CWE-89
AllowedImproper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Abstraction: Base · Status: Stable
The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.
27439 vulnerabilities reference this CWE, most recent first.
GHSA-RFRF-JQFV-23VC
Vulnerability from github – Published: 2022-06-25 00:01 – Updated: 2022-06-30 00:00Prison Management System v1.0 was discovered to contain a SQL injection vulnerability via the 'id' parameter at /pms/admin/cells/manage_cell.php:4
{
"affected": [],
"aliases": [
"CVE-2022-32398"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-06-24T02:15:00Z",
"severity": "HIGH"
},
"details": "Prison Management System v1.0 was discovered to contain a SQL injection vulnerability via the \u0027id\u0027 parameter at /pms/admin/cells/manage_cell.php:4",
"id": "GHSA-rfrf-jqfv-23vc",
"modified": "2022-06-30T00:00:29Z",
"published": "2022-06-25T00:01:01Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-32398"
},
{
"type": "WEB",
"url": "https://github.com/Dyrandy/BugBounty/blob/main/pms/cve-2022-32398.md"
},
{
"type": "WEB",
"url": "https://www.sourcecodester.com/php/15368/prison-management-system-phpoop-free-source-code.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-RFV8-G2V3-QFJ9
Vulnerability from github – Published: 2022-05-17 05:44 – Updated: 2022-05-17 05:44SQL injection vulnerability in gallery.php in Gallarific PHP Photo Gallery script 2.1 and possibly other versions allows remote attackers to execute arbitrary SQL commands via the id parameter.
{
"affected": [],
"aliases": [
"CVE-2011-0519"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2011-01-20T19:00:00Z",
"severity": "HIGH"
},
"details": "SQL injection vulnerability in gallery.php in Gallarific PHP Photo Gallery script 2.1 and possibly other versions allows remote attackers to execute arbitrary SQL commands via the id parameter.",
"id": "GHSA-rfv8-g2v3-qfj9",
"modified": "2022-05-17T05:44:09Z",
"published": "2022-05-17T05:44:09Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2011-0519"
},
{
"type": "WEB",
"url": "http://secunia.com/advisories/42792"
},
{
"type": "WEB",
"url": "http://www.exploit-db.com/exploits/15891"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-RFVP-5HHC-VCHW
Vulnerability from github – Published: 2022-05-24 19:18 – Updated: 2022-05-24 19:18Macrob7 Macs Framework Content Management System - 1.14f was discovered to contain a SQL injection vulnerability via the 'roleId' parameter of the editRole and deletUser modules.
{
"affected": [],
"aliases": [
"CVE-2020-23045"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-10-22T20:15:00Z",
"severity": "HIGH"
},
"details": "Macrob7 Macs Framework Content Management System - 1.14f was discovered to contain a SQL injection vulnerability via the \u0027roleId\u0027 parameter of the `editRole` and `deletUser` modules.",
"id": "GHSA-rfvp-5hhc-vchw",
"modified": "2022-05-24T19:18:35Z",
"published": "2022-05-24T19:18:35Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-23045"
},
{
"type": "WEB",
"url": "https://www.vulnerability-lab.com/get_content.php?id=2206"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-RFWH-3J94-GXCR
Vulnerability from github – Published: 2022-05-14 03:44 – Updated: 2022-05-14 03:44SQL Injection exists in TSiteBuilder 1.0 via the id parameter to /site.php, /pagelist.php, or /page_new.php.
{
"affected": [],
"aliases": [
"CVE-2018-6365"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2018-01-29T05:29:00Z",
"severity": "CRITICAL"
},
"details": "SQL Injection exists in TSiteBuilder 1.0 via the id parameter to /site.php, /pagelist.php, or /page_new.php.",
"id": "GHSA-rfwh-3j94-gxcr",
"modified": "2022-05-14T03:44:51Z",
"published": "2022-05-14T03:44:51Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-6365"
},
{
"type": "WEB",
"url": "https://packetstormsecurity.com/files/146128/TSiteBuilder-1.0-SQL-Injection.html"
},
{
"type": "WEB",
"url": "https://www.exploit-db.com/exploits/43915"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-RFWR-VFR5-H8M9
Vulnerability from github – Published: 2022-05-02 03:17 – Updated: 2022-05-02 03:17SQL injection vulnerability in the Resend_Email module in Raven Web Services RavenNuke 2.30 allows remote authenticated administrators to execute arbitrary SQL commands via the user_prefix parameter to modules.php.
