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12 KiB
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1 line
12 KiB
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{"schema_version":"1.9.2","id":"GHSA-26mh-57q7-jfvr","published":"2026-10-29T16:34:26Z","modified":"2026-10-29T16:45:04.443428186Z","aliases":["CVE-2026-61438"],"summary":"PraisonAI vulnerable to Remote Code Execution via Broken AST Sandbox","details":"### Summary\nJobWorkflowExecutor._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.\n\nThe 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.\n\nAttack Scenario\n\nAttacker creates or contributes a YAML workflow file (type: job) with a script: step containing import os; os.system(...).\nA user or CI pipeline with PRAISONAI_ALLOW_JOB_WORKFLOWS=true executes the workflow via praisonai workflow run malicious.yaml.\nArbitrary OS commands execute with the privileges of the calling process.\n\n\nThis 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).\n### PoC\n_Complete instructions, including specific configuration details, to reproduce the vulnerability._\n\n### Impact\n\nRoot Cause — Lines 364–372:\n\npythonallowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'}\nif isinstance(node, ast.Import):\n for alias in node.names:\n if alias.name.split('.')[0] not in allowed_modules:\n return {\"ok\": False, \"error\": f\"Import of '{alias.name}' not allowed...\"}\n\nos 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.\n\nThe __builtins__ restriction (blocking __import__) is irrelevant because the code uses a real import statement processed by the Python bytecode compiler — not a __import__() call.\n\nProof-of-Concept validation (static — no remote network call made):\n\npythonimport ast\n\n_ALLOWED_NODES = (\n ast.Expression, ast.BoolOp, ast.BinOp, ast.UnaryOp, ast.Compare,\n ast.IfExp, ast.Constant, ast.Name, ast.Load, ast.Store, ast.Subscript,\n ast.List, ast.Tuple, ast.Dict, ast.Set,\n ast.And, ast.Or, ast.Not, ast.Eq, ast.NotEq, ast.Lt, ast.LtE,\n ast.Gt, ast.GtE, ast.In, ast.NotIn, ast.Add, ast.Sub, ast.Mult,\n ast.Div, ast.Mod, ast.FloorDiv, ast.USub, ast.UAdd,\n ast.Call, ast.Attribute, ast.keyword, ast.Starred,\n ast.Module, ast.Assign, ast.Import, ast.ImportFrom, ast.alias,\n)\nallowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'}\n\nmalicious = \"import os\\nresult = os.system('id')\"\ntree = ast.parse(malicious, mode=\"exec\")\n\nall_pass = True\nfor node in ast.walk(tree):\n if not isinstance(node, _ALLOWED_NODES):\n print(f\"BLOCKED: {type(node).__name__}\")\n all_pass = False\n if isinstance(node, ast.Import):\n for alias in node.names:\n if alias.name.split('.')