PYSEC-2026-4256

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/praisonai/PYSEC-2026-4256.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2026-4256
Aliases
Published
2026-10-15T10:22:47Z
Modified
2026-10-15T14:56:12Z
Severity
  • 9.1 (Critical) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:H CVSS Calculator
Summary
PraisonAI: Code Injection via f-string Interpolation in Deploy API Server Generation
Details

Summary

The deploy/api.py module generates Python server code by directly interpolating the agents_file parameter into an f-string that is then written to a file and executed via subprocess.Popen(). An attacker who controls the agents_file value (via CLI argument, configuration, or upstream API) can inject arbitrary Python code.

Details

src/praisonai/praisonai/deploy/api.py (line 80):

code = f'''...
    praisonai = PraisonAI(agent_file="{agents_file}")
...
    "agent_file": "{agents_file}"
...'''

The generated code is then executed (line 190):

subprocess.Popen(['python', server_file])

agents_file is never sanitized or validated. A malicious value breaks out of the string context:

agents_file = '"); import os; os.system("id"); #'
# Generated code becomes:
# praisonai = PraisonAI(agent_file=""); import os; os.system("id"); #")

The same pattern exists in deploy/docker.py (line 33) for Dockerfile generation.

PoC

# The injection:
agents_file = '"); import os; os.system("id"); #'

# What the generated code looks like:
template = f'praisonai = PraisonAI(agent_file="{agents_file}")'
print(template)
# Output: praisonai = PraisonAI(agent_file=""); import os; os.system("id"); #")

Impact

  • Arbitrary code execution on the machine running the deploy command
  • Supply chain risk if agents_file comes from a configuration file or CI/CD pipeline
References

Affected packages

PyPI / praisonai

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0 Unknown introduced version / All previous versions are affected
Fixed
4.6.78

