Introducing Clean Fix: Clean the Noise, Fix What Matters

Mobb, the security remediation platform, was built with a single mission: to empower teams to address and resolve security issues. Yet, as we evolved, one persistent question kept emerging: How does Mobb address false positives?

At first, we dismissed the concern with a few self-assuring arguments. We told ourselves, “We can’t change the SAST industry — let the scanners improve their false positive rates, and we’ll focus on fixing what’s valid.” Then, we claimed that fixing issues with Mobb is so straightforward that it hardly matters whether an alert is genuine — just fix it and move on. I vividly recall a dev lead’s look during a prospect meeting — a look that said, “When pigs fly, buddy”. After seeing that reaction, it became clear; it’s wrong to fix something that isn’t broken. People simply won’t address an issue if they don’t trust its validity, even if the fix is fast and risk-free.

Today, we acknowledge that a clean start is essential for effective remediation. That’s why we’re thrilled to introduce Clean Fix: A new feature that uses Mobb to clean the noise, so you can fix what matters most. With this advanced false positive detection engine, you can eliminate the clutter and focus on what truly matters — moving fast and staying secure.

The Noise Problem (or, why developers hate SAST)

Static Application Security Testing (SAST) tools are critical for uncovering vulnerabilities, but they come with a major drawback: false positive rates can soar as high as 70-90% (according to some studies). [ As a result, teams often spend an inordinate amount of time sifting through alerts that turn out to be non-issues, drastically reducing the ROI of these tools—not only in their effectiveness but also in the cost of acting on their results—and in many cases, dismissing their findings entirely, rendering them nearly unusable.

Worse yet, this flood of false alarms erodes trust between security teams and developers. When developers are overwhelmed by bogus issue reports, they begin to disregard important warnings, leading to poor collaboration and a weakened overall security posture.

Clean Fix is designed to tackle these challenges head-on by intelligently filtering out false positives. By cutting through the noise, Clean Fix restores developers’ confidence in your SAST tools and encourages them to focus on genuine, actionable issues rather than getting lost in the clutter.

How Clean Fix Works

When you run a fix analysis with Mobb, issues are automatically organized into three categories:

• Fixable Issues: valid issues, for which Mobb offers code fixes.
• Irrelevant Issues: issues identified as false positives or deemed irrelevant to your context (details below).‍
• Remaining Issues: issues that are either unfixable or not yet supported by Mobb.

Whenever an issue is flagged as irrelevant, you’ll always see a reason provided. Common reasons include:

• False Positive: The issue has been verified as non-existent.
• Test Code: The issue was found in test files and doesn’t affect production.
• Vendor Code: The issue occurs in external libraries or dependencies not maintained by your team.
• Autogenerated Code: The issue appears in code generated by tools or frameworks rather than being manually written.‍
• Auxiliary: The issue was detected in supporting files (typically developers’ automation scripts) that don’t impact core functionality.

Now, users can focus on addressing the relevant issues, ignore the irrelevant ones and triage the remaining ones.

What's Under the Hood?

In our quest to eliminate false positives, we experimented with many approaches. At Mobb, accuracy is our hallmark, and this feature is no exception — it must be both precise and trusted. Misclassifying a genuine issue as a false positive can put our customers at risk, so we took a responsible approach rather than solely relying on AI.

Much like our fixes, we discovered that the secret sauce lies in a hybrid strategy: harnessing the power of AI while applying deterministic logic when needed. No one wants an LLM to hallucinate and dismiss real issues, yet a purely rule-based system wouldn’t scale to handle the nuances of every code variation. Our solution begins by analyzing the issue type and its specific code context. When the situation is clear-cut, the LLM steps in. But if the context is ambiguous and prone to error, our in-house logic takes over — only leveraging AI for targeted tasks during the process.

Let’s look at two different use cases:

Hardcoded Passwords

• SAST tools often flag hardcoded passwords, generating so many false positives that even a non-developer can quickly recognize when no password is present. In this classic scenario, the LLM accurately identifies these cases as false alarms.

SQL Injection

• SQL injection issues are more challenging for an LLM to evaluate. In our tests, a purely black-box approach led to numerous errors and even hallucinations. For these nuanced cases, our system carefully analyzes the context and assigns specific tasks to the LLM based on how the SQL query is constructed and how inputs propagate.

By combining the flexibility of AI with deterministic, rule-based logic, Clean Fix scales effectively while maintaining the high level of accuracy you’ve come to expect from Mobb.

Cleaning the Noise in Numbers

Clean Fix is engineered for impeccable accuracy — in our early usage, not a single issue flagged as irrelevant has ever been reported as a true issue by our users. While false positive rates can vary widely across different SAST tools, programming languages, and repositories, Clean Fix typically identifies between 30% and 60% of issues as irrelevant. Since Mobb is SAST-agnostic, we’ll soon be able to measure and compare false positive rates across various tools. Stay tuned to our blog for more insights and updates.

Get Started with Clean Fix Today — and Share Your Feedback!

Ready to experience the difference? Clean Fix is open to all Mobb users today, and available for free trial. If you maintain an open-source repository - notice that Mobb, including Clean Fix, is free for your public repositories forever. Go to app.mobb.ai and start fixing today. Book a demo with us to understand the full potential of Mobb for your organization. For more detailed instructions, check out our Clean Fix documentation.