Improper Output Neutralization for Logs

Description

This vulnerability occurs when an application creates log entries using unvalidated external data, allowing attackers to inject malicious characters or commands that can corrupt log files, trigger parsing errors, or enable log injection attacks.

Extended Description

Log injection happens when user-supplied data containing special characters like newlines (\n), carriage returns (\r), or log-specific control sequences is written directly into log files without proper sanitization. Attackers can exploit this to forge fake log entries, break log file formatting, or obfuscate their malicious activities by injecting deceptive lines that mislead forensic analysis. To prevent this, developers should treat log entries as structured data rather than free-form text. Always sanitize or encode external inputs before writing them to logs, using appropriate logging frameworks that automatically handle escaping. Consider using parameterized logging functions that separate data from the log message template, which neutralizes dangerous characters while maintaining log integrity and readability.

Common Consequences 1

Scope: IntegrityConfidentialityAvailabilityNon-Repudiation

Impact: Modify Application DataHide ActivitiesExecute 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.

Detection Methods 1

Automated Static AnalysisHigh

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.)

Potential Mitigations 3

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 (Incorrect Behavior Order: Validate Before Canonicalize). Make sure that the application does not decode the same input twice (Double Decoding of the Same Data). Such errors could be used to bypass allowlist validation schemes by introducing dangerous inputs after they have been checked.

Demonstrative Examples 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.

Code Example:Bad
Java
java

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 1

CVE-2006-4624Chain: inject fake log entries with fake timestamps using CRLF injection

References 4

Seven Pernicious Kingdoms: A Taxonomy of Software Security Errors

Katrina Tsipenyuk, Brian Chess, and Gary McGraw

NIST Workshop on Software Security Assurance Tools Techniques and Metrics • NIST

07-11-2005

https://samate.nist.gov/SSATTM_Content/papers/Seven%20Pernicious%20Kingdoms%20-%20Taxonomy%20of%20Sw%20Security%20Errors%20-%20Tsipenyuk%20-%20Chess%20-%20McGraw.pdf

ID: REF-6

Exploiting Software: How to Break Code

Greg Hoglund and Gary McGraw

Addison-Wesley

27-02-2004

http://www.exploitingsoftware.com/

ID: REF-52

The night the log was forged

Alec Muffet

http://doc.novsu.ac.ru/oreilly/tcpip/puis/ch10_05.htm

ID: REF-53

OWASP TOP 10

OWASP

18-05-2007

https://github.com/owasp-top/owasp-top-2007

ID: REF-43

Likelihood of Exploit

Medium

Applicable Platforms

Languages:

Not Language-Specific : Undetermined

Modes of Introduction

Implementation

Related Attack Patterns

Alternate Terms

Log forging

An attack-oriented term that could be used in cases in which the adversary can add additional log entries or modify how a log entry is parsed.

Related Weaknesses

ChildOf:

Improper Encoding or Escaping of Output (CWE-116)

ChildOf:

Improper Input Validation (CWE-20)

Taxonomy Mapping

7 Pernicious Kingdoms
Software Fault Patterns
The CERT Oracle Secure Coding Standard for Java (2011)
SEI CERT Oracle Coding Standard for Java