Fuzzing and dynamic detection: Lab, Review, and Transfer
This is 55AA-002, week 9, session 2. It focuses on "Fuzzing and dynamic detection" and turns the weekly plan into discussable, practicable, and reviewable class artifacts.
Learning Objectives
- Explain where "Fuzzing and dynamic detection" fits in this course and what core problem it addresses.
- Analyze a case or system related to "Fuzzing and dynamic detection" using today's method.
- Connect the session task to the course outcome: Explain root causes and exploitability conditions for common software vulnerabilities.
- Complete the questions, notes, and synthesis required by workshop, exercise, and review.
Prerequisites
- Familiarity with one systems or backend programming language.
- Have read the weekly task: Add a fuzz harness and sanitizers to a target library.
- Be able to record assumptions, evidence, risks, and questions to validate in class.
Preparation
- Open the 55AA-002 course repository, readings, and this week's task brief.
- Write two true/false claims or open questions about "Fuzzing and dynamic detection" before class.
- Be ready to show questions, lab notes, or project fragments from the previous meeting.
Class Flow
0-8Review previous conclusionsQuickly review the concept framework and unresolved questions for "Fuzzing and dynamic detection".
review
Quickly review the concept framework and unresolved questions for "Fuzzing and dynamic detection".
When judging "Fuzzing and dynamic detection", what fact should be confirmed first?
Expected answer: First confirm the object, boundary, attacker or user capability, observable evidence, and evaluation criteria.
Follow-up: If that fact is not directly observable, what minimal experiment would you design?
Opening
Today's session focuses on "Fuzzing and dynamic detection". We will not treat it as an isolated topic. We place it in the course workflow: define the object and boundary, gather evidence, and turn the result into engineering action.
Fuzzing and dynamic detection class demo
Open the example, data, or project fragment related to "Fuzzing and dynamic detection".
Fuzzing and dynamic detection: lecture video
8-18Lab goal and acceptance criteriaDefine today's deliverable, evaluation criteria, and minimum completion line.
setup
Define today's deliverable, evaluation criteria, and minimum completion line.
When judging "Fuzzing and dynamic detection", what fact should be confirmed first?
Expected answer: First confirm the object, boundary, attacker or user capability, observable evidence, and evaluation criteria.
Follow-up: If that fact is not directly observable, what minimal experiment would you design?
Review
Return to the previous discussion. State one important conclusion in a sentence, then state one remaining uncertainty. We will carry those uncertainties into today's analysis.
Fuzzing and dynamic detection class demo
For the weekly task "Add a fuzz harness and sanitizers to a target library.", write the object, boundary, evidence, risk, and next action.
Fuzzing and dynamic detection: lecture video
18-35Instructor demoDemonstrate how to turn the method into reproducible steps or a project fragment.
demo
Demonstrate how to turn the method into reproducible steps or a project fragment.
Where is the weekly task "Add a fuzz harness and sanitizers to a target library." most likely to fail?
Expected answer: Common failures include unclear goals, insufficient evidence, unreproducible environment, and conclusions without process.
Follow-up: What checklist item would reveal this failure early?
Guided question
Here is the first judgment question: if we know only the conclusion but not the environment, inputs, or evidence, can that conclusion guide engineering decisions? Answer yes or no first, then name your assumptions.
Fuzzing and dynamic detection class demo
Open the example, data, or project fragment related to "Fuzzing and dynamic detection".
Fuzzing and dynamic detection: lecture video
35-58Group labStudents execute the weekly task, record evidence, and mark failure points.
lab
Students execute the weekly task, record evidence, and mark failure points.
Where is the weekly task "Add a fuzz harness and sanitizers to a target library." most likely to fail?
Expected answer: Common failures include unclear goals, insufficient evidence, unreproducible environment, and conclusions without process.
Follow-up: What checklist item would reveal this failure early?
Explanation
For "Fuzzing and dynamic detection", the key is not memorizing definitions but following an analysis order: define the object, list boundaries, state who can do what, find observable evidence, and turn the conclusion into a task or test.
Fuzzing and dynamic detection class demo
For the weekly task "Add a fuzz harness and sanitizers to a target library.", write the object, boundary, evidence, risk, and next action.
Fuzzing and dynamic detection: demo and review video
58-70Peer reviewExchange results and check reproducibility, explanation quality, and missed risks.
review
Exchange results and check reproducibility, explanation quality, and missed risks.
What makes a lab result reviewable by someone else?
Expected answer: It needs environment, commands, inputs, outputs, failure conditions, screenshots or logs, and explanations for anomalous results.
Follow-up: How would you write this requirement into homework or project acceptance criteria?
Practice transition
Now apply that order to the weekly task: Add a fuzz harness and sanitizers to a target library. Do not write only the final answer; preserve how you ruled out alternatives.
Fuzzing and dynamic detection class demo
Open the example, data, or project fragment related to "Fuzzing and dynamic detection".
Fuzzing and dynamic detection: demo and review video
70-80In-class revisionRevise notes, code, configuration, models, or report structure based on review feedback.
fix
Revise notes, code, configuration, models, or report structure based on review feedback.
What makes a lab result reviewable by someone else?
Expected answer: It needs environment, commands, inputs, outputs, failure conditions, screenshots or logs, and explanations for anomalous results.
Follow-up: How would you write this requirement into homework or project acceptance criteria?
Summary
Today's deliverable is not polished prose. It is a set of reviewable judgments. After class, complete the required evidence, commands, screenshots, logs, or review notes.
Fuzzing and dynamic detection class demo
For the weekly task "Add a fuzz harness and sanitizers to a target library.", write the object, boundary, evidence, risk, and next action.
Fuzzing and dynamic detection: demo and review video
80-87Selected sharingSelect two or three groups to explain findings, tradeoffs, and next steps.
share
Select two or three groups to explain findings, tradeoffs, and next steps.
What makes a lab result reviewable by someone else?
Expected answer: It needs environment, commands, inputs, outputs, failure conditions, screenshots or logs, and explanations for anomalous results.
Follow-up: How would you write this requirement into homework or project acceptance criteria?
Summary
Today's deliverable is not polished prose. It is a set of reviewable judgments. After class, complete the required evidence, commands, screenshots, logs, or review notes.
Fuzzing and dynamic detection class demo
Open the example, data, or project fragment related to "Fuzzing and dynamic detection".
Fuzzing and dynamic detection: demo and review video
87-90Submission checkConfirm homework, naming conventions, evidence artifacts, and deadline.
summary
Confirm homework, naming conventions, evidence artifacts, and deadline.
What makes a lab result reviewable by someone else?
Expected answer: It needs environment, commands, inputs, outputs, failure conditions, screenshots or logs, and explanations for anomalous results.
Follow-up: How would you write this requirement into homework or project acceptance criteria?
Summary
Today's deliverable is not polished prose. It is a set of reviewable judgments. After class, complete the required evidence, commands, screenshots, logs, or review notes.
Fuzzing and dynamic detection class demo
For the weekly task "Add a fuzz harness and sanitizers to a target library.", write the object, boundary, evidence, risk, and next action.
Fuzzing and dynamic detection: demo and review video
Homework
Add a fuzz harness and sanitizers to a target library. Submit lab notes, review feedback, and the next improvement plan.