{
"affected": [],
"aliases": [
"CVE-2009-0672"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2009-02-22T22:30:00Z",
"severity": "MODERATE"
},
"details": "SQL injection vulnerability in the Resend_Email module in Raven Web Services RavenNuke 2.30 allows remote authenticated administrators to execute arbitrary SQL commands via the user_prefix parameter to modules.php.",
"id": "GHSA-rfwr-vfr5-h8m9",
"modified": "2022-05-02T03:17:24Z",
"published": "2022-05-02T03:17:24Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2009-0672"
},
{
"type": "WEB",
"url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/48791"
},
{
"type": "WEB",
"url": "https://www.exploit-db.com/exploits/8068"
},
{
"type": "WEB",
"url": "http://osvdb.org/52298"
},
{
"type": "WEB",
"url": "http://ravenphpscripts.com/postt17156.html"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/archive/1/500988/100/0/threaded"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/bid/33787"
},
{
"type": "WEB",
"url": "http://www.waraxe.us/advisory-72.html"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-RG35-5RQ5-XX9X
Vulnerability from github – Published: 2023-11-15 00:31 – Updated: 2023-11-20 21:31SQL injection vulnerability in Inventory Management v.1.0 allows a local attacker to execute arbitrary SQL commands via the id paramter in the deleteProduct.php component.
{
"affected": [],
"aliases": [
"CVE-2023-46582"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-11-14T22:15:30Z",
"severity": "HIGH"
},
"details": "SQL injection vulnerability in Inventory Management v.1.0 allows a local attacker to execute arbitrary SQL commands via the id paramter in the deleteProduct.php component.",
"id": "GHSA-rg35-5rq5-xx9x",
"modified": "2023-11-20T21:31:00Z",
"published": "2023-11-15T00:31:07Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-46582"
},
{
"type": "WEB",
"url": "https://github.com/ersinerenler/Code-Projects-Inventory-Management-1.0/blob/main/CVE-2023-46582-Code-Projects-Inventory-Management-1.0-SQL-Injection-Vulnerability.md"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-RG37-QJM5-VW5P
Vulnerability from github – Published: 2026-01-09 18:31 – Updated: 2026-01-09 18:31A flaw has been found in RainyGao DocSys up to 2.02.36. The impacted element is an unknown function of the file src/com/DocSystem/mapping/ReposAuthMapper.xml. Executing a manipulation of the argument searchWord can lead to sql injection. It is possible to launch the attack remotely. The exploit has been published and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
{
"affected": [],
"aliases": [
"CVE-2025-15493"
],
"database_specific": {
"cwe_ids": [
"CWE-74",
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-01-09T17:15:51Z",
"severity": "MODERATE"
},
"details": "A flaw has been found in RainyGao DocSys up to 2.02.36. The impacted element is an unknown function of the file src/com/DocSystem/mapping/ReposAuthMapper.xml. Executing a manipulation of the argument searchWord can lead to sql injection. It is possible to launch the attack remotely. The exploit has been published and may be used. The vendor was contacted early about this disclosure but did not respond in any way.",
"id": "GHSA-rg37-qjm5-vw5p",
"modified": "2026-01-09T18:31:36Z",
"published": "2026-01-09T18:31:36Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-15493"
},
{
"type": "WEB",
"url": "https://github.com/xkalami-Tta0/CVE/blob/main/DocSys/sql%E6%B3%A8%E5%85%A52.md"
},
{
"type": "WEB",
"url": "https://github.com/xkalami-Tta0/CVE/blob/main/DocSys/sql%E6%B3%A8%E5%85%A52.md#vulnerability-analysis-and-reproduction%E6%BC%8F%E6%B4%9E%E5%88%86%E6%9E%90%E5%A4%8D%E7%8E%B0"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.340271"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.340271"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.725374"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-RG3H-X3JW-7JM5
Vulnerability from github – Published: 2026-04-17 22:24 – Updated: 2026-05-12 13:32The fix for CVE-2026-40315 added input validation to SQLiteConversationStore only. Nine sibling backends — MySQL, PostgreSQL, async SQLite/MySQL/PostgreSQL, Turso, SingleStore, Supabase, SurrealDB — pass table_prefix straight into f-string SQL. Same root cause, same code pattern, same exploitation. 52 unvalidated injection points across the codebase.
postgres.py additionally accepts an unvalidated schema parameter used directly in DDL.
