Question 1
Difficulty: medium
How do you approach reviewing a new codebase for security risks when you have limited time and little prior context?
Sample answer
I start by getting a quick map of the application: what it does, where user input enters, what data it handles, and which parts are most exposed. Then I prioritize the highest-risk flows first, such as authentication, authorization, file handling, serialization, database access, and anything touching secrets or external integrations. I don’t try to read every line equally; I look for patterns that historically lead to real issues, like insecure defaults, weak validation, unsafe deserialization, injection points, and privilege boundary mistakes. I also check the project’s threat model if one exists, or I build a lightweight one myself from the architecture. When time is limited, I focus on finding issues that are exploitable and high impact rather than cosmetic concerns. I document findings clearly, explain why they matter in business terms, and suggest practical fixes that fit the team’s workflow. That gives the most value quickly.
Question 2
Difficulty: medium
Tell me about a time you found a serious security issue in code. How did you handle it?
Sample answer
In one review, I found that a seemingly internal admin endpoint accepted a user-controlled parameter that ultimately controlled which record was updated. At first glance it looked low risk because it sat behind authentication, but after tracing the logic I realized there was no object-level authorization check. That meant any authenticated user could modify records they shouldn’t have access to. I confirmed the issue with a safe proof of concept, then wrote up the finding in a way that showed the path from input to impact, not just the code defect. I included the affected role, the potential business impact, and a minimal fix: enforce authorization at the service layer and add tests for unauthorized access attempts. I also discussed with the team how the bug happened so they could prevent similar patterns elsewhere. The key for me was staying calm, being precise, and helping the developers fix it fast without turning it into blame.
Question 3
Difficulty: medium
What secure coding patterns do you look for when reviewing authentication and session management code?
Sample answer
I look for a few core things right away: strong password handling, consistent session invalidation, secure token generation, and clear separation between authentication and authorization. For passwords, I want to see modern hashing algorithms with appropriate work factors and no custom crypto. For sessions or JWTs, I check token lifetime, revocation strategy, signing algorithms, audience and issuer validation, and whether sensitive claims are being overused. I also watch for account recovery flows, because that’s where insecure shortcuts often appear. For example, password reset tokens should be single-use, time-limited, and tied to the right identity. Another big area is session fixation and CSRF protections, especially for browser-based apps. I also look at logging behavior to make sure secrets, OTPs, and tokens are never written to logs. If the code uses third-party identity providers, I verify the trust boundaries and make sure the app isn’t blindly accepting identity assertions without validating them properly.
Question 4
Difficulty: hard
How do you distinguish between a real security vulnerability and a false positive during code review?
Sample answer
I try to separate theoretical risk from actual exploitability. A real vulnerability usually has a clear path from attacker-controlled input to a sensitive action or data exposure, along with weak or missing controls. When I spot something suspicious, I trace the data flow and ask: can an attacker influence this input, does it reach a sink that matters, and are there compensating controls that truly block abuse? I also consider the deployment context. A pattern that looks dangerous in isolation may be safe if a framework escapes output automatically, an allowlist is enforced earlier, or the feature is only reachable in a trusted internal environment. Still, I’m careful not to dismiss findings too quickly, because edge cases matter. If I’m uncertain, I validate with tests or a small proof of concept rather than guessing. The goal is to be accurate and useful: I’d rather escalate a plausible issue with evidence than waste time on noise or, worse, miss something real.
Question 5
Difficulty: medium
Which vulnerability classes do you prioritize most in application code reviews, and why?
Sample answer
I prioritize issues that are both common and high impact: authorization failures, injection flaws, insecure deserialization, cross-site scripting in sensitive contexts, insecure direct object references, cryptographic misuse, and secrets handling problems. Authorization is especially important because it often survives authentication and still leads to serious data exposure or privilege escalation. Injection issues remain high priority because they can turn input handling into full compromise, depending on the sink. I also pay close attention to business-logic flaws, which don’t always look like classic vulnerabilities but can be just as damaging, especially in payment, account recovery, and workflow abuse scenarios. Cryptography and secrets matter because mistakes there can invalidate the rest of the system’s protections. I don’t ignore lower-severity issues, but I triage based on attacker control, reachable impact, and how likely the weakness is to be used in the real world. In practice, the best review strategy is risk-based, not checklist-only.
