CWE-117

Improper Output Neutralization for Logs

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.

Mitigation ID: MIT-5

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.
Mitigation ID: MIT-30

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.
Mitigation ID: MIT-20

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.
CAPEC-268: Audit Log Manipulation

The attacker injects, manipulates, deletes, or forges malicious log entries into the log file, in an attempt to mislead an audit of the log file or cover tracks of an attack. Due to either insufficient access controls of the log files or the logging mechanism, the attacker is able to perform such actions.

CAPEC-81: Web Server Logs Tampering

Web Logs Tampering attacks involve an attacker injecting, deleting or otherwise tampering with the contents of web logs typically for the purposes of masking other malicious behavior. Additionally, writing malicious data to log files may target jobs, filters, reports, and other agents that process the logs in an asynchronous attack pattern. This pattern of attack is similar to "Log Injection-Tampering-Forging" except that in this case, the attack is targeting the logs of the web server and not the application.

CAPEC-93: Log Injection-Tampering-Forging

This attack targets the log files of the target host. The attacker injects, manipulates or forges malicious log entries in the log file, allowing them to mislead a log audit, cover traces of attack, or perform other malicious actions. The target host is not properly controlling log access. As a result tainted data is resulting in the log files leading to a failure in accountability, non-repudiation and incident forensics capability.

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