CWE-117: Improper Output Neutralization for Logs (Base)

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: Data enters an application from an untrusted source. The data is written to an application or system log file.

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.::


Applicable Platforms: ::LANGUAGE CLASS:Not Language-Specific:LANGUAGE PREVALENCE:Undetermined::

Modes of Introduction: ::PHASE:Implementation:NOTE:REALIZATION: This weakness is caused during implementation of an architectural security tactic.::



Common Consequences: ::SCOPE:Integrity:SCOPE:Confidentiality:SCOPE:Availability:SCOPE:Non-Repudiation:IMPACT:Modify Application Data:IMPACT:Hide Activities:IMPACT:Execute Unauthorized Code or Commands:NOTE: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: ::METHOD:Automated Static Analysis:DESCRIPTION: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::

Potential Mitigations: ::PHASE:Implementation:STRATEGY:Input Validation:DESCRIPTION: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:DESCRIPTION: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:DESCRIPTION: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.::

Observed Examples: ::REFERENCE:CVE-2006-4624:DESCRIPTION:Chain: inject fake log entries with fake timestamps using CRLF injection:LINK:https://www.cve.org/CVERecord?id=CVE-2006-4624::