Ship knowing your product will hold.
The people who built it are too close to see the gaps. I've spent 18 years being the outside eye — for banks, a $46M-backed startup, and teams shipping under pressure. One senior engineer, direct access, answers in weeks.
Case Studies
A fast-moving startup was spending more time verifying code than shipping it.
Situation
Alyce, a $46M-backed startup in Boston, had a growing engineering team shipping updates under constant pressure. Every release required hours of manual verification — and things still slipped through.
Approach
Built an automated verification layer from scratch and integrated it into their development workflow — so every change got checked automatically without slowing anyone down.
What I found
The manual process didn't scale with the team. It was adding days to every release cycle and creating anxiety instead of confidence — exactly when speed mattered most.
Outcome
Manual release checks eliminated entirely. The team shipped faster, with consistent confidence that each release was solid. Six years of clean releases followed.
A Chinese company almost launched with the doors wide open.
Situation
A SaaS platform for auto parts was ready to enter the Russian market. Product built, launch date set, team confident. They needed one final check.
Approach
Two rounds of testing across the web platform and mobile apps — looking at the product the way an attacker would, not the way a user would.
What I found
84 issues, 12 critical: anyone could access any user's account by changing one number in the URL, pull the entire customer database with a malformed query, or upload malicious files directly to the server. Any one of these, found by the wrong person, ends a launch before it starts.
Outcome
Every critical issue was fixed before go-live. The platform launched on schedule and has been running incident-free since.
They didn't know if their store would survive the holiday rush. Now they do.
Situation
An e-commerce platform was approaching its biggest sales period with no data on how much traffic their system could actually handle. The previous year was fine — but traffic had grown 3x since then, and nobody had tested the new limits.
Approach
Put the system under realistic peak-season pressure, mapped exactly where it would fail, and delivered specific fixes — not a list of observations.
What I found
Performance bottlenecks that would have caused failures under peak load — none visible under normal traffic. The risk wasn't just downtime: it was losing the most valuable sales window of the year.
Outcome
Fixed before peak season. The store stayed up through the holiday rush without a single minute of downtime. Revenue protected.
A content platform shipped without the security holes it had going in.
Situation
The service accepted user uploads, had a custom editor, activation codes, and marketplace integrations — each of those is a potential entry point for an attacker.
Approach
Full security review of the web application and API, including the activation flow, user editor, and file handling.
What I found
Vulnerabilities in how user content was handled and how activation codes were validated — both of which could be exploited without technical knowledge.
Outcome
All issues fixed before launch. The service went live without the security problems it had going in.
Five fintech platforms. One had its entire source code exposed to the public internet.
Situation
A group of fintech companies needed an independent review of their web and mobile platforms before a compliance audit. Five products, each processing sensitive personal and financial data — and none had been tested by anyone outside the development team.
Approach
Full-cycle engagement across all five platforms: functional testing of web applications and mobile apps (iOS and Android), followed by a security audit of each platform — authentication flows, APIs, server configurations, and data handling.
What I found
Functional testing uncovered dozens of issues in business logic, form validation, and mobile-specific edge cases that internal teams had missed. The security audit went deeper: one platform had its entire Git repository publicly accessible — database credentials, API keys, internal service passwords, full source code. Anyone with a browser could reconstruct the project. Another platform had zero brute-force protection on user access codes — a simple script could try all 10,000 combinations in under three hours.
Outcome
All critical vulnerabilities were patched within a week. The exposed repository was secured, every credential rotated, and rate limiting implemented across all platforms. Functional issues were resolved before the compliance deadline. All five platforms passed their audit.
A company was about to pay for every API call. They didn't have to.
Situation
An e-commerce platform relied on a paid third-party service with a free tier of 300 requests. Starting from request 301, every call was billed. The company assumed the cutoff was handled correctly — but nobody had actually tested it under real traffic.
Approach
Built a sandbox environment, redirected the third-party service traffic into it, and ran load tests simulating real production patterns — including the exact moment the free tier runs out.
What I found
The 301st request wasn't handled properly. Under load, the system blew past the free tier without triggering the control logic — silently racking up charges on every single request. In production, this would have gone unnoticed until the next invoice.
Outcome
Fixed the threshold logic before it hit production. Post-fix analysis showed the company would have been overpaying by ₽300,000 per month — roughly $3,600 — on API calls that should have been free.
I asked the AI assistant to tell me about itself. It told me everything.
