CVE-2026-61447 in PraisonAI
Summary
by MITRE • 07/11/2026
PraisonAI before 1.6.78 contains a remote code execution vulnerability in CodeAgent._execute_python() that executes LLM-generated Python code without AST validation, import restrictions, or sandbox enforcement. Attackers can influence LLM output through prompt injection to exfiltrate all environment secrets and execute arbitrary code on the host system.
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Analysis
by VulDB Data Team • 07/11/2026
The PraisonAI vulnerability represents a critical remote code execution flaw in versions prior to 1.6.78 that fundamentally undermines the security posture of systems utilizing this framework. This vulnerability exists within the CodeAgent._execute_python() method where Python code generated by large language models is executed without proper validation mechanisms or security restrictions. The absence of Abstract Syntax Tree validation creates a pathway for malicious code injection that bypasses traditional input sanitization measures. Security researchers categorize this type of vulnerability under CWE-94, which specifically addresses the execution of arbitrary code due to insufficient input validation and lack of proper code sandboxing. The flaw demonstrates a fundamental architectural weakness in how dynamically generated code is handled within the application environment.
The technical exploitation of this vulnerability relies heavily on prompt injection techniques that allow attackers to manipulate the language model's output to generate malicious Python code. Through carefully crafted inputs, adversaries can influence the LLM to produce code that accesses system environment variables, reads sensitive configuration files, and executes arbitrary commands on the host system. This capability extends beyond simple code execution to include complete system compromise through environment variable exfiltration, which can reveal database credentials, API keys, and other sensitive information stored in the application's runtime environment. The vulnerability creates a direct pathway for attackers to escalate privileges and establish persistent access within the compromised system.
Operational impact of this vulnerability extends far beyond immediate code execution capabilities as it fundamentally compromises the security boundaries of the PraisonAI framework. Organizations relying on this software face potential data breaches, system compromise, and unauthorized access to sensitive resources that could include customer information, internal communications, and proprietary business data. The vulnerability's remote nature means attackers can exploit it without physical access to the target systems, making it particularly dangerous for cloud-based deployments or distributed environments where multiple instances may be running. The lack of import restrictions in the execution environment allows attackers to leverage system libraries and modules that could provide additional attack vectors or facilitate further exploitation.
Mitigation strategies for this vulnerability must address both immediate remediation and long-term architectural improvements to prevent similar issues in future implementations. Organizations should immediately update to PraisonAI version 1.6.78 or later where proper input validation, AST analysis, and code sandboxing mechanisms have been implemented. Security controls should include mandatory code review processes for dynamically generated content, implementation of strict import restrictions, and deployment of runtime monitoring systems that can detect anomalous execution patterns. The ATT&CK framework categorizes this type of vulnerability under T1059 which covers command and scripting interpreter techniques, highlighting the need for comprehensive endpoint detection and response capabilities. Additionally, organizations should implement network segmentation and access controls to limit the potential impact of successful exploitation attempts while maintaining proper logging and audit trails for incident response purposes.