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CWE-117: Improper Output Neutralization for Logs

Weakness ID: 117
Abstraction: Base
Status: Draft
Presentation Filter:
+ Description

Description Summary

The software does not neutralize or incorrectly neutralizes 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



+ Common Consequences

Technical Impact: Modify application data; Hide activities; Execute unauthorized code or commands

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


+ Demonstrative Examples

Example 1

The following web application code attempts to read an integer value from a request object. If the parseInt call fails, 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) {"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
Chain: inject fake log entries with fake timestamps using CRLF injection
+ Potential Mitigations

Phase: Implementation

Strategy: Input Validation

Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a whitelist 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 (i.e., do not rely on a blacklist). A blacklist 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, blacklists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

Phase: Implementation

Strategy: Output Encoding

Use and specify an output encoding that can be handled by the downstream component that is reading the output. Common encodings include ISO-8859-1, UTF-7, and UTF-8. When an encoding is not specified, a downstream component may choose a different encoding, either by assuming a default encoding or automatically inferring which encoding is being used, which can be erroneous. When the encodings are inconsistent, the downstream component might treat some character or byte sequences as special, even if they are not special in the original encoding. Attackers might then be able to exploit this discrepancy and conduct injection attacks; they even might be able to bypass protection mechanisms that assume the original encoding is also being used by the downstream component.

Phase: Implementation

Strategy: Input Validation

Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180). Make sure that the application does not decode the same input twice (CWE-174). Such errors could be used to bypass whitelist validation 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
(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
ChildOfCategoryCategory963SFP Secondary Cluster: Exposed Data
Software Fault Pattern (SFP) Clusters (primary)888
MemberOfViewView884CWE Cross-section
CWE Cross-section (primary)884
CanFollowWeakness BaseWeakness Base93Improper Neutralization of CRLF Sequences ('CRLF Injection')
Research Concepts1000
+ Causal Nature


+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
7 Pernicious KingdomsLog Forging
Software Fault PatternsSFP23Exposed Data
+ References
G. Hoglund and G. McGraw. "Exploiting Software: How to Break Code". Addison-Wesley. February 2004.
A. Muffet. "The night the log was forged". <>.
+ Content History
Submission DateSubmitterOrganizationSource
7 Pernicious KingdomsExternally Mined
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
2010-06-21CWE Content TeamMITREInternal
updated Description, Name
2010-12-13CWE Content TeamMITREInternal
updated Demonstrative_Examples
2011-03-29CWE Content TeamMITREInternal
updated Description, Potential_Mitigations
2011-06-01CWE Content TeamMITREInternal
updated Common_Consequences
2012-05-11CWE Content TeamMITREInternal
updated Common_Consequences, Relationships
2012-10-30CWE Content TeamMITREInternal
updated Potential_Mitigations
2014-07-30CWE Content TeamMITREInternal
updated Relationships, Taxonomy_Mappings
Previous Entry Names
Change DatePrevious Entry Name
2008-04-11Log Forging
2009-05-27Incorrect Output Sanitization for Logs
2010-06-21Improper Output Sanitization for Logs

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Page Last Updated: January 18, 2017