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
0.0.52
0.0.53
0.0.54
0.0.55
0.0.56
0.0.57
0.0.58
0.0.59rc2
0.0.59rc3
0.0.59rc5
0.0.59rc6
0.0.59rc7
0.0.59rc8
0.0.59rc9
0.0.59rc11
0.0.59
0.0.61
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
0.1.0
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
1.*
1.0.0
1.0.1
1.0.2
1.0.3
1.0.4
1.0.5
1.0.6
1.0.8
1.0.9
1.0.10
1.0.11
2.*
2.0.0
2.0.1
2.0.2
2.0.3
2.0.5
2.0.6
2.0.7
2.0.8
2.0.9
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
2.0.20
2.0.22
2.0.23
2.0.24
2.0.25
2.0.26
2.0.27
2.0.28
2.0.29
2.0.30
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
2.0.50
2.0.51
2.0.53
2.0.54
2.0.55
2.0.56
2.0.57
2.0.58
2.0.59
2.0.60
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
2.0.70
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
2.0.80
2.0.81
2.1.0
2.1.1
2.1.4
2.1.5
2.1.6
2.2.1
2.2.2
2.2.3
2.2.4
2.2.5
2.2.6
2.2.7
2.2.8
2.2.9
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
2.2.20
2.2.21
2.2.22
2.2.24
2.2.25
2.2.26
2.2.27
2.2.28
2.2.29
2.2.30
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
2.2.40
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
2.2.50
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
2.2.60
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
2.2.70
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
2.2.80
2.2.81
2.2.82
2.2.83
2.2.84
2.2.86
2.2.87
2.2.88
2.2.89
2.2.90
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
2.3.2
2.3.3
2.3.4
2.3.5
2.3.6
2.3.7
2.3.8
2.3.9
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
2.3.20
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
2.3.30
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
2.3.40
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
2.3.50
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
2.3.60
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
2.3.70
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
2.3.80
2.3.81
2.3.82
2.3.83
2.3.84
2.3.85
2.3.86
2.3.87
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.*
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
3.2.0
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
3.8.2
3.8.3
3.8.4
3.8.5
3.8.6
3.8.7
3.8.8
3.8.9
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
3.8.20
3.8.21
3.8.22
3.9.0
3.9.1
3.9.2
3.9.3
3.9.4
3.9.5
3.9.6
3.9.7
3.9.8
3.9.9
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
3.9.20
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
3.9.30
3.9.31
3.9.32
3.9.33
3.9.34
3.9.35
3.10.0
3.10.1
3.10.2
3.10.3
3.10.4
3.10.5
3.10.6
3.10.7
3.10.8
3.10.9
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
3.10.20
3.10.21
3.10.22
3.10.23
3.10.24
3.10.25
3.10.26
3.10.27
3.11.0
3.11.1
3.11.2
3.11.3
3.11.4
3.11.8
3.11.9
3.11.10
3.11.11
3.11.12
3.11.13
3.11.14
3.12.0
3.12.1
3.12.2
3.12.3
4.*
4.0.0
4.1.0
4.2.0
4.2.1
4.2.2
4.2.3
4.2.4
4.3.0
4.3.1
4.4.0
4.4.2
4.4.3
4.4.4
4.4.5
4.4.6
4.4.7
4.4.8
4.4.9
4.4.10
4.4.11
4.4.12
4.5.0
4.5.1
4.5.2
4.5.3
4.5.5
4.5.6
4.5.7
4.5.8
4.5.9
4.5.10
4.5.11
4.5.12
4.5.13
4.5.14
4.5.15
4.5.16
4.5.18
4.5.19
4.5.20
4.5.21
4.5.22
4.5.23
4.5.24
4.5.25
4.5.26
4.5.27
4.5.28
4.5.29
4.5.30
4.5.31
4.5.32
4.5.33
4.5.34
4.5.35
4.5.36
4.5.37
4.5.38
4.5.39
4.5.40
4.5.41
4.5.42
4.5.43
4.5.44
4.5.45
4.5.46
4.5.48
4.5.49
4.5.51
4.5.52
4.5.54
4.5.55
4.5.56
4.5.57
4.5.58
4.5.59
4.5.60
4.5.62
4.5.63
4.5.64
4.5.65
4.5.67
4.5.68
4.5.69
4.5.70
4.5.71
4.5.72
4.5.73
4.5.74
4.5.76
4.5.77
4.5.78
4.5.79
4.5.80
4.5.81
4.5.82
4.5.83
4.5.85
4.5.87
4.5.88
4.5.89
4.5.90
4.5.93
4.5.94
4.5.95
4.5.96
4.5.97
4.5.98
4.5.100
4.5.101
4.5.102
4.5.103
4.5.104
4.5.105
4.5.106
4.5.107
4.5.108
4.5.109
4.5.110
4.5.111
4.5.112
4.5.113
4.5.114
4.5.115
4.5.117
4.5.118
4.5.119
4.5.120
4.5.121
4.5.122
4.5.123
4.5.124
4.5.125
4.5.126
4.5.127
4.5.128
4.5.129
4.5.130
4.5.131
4.5.132
4.5.133
4.5.134
4.5.135
4.5.136
4.5.137
4.5.139
4.5.140
4.5.143
4.5.144
4.5.145
4.5.149
4.6.9
4.6.10
4.6.11
4.6.12
4.6.13
4.6.14
4.6.15
4.6.16
4.6.18
4.6.19
4.6.20
4.6.21
4.6.22
4.6.23
4.6.24
4.6.25
4.6.26
4.6.27
4.6.28
4.6.29
4.6.30
4.6.31
4.6.32
4.6.33
4.6.34
4.6.35
4.6.36
4.6.37
4.6.38
4.6.39
4.6.40
4.6.41
4.6.42
4.6.43
4.6.44
4.6.45
4.6.46
4.6.47
4.6.48
4.6.50
4.6.51
4.6.52
4.6.53
4.6.54
4.6.55
4.6.56
4.6.57
4.6.58
4.6.59
4.6.60
4.6.62
4.6.63
4.6.64
4.6.65
4.6.67
4.6.68
4.6.70
4.6.71
4.6.72
4.6.74
4.6.75
4.6.77

Database specific

source
"https://github.com/pypa/advisory-database/blob/main/vulns/praisonai/PYSEC-2026-4256.yaml"