CWE

Common Weakness Enumeration

A Community-Developed List of Software Weakness Types

CWE/SANS Top 25 Most Dangerous Software Errors
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ID

CWE-117: Improper Output Neutralization for Logs

Weakness ID: 117
Abstraction: Base
Structure: Simple
Status: Draft
Presentation Filter:
+ Description
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.
+ Relationships

The table(s) below shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.

+ Relevant to the view "Research Concepts" (CWE-1000)
+ Relevant to the view "Architectural Concepts" (CWE-1008)
NatureTypeIDName
MemberOfCategoryCategory1009Audit
+ Relevant to the view "Development Concepts" (CWE-699)
NatureTypeIDName
ChildOfClassClass116Improper Encoding or Escaping of Output
+ Relevant to the view "Seven Pernicious Kingdoms" (CWE-700)
NatureTypeIDName
ChildOfClassClass20Improper Input Validation
+ Modes Of Introduction

The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the software life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.

PhaseNote
ImplementationREALIZATION: This weakness is caused during implementation of an architectural security tactic.
+ Applicable Platforms
The listings below show possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.

Languages

(Language-Independent classes): (Undetermined Prevalence)

+ Common Consequences

The table below specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.

ScopeImpactLikelihood
Integrity
Confidentiality
Availability
Non-Repudiation

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
Medium
+ 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)
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
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.
+ Weakness Ordinalities
OrdinalityDescription
Primary
(where the weakness exists independent of other weaknesses)
+ Memberships
This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
NatureTypeIDName
MemberOfCategoryCategory727OWASP Top Ten 2004 Category A6 - Injection Flaws
MemberOfViewView884CWE Cross-section
MemberOfCategoryCategory963SFP Secondary Cluster: Exposed Data
+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
7 Pernicious KingdomsLog Forging
Software Fault PatternsSFP23Exposed Data
+ References
[REF-52] Greg Hoglund and Gary McGraw. "Exploiting Software: How to Break Code". Addison-Wesley. 2004-02-27. <http://www.exploitingsoftware.com/>.
[REF-53] Alec Muffet. "The night the log was forged". <http://doc.novsu.ac.ru/oreilly/tcpip/puis/ch10_05.htm>.
[REF-43] OWASP. "OWASP TOP 10". <http://www.owasp.org/index.php/Top_10_2007>.
+ Content History
Submissions
Submission DateSubmitterOrganizationSource
7 Pernicious Kingdoms
Modifications
Modification DateModifierOrganizationSource
2008-07-01Eric DalciCigital
updated References, Potential_Mitigations, Time_of_Introduction
2008-09-08CWE Content TeamMITRE
updated Relationships, Other_Notes, References, Taxonomy_Mappings, Weakness_Ordinalities
2008-11-24CWE Content TeamMITRE
updated Background_Details, Common_Consequences, Description, Other_Notes, References
2009-03-10CWE Content TeamMITRE
updated Relationships
2009-05-27CWE Content TeamMITRE
updated Demonstrative_Examples, Description, Name, Related_Attack_Patterns
2009-07-27CWE Content TeamMITRE
updated Potential_Mitigations
2009-10-29CWE Content TeamMITRE
updated Common_Consequences, Other_Notes, Relationships
2010-06-21CWE Content TeamMITRE
updated Description, Name
2010-12-13CWE Content TeamMITRE
updated Demonstrative_Examples
2011-03-29CWE Content TeamMITRE
updated Description, Potential_Mitigations
2011-06-01CWE Content TeamMITRE
updated Common_Consequences
2012-05-11CWE Content TeamMITRE
updated Common_Consequences, Relationships
2012-10-30CWE Content TeamMITRE
updated Potential_Mitigations
2014-07-30CWE Content TeamMITRE
updated Relationships, Taxonomy_Mappings
2017-05-03CWE Content TeamMITRE
updated Related_Attack_Patterns
2017-11-08CWE Content TeamMITRE
updated Applicable_Platforms, Causal_Nature, Modes_of_Introduction, References, Relationships
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: November 14, 2017