Fixing DefectDojo's Duplicate Findings Bug

by SLV Team 43 views
Fixing DefectDojo's Duplicate Findings Bug

Hey guys, let's dive into a small but important bug fix in DefectDojo, specifically concerning how it handles duplicate findings. This isn't a massive issue impacting everyone, but it's a good example of how even small details can matter for accurate vulnerability management. We're going to talk about the DEDUPE_ALGO_UNIQUE_ID_FROM_TOOL algorithm and why it was incorrectly identifying findings from different scanners as duplicates. Don't worry, it's not as technical as it sounds! I'll break it down in a way that's easy to understand.

The Core Problem: Misidentifying Duplicate Findings

So, the main issue revolves around how DefectDojo identifies duplicate findings. The goal is to avoid showing the same vulnerability multiple times, making it easier for security teams to focus on what's truly important. The system uses an algorithm (DEDUPE_ALGO_UNIQUE_ID_FROM_TOOL) to compare findings and determine if they're the same. The trouble starts with the unique_id_from_tool field. This field is supposed to be a parser-specific value. Think of it like this: each scanner (like a vulnerability scanner) generates its own unique identifier for each finding. These IDs are only relevant within the context of that specific scanner. If two different scanners report the same vulnerability, they should have different unique_id_from_tool values.

However, the faulty algorithm, in certain scenarios, was mistakenly treating findings from different scanners as duplicates if their unique_id_from_tool values matched. This is incorrect because the algorithm was, in essence, comparing apples and oranges. Each scanner's IDs are unique to that scanner. The bug caused DefectDojo to incorrectly mark findings from different scanners as duplicates, which led to potential inaccuracies in reporting and analysis. This meant that valuable data might have been hidden, which is not what we want. The original intention of the unique_id_from_tool was that the unique ID would only be applicable to a specific tool, and using it to compare findings between different tools was not valid. It's like using a serial number from a Ford car to identify a part on a Honda. They're just not compatible. That is to say, two findings from different scanners, even if they have the same vulnerability, should not be considered duplicate if the unique_id_from_tool matches. I hope this makes sense, as I will continue to provide more insights into the issues.

Impact Assessment and Real-World Implications

You might be thinking, "How big of a deal is this, really?" Well, the good news is that the impact is likely limited. This bug has been around for about five years, and it's not been widely reported. This suggests that the situations where this error would occur are relatively rare. Even if you don't run a complex setup, you can see how this could be an issue. If you use several different scanners, and one of them generates duplicate IDs with a different scanner, that could be an issue. But it is not a big deal.

Here is an example: let's say you're using two different vulnerability scanners, Scanner A and Scanner B. Scanner A identifies a cross-site scripting (XSS) vulnerability and assigns it a unique_id_from_tool of "XSS-001". Scanner B also finds an XSS vulnerability, and by chance, it also assigns it the ID "XSS-001". Because of the bug, DefectDojo might incorrectly flag these as duplicates, even though they originated from different scanners. This could lead to a false sense of security (thinking you only have one XSS vulnerability when you actually have two) or, conversely, cause you to ignore a real vulnerability. It could also cause you to perform an unnecessary amount of work, such as fixing something that is not even a problem. Although, the chances of the same ID being generated by two separate tools are low, this vulnerability presents a potential problem. It is for this reason that we want to get the bug fixed. The longer it is around, the more likely the problem will get.

The Corrective Action: Ensuring Accurate Duplicate Detection

The fix involves making sure that the DEDUPE_ALGO_UNIQUE_ID_FROM_TOOL algorithm is only used to compare findings within the same scanner type. In other words, the algorithm should now correctly recognize that unique_id_from_tool values are parser-specific and should not be used to compare findings from different scanners. The main solution is pretty simple: adjust the logic so that the unique_id_from_tool is not used in the duplicate finding check if the findings come from different scanners. This way, the algorithm will correctly identify duplicates within a single scanner's results while avoiding false positives across different scanners. Now, the logic checks will work correctