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.
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.
Chain: inject fake log entries with fake
timestamps using CRLF injection
Potential Mitigations
Phase: Implementation
Strategy: Input Validation
Assume all input is malicious. Use an "accept known good" input
validation strategy, i.e., use a whitelist 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
(i.e., do not rely on a blacklist). A blacklist 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, blacklists 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 whitelist validation schemes by introducing dangerous inputs after they have been checked.
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.
Weakness Ordinalities
Ordinality
Description
Primary
(where
the weakness exists independent of other weaknesses)
Description
