PYSEC-2026-483

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/praisonaiagents/PYSEC-2026-483.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2026-483
Aliases
Published
2026-06-29T11:50:50.769396Z
Modified
2026-06-29T12:26:46.215625163Z
Severity
  • 9.9 (Critical) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H CVSS Calculator
Summary
PraisonAI vulnerable to sandbox escape via `print.__self__` builtins module leak in `execute_code` (subprocess mode)
Details

Summary

execute_code() in praisonaiagents/tools/python_tools.py (v1.6.37, subprocess sandbox mode) can be fully bypassed using print.__self__ to retrieve the real Python builtins module, from which __import__ can be extracted via vars() and runtime string construction. This achieves arbitrary OS command execution on the host, completely defeating the sandbox.

This is a novel bypass that survives all patches for CVE-2026-39888 (frame traversal), CVE-2026-34938 (str subclass), and CVE-2026-40158 (type.__getattribute__ trampoline).

Severity

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H — 9.9 Critical

Root Cause

Three independent gaps in the AST-based security validation:

Gap 1: __self__ missing from _blocked_attrs

In CPython, all built-in functions (C-level functions) have a __self__ attribute that returns the module they belong to. The built-in functions in safe_builtins (print, len, range, etc.) are the real CPython built-in functions, so print.__self__ returns <module 'builtins' (built-in)>.

The _blocked_attrs frozenset (line 52) does NOT include __self__. The AST check at line 74 only blocks attributes that are IN this set, so print.__self__ passes.

Gap 2: vars not blocked as callable or attribute

builtins.vars(obj) returns obj.__dict__. The function name vars is not in the AST Call blocklist (line 83: only blocks exec, eval, compile, __import__, open, input, breakpoint, setattr, delattr, dir). And vars is not in _blocked_attrs for attribute access.

So b.vars(b) (where b is the builtins module) returns builtins.__dict__ — a dict containing ALL built-in functions including __import__, exec, eval, open, etc.

Gap 3: AST Call check only catches ast.Name nodes

The dangerous-call check (line 82-88) only fires when isinstance(func, ast.Name) — i.e., bare-name calls like exec(...). It does NOT catch: - Attribute calls: b.exec(...) — func is ast.Attribute - Subscript calls: d["exec"](...) — func is ast.Subscript

Gap 4: Runtime string construction bypasses string constant check

The string constant check (line 92-98) catches literals like "__import__", but NOT runtime concatenation like "_" + "_" + "import" + "_" + "_". The AST sees 5 separate Constant nodes ("_", "_", "import", "_", "_"), none of which contain any blocked attr as a substring.

Proof of Concept

from praisonaiagents.tools.python_tools import execute_code

# Exploit: 4 lines, bypasses ALL security layers
payload = """
b = print.__self__
d = b.vars(b)
key = "_" + "_" + "import" + "_" + "_"
imp = d[key]
mod = imp("os")
print(mod.popen("id").read())
"""

result = execute_code(code=payload)
print(result)
# Output: {'result': None, 'stdout': 'uid=1000(user) gid=1000(user) ...\n', 'stderr': '', 'success': True}

Step-by-step bypass analysis:

| Line | AST node | Check | Result | |---|---|---|---| | print.__self__ | Attribute(attr='__self__') | __self__ in _blocked_attrs? | NO → passes | | b.vars | Attribute(attr='vars') | vars in _blocked_attrs? | NO → passes | | b.vars(b) | Call(func=Attribute) | isinstance(func, ast.Name)? | NO → passes | | "_", "import" | Constant(value=str) | Contains blocked attr? | NO → passes | | d[key] | Subscript | Not checked | passes | | imp("os") | Call(func=Name('imp')) | imp in blocked calls? | NO → passes |

Result: Full sandbox escape → arbitrary command execution

Impact

An attacker who can influence agent input (via prompt injection, malicious documents, or direct code submission) can:

  • Execute arbitrary commands on the host system
  • Read/write any file accessible to the process
  • Exfiltrate environment variables, API keys, and credentials
  • Pivot to internal networks
    • Install persistent backdoors

Affected

  • Package: praisonaiagents (PyPI)
  • Affected versions: All versions through 1.6.37 (latest)
  • Component: praisonaiagents/tools/python_tools.py, _execute_code_sandboxed() function
    • Default configuration affected: Yes (sandbox_mode="sandbox" is the default)