Severity
High — CWE-89 (SQL Injection)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N — 8.1
Exploitable in any deployment where table_prefix is derived from external input (multi-tenant setups, API-driven configuration, user-modifiable config files). Default config ("praison_") is not affected.
Details
The CVE-2026-40315 fix added this guard to sqlite.py:52:
# sqlite.py — PATCHED
import re
if not re.match(r'^[a-zA-Z0-9_]*$', table_prefix):
raise ValueError("table_prefix must contain only alphanumeric characters and underscores")
The following backends perform the identical table_prefix → f-string SQL pattern without this guard:
| Backend | File | Line | Injection points |
|---|---|---|---|
| MySQL | persistence/conversation/mysql.py |
65 | 5 |
| PostgreSQL | persistence/conversation/postgres.py |
89 (+schema:88) | 10 |
| Async SQLite | persistence/conversation/async_sqlite.py |
43 | 13 |
| Async MySQL | persistence/conversation/async_mysql.py |
65 | 13 |
| Async PostgreSQL | persistence/conversation/async_postgres.py |
63 | 13 |
| Turso/LibSQL | persistence/conversation/turso.py |
66 | 9 |
| SingleStore | persistence/conversation/singlestore.py |
51 | 7 |
| Supabase | persistence/conversation/supabase.py |
68 | 9 |
| SurrealDB | persistence/conversation/surrealdb.py |
57 | 8 |
| Total | 9 backends | 52 injection points |
Additionally, praisonai-agents/praisonaiagents/storage/backends.py:179 (SQLiteBackend) accepts table_name without validation.
PoC
#!/usr/bin/env python3
"""
Demonstrates: sqlite.py rejects malicious table_prefix, mysql.py accepts it.
Run: python3 poc.py (no dependencies required)
"""
import re
payload = "x'; DROP TABLE users; --"
# ── SQLite (patched) ────────────────────────────────────────────────
try:
if not re.match(r'^[a-zA-Z0-9_]*$', payload):
raise ValueError("blocked")
print(f"[SQLite] FAIL — accepted: {payload}")
except ValueError:
print(f"[SQLite] OK — rejected malicious table_prefix")
# ── MySQL (unpatched) ───────────────────────────────────────────────
sessions_table = f"{payload}sessions"
sql = f"CREATE TABLE IF NOT EXISTS {sessions_table} (session_id VARCHAR(255) PRIMARY KEY)"
print(f"[MySQL] VULN — generated SQL:\n {sql}")
# ── PostgreSQL (unpatched — both table_prefix AND schema) ──────────
schema = "public; DROP SCHEMA data CASCADE; --"
sessions_table = f"{schema}.praison_sessions"
sql = f"CREATE SCHEMA IF NOT EXISTS {schema}"
print(f"[Postgres] VULN — schema injection:\n {sql}")
Output:
[SQLite] OK — rejected malicious table_prefix
[MySQL] VULN — generated SQL:
CREATE TABLE IF NOT EXISTS x'; DROP TABLE users; --sessions (session_id VARCHAR(255) PRIMARY KEY)
[Postgres] VULN — schema injection:
CREATE SCHEMA IF NOT EXISTS public; DROP SCHEMA data CASCADE; --
Vulnerable code (mysql.py, representative)
# mysql.py:65-67 — NO validation
self.table_prefix = table_prefix # ← raw input
self.sessions_table = f"{table_prefix}sessions" # ← into identifier
self.messages_table = f"{table_prefix}messages"
# mysql.py:105 — straight into DDL
cur.execute(f"""
CREATE TABLE IF NOT EXISTS {self.sessions_table} (
session_id VARCHAR(255) PRIMARY KEY, ...
)
""")
Compare with the patched sqlite.py:52:
# sqlite.py:52-53 — HAS validation
if not re.match(r'^[a-zA-Z0-9_]*$', table_prefix):
raise ValueError("table_prefix must contain only alphanumeric characters and underscores")
Impact
When table_prefix originates from untrusted input — multi-tenant tenant names, API request parameters, user-editable config — an attacker achieves arbitrary SQL execution against the backing database. The injected SQL runs in the context of DDL and DML operations (CREATE TABLE, INSERT, SELECT, DELETE), giving the attacker read/write/delete access to the entire database.