Situation
A product company had integrated an AI assistant into their platform. It was live, customer-facing, and had access to internal tools. The team wanted to know if the AI could be manipulated into leaking sensitive information.
Approach
Ran a series of prompt injection tests — from basic instruction overrides to multi-step social engineering, role manipulation, and indirect injection techniques.
What I found
The AI disclosed its complete production architecture: three-tier system design, exact technology stack, container orchestration details, firewall rules, internal API endpoints, and cloud storage configuration. It confirmed which vulnerabilities were unpatched. Then it went further — and started suggesting new attack vectors the tester hadn't even asked about.
Outcome
The company disabled the bot within hours and redesigned the system prompt from scratch. Every disclosed component was audited, credentials rotated, and the confirmed gaps patched. The AI was relaunched with proper guardrails a week later.
Services
Release Without Fear
I build a verification layer that catches problems automatically before code reaches your users. Every change gets checked, every edge case covered. A green light you can actually trust.
Close the Back Doors
I look at your product the way an attacker would — then document and prioritize everything they'd exploit. Account takeovers, data leaks, unauthorized access: found before the wrong people do.
Built for Peak
I put your product under realistic pressure and tell you exactly where it will fail. You get specific fixes and a clear threshold — not a report to file.
Data You Can Trust
I verify that what goes into your system matches what comes out. Nothing lost, nothing transformed incorrectly. Wrong data presented confidently is the most expensive kind of mistake.
Ship Faster, Stay Solid
I use AI tooling to handle repetitive verification automatically, so your team spends time building — not checking. Coverage of a larger team at a fraction of the cost.
How It Works
We talk.
A free 20-minute call — no pitch, no proposal pressure. You describe what you're building, what you're worried about, and when you need answers. I tell you honestly what's worth looking at and what the work would involve. You'll know by the end of the call whether this makes sense.
I dig in.
Depending on what we agree on, I spend 1 to 3 weeks on a focused review, or 1 to 3 months on a full infrastructure build. You get updates throughout — not a black-box process with a report at the end.
You have answers.
I deliver clear findings: what I found, what it means for your business, and what to fix — in order of priority. If something needs addressing before you launch, you'll know exactly what and why. If everything's solid, you'll know that too.
About
Stanislav Romanov
Software Quality & Security Consultant
I got tired of watching companies ship products that weren't ready.
After 18 years inside banks, funded startups, and fast-moving product teams, I saw the same pattern: pressure to launch, a team too close to their own code to see the gaps, and users who find the problems first. I went independent so I could be the person who prevents that — without agency overhead or junior-level uncertainty.
Five of Russia's top-20 banks. Alyce ($46M, General Catalyst). E-commerce on three continents. I also run a community of 1,200+ engineers, which keeps me sharper than any single company would.
Outside of work: I box twice a week. You learn to find weak spots quickly — in the ring and in software.
If you're getting ready to launch, I'd like to hear what you're building.
FAQ
How much does this cost?
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Projects typically start at $4,800 for a focused security or performance review. Most engagements fall between $8,000 and $20,000. Complex or ongoing work runs $20,000+. The first call is free — we figure out what you actually need before talking about price.
How long does it take?
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A security or performance review: 1–3 weeks. Building a reliable release process from scratch: 1–3 months, depending on complexity. I'll give you a specific timeline on our first call — not a range designed to protect my schedule.
How are you different from a testing agency?
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When you hire an agency, you pay for an account manager, a coordinator, and a junior tester — then wait while they brief each other. With me, you get a senior engineer on day one. Direct communication. Faster decisions. Usually a lower total cost for the same quality of work.
How are you different from a freelancer?
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18 years. Five banks. A $46M-backed startup. An e-commerce platform that survived three peak seasons without a single outage. I'm not building a portfolio — I'm maintaining a reputation I've spent two decades earning. That's a different kind of accountability.
I'm not sure what I need. Is that okay?
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Yes — that's exactly why the first call is free. Tell me what you're building, what's worrying you, and what's at stake if something goes wrong. In 20 minutes, you'll have a clear picture of where the risk actually sits and whether I can help.
Tell me about your project
Takes 2 minutes. I'll respond within 24 hours.
Got it.
I'll read this carefully and respond within 24 hours.
1 / 5
What's keeping you up at night?
Choose what fits best — we'll cover the details on our call.
How urgent is this?
Helps me understand how quickly we need to move.
Have you tried to address this already?
No wrong answer — helps me understand what you've already tried.
What's your approximate budget?
Rough range is fine. Helps me suggest the right scope.