input validation practices and inadequate sanitization of data structures that are expected to remain within the application's trusted execution environment.
The operational impact of this vulnerability is significant despite its local execution restriction. While attackers need pre-existing system access, this limitation does not diminish the threat level considerably since local privilege escalation or other initial compromise methods could still lead to full system control. The public availability of exploits for this vulnerability increases the risk exposure, as it enables both skilled and less experienced attackers to leverage the flaw. The delayed response from the project maintainers following the initial issue report indicates a potential gap in security monitoring and incident response protocols, leaving users exposed to potential exploitation without adequate warning or mitigation guidance.
Mitigation strategies for this vulnerability should focus on immediate code-level fixes including enhanced input validation and sanitization within the Message.check_instruct_content function. The implementation should include strict parameter validation before any deserialization occurs, potentially employing whitelisting approaches for acceptable argument mappings. Organizations using MetaGPT should consider implementing additional security controls such as runtime monitoring and anomaly detection for unusual deserialization patterns. The ATT&CK framework's T1059.001 technique for command and scripting interpreter could be relevant in monitoring for malicious payload execution. Regular security audits and vulnerability assessments should be conducted to identify similar patterns in other components, while maintaining active communication with project maintainers to ensure timely patch deployment. System administrators should also consider implementing principle of least privilege access controls to minimize potential damage from local exploitation attempts.