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Common Weakness Enumeration

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ID

CWE-117: Improper Output Neutralization for Logs

Weakness ID: 117
Vulnerability Mapping: ALLOWEDThis CWE ID may be used to map to real-world vulnerabilities
Abstraction: BaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.
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+ Description
The product 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.
+ Common Consequences
Section HelpThis table 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.
+ Potential Mitigations

Phase: Implementation

Strategy: Input Validation

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.

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 allowlist validation schemes by introducing dangerous inputs after they have been checked.
+ Relationships
Section HelpThis table 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)
NatureTypeIDName
ChildOfClassClass - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource.116Improper Encoding or Escaping of Output
CanFollowBaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.93Improper Neutralization of CRLF Sequences ('CRLF Injection')
Section HelpThis table 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 "Software Development" (CWE-699)
NatureTypeIDName
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1210Audit / Logging Errors
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.137Data Neutralization Issues
Section HelpThis table 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 "Architectural Concepts" (CWE-1008)
NatureTypeIDName
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1009Audit
Section HelpThis table 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 "Seven Pernicious Kingdoms" (CWE-700)
NatureTypeIDName
ChildOfClassClass - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource.20Improper Input Validation
+ 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.
+ Modes Of Introduction
Section HelpThe different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the 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
Section HelpThis listing shows 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

Class: Not Language-Specific (Undetermined Prevalence)

+ 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 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
Chain: inject fake log entries with fake timestamps using CRLF injection
+ Weakness Ordinalities
OrdinalityDescription
Primary
(where the weakness exists independent of other weaknesses)
+ Detection Methods

Automated Static Analysis

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)

Effectiveness: High

+ Memberships
Section HelpThis 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
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.727OWASP Top Ten 2004 Category A6 - Injection Flaws
MemberOfViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries).884CWE Cross-section
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.963SFP Secondary Cluster: Exposed Data
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1134SEI CERT Oracle Secure Coding Standard for Java - Guidelines 00. Input Validation and Data Sanitization (IDS)
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1355OWASP Top Ten 2021 Category A09:2021 - Security Logging and Monitoring Failures
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1407Comprehensive Categorization: Improper Neutralization
+ Vulnerability Mapping Notes

Usage: ALLOWED

(this CWE ID could be used to map to real-world vulnerabilities)

Reason: Acceptable-Use

Rationale:

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.

Comments:

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.
+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
7 Pernicious KingdomsLog Forging
Software Fault PatternsSFP23Exposed Data
The CERT Oracle Secure Coding Standard for Java (2011)IDS03-JExactDo not log unsanitized user input
SEI CERT Oracle Coding Standard for JavaIDS03-JExactDo not log unsanitized user input
+ References
[REF-6] Katrina Tsipenyuk, Brian Chess and Gary McGraw. "Seven Pernicious Kingdoms: A Taxonomy of Software Security Errors". NIST Workshop on Software Security Assurance Tools Techniques and Metrics. NIST. 2005-11-07. <https://samate.nist.gov/SSATTM_Content/papers/Seven%20Pernicious%20Kingdoms%20-%20Taxonomy%20of%20Sw%20Security%20Errors%20-%20Tsipenyuk%20-%20Chess%20-%20McGraw.pdf>.
[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". 2007-05-18. <https://github.com/owasp-top/owasp-top-2007>.
+ Content History
+ Submissions
Submission DateSubmitterOrganization
2006-07-19
(CWE Draft 3, 2006-07-19)
7 Pernicious Kingdoms
+ Modifications
Modification DateModifierOrganization
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
2019-01-03CWE Content TeamMITRE
updated Relationships, Taxonomy_Mappings
2019-06-20CWE Content TeamMITRE
updated Related_Attack_Patterns
2020-02-24CWE Content TeamMITRE
updated Potential_Mitigations, References, Relationships
2020-06-25CWE Content TeamMITRE
updated Potential_Mitigations
2021-10-28CWE Content TeamMITRE
updated Relationships
2023-01-31CWE Content TeamMITRE
updated Description
2023-04-27CWE Content TeamMITRE
updated Detection_Factors, References, Relationships
2023-06-29CWE Content TeamMITRE
updated Mapping_Notes
+ 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
Page Last Updated: July 16, 2024