[0] not in allowed_modules:\n print(f\"IMPORT BLOCKED: {alias.name}\")\n all_pass = False\n\nprint(\"SANDBOX BYPASSED\" if all_pass else \"sandbox holds\")\n# Output: SANDBOX BYPASSED\n\n\nRecommended Fix\n\nRemove '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:\n\npython# BEFORE (vulnerable)\nallowed_modules = {'os', 'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools'}\n\n# AFTER (safe)\nallowed_modules = {'datetime', 'time', 'json', 'math', 're', 'collections', 'itertools', 'pathlib'}\n\n# If os.path is needed, handle it explicitly:\nif isinstance(node, ast.ImportFrom):\n if node.module == 'os.path':\n pass # allow 'from os.path import join, exists' only\n elif node.module and node.module.split('.')[0] not in allowed_modules:\n return {\"ok\": False, \"error\": f\"Import of '{node.module}' not allowed.\"}\n\nAdditionally, 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).","affected":[{"package":{"name":"praisonai","ecosystem":"PyPI","purl":"pkg:pypi/praisonai"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"4.6.78"}]}],"versions":["0.0.1","0.0.10","0.0.11","0.0.12","0.0.13","0.0.14","0.0.15","0.0.16","0.0.17","0.0.18","0.0.19","0.0.2","0.0.20","0.0.21","0.0.22","0.0.23","0.0.24","0.0.25","0.0.26","0.0.27","0.0.28","0.0.29","0.0.3","0.0.30","0.0.31","0.0.32","0.0.33","0.0.34","0.0.35","0.0.36","0.0.37","0.0.38","0.0.39","0.0.4","0.0.40","0.0.41","0.0.42","0.0.43","0.0.44","0.0.45","0.0.46","0.0.47","0.0.48","0.0.49","0.0.5","0.0.50","0.0.52","0.0.53","0.0.54","0.0.55","0.0.56","0.0.57","0.0.58","0.0.59","0.0.59rc11","0.0.59rc2","0.0.59rc3","0.0.59rc5","0.0.59rc6","0.0.59rc7","0.0.59rc8","0.0.59rc9","0.0.6","0.0.61","0.0.64","0.0.65","0.0.66","0.0.67","0.0.68","0.0.69","0.0.7","0.0.70","0.0.71","0.0.72","0.0.73","0.0.74","0.0.8","0.0.9","0.1.0","0.1.1","0.1.10","0.1.2","0.1.3","0.1.4","0.1.5","0.1.6","0.1.7","0.1.8","0.1.9","1.0.0","1.0.1","1.0.10","1.0.11","1.0.2","1.0.3","1.0.4","1.0.5","1.0.6","1.0.8","1.0.9","2.0.0","2.0.1","2.0.10","2.0.11","2.0.12","2.0.13","2.0.14","2.0.15","2.0.16","2.0.17","2.0.18","2.0.19","2.0.2","2.0.20","2.0.22","2.0.23","2.0.24","2.0.25","2.0.26","2.0.27","2.0.28","2.0.29","2.0.3","2.0.30","2.0.31","2.0.32","2.0.33","2.0.34","2.0.35","2.0.36","2.0.37","2.0.38","2.0.39","2.0.40","2.0.41","2.0.42","2.0.43","2.0.44","2.0.45","2.0.46","2.0.47","2.0.48","2.0.49","2.0.5","2.0.50","2.0.51","2.0.53","2.0.54","2.0.55","2.0.56","2.0.57","2.0.58","2.0.59","2.0.6","2.0.60","2.0.61","2.0.62","2.0.63","2.0.64","2.0.65","2.0.66","2.0.67","2.0.68","2.0.69","2.0.7","2.0.70","2.0.71","2.0.72","2.0.73","2.0.74","2.0.75","2.0.76","2.0.77","2.0.78","2.0.79","2.0.8","2.0.80","2.0.81","2.0.9","2.1.0","2.1.1","2.1.4","2.1.5","2.1.6","2.2.1","2.2.10","2.2.11","2.2.12","2.2.13","2.2.14","2.2.15","2.2.16","2.2.17","2.2.18","2.2.19","2.2.2","2.2.20","2.2.21","2.2.22","2.2.24","2.2.25","2.2.26","2.2.27","2.2.28","2.2.29","2.2.3","2.2.30","2.2.31","2.2.32","2.2.33","2.2.34","2.2.35","2.2.36","2.2.37","2.2.38","2.2.39","2.2.4","2.2.40","2.2.41","2.2.42","2.2.43","2.2.44","