Question 6
Difficulty: medium
How would you review a pull request that introduces a new file upload feature?
Sample answer
I’d treat file upload as high risk and look at the entire lifecycle, not just the upload endpoint. First I’d check whether the application validates file type by content, not just extension or MIME header, and whether size limits are enforced early. I’d verify where files are stored, how they’re named, and whether user-controlled names can lead to path traversal or overwriting existing content. I’d look for any processing step that might parse the file, generate previews, or hand it off to another service, since that can introduce code execution or parser abuse risks. I’d also check access controls: who can upload, who can download, whether uploaded files are publicly reachable, and whether signed URLs expire correctly. On the defensive side, I want malware scanning, safe handling of metadata, and isolation between uploaded content and application code. Finally, I’d recommend tests for dangerous file types, oversized inputs, and permission boundaries so the security posture is maintained over time, not just at launch.
Question 7
Difficulty: hard
Describe how you review code for authorization issues in APIs or backend services.
Sample answer
I start by identifying every place the code checks identity and every place it checks permission, because those are not the same thing. I want to see consistent authorization enforced close to the data or action being protected, not scattered only in controllers or UI logic. Then I trace object access patterns: can one user read, update, delete, or list another user’s data by changing an ID, tenant key, or role flag? I also look at bulk endpoints, search filters, export functions, and background jobs, because authorization bugs often hide there. If the service supports roles, I check whether role checks are explicit and whether privileged actions are covered by tests. I pay attention to default behavior too; a missing check that falls back to “allow” is a common failure mode. Good authorization code is usually boring: centralized, testable, and consistent. I like to see policy decisions expressed in one place, with clear deny-by-default behavior and audit logs for sensitive actions.
Question 8
Difficulty: easy
How do you communicate security findings to developers who may feel the issue is low priority or disruptive?
Sample answer
I try to make the finding concrete, respectful, and actionable. First I explain what the code does in plain language, then I describe the risk in terms the team cares about: customer impact, fraud potential, data exposure, service abuse, or compliance consequences. I avoid alarmist wording, because that usually makes people defensive. Instead, I show the exact path from input to impact and, if possible, a small reproducible example. I also make sure the remediation is practical. If I can suggest a fix pattern, a test case, or a safer library approach, the conversation becomes much easier. I’ve found that developers respond well when they see I’m trying to help them ship securely, not just hand them a report. If there’s disagreement about severity, I’m open to discussing assumptions and threat model details. The goal is alignment: we want the same thing, which is to reduce risk without creating unnecessary friction for the team.
Question 9
Difficulty: medium
What tools or methods do you use during secure code review, and how do you avoid overreliance on automated scanners?
Sample answer
I use scanners, but I treat them as support rather than the decision-maker. Automated tools are useful for finding known patterns quickly, especially obvious injection issues, risky dependencies, secrets, and some insecure API usage. But they miss context, business logic, and authorization problems, which are often the most serious findings. My process usually combines manual reading, data-flow tracing, grep-style searches for dangerous functions, and targeted tests or proofs of concept when needed. I also use source control history and architecture docs to understand why code exists and where hidden trust boundaries are. The biggest mistake is assuming a clean scan means the code is secure. It doesn’t. Equally, a noisy scan can distract from the actual risk. So I tune tools to reduce obvious false positives, then focus my attention on high-value areas the tools are bad at judging. That balance gives the best results and keeps review time focused on real threats.
Question 10
Difficulty: hard
If you were asked to improve the security review process for an engineering team, what would you change first?
Sample answer
I would start by making security review more predictable and earlier in the development lifecycle. The first improvement I’d push for is a lightweight secure design check for new features that touch sensitive data, authentication, payments, or external integrations. That catches risk before code is merged, when it’s cheaper to fix. Next, I’d create a small set of review priorities tailored to the team’s actual stack and threat profile, so reviewers know what to look for without relying on guesswork. I’d also standardize secure coding checklists for recurring patterns like auth, file uploads, input validation, and logging, but keep them concise so they’re usable. Finally, I’d close the loop by tracking findings, recurring root causes, and remediation time. That lets the team improve instead of repeating the same mistakes. My goal would be to make security part of normal engineering flow, not a last-minute gate that slows delivery or creates frustration.