PostgreSQL's schema parameter adds a second injection vector in DDL (CREATE SCHEMA IF NOT EXISTS {schema}).
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 4.5.148"
},
"package": {
"ecosystem": "PyPI",
"name": "praisonai"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "4.5.149"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.6.7"
},
"package": {
"ecosystem": "PyPI",
"name": "praisonaiagents"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.6.8"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-41496"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-17T22:24:19Z",
"nvd_published_at": "2026-05-08T14:16:33Z",
"severity": "HIGH"
},
"details": "The fix for [CVE-2026-40315](https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-x783-xp3g-mqhp) added input validation to `SQLiteConversationStore` only. Nine sibling backends \u2014 MySQL, PostgreSQL, async SQLite/MySQL/PostgreSQL, Turso, SingleStore, Supabase, SurrealDB \u2014 pass `table_prefix` straight into f-string SQL. Same root cause, same code pattern, same exploitation. 52 unvalidated injection points across the codebase.\n\n`postgres.py` additionally accepts an unvalidated `schema` parameter used directly in DDL.\n\n### Severity\n\n**High** \u2014 CWE-89 (SQL Injection)\n\nCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N \u2014 **8.1**\n\nExploitable in any deployment where `table_prefix` is derived from external input (multi-tenant setups, API-driven configuration, user-modifiable config files). Default config (`\"praison_\"`) is not affected.\n\n### Details\n\nThe [CVE-2026-40315 fix](https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-x783-xp3g-mqhp) added this guard to `sqlite.py:52`:\n\n```python\n# sqlite.py \u2014 PATCHED\nimport re\nif not re.match(r\u0027^[a-zA-Z0-9_]*$\u0027, table_prefix):\n raise ValueError(\"table_prefix must contain only alphanumeric characters and underscores\")\n```\n\nThe following backends perform the identical `table_prefix \u2192 f-string SQL` pattern **without this guard**:\n\n| Backend | File | Line | Injection points |\n| ---------------- | -------------------------------------------- | --------------- | ----------------------- |\n| MySQL | `persistence/conversation/mysql.py` | 65 | 5 |\n| PostgreSQL | `persistence/conversation/postgres.py` | 89 (+schema:88) | 10 |\n| Async SQLite | `persistence/conversation/async_sqlite.py` | 43 | 13 |\n| Async MySQL | `persistence/conversation/async_mysql.py` | 65 | 13 |\n| Async PostgreSQL | `persistence/conversation/async_postgres.py` | 63 | 13 |\n| Turso/LibSQL | `persistence/conversation/turso.py` | 66 | 9 |\n| SingleStore | `persistence/conversation/singlestore.py` | 51 | 7 |\n| Supabase | `persistence/conversation/supabase.py` | 68 | 9 |\n| SurrealDB | `persistence/conversation/surrealdb.py` | 57 | 8 |\n| **Total** | **9 backends** | | **52 injection points** |\n\nAdditionally, `praisonai-agents/praisonaiagents/storage/backends.py:179` (`SQLiteBackend`) accepts `table_name` without validation.\n\n### PoC\n\n```python\n#!/usr/bin/env python3\n\"\"\"\nDemonstrates: sqlite.py rejects malicious table_prefix, mysql.py accepts it.\nRun: python3 poc.py (no dependencies required)\n\"\"\"\nimport re\n\npayload = \"x\u0027; DROP TABLE users; --\"\n\n# \u2500\u2500 SQLite (patched) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\ntry:\n if not re.match(r\u0027^[a-zA-Z0-9_]*$\u0027, payload):\n raise ValueError(\"blocked\")\n print(f\"[SQLite] FAIL \u2014 accepted: {payload}\")\nexcept ValueError:\n print(f\"[SQLite] OK \u2014 rejected malicious table_prefix\")\n\n# \u2500\u2500 MySQL (unpatched) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nsessions_table = f\"{payload}sessions\"\nsql = f\"CREATE TABLE IF NOT EXISTS {sessions_table} (session_id VARCHAR(255) PRIMARY KEY)\"\nprint(f\"[MySQL] VULN \u2014 generated SQL:\\n {sql}\")\n\n# \u2500\u2500 PostgreSQL (unpatched \u2014 both table_prefix AND schema) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nschema = \"public; DROP SCHEMA data CASCADE; --\"\nsessions_table = f\"{schema}.praison_sessions\"\nsql = f\"CREATE SCHEMA IF NOT EXISTS {schema}\"\nprint(f\"[Postgres] VULN \u2014 schema injection:\\n {sql}\")\n```\n\nOutput:\n\n```\n[SQLite] OK \u2014 rejected malicious table_prefix\n[MySQL] VULN \u2014 generated SQL:\n CREATE TABLE IF NOT EXISTS x\u0027; DROP TABLE users; --sessions (session_id VARCHAR(255) PRIMARY KEY)\n[Postgres] VULN \u2014 schema injection:\n CREATE SCHEMA IF NOT EXISTS public; DROP SCHEMA data CASCADE; --\n```\n\n### Vulnerable code (mysql.py, representative)\n\n```python\n# mysql.py:65-67 \u2014 NO validation\nself.table_prefix = table_prefix # \u2190 raw input\nself.sessions_table = f\"{table_prefix}sessions\" # \u2190 into identifier\nself.messages_table = f\"{table_prefix}messages\"\n\n# mysql.py:105 \u2014 straight into DDL\ncur.execute(f\"\"\"\n CREATE TABLE IF NOT EXISTS {self.sessions_table} (\n session_id VARCHAR(255) PRIMARY KEY, ...\n )\n\"\"\")\n```\n\nCompare with the patched `sqlite.py:52`:\n\n```python\n# sqlite.py:52-53 \u2014 HAS validation\nif not re.match(r\u0027^[a-zA-Z0-9_]*$\u0027, table_prefix):\n raise ValueError(\"table_prefix must contain only alphanumeric characters and underscores\")\n```\n\n### Impact\n\nWhen `table_prefix` originates from untrusted input \u2014 multi-tenant tenant names, API request parameters, user-editable config \u2014 an attacker achieves **arbitrary SQL execution** against the backing database. The injected SQL runs in the context of DDL and DML operations (CREATE TABLE, INSERT, SELECT, DELETE), giving the attacker read/write/delete access to the entire database.\n\nPostgreSQL\u0027s `schema` parameter adds a second injection vector in DDL (`CREATE SCHEMA IF NOT EXISTS {schema}`).",
"id": "GHSA-rg3h-x3jw-7jm5",
"modified": "2026-05-12T13:32:02Z",
"published": "2026-04-17T22:24:19Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-rg3h-x3jw-7jm5"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-41496"
},
{
"type": "PACKAGE",
"url": "https://github.com/MervinPraison/PraisonAI"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
"type": "CVSS_V3"
}
],
"summary": "PraisonAI: SQL Injection via unvalidated `table_prefix` in 9 conversation store backends (incomplete fix for CVE-2026-40315)"
}
GHSA-RG4P-86VF-V29C
Vulnerability from github – Published: 2026-05-29 18:31 – Updated: 2026-05-29 18:31MaxOn ERP Software 8.x-9.x contains an SQL injection vulnerability that allows authenticated users to execute arbitrary SQL queries through the nomor, user, and jenis parameters in the log_activity function. Attackers can send POST requests to /index.php/user/log_activity with malicious SQL code in these parameters to extract sensitive database information including version and database names.
{
"affected": [],
"aliases": [
"CVE-2018-25392"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-05-29T16:16:18Z",
"severity": "HIGH"
},
"details": "MaxOn ERP Software 8.x-9.x contains an SQL injection vulnerability that allows authenticated users to execute arbitrary SQL queries through the nomor, user, and jenis parameters in the log_activity function. Attackers can send POST requests to /index.php/user/log_activity with malicious SQL code in these parameters to extract sensitive database information including version and database names.",
"id": "GHSA-rg4p-86vf-v29c",
"modified": "2026-05-29T18:31:31Z",
"published": "2026-05-29T18:31:31Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-25392"
},
{
"type": "WEB",
"url": "https://www.exploit-db.com/exploits/45605"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/maxon-erp-software-8-x-9-x-sql-injection-via-nomor-parameter"
},
{
"type": "WEB",
"url": "http://demo.maxonerp.com"
},
{
"type": "WEB",
"url": "http://www.talagasoft.com"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-RG4R-734P-28PQ
Vulnerability from github – Published: 2022-05-24 17:37 – Updated: 2022-05-24 17:37SourceCodester Online Health Care System 1.0 is affected by SQL Injection which allows a potential attacker to bypass the authentication system and become an admin.
