Portée | Impact | Probabilité |
---|---|---|
Integrity Confidentiality Availability Non-Repudiation | Modify Application Data, Hide Activities, Execute Unauthorized Code or Commands Note: Interpretation of the log files may be hindered or misdirected if an attacker can supply data to the application that is subsequently logged verbatim. In the most benign case, an attacker may be able to insert false entries into the log file by providing the application with input that includes appropriate characters. Forged or otherwise corrupted log files can be used to cover an attacker's tracks, possibly by skewing statistics, or even to implicate another party in the commission of a malicious act. If the log file is processed automatically, the attacker can render the file unusable by corrupting the format of the file or injecting unexpected characters. An attacker may inject code or other commands into the log file and take advantage of a vulnerability in the log processing utility. |
Références | Description |
---|---|
CVE-2006-4624 | Chain: inject fake log entries with fake timestamps using CRLF injection |
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.
CAPEC-ID | Nom du modèle d'attaque |
---|---|
CAPEC-268 | Audit Log Manipulation The attacker injects, manipulates, deletes, or forges malicious log entries into the log file, in an attempt to mislead an audit of the log file or cover tracks of an attack. Due to either insufficient access controls of the log files or the logging mechanism, the attacker is able to perform such actions. |
CAPEC-81 | Web Server Logs Tampering Web Logs Tampering attacks involve an attacker injecting, deleting or otherwise tampering with the contents of web logs typically for the purposes of masking other malicious behavior. Additionally, writing malicious data to log files may target jobs, filters, reports, and other agents that process the logs in an asynchronous attack pattern. This pattern of attack is similar to "Log Injection-Tampering-Forging" except that in this case, the attack is targeting the logs of the web server and not the application. |
CAPEC-93 | Log Injection-Tampering-Forging This attack targets the log files of the target host. The attacker injects, manipulates or forges malicious log entries in the log file, allowing them to mislead a log audit, cover traces of attack, or perform other malicious actions. The target host is not properly controlling log access. As a result tainted data is resulting in the log files leading to a failure in accountability, non-repudiation and incident forensics capability. |
Nom | Organisation | Date | Date de publication | Version |
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7 Pernicious Kingdoms | Draft 3 |
Nom | Organisation | Date | Commentaire |
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Eric Dalci | Cigital | updated References, Potential_Mitigations, Time_of_Introduction | |
CWE Content Team | MITRE | updated Relationships, Other_Notes, References, Taxonomy_Mappings, Weakness_Ordinalities | |
CWE Content Team | MITRE | updated Background_Details, Common_Consequences, Description, Other_Notes, References | |
CWE Content Team | MITRE | updated Relationships | |
CWE Content Team | MITRE | updated Demonstrative_Examples, Description, Name, Related_Attack_Patterns | |
CWE Content Team | MITRE | updated Potential_Mitigations | |
CWE Content Team | MITRE | updated Common_Consequences, Other_Notes, Relationships | |
CWE Content Team | MITRE | updated Description, Name | |
CWE Content Team | MITRE | updated Demonstrative_Examples | |
CWE Content Team | MITRE | updated Description, Potential_Mitigations | |
CWE Content Team | MITRE | updated Common_Consequences | |
CWE Content Team | MITRE | updated Common_Consequences, Relationships | |
CWE Content Team | MITRE | updated Potential_Mitigations | |
CWE Content Team | MITRE | updated Relationships, Taxonomy_Mappings | |
CWE Content Team | MITRE | updated Related_Attack_Patterns | |
CWE Content Team | MITRE | updated Applicable_Platforms, Causal_Nature, Modes_of_Introduction, References, Relationships | |
CWE Content Team | MITRE | updated Relationships, Taxonomy_Mappings | |
CWE Content Team | MITRE | updated Related_Attack_Patterns | |
CWE Content Team | MITRE | updated Potential_Mitigations, References, Relationships | |
CWE Content Team | MITRE | updated Potential_Mitigations | |
CWE Content Team | MITRE | updated Relationships | |
CWE Content Team | MITRE | updated Description | |
CWE Content Team | MITRE | updated Detection_Factors, References, Relationships | |
CWE Content Team | MITRE | updated Mapping_Notes | |
CWE Content Team | MITRE | updated Alternate_Terms, Description, Diagram |