Which Python function is used to protect against log injection attacks?

Which Python function is used to protect against log injection attacks?

• A. validate()
• B. sanitize()
• C. escape()
• D. filter()

Answer: (A)

Preventing log injection means making sure any data you write to logs cannot break the log format or inject extra lines. The reliable approach is to sanitize or escape user input before logging. Escaping converts control characters like newline and carriage return into safe representations (for example turning real newlines into \n) so each log entry stays on a single line. Sanitizing might involve removing or replacing problematic characters with safe placeholders. In Python, there isn’t a single built-in function dedicated to this task, so you typically implement a small helper or use existing encoding tools to produce a safe string. For example, you can sanitize by escaping problematic characters: safe = user_input.replace('\\','\\\\').replace('\n','\\n').replace('\r','\\r') and then log the sanitized string. Alternatively, serializing data with json.dumps or using a structured logger can help ensure logs remain well-formed and parsable. The core idea is to neutralize control characters and other risky content before writing to the log.

Preventing log injection means making sure any data you write to logs cannot break the log format or inject extra lines. The reliable approach is to sanitize or escape user input before logging. Escaping converts control characters like newline and carriage return into safe representations (for example turning real newlines into \n) so each log entry stays on a single line. Sanitizing might involve removing or replacing problematic characters with safe placeholders. In Python, there isn’t a single built-in function dedicated to this task, so you typically implement a small helper or use existing encoding tools to produce a safe string. For example, you can sanitize by escaping problematic characters: safe = user_input.replace('\','\\').replace('\n','\n').replace('\r','\r') and then log the sanitized string. Alternatively, serializing data with json.dumps or using a structured logger can help ensure logs remain well-formed and parsable. The core idea is to neutralize control characters and other risky content before writing to the log.