Remediation

Immediate fix

Add __self__ to _blocked_attrs: python _blocked_attrs = frozenset({ ..., '__self__', # Built-in functions leak their parent module })

Additional hardening

  1. Block vars in the callable blocklist
  2. Extend the ast.Call check to also catch ast.Attribute and ast.Subscript function nodes
  3. Add AST check for BinOp string concatenation that could construct blocked attr names

Fundamental recommendation

Denylist-based Python sandboxes are fundamentally insecure. Each patch introduces a new bypass opportunity. Consider: - Using isolated-vm (Node.js) or WebAssembly-based isolation - Using OS-level sandboxing (seccomp, namespaces, gVisor) - Removing in-process code execution entirely in favor of containerized execution

References

Affected packages

PyPI / praisonaiagents

Package

Name
praisonaiagents
View open source insights on deps.dev
Purl
pkg:pypi/praisonaiagents

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
1.6.40

Affected versions

0.*
0.0.1
0.0.2
0.0.3
0.0.4
0.0.5
0.0.6
0.0.7
0.0.8
0.0.9
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
0.0.20
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
0.0.30
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
0.0.40
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
0.0.50
0.0.51
0.0.52
0.0.53
0.0.54
0.0.56
0.0.57
0.0.58
0.0.59
0.0.60
0.0.61
0.0.62
0.0.63
0.0.64
0.0.65
0.0.66
0.0.67
0.0.68
0.0.69
0.0.70
0.0.71
0.0.72
0.0.73
0.0.74
0.0.75
0.0.76
0.0.77
0.0.78
0.0.79
0.0.80
0.0.81
0.0.82
0.0.83
0.0.84
0.0.85
0.0.86
0.0.87
0.0.88
0.0.89
0.0.90
0.0.91
0.0.92
0.0.93
0.0.94
0.0.95
0.0.96
0.0.97
0.0.98
0.0.99
0.0.100
0.0.101
0.0.102
0.0.103
0.0.104
0.0.105
0.0.106
0.0.107
0.0.108
0.0.109
0.0.110
0.0.111
0.0.112
0.0.113
0.0.114
0.0.115
0.0.116
0.0.117
0.0.118
0.0.119
0.0.120
0.0.121
0.0.122
0.0.123
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0.0.126
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0.0.129
0.0.130
0.0.131
0.0.132
0.0.133
0.0.134
0.0.135
0.0.136
0.0.137
0.0.138
0.0.139
0.0.140
0.0.141
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0.0.171
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0.0.174
0.0.175
0.0.176
0.0.177
0.0.178
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0.0.180
0.0.181
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0.0.183
0.0.184
0.0.185
0.0.187
0.0.188
0.0.189
0.0.190
0.0.191
0.0.192
0.0.193
0.0.194
0.0.195
0.0.196
0.0.197
0.0.198
0.0.199
0.1.0
0.1.1
0.1.2
0.1.3
0.1.4
0.1.5
0.1.6
0.1.7
0.1.8
0.1.9
0.1.10
0.1.11
0.1.12
0.1.13
0.1.14
0.1.15
0.1.16
0.1.17
0.1.18
0.1.19
0.1.20
0.1.21
0.1.22
0.1.23
0.1.24
0.1.25
0.1.26
0.1.27
