Integer overflow to memory corruption
Learn Integer overflow to memory corruption through a safe, repeatable binary exploitation workflow.
This tutorial is part of the Binary exploitation track. It focuses on Integer overflow to memory corruption as a practical skill you can apply in labs, CTFs, and authorized assessments.
What you will learn
- describe memory behavior
- triage a crash safely
- connect exploitability to mitigations and remediation
The core idea
Integer overflow to memory corruption is useful when you can explain the system in front of you before you touch it. Start by naming the asset, the user, the trust boundary, and the expected control. Then compare the expected behavior with what the system actually does.
For this topic, write a one-sentence claim before testing: “I expect this control to stop this user from doing this action.” If the evidence contradicts the claim, you have something worth investigating. If it matches, record the result and move on.
Technique focus
- Trace the type, signedness, truncation, allocation size, and copy size that connect arithmetic to memory.
- Build boundary test cases around zero, maximum values, wraparound, and one-byte differences.
- Recommend explicit bounds checks, safer integer helpers, and tests that lock in edge behavior.
Safe practice workflow
- Define the target and confirm it is allowed.
- Create or choose test data that belongs to you.
- Record the normal behavior before changing inputs or state.
- Change one variable at a time and compare the response.
- Save only the evidence needed to explain the behavior.
- Write the likely fix or defensive control in plain language.
Checklist
- Can you describe the security boundary without naming a tool?
- Do you have a clean baseline request, file, log entry, or screenshot?
- Did you avoid destructive actions and real user data?
- Can another learner reproduce your observation from your notes?
- Can you state the impact and the fix in one paragraph?
Checkpoint
Before moving on, write three lines in your notes: what you expected, what you observed, and what you would test next. That habit matters more than memorizing a payload because it scales across targets and technologies.