How do I fix security vulnerabilities in my app?

Most security breaches do not come from sophisticated attacks. They come from a login page that never validated user input properly, or an admin panel that was never locked down, or an API endpoint that hands out data to anyone who asks.

If your app has been running for more than six months without a dedicated security review, there is a reasonable chance it has at least one of these. The IBM Cost of a Data Breach report (2023) found the average cost of a breach hit $4.45 million, and that number does not account for the founder hours spent managing the fallout. Fixing vulnerabilities before they are exploited costs a fraction of that.

This article walks through what the most common vulnerabilities look like, how an audit finds them, what remediation actually costs, and what keeps new problems from reappearing.

The OWASP Foundation publishes a ranked list of the most common web application security risks, updated every few years based on data from thousands of real applications. In 2023, broken access control topped the list, appearing in 94% of tested applications. That is not a typo.

Broken access control means a user can do things they should not be allowed to do. A customer viewing another customer's order history. A free-tier user accessing a paid feature because the check was never added. An admin-only action that any logged-in user can trigger if they know the right URL.

Right behind it, injection attacks (where a malicious user sends code through a form field and your app runs it) and authentication failures (weak passwords, sessions that never expire, no rate limiting on login attempts) round out the top three issues.

Security misconfiguration is a close fourth. This is not a coding problem at all, it is a setup problem. Default passwords left unchanged. Error messages that print your database structure to anyone who triggers them. File storage that is technically public when it should be private. These are the easiest to fix and, surprisingly, among the most commonly found.

The 2023 Verizon Data Breach Investigations Report found that stolen credentials and web application attacks account for over 80% of confirmed breaches. Neither requires a sophisticated attacker. Both are preventable with a proper review.

A security audit is not a single scan. Think of it as three different investigations happening in parallel.

Automated scanning is the first type, where software tools check your entire codebase and running application for known vulnerability patterns. These tools catch obvious things fast: dependency libraries with known security flaws, form fields missing input validation, configuration settings left at defaults. A good automated scan takes a few hours and produces a prioritized list of issues.

Manual code review is next. A security engineer reads through the sections of your app that handle sensitive operations: login, payments, user data access, admin functions. Automated tools miss logic errors because logic errors are not patterns, they are design decisions. The scanner cannot tell you that your coupon system can be exploited to get 100% off because no one checks whether a coupon has already been used on the same account. A human reviewer can.

Penetration testing rounds out the approach, where a reviewer actively tries to break your app the way an attacker would. They attempt to access accounts that are not theirs, inject code through search bars and contact forms, and probe API endpoints for data they should not be able to retrieve. NIST data from 2023 shows that manual penetration testing catches 20–30% more vulnerabilities than automated tools alone.

The output is a prioritized report: critical issues that need immediate attention, high-severity issues that should be addressed within weeks, and lower-priority items for the maintenance backlog. A good report tells you what is broken, why it matters to your business, and what to do about it.

This depends on two things: how severe the issues are, and whether the engineer who originally built the feature is still available.

For low-severity items, updating a library or tightening a configuration setting, a developer who knows the codebase can handle these in a few hours each. No specialist required.

For critical and high-severity issues, the calculation changes. Fixing broken access control requires understanding every place in the app where data is accessed, not just the one location the audit flagged. Fixing authentication failures requires understanding your entire login flow, session management, and how user data moves through the system. Getting these wrong a second time is worse than the original problem.

A developer who builds features all day is not the same person as a developer who thinks about what could go wrong. Security is a discipline, and it benefits from someone who has seen dozens of these issues before.

The cost question is real. A security specialist from a Western agency charges $15,000–$30,000 for a full remediation engagement. An AI-native team handles the same scope for $3,000–$8,000. The reason is the same one that applies to any software work: AI-assisted development compresses the time spent writing the fix. The thinking still requires an experienced engineer. The typing does not.

One consideration worth naming: the engineer fixing the issue should not be the same one who wrote it. Not because of incompetence, but because the mental model that produced the original mistake tends to produce the same fix. A second set of eyes catches the cases the first developer did not consider.

A one-time audit is not a solution. Applications change. Libraries get new security patches. Features get added by developers who were not on the team when the security review was done. The 2023 Synopsys Open Source Security and Risk Analysis report found that 84% of codebases contained at least one open-source vulnerability, and 48% contained high-risk vulnerabilities in libraries that had a fix available, just not yet applied.

Three practices account for most of the ongoing risk reduction.

Automated dependency monitoring is the first practice. Every app uses open-source libraries. When a security flaw is found in one of those libraries, a fix is published, but your app does not automatically get it. Dependency monitoring tools alert your team when a library in your app has a known security issue and a patch is available. This is preventive work that costs almost nothing and eliminates an entire category of risk.

Regular penetration testing comes next. Once a year is the baseline for most early-stage apps. Twice a year makes sense once you are handling payments or sensitive user data at any volume. Each test catches the vulnerabilities introduced since the last one.

Code review for security during new feature development, not after, rounds out the list. A 2022 IBM Systems Sciences Institute study found that fixing a security issue during development costs about $80. Fixing the same issue after launch costs around $960. Reviewing security before a feature ships is not optional work, it is the cheapest version of the same work.

These three practices together cost less per month than a single incident response bill.

The short version: a focused remediation of critical and high-severity issues found in a typical early-stage app costs $5,000–$10,000 at an AI-native team. A full audit with remediation and retest costs $8,000–$15,000. Ongoing maintenance runs $1,500–$2,500 per month.

Western agencies charge 3–4x more for the same work. The remediation process is the same: review the audit findings, write the fixes, test that the fixes work, and confirm no new issues were introduced. AI compresses the time to write and test each fix. The experienced engineer who designs the fix and verifies the logic still earns that cost.

A few things affect where your cost lands within that range. More critical issues means more time, and therefore higher cost. Applications with payments, healthcare data, or regulatory requirements need more thorough verification after the fix. Applications built on standard technology are faster to work with because AI tools are better trained on common patterns.

There is a number worth thinking about here. The average time between a vulnerability being introduced and it being discovered is 207 days, according to IBM's 2023 report. During those 207 days, the flaw is present. A security review scheduled this month finds issues introduced last year. Waiting another quarter adds another quarter of exposure time.

Timespade handles security audits and remediation as part of its Product Engineering practice. The same team that builds your app can audit it, fix it, and put the monitoring in place to keep it clean. That means no handoff between the team that understands the codebase and the team responsible for its security.

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