0.2.0
0.2.1
0.2.2
0.3.0
0.3.1
0.3.2
0.3.3
0.3.4
0.4.0
0.4.1
0.5.0
0.5.1
0.5.2
0.5.3
0.6.0
0.6.1
0.6.2
0.6.3
0.6.4
0.6.5
0.6.6
0.6.7
0.6.8
0.7.0
0.7.1
0.8.0
0.8.1
0.9.0
0.9.1
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.10.5
0.10.6
0.10.7
0.10.8
0.10.9
0.10.10
0.11.0
0.11.1
0.11.2
0.11.3
0.11.4
0.11.5
0.11.6
0.11.7
0.11.8
0.11.9
0.11.10
0.11.11
0.11.12
0.11.13
0.11.14
0.11.15
0.11.16
0.11.17
0.11.18
0.11.19
0.11.20
0.11.21
0.11.22
0.11.23
0.11.24
0.11.25
0.11.27
0.11.28
0.11.29
0.11.30
0.11.31
0.12.0
0.12.1
0.12.2
0.12.3
0.12.4
0.12.5
0.12.6
0.12.7
0.12.8
0.12.9
0.12.10
0.12.11
0.12.12
0.12.13
0.12.14
0.12.15
0.12.16
0.12.17
0.12.18
0.12.19
0.12.20
0.12.21
0.13.0
0.13.1
0.13.2
0.13.3
0.13.4
0.13.5
0.13.6
0.13.7
0.13.8
0.13.9
0.13.10
0.13.11
0.13.12
0.13.13
0.13.14
0.13.15
0.13.16
0.13.17
0.13.18
0.13.19
0.13.20
0.13.21
0.13.22
0.13.23
0.14.0
0.14.1
0.14.2
0.14.3
0.14.4
0.14.5
0.14.6
0.14.7
0.14.8
0.14.9
0.14.10
0.14.11
0.14.12
0.14.14
0.14.15
0.14.16
0.15.0
0.15.1
0.15.2
0.15.3
1.*
1.0.0
1.1.0
1.2.0
1.2.1
1.2.2
1.2.3
1.2.4
1.3.0
1.3.1
1.4.0
1.4.1
1.4.2
1.4.3
1.4.4
1.4.5
1.4.6
1.4.7
1.4.8
1.5.0
1.5.1
1.5.2
1.5.3
1.5.5
1.5.6
1.5.7
1.5.8
1.5.9
1.5.10
1.5.11
1.5.12
1.5.13
1.5.14
1.5.15
1.5.16
1.5.17
1.5.18
1.5.19
1.5.20
1.5.21
1.5.22
1.5.23
1.5.24
1.5.25
1.5.26
1.5.27
1.5.28
1.5.29
1.5.30
1.5.31
1.5.32
1.5.33
1.5.34
1.5.35
1.5.36
1.5.37
1.5.38
1.5.39
1.5.40
1.5.41
1.5.42
1.5.43
1.5.44
1.5.45
1.5.46
1.5.47
1.5.48
1.5.49
1.5.50
1.5.51
1.5.52
1.5.53
1.5.54
1.5.55
1.5.56
1.5.57
1.5.58
1.5.59
1.5.60
1.5.61
1.5.62
1.5.63
1.5.64
1.5.65
1.5.66
1.5.67
1.5.68
1.5.69
1.5.70
1.5.71
1.5.72
1.5.73
1.5.74
1.5.75
1.5.76
1.5.77
1.5.78
1.5.79
1.5.80
1.5.81
1.5.82
1.5.83
1.5.84
1.5.85
1.5.86
1.5.87
1.5.88
1.5.89
1.5.90
1.5.91
1.5.92
1.5.93
1.5.94
1.5.95
1.5.96
1.5.97
1.5.98
1.5.99
1.5.100
1.5.101
1.5.102
1.5.103
1.5.104
1.5.105
1.5.106
1.5.107
1.5.108
1.5.109
1.5.110
1.5.111
1.5.112
1.5.113
1.5.114
1.5.115
1.5.116
1.5.117
1.5.118
1.5.119
1.5.120
1.5.121
1.5.122
1.5.123
1.5.124
1.5.125
1.5.126
1.5.127
1.5.128
1.5.129
1.5.130
1.5.131
1.5.132
1.5.133
1.5.134
1.5.135
1.5.136
1.5.137
1.5.138
1.5.139
1.5.140
1.5.141
1.5.142
1.5.143
1.5.144
1.5.145
1.5.146
1.5.147
1.5.148
1.5.149
1.6.1
1.6.2
1.6.3
1.6.4
1.6.5
1.6.6
1.6.7
1.6.8
1.6.9
1.6.10
1.6.11
1.6.12
1.6.13
1.6.14
1.6.15
1.6.16
1.6.17
1.6.18
1.6.19
1.6.20
1.6.21
1.6.22
1.6.23
1.6.24
1.6.25
1.6.26
1.6.27
1.6.28
1.6.29
1.6.30
1.6.31
1.6.32
1.6.33
1.6.34
1.6.35
1.6.36
1.6.37
1.6.38
1.6.39

Database specific

last_known_affected_version_range 
"<= 1.6.39"
source 
"https://github.com/pypa/advisory-database/blob/main/vulns/praisonaiagents/PYSEC-2026-483.yaml"