Improper Output Sanitization for Logs
Weakness ID: 117 (Weakness Base)Status: Draft
+ Description

Description Summary

The software does not properly sanitize or incorrectly sanitizes output that is written to logs.

Extended Description

This can allow an attacker to forge log entries or inject malicious content into logs.

Log forging vulnerabilities occur when:

1. Data enters an application from an untrusted source.

2. The data is written to an application or system log file.

+ Time of Introduction
  • Implementation
+ Applicable Platforms

Languages

All

+ Common Consequences
ScopeEffect
Integrity

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.

+ Likelihood of Exploit

Medium

+ Demonstrative Examples

Example 1

The following web application code attempts to read an integer value from a request object. If the value fails to parse as an integer, then the input is logged with an error message indicating what happened.

(Bad Code)
Example Language: Java 
String val = request.getParameter("val");
try {

int value = Integer.parseInt(val);
}
catch (NumberFormatException) {
log.info("Failed to parse val = " + val);
}
...

If a user submits the string "twenty-one" for val, the following entry is logged: INFO: Failed to parse val=twenty-one However, if an attacker submits the string "twenty-one%0a%0aINFO:+User+logged+out%3dbadguy", the following entry is logged: INFO: Failed to parse val=twenty-one INFO: User logged out=badguy Clearly, attackers can use this same mechanism to insert arbitrary log entries.

+ Observed Examples
ReferenceDescription
CVE-2006-4624Chain: inject fake log entries with fake timestamps using CRLF injection
+ Potential Mitigations

Phase: Architecture and Design

Assume all input is malicious. Use a standard input validation mechanism to validate all input for length, type, syntax, and business rules before accepting the data to be displayed or stored. Use an "accept known good" validation strategy.

Use and specify a strong output encoding (such as ISO 8859-1 or UTF 8).

Do not rely exclusively on blacklist validation to detect malicious input or to encode output. There are too many variants to encode a character; you're likely to miss some variants.

Inputs should be decoded and canonicalized to the application's current internal representation before being validated. Make sure that your application does not decode the same input twice. Such errors could be used to bypass whitelist schemes by introducing dangerous inputs after they have been checked.

+ Background Details

Applications typically use log files to store a history of events or transactions for later review, statistics gathering, or debugging. Depending on the nature of the application, the task of reviewing log files may be performed manually on an as-needed basis or automated with a tool that automatically culls logs for important events or trending information.

+ Weakness Ordinalities
OrdinalityDescription
Primary
(where the weakness exists independent of other weaknesses)
+ Relationships
NatureTypeIDNameView(s) this relationship pertains toView(s)
ChildOfWeakness ClassWeakness Class20Improper Input Validation
Seven Pernicious Kingdoms (primary)700
ChildOfWeakness ClassWeakness Class116Improper Encoding or Escaping of Output
Development Concepts (primary)699
Research Concepts (primary)1000
ChildOfCategoryCategory727OWASP Top Ten 2004 Category A6 - Injection Flaws
Weaknesses in OWASP Top Ten (2004) (primary)711
CanFollowWeakness BaseWeakness Base93Failure to Sanitize CRLF Sequences ('CRLF Injection')
Research Concepts1000
+ Causal Nature

Explicit

+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
7 Pernicious KingdomsLog Forging
+ Related Attack Patterns
CAPEC-IDAttack Pattern Name
(CAPEC Version: 1.4)
93Log Injection-Tampering-Forging
81Web Logs Tampering
106Cross Site Scripting through Log Files
+ References
G. Hoglund and G. McGraw. "Exploiting Software: How to Break Code". Addison-Wesley. February 2004.
A. Muffet. "The night the log was forged". <http://doc.novsu.ac.ru/oreilly/tcpip/puis/ch10_05.htm>.
OWASP. "OWASP TOP 10". <http://www.owasp.org/index.php/Top_10_2007>.
+ Content History
Submissions
Submission DateSubmitterOrganizationSource
7 Pernicious KingdomsExternally Mined
Modifications
Modification DateModifierOrganizationSource
2008-07-01Eric DalciCigitalExternal
updated References, Potential Mitigations, Time of Introduction
2008-09-08CWE Content TeamMITREInternal
updated Relationships, Other Notes, References, Taxonomy Mappings, Weakness Ordinalities
2008-11-24CWE Content TeamMITREInternal
updated Background Details, Common Consequences, Description, Other Notes, References
2009-03-10CWE Content TeamMITREInternal
updated Relationships
2009-05-27CWE Content TeamMITREInternal
updated Demonstrative Examples, Description, Name, Related Attack Patterns
2009-07-27CWE Content TeamMITREInternal
updated Potential Mitigations
2009-10-29CWE Content TeamMITREInternal
updated Common Consequences, Other Notes, Relationships
Previous Entry Names
Change DatePrevious Entry Name
2008-04-11Log Forging
2009-05-27Incorrect Output Sanitization for Logs