CVE-2026-109442 in piflow
Summary
by MITRE • 10/20/2026
piflow 2.0.0 through 2.0.1 contains a remote code execution vulnerability in its DeepAgents chat agent, whose POST /chat and POST /chat/stream endpoints lack authentication. Attackers can instruct the agent to call the exec_shell tool, which runs arbitrary commands via subprocess.run without human approval or an allow-list, exposing environment secrets such as LLM API keys and database credentials.
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Analysis
by VulDB Data Team • 10/20/2026
The vulnerability identified in PiFlow versions 2.0.0 through 2.0.1 represents a critical security failure centered on the DeepAgents chat agent component. This flaw is primarily characterized by an absence of authentication mechanisms for specific application programming interfaces, namely the POST /chat and POST /chat/stream endpoints. In a properly secured system, any endpoint that facilitates interaction with backend services or executes logic based on user input must enforce strict access controls to ensure that only authorized users can initiate these processes. The lack of such enforcement allows unauthenticated remote attackers to directly interact with the chat agent interface from anywhere on the network where the service is accessible. This fundamental misconfiguration effectively bypasses any intended security boundaries, granting external actors direct control over the application's conversational logic without requiring valid credentials or session tokens.
The technical core of this vulnerability lies in how the DeepAgents component processes instructions received through these unauthenticated endpoints. The agent possesses access to a tool called exec_shell, which is designed to execute shell commands via Python’s subprocess.run function. Crucially, this execution occurs without any requirement for human approval and lacks an allow-list or command whitelist mechanism. This design choice means that the system trusts arbitrary input from the user as valid executable code. When an attacker sends a crafted payload instructing the agent to invoke exec_shell with specific arguments, the underlying operating system executes these commands directly within the context of the application process. The absence of sandboxing, privilege separation, or command filtering transforms this feature into a direct remote code execution vector, allowing attackers to run any shell command supported by the host environment.
The operational impact of this vulnerability is severe due to the high-privilege nature of the processes typically running such AI agents and data pipelines. Because the exec_shell tool operates without restriction, an attacker can exploit it to exfiltrate sensitive environmental secrets stored in the system's configuration or runtime variables. This includes LLM API keys, which could be used to incur significant financial costs through unauthorized model usage, as well as database credentials that provide access to persistent data stores containing proprietary information and user records. Beyond credential theft, an attacker with remote code execution capabilities can modify application configurations, install malware, pivot further into the internal network by scanning for other vulnerable services, or destroy system integrity by deleting critical files. The combination of unauthenticated access and unrestricted command execution creates a scenario where complete compromise of the underlying infrastructure is highly probable.
This vulnerability aligns closely with CWE-798, which describes the use of hardcoded credentials or default configurations that facilitate unauthorized access, as well as CWE-20, indicating improper input validation leading to code injection. From an offensive security perspective, this exploit path maps directly to MITRE ATT&CK technique T1059, specifically Command and Scripting Interpreter subtechniques such as sh (T1059.004) or python (T1059.006), which describe the execution of system commands via interpreters. Furthermore, it relates to T1133, External Remote Services, due to the unauthenticated nature of the API endpoints being exploited. The scenario also reflects CWE-862, missing authorization checks, and CWE-77, command injection through improper neutralization of special elements in user-controlled input.
Mitigation strategies must address both the immediate exposure and the underlying architectural flaws. Immediately, organizations should restrict network access to the PiFlow application endpoints using firewall rules or reverse proxy configurations that require authentication before requests reach the application layer. Implementing robust API gateway security policies is essential to enforce identity verification for all POST /chat interactions. Long-term remediation requires a comprehensive redesign of the DeepAgents component to implement strict allow-lists for shell commands, ensuring that only predefined, safe operations can be executed by the agent. Additionally, integrating human-in-the-loop approval mechanisms for any action involving system-level changes or data access is critical. Developers should also adopt principle of least privilege when configuring service accounts and environment variables, ensuring that even if code execution occurs, the impact on sensitive secrets and infrastructure is minimized through proper isolation and permission scoping.