2.2.45","2.2.46","2.2.47","2.2.48","2.2.49","2.2.5","2.2.50","2.2.51","2.2.52","2.2.53","2.2.54","2.2.55","2.2.56","2.2.57","2.2.58","2.2.59","2.2.6","2.2.60","2.2.61","2.2.62","2.2.63","2.2.64","2.2.65","2.2.66","2.2.67","2.2.68","2.2.69","2.2.7","2.2.70","2.2.71","2.2.72","2.2.73","2.2.74","2.2.75","2.2.76","2.2.77","2.2.78","2.2.79","2.2.8","2.2.80","2.2.81","2.2.82","2.2.83","2.2.84","2.2.86","2.2.87","2.2.88","2.2.89","2.2.9","2.2.90","2.2.91","2.2.93","2.2.95","2.2.96","2.2.97","2.2.98","2.2.99","2.3.0","2.3.1","2.3.10","2.3.11","2.3.12","2.3.13","2.3.14","2.3.15","2.3.16","2.3.18","2.3.19","2.3.2","2.3.20","2.3.21","2.3.22","2.3.23","2.3.24","2.3.25","2.3.26","2.3.27","2.3.28","2.3.29","2.3.3","2.3.30","2.3.31","2.3.32","2.3.33","2.3.34","2.3.35","2.3.36","2.3.37","2.3.38","2.3.39","2.3.4","2.3.40","2.3.41","2.3.42","2.3.43","2.3.44","2.3.45","2.3.46","2.3.47","2.3.48","2.3.49","2.3.5","2.3.50","2.3.51","2.3.52","2.3.53","2.3.54","2.3.55","2.3.56","2.3.57","2.3.58","2.3.59","2.3.6","2.3.60","2.3.61","2.3.62","2.3.63","2.3.64","2.3.65","2.3.66","2.3.67","2.3.68","2.3.69","2.3.7","2.3.70","2.3.71","2.3.72","2.3.73","2.3.74","2.3.75","2.3.76","2.3.77","2.3.78","2.3.79","2.3.8","2.3.80","2.3.81","2.3.82","2.3.83","2.3.84","2.3.85","2.3.86","2.3.87","2.3.9","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.5.4","2.5.5","2.5.6","2.5.7","2.6.0","2.6.1","2.6.2","2.6.3","2.6.4","2.6.5","2.6.6","2.6.7","2.6.8","2.7.0","2.8.3","2.8.4","2.8.5","2.8.6","2.8.7","2.8.8","2.8.9","2.9.0","2.9.1","2.9.2","3.0.0","3.0.1","3.0.2","3.0.3","3.0.4","3.0.5","3.0.6","3.0.7","3.0.8","3.0.9","3.1.0","3.1.1","3.1.2","3.1.3","3.1.4","3.1.5","3.1.6","3.1.7","3.1.8","3.1.9","3.10.0","3.10.1","3.10.10","3.10.11","3.10.12","3.10.13","3.10.14","3.10.15","3.10.16","3.10.17","3.10.18","3.10.19","3.10.2","3.10.20","3.10.21","3.10.22","3.10.23","3.10.24","3.10.25","3.10.26","3.10.27","3.10.3","3.10.4","3.10.5","3.10.6","3.10.7","3.10.8","3.10.9","3.11.0","3.11.1","3.11.10","3.11.11","3.11.12","3.11.13","3.11.14","3.11.2","3.11.3","3.11.4","3.11.8","3.11.9","3.12.0","3.12.1","3.12.2","3.12.3","3.2.0","3.2.1","3.3.0","3.3.1","3.4.0","3.4.1","3.5.0","3.5.1","3.5.2","3.5.3","3.5.4","3.5.5","3.5.6","3.5.7","3.5.8","3.5.9","3.6.0","3.6.1","3.6.2","3.7.0","3.7.1","3.7.2","3.7.3","3.7.4","3.7.5","3.7.6","3.7.7","3.7.8","3.7.9","3.8.0","3.8.1","3.8.10","3.8.11","3.8.12","3.8.13","3.8.14","3.8.16","3.8.17","3.8.18","3.8.19","3.8.2","3.8.20","3.8.21","3.8.22","3.8.3","3.8.4","3.8.5","3.8.6","3.8.7","3.8.8","3.8.9","3.9.0","3.9.1","3.9.10","3.9.11","3.9.12","3.9.13","3.9.14","3.9.15","3.9.16","3.9.17","3.9.18","3.9.19","3.9.2","3.9.20","3.9.21","3.9.22","3.9.23","3.9.24","3.9.25","3.9.26","3.9.27","3.9.28","3.9.29","3.9.3","3.9.30","3.9.31","3.9.32","3.9.33","3.9.34","3.9.35","3.9.4","3.9.5","3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