{
"affected": [],
"aliases": [
"CVE-2020-28074"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2020-12-23T18:15:00Z",
"severity": "CRITICAL"
},
"details": "SourceCodester Online Health Care System 1.0 is affected by SQL Injection which allows a potential attacker to bypass the authentication system and become an admin.",
"id": "GHSA-rg4r-734p-28pq",
"modified": "2022-05-24T17:37:05Z",
"published": "2022-05-24T17:37:05Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-28074"
},
{
"type": "WEB",
"url": "https://www.sourcecodester.com/php/14526/online-health-care-system-php-full-source-code-2020.html"
},
{
"type": "WEB",
"url": "http://packetstormsecurity.com/files/160599/Online-Health-Card-System-1.0-SQL-Injection.html"
}
],
"schema_version": "1.4.0",
"severity": []
}
Mitigation MIT-4
Strategy: Libraries or Frameworks
- Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid [REF-1482].
- For example, consider using persistence layers such as Hibernate or Enterprise Java Beans, which can provide significant protection against SQL injection if used properly.
Mitigation MIT-27
Strategy: Parameterization
- If available, use structured mechanisms that automatically enforce the separation between data and code. These mechanisms may be able to provide the relevant quoting, encoding, and validation automatically, instead of relying on the developer to provide this capability at every point where output is generated.
- Process SQL queries using prepared statements, parameterized queries, or stored procedures. These features should accept parameters or variables and support strong typing. Do not dynamically construct and execute query strings within these features using "exec" or similar functionality, since this may re-introduce the possibility of SQL injection. [REF-867]
Mitigation MIT-17
Strategy: Environment Hardening
- Run your code using the lowest privileges that are required to accomplish the necessary tasks [REF-76]. If possible, create isolated accounts with limited privileges that are only used for a single task. That way, a successful attack will not immediately give the attacker access to the rest of the software or its environment. For example, database applications rarely need to run as the database administrator, especially in day-to-day operations.
- Specifically, follow the principle of least privilege when creating user accounts to a SQL database. The database users should only have the minimum privileges necessary to use their account. If the requirements of the system indicate that a user can read and modify their own data, then limit their privileges so they cannot read/write others' data. Use the strictest permissions possible on all database objects, such as execute-only for stored procedures.
Mitigation MIT-15
For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
Mitigation MIT-28
Strategy: Output Encoding
- While it is risky to use dynamically-generated query strings, code, or commands that mix control and data together, sometimes it may be unavoidable. Properly quote arguments and escape any special characters within those arguments. The most conservative approach is to escape or filter all characters that do not pass an extremely strict allowlist (such as everything that is not alphanumeric or white space). If some special characters are still needed, such as white space, wrap each argument in quotes after the escaping/filtering step. Be careful of argument injection (CWE-88).
- Instead of building a new implementation, such features may be available in the database or programming language. For example, the Oracle DBMS_ASSERT package can check or enforce that parameters have certain properties that make them less vulnerable to SQL injection. For MySQL, the mysql_real_escape_string() API function is available in both C and PHP.
Mitigation MIT-5
Strategy: Input Validation
- Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
- When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
- Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- When constructing SQL query strings, use stringent allowlists that limit the character set based on the expected value of the parameter in the request. This will indirectly limit the scope of an attack, but this technique is less important than proper output encoding and escaping.
- Note that proper output encoding, escaping, and quoting is the most effective solution for preventing SQL injection, although input validation may provide some defense-in-depth. This is because it effectively limits what will appear in output. Input validation will not always prevent SQL injection, especially if you are required to support free-form text fields that could contain arbitrary characters. For example, the name "O'Reilly" would likely pass the validation step, since it is a common last name in the English language. However, it cannot be directly inserted into the database because it contains the "'" apostrophe character, which would need to be escaped or otherwise handled. In this case, stripping the apostrophe might reduce the risk of SQL injection, but it would produce incorrect behavior because the wrong name would be recorded.
- When feasible, it may be safest to disallow meta-characters entirely, instead of escaping them. This will provide some defense in depth. After the data is entered into the database, later processes may neglect to escape meta-characters before use, and you may not have control over those processes.
Mitigation MIT-21
Strategy: Enforcement by Conversion
When the set of acceptable objects, such as filenames or URLs, is limited or known, create a mapping from a set of fixed input values (such as numeric IDs) to the actual filenames or URLs, and reject all other inputs.
Mitigation MIT-39
- Ensure that error messages only contain minimal details that are useful to the intended audience and no one else. The messages need to strike the balance between being too cryptic (which can confuse users) or being too detailed (which may reveal more than intended). The messages should not reveal the methods that were used to determine the error. Attackers can use detailed information to refine or optimize their original attack, thereby increasing their chances of success.
- If errors must be captured in some detail, record them in log messages, but consider what could occur if the log messages can be viewed by attackers. Highly sensitive information such as passwords should never be saved to log files.
- Avoid inconsistent messaging that might accidentally tip off an attacker about internal state, such as whether a user account exists or not.
- In the context of SQL Injection, error messages revealing the structure of a SQL query can help attackers tailor successful attack strings.
Mitigation MIT-29
Strategy: Firewall
Use an application firewall that can detect attacks against this weakness. It can be beneficial in cases in which the code cannot be fixed (because it is controlled by a third party), as an emergency prevention measure while more comprehensive software assurance measures are applied, or to provide defense in depth [REF-1481.
Mitigation MIT-16
Strategy: Environment Hardening
When using PHP, configure the application so that it does not use register_globals. During implementation, develop the application so that it does not rely on this feature, but be wary of implementing a register_globals emulation that is subject to weaknesses such as CWE-95, CWE-621, and similar issues.
CAPEC-108: Command Line Execution through SQL Injection
An attacker uses standard SQL injection methods to inject data into the command line for execution. This could be done directly through misuse of directives such as MSSQL_xp_cmdshell or indirectly through injection of data into the database that would be interpreted as shell commands. Sometime later, an unscrupulous backend application (or could be part of the functionality of the same application) fetches the injected data stored in the database and uses this data as command line arguments without performing proper validation. The malicious data escapes that data plane by spawning new commands to be executed on the host.
CAPEC-109: Object Relational Mapping Injection
An attacker leverages a weakness present in the database access layer code generated with an Object Relational Mapping (ORM) tool or a weakness in the way that a developer used a persistence framework to inject their own SQL commands to be executed against the underlying database. The attack here is similar to plain SQL injection, except that the application does not use JDBC to directly talk to the database, but instead it uses a data access layer generated by an ORM tool or framework (e.g. Hibernate). While most of the time code generated by an ORM tool contains safe access methods that are immune to SQL injection, sometimes either due to some weakness in the generated code or due to the fact that the developer failed to use the generated access methods properly, SQL injection is still possible.
CAPEC-110: SQL Injection through SOAP Parameter Tampering
An attacker modifies the parameters of the SOAP message that is sent from the service consumer to the service provider to initiate a SQL injection attack. On the service provider side, the SOAP message is parsed and parameters are not properly validated before being used to access a database in a way that does not use parameter binding, thus enabling the attacker to control the structure of the executed SQL query. This pattern describes a SQL injection attack with the delivery mechanism being a SOAP message.
CAPEC-470: Expanding Control over the Operating System from the Database
An attacker is able to leverage access gained to the database to read / write data to the file system, compromise the operating system, create a tunnel for accessing the host machine, and use this access to potentially attack other machines on the same network as the database machine. Traditionally SQL injections attacks are viewed as a way to gain unauthorized read access to the data stored in the database, modify the data in the database, delete the data, etc. However, almost every data base management system (DBMS) system includes facilities that if compromised allow an attacker complete access to the file system, operating system, and full access to the host running the database. The attacker can then use this privileged access to launch subsequent attacks. These facilities include dropping into a command shell, creating user defined functions that can call system level libraries present on the host machine, stored procedures, etc.
CAPEC-66: SQL Injection
This attack exploits target software that constructs SQL statements based on user input. An attacker crafts input strings so that when the target software constructs SQL statements based on the input, the resulting SQL statement performs actions other than those the application intended. SQL Injection results from failure of the application to appropriately validate input.
CAPEC-7: Blind SQL Injection
Blind SQL Injection results from an insufficient mitigation for SQL Injection. Although suppressing database error messages are considered best practice, the suppression alone is not sufficient to prevent SQL Injection. Blind SQL Injection is a form of SQL Injection that overcomes the lack of error messages. Without the error messages that facilitate SQL Injection, the adversary constructs input strings that probe the target through simple Boolean SQL expressions. The adversary can determine if the syntax and structure of the injection was successful based on whether the query was executed or not. Applied iteratively, the adversary determines how and where the target is vulnerable to SQL Injection.