GHSA-26mh-57q7-jfvr PraisonAI vulnerable to Remote Code Execution via Broken AST Sandbox

• PyPI praisonai: < 4.6.78 → fixed in 4.6.78

Summary JobWorkflowExecutor._exec_inline_python() is designed to safely execute inline Python expressions from YAML workflow script: steps using AST validation. The function claims to block dangerous operations by (a) checking all AST nodes against an allowlist, and (b) providing a __builtins__ whitelist that omits __import__, exec, eval, and open. The sandbox is broken. The module import allowlist (allowed_modules) explicitly includes 'os', and the AST allowlist permits ast.Import, ast.ImportFrom, ast.Call, and ast.Attribute nodes. This means the following malicious workflow script: step passes all AST validation checks and executes without error. Attack Scenario Attacker creates or contributes a YAML workflow file (type: job) with a script: step containing import os; os.system(...). A user or CI pipeline with PRAISONAI_ALLOW_JOB_WORKFLOWS=true executes the workflow via praisonai workflow run malicious.yaml. Arbitrary OS commands execute with the privileges of the calling process. This is particularly dangerous in multi-tenant or CI environments where YAML workflows may originate from untrusted sources (e.g., downloaded templates, shared repositories, AI-generated workflows). PoC _Complete instructions, including specific configuration details, to reproduce the vulnerability._ Impact Root Cause — Lines 364–372: pythonallowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'} if isinstance(node, ast.Import): for alias in node.names: if alias.name.split('.')[0] not in allowed_modules: return {"ok": False, "error": f"Import of '{alias.name}' not allowed..."} os is trusted because it is commonly used for path operations (os.path, os.getcwd). However, os.system(), os.popen(), os.execvp(), os.spawn*(), and os._exit() are all accessible once the module is imported, none of which are individually blocked. The __builtins__ restriction (blocking __import__) is irrelevant because the code uses a real import statement processed by the Python bytecode compiler — not a __import__() call. Proof-of-Concept validation (static — no remote network call made): pythonimport ast _ALLOWED_NODES = ( ast.Expression, ast.BoolOp, ast.BinOp, ast.UnaryOp, ast.Compare, ast.IfExp, ast.Constant, ast.Name, ast.Load, ast.Store, ast.Subscript, ast.List, ast.Tuple, ast.Dict, ast.Set, ast.And, ast.Or, ast.Not, ast.Eq, ast.NotEq, ast.Lt, ast.LtE, ast.Gt, ast.GtE, ast.In, ast.NotIn, ast.Add, ast.Sub, ast.Mult, ast.Div, ast.Mod, ast.FloorDiv, ast.USub, ast.UAdd, ast.Call, ast.Attribute, ast.keyword, ast.Starred, ast.Module, ast.Assign, ast.Import, ast.ImportFrom, ast.alias, ) allowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'} malicious = "import os\nresult = os.system('id')" tree = ast.parse(malicious, mode="exec") all_pass = True for node in ast.walk(tree): if not isinstance(node, _ALLOWED_NODES): print(f"BLOCKED: {type(node).__name__}") all_pass = False if isinstance(node, ast.Import): for alias in node.names: if alias.name.split('.')[0] not in allowed_modules: print(f"IMPORT BLOCKED: {alias.name}") all_pass = False print("SANDBOX BYPASSED" if all_pass else "sandbox holds") Output: SANDBOX BYPASSED Recommended Fix Remove 'os' from allowed_modules and replace it with only the safe submodule: 'os.path'. Then validate that the imported name is specifically os.path, not os: python# BEFORE (vulnerable) allowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'} AFTER (safe) allowed_modules = {'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools', 'pathlib'} If os.path is needed, handle it explicitly: if isinstance(node, ast.ImportFrom): if node.module == 'os.path': pass # allow 'from os.path import join, exists' only elif node.module and node.module.split('.')[0] not in allowed_modules: return {"ok": False, "error": f"Import of '{node.module}' not allowed."} Additionally, block ast.Import of os entirely, and consider also removing re (which can be used for ReDoS/CPU exhaustion) and collections (which can be used to reach __subclasses__-style gadgets).