Input validation and sanitization in Agentic AI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is input validation in AI systems?

Input validation is the process of checking if the data provided to an AI system meets the expected format, type, and rules before it is processed. It helps prevent errors and unexpected behavior.

beginner

Why is input sanitization important in AI applications?

Input sanitization cleans or modifies input data to remove harmful or unwanted parts, such as malicious code or invalid characters, ensuring the AI system processes safe and clean data.

beginner

Give an example of input validation for a text input field.

An example is checking if the text input contains only letters and spaces, and is not empty. For instance, a name field should not accept numbers or special symbols.

intermediate

How does input validation help improve AI model performance?

By ensuring only correct and expected data is fed to the model, input validation reduces errors and noise, helping the model learn and predict more accurately.

intermediate

What could happen if input sanitization is skipped in an AI system?

Skipping input sanitization can lead to security risks like injection attacks, corrupted data, or crashes, which can harm the AI system's reliability and safety.

What is the main goal of input validation?

A To clean data from harmful parts

B To check if input data meets expected rules

C To train the AI model

D To store data in a database

Input validation ensures the data fits expected formats and rules before processing.

Which of the following is an example of input sanitization?

A Checking if a number is positive

B Normalizing numerical values

C Splitting data into training and test sets

D Removing script tags from user input

Removing script tags is sanitizing input to prevent harmful code execution.

What risk does skipping input sanitization pose?

A Security vulnerabilities

B Slower model training

C Better data quality

D Improved accuracy

Without sanitization, harmful inputs can cause security issues.

Input validation helps AI models by:

A Adding noise to data

B Increasing data size randomly

C Ensuring data is correct and consistent

D Ignoring data errors

Validating input ensures the model receives clean, correct data.

Which step comes first in handling user input?

A Input validation

B Model prediction

C Output formatting

D Input sanitization

Input validation checks data before any cleaning or processing.

Explain why input validation and sanitization are crucial for AI systems.

Think about what happens if bad data enters the system.

Describe a simple example of input validation and sanitization in a chatbot application.

Consider how a chatbot handles user messages safely.

Practice

1. What is the main purpose of input validation in machine learning systems?

easy

A. To train the model with new data

B. To clean the data by removing unwanted characters

C. To check if the input data is the correct type and format

D. To store data securely in a database

Solution

1. Step 1: Understand input validation

   Input validation means checking if the data is the right type and format before using it.

2. Step 2: Differentiate from sanitization

   Input sanitization cleans data, but validation focuses on correctness and format.

3. Final Answer:

   To check if the input data is the correct type and format -> Option C

4. Quick Check:

   Input validation = Check data type and format [OK]

Hint: Validation means checking data type and format [OK]

Common Mistakes:

• Confusing validation with sanitization
• Thinking validation trains the model
• Assuming validation stores data

2. Which of the following is the correct way to validate that an input is a positive integer in Python?

easy

A. if isinstance(input_value, int) and input_value > 0:

B. if type(input_value) == 'int' and input_value > 0:

C. if input_value.isdigit() and input_value > 0:

D. if input_value > 0:

Solution

1. Step 1: Check type correctly

   Use isinstance(input_value, int) to check if input is an integer.

2. Step 2: Check positivity

   Ensure the integer is greater than zero with input_value > 0.

3. Final Answer:

   if isinstance(input_value, int) and input_value > 0: -> Option A

4. Quick Check:

   Use isinstance and > 0 for positive integer check [OK]

Hint: Use isinstance() to check type, then compare value [OK]

Common Mistakes:

• Using type() == 'int' (wrong syntax)
• Calling isdigit() on non-string input
• Skipping type check before comparison

3. Given the code below, what will be the output?

def sanitize_input(text):
    return text.strip().lower()

user_input = '  Hello World!  '
cleaned = sanitize_input(user_input)
print(cleaned)

medium

A. Hello World!

B. !dlroW olleH

C. HELLO WORLD!

D. hello world!

Solution

1. Step 1: Understand strip()

   The strip() method removes spaces from the start and end of the string.

2. Step 2: Understand lower()

   The lower() method converts all letters to lowercase.

3. Final Answer:

   hello world! -> Option D

4. Quick Check:

   strip + lower = 'hello world!' [OK]

Hint: strip removes spaces, lower makes all letters small [OK]

Common Mistakes:

• Ignoring strip() effect on spaces
• Confusing lower() with upper()
• Expecting original casing in output

4. Identify the error in this input validation code snippet:

def validate_age(age):
    if age.isdigit() and age > 0:
        return True
    else:
        return False

medium

A. Comparing string with integer using > operator

B. Using isdigit() on a non-string type

C. Missing return statement in else block

D. Function name is invalid

Solution

1. Step 1: Check isdigit() usage

   isdigit() works on strings, so age should be a string here.

2. Step 2: Identify type mismatch in comparison

   Comparing age > 0 compares string to int, which causes error.

3. Final Answer:

   Comparing string with integer using > operator -> Option A

4. Quick Check:

   String > int comparison causes error [OK]

Hint: Check types before comparing values [OK]

Common Mistakes:

• Assuming isdigit() converts type
• Ignoring type mismatch in comparisons
• Thinking function name affects validation

5. You receive user data as a list of strings representing ages: ['25', ' 30', 'twenty', '40', '']. Which code snippet correctly validates and sanitizes this data to keep only valid positive integers?

hard

A. valid_ages = [age for age in ages if age.isdigit() and age > 0]

B. valid_ages = [int(age.strip()) for age in ages if age.strip().isdigit() and int(age.strip()) > 0]

C. valid_ages = [int(age) for age in ages if age.isnumeric()]

D. valid_ages = [int(age) for age in ages if age.strip() != '']

Solution

1. Step 1: Sanitize input by stripping spaces

   Use age.strip() to remove spaces before validation.

2. Step 2: Validate with isdigit() and positive check

   Check if stripped string is digits only and convert to int to check > 0.

3. Step 3: Convert valid strings to integers

   Use int(age.strip()) to convert valid strings to integers.

4. Final Answer:

   valid_ages = [int(age.strip()) for age in ages if age.strip().isdigit() and int(age.strip()) > 0] -> Option B

5. Quick Check:

   Strip spaces, check digits, convert to int > 0 [OK]

Hint: Strip spaces before isdigit(), then convert and check > 0 [OK]

Common Mistakes:

• Not stripping spaces before validation
• Comparing strings directly to numbers
• Including empty or non-digit strings