Improper Output Neutralization for Logs
Draft Base
Structure: Simple
Description
The product constructs a log message from external input, but it does not neutralize or incorrectly neutralizes special elements when the message is written to a log file.
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
javaIf 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
ID: REF-6
Exploiting Software: How to Break Code
Greg Hoglund and Gary McGraw
Addison-Wesley
27-02-2004
ID: REF-52
The night the log was forged
Alec Muffet
ID: REF-53
Likelihood of Exploit
Medium
Applicable Platforms
Languages:
Not Language-Specific : Undetermined
Modes of Introduction
Implementation
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
Taxonomy Mapping
- 7 Pernicious Kingdoms
- Software Fault Patterns
- The CERT Oracle Secure Coding Standard for Java (2011)
- SEI CERT Oracle Coding Standard for Java