CWE-89
Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Hoch
Stable
2006-07-19
00h00 +00:00
00h00 +00:00
2025-12-11
00h00 +00:00
00h00 +00:00
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Name: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
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.
Allgemeine Informationen
Einführungsmodi
Implementation : REALIZATION: This weakness is caused during implementation of an architectural security tactic.Implementation : This weakness typically appears in data-rich applications that save user inputs in a database.
Anwendbare Plattformen
Sprache
Class: Not Language-Specific (Undetermined)Name: SQL (Often)
Technologien
Name: Database Server (Undetermined)Häufige Konsequenzen
| Bereich | Auswirkung | Wahrscheinlichkeit |
|---|---|---|
| Confidentiality Integrity Availability | Execute Unauthorized Code or Commands Note: Adversaries could execute system commands, typically by changing the SQL statement to redirect output to a file that can then be executed. | |
| Confidentiality | Read Application Data Note: Since SQL databases generally hold sensitive data, loss of confidentiality is a frequent problem with SQL injection vulnerabilities. | |
| Authentication | Gain Privileges or Assume Identity, Bypass Protection Mechanism Note: If poor SQL commands are used to check user names and passwords or perform other kinds of authentication, it may be possible to connect to the product as another user with no previous knowledge of the password. | |
| Access Control | Bypass Protection Mechanism Note: If authorization information is held in a SQL database, it may be possible to change this information through the successful exploitation of a SQL injection vulnerability. | |
| Integrity | Modify Application Data Note: Just as it may be possible to read sensitive information, it is also possible to modify or even delete this information with a SQL injection attack. |
Beobachtete Beispiele
| Referenzen | Beschreibung |
|---|---|
CVE-2024-6847 | SQL injection in AI chatbot via a conversation message |
CVE-2025-26794 | SQL injection in e-mail agent through SQLite integration |
CVE-2023-32530 | SQL injection in security product dashboard using crafted certificate fields |
CVE-2021-42258 | SQL injection in time and billing software, as exploited in the wild per CISA KEV. |
CVE-2021-27101 | SQL injection in file-transfer system via a crafted Host header, as exploited in the wild per CISA KEV. |
CVE-2020-12271 | SQL injection in firewall product's admin interface or user portal, as exploited in the wild per CISA KEV. |
CVE-2019-3792 | An automation system written in Go contains an API that is vulnerable to SQL injection allowing the attacker to read privileged data. |
CVE-2004-0366 | chain: SQL injection in library intended for database authentication allows SQL injection and authentication bypass. |
CVE-2008-2790 | SQL injection through an ID that was supposed to be numeric. |
CVE-2008-2223 | SQL injection through an ID that was supposed to be numeric. |
CVE-2007-6602 | SQL injection via user name. |
CVE-2008-5817 | SQL injection via user name or password fields. |
CVE-2003-0377 | SQL injection in security product, using a crafted group name. |
CVE-2008-2380 | SQL injection in authentication library. |
CVE-2017-11508 | SQL injection in vulnerability management and reporting tool, using a crafted password. |
Mögliche Gegenmaßnahmen
Phases : Architecture and DesignPhases : Architecture and Design
Phases : Architecture and Design // Operation
Phases : 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.
Phases : Implementation
Phases : Implementation
Phases : Architecture and Design
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.
Phases : Implementation
Phases : Operation
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.
Phases : Operation // Implementation
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.
Erkennungsmethoden
Automated Static Analysis
Automated Dynamic Analysis
This weakness can be detected using dynamic tools and techniques that interact with the software using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The software's operation may slow down, but it should not become unstable, crash, or generate incorrect results.Wirksamkeit : Moderate
Manual Analysis
Manual analysis can be useful for finding this weakness, but it might not achieve desired code coverage within limited time constraints. This becomes difficult for weaknesses that must be considered for all inputs, since the attack surface can be too large.Automated Static Analysis - Binary or Bytecode
Wirksamkeit : HighDynamic Analysis with Automated Results Interpretation
Wirksamkeit : HighDynamic Analysis with Manual Results Interpretation
Wirksamkeit : SOAR PartialManual Static Analysis - Source Code
Wirksamkeit : HighAutomated Static Analysis - Source Code
Wirksamkeit : HighArchitecture or Design Review
Wirksamkeit : HighHinweise zur Schwachstellen-Zuordnung
Begründung : This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.Kommentar : Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.
Verwandte Angriffsmuster
| CAPEC-ID | Name des Angriffsmusters |
|---|---|
| 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. |
Hinweise
SQL injection can be resultant from special character mismanagement, MAID, or denylist/allowlist problems. It can be primary to authentication errors.Referenzen
REF-1460
NT Web Technology Vulnerabilitiesrain.forest.puppy.
https://phrack.org/issues/54/8
REF-44
24 Deadly Sins of Software SecurityMichael Howard, David LeBlanc, John Viega.
REF-7
Writing Secure CodeMichael Howard, David LeBlanc.
https://www.microsoftpressstore.com/store/writing-secure-code-9780735617223
REF-867
SQL Injection Prevention Cheat SheetOWASP.
https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html
REF-868
SQL Injection Attacks by ExampleSteven Friedl.
http://www.unixwiz.net/techtips/sql-injection.html
REF-869
SQL Injection Cheat SheetFerruh Mavituna.
https://web.archive.org/web/20080126180244/http://ferruh.mavituna.com/sql-injection-cheatsheet-oku/
REF-870
The Database Hacker's Handbook: Defending Database ServersDavid Litchfield, Chris Anley, John Heasman, Bill Grindlay.
REF-871
The Oracle Hacker's Handbook: Hacking and Defending OracleDavid Litchfield.
REF-872
SQL InjectionMicrosoft.
https://learn.microsoft.com/en-us/previous-versions/sql/sql-server-2008-r2/ms161953(v=sql.105)?redirectedfrom=MSDN
REF-873
SQL Injection AttackMicrosoft Security Vulnerability Research & Defense.
https://msrc.microsoft.com/blog/2008/05/sql-injection-attack/
REF-874
Giving SQL Injection the Respect it DeservesMichael Howard.
https://learn.microsoft.com/en-us/archive/blogs/michael_howard/giving-sql-injection-the-respect-it-deserves
REF-875
Top 25 Series - Rank 2 - SQL InjectionFrank Kim.
https://www.sans.org/blog/top-25-series-rank-2-sql-injection/
REF-76
Least PrivilegeSean Barnum, Michael Gegick.
https://web.archive.org/web/20211209014121/https://www.cisa.gov/uscert/bsi/articles/knowledge/principles/least-privilege
REF-62
The Art of Software Security AssessmentMark Dowd, John McDonald, Justin Schuh.
REF-62
The Art of Software Security AssessmentMark Dowd, John McDonald, Justin Schuh.
REF-962
Automated Source Code Security Measure (ASCSM)Object Management Group (OMG).
http://www.omg.org/spec/ASCSM/1.0/
REF-1447
Secure by Design Alert: Eliminating SQL Injection Vulnerabilities in SoftwareCybersecurity and Infrastructure Security Agency.
https://www.cisa.gov/resources-tools/resources/secure-design-alert-eliminating-sql-injection-vulnerabilities-software
REF-1479
State-of-the-Art Resources (SOAR) for Software Vulnerability Detection, Test, and EvaluationGregory Larsen, E. Kenneth Hong Fong, David A. Wheeler, Rama S. Moorthy.
https://www.ida.org/-/media/feature/publications/s/st/stateoftheart-resources-soar-for-software-vulnerability-detection-test-and-evaluation/p-5061.ashx
REF-1481
D3FEND: Application Layer FirewallD3FEND.
https://d3fend.mitre.org/dao/artifact/d3f:ApplicationLayerFirewall/
REF-1482
D3FEND: D3-TL Trusted LibraryD3FEND.
https://d3fend.mitre.org/technique/d3f:TrustedLibrary/
Einreichung
| Name | Organisation | Datum | Veröffentlichungsdatum | Version |
|---|---|---|---|---|
| PLOVER | Draft 3 |
Änderungen
| Name | Organisation | Datum | Kommentar |
|---|---|---|---|
| Eric Dalci | Cigital | updated Time_of_Introduction | |
| KDM Analytics | added/updated white box definitions | ||
| Veracode | Suggested OWASP Top Ten 2004 mapping | ||
| CWE Content Team | MITRE | updated Applicable_Platforms, Common_Consequences, Modes_of_Introduction, Name, Relationships, Other_Notes, Relationship_Notes, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Description | |
| CWE Content Team | MITRE | updated Observed_Examples | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Description, Enabling_Factors_for_Exploitation, Modes_of_Introduction, Name, Observed_Examples, Other_Notes, Potential_Mitigations, References, Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Name, Related_Attack_Patterns | |
| KDM Analytics | Improved the White_Box_Definition | ||
| CWE Content Team | MITRE | updated Description, Name, White_Box_Definitions | |
| CWE Content Team | MITRE | updated Potential_Mitigations | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Detection_Factors, Potential_Mitigations, References, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Potential_Mitigations | |
| CWE Content Team | MITRE | updated Common_Consequences, Demonstrative_Examples, Description, Detection_Factors, Name, Potential_Mitigations, References, Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations | |
| CWE Content Team | MITRE | updated Demonstrative_Examples | |
| CWE Content Team | MITRE | updated Common_Consequences | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations, References | |
| CWE Content Team | MITRE | updated Potential_Mitigations, References, Related_Attack_Patterns, Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Detection_Factors, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Applicable_Platforms, Demonstrative_Examples, Enabling_Factors_for_Exploitation, Likelihood_of_Exploit, Modes_of_Introduction, Observed_Examples, References, Relationships, White_Box_Definitions | |
| CWE Content Team | MITRE | updated References, Relationships | |
| CWE Content Team | MITRE | updated References, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations, Relationships, Time_of_Introduction | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Potential_Mitigations, Relationship_Notes | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations, Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Observed_Examples, Relationships | |
| CWE Content Team | MITRE | updated Observed_Examples, References | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Description | |
| CWE Content Team | MITRE | updated References, Relationships, Time_of_Introduction | |
| CWE Content Team | MITRE | updated Mapping_Notes, Relationships | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Observed_Examples | |
| CWE Content Team | MITRE | updated Alternate_Terms, Common_Consequences, Description, Diagram, References | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Applicable_Platforms, Demonstrative_Examples, References | |
| CWE Content Team | MITRE | updated Detection_Factors, Potential_Mitigations, References | |
| CWE Content Team | MITRE | updated Observed_Examples, Relationships, Weakness_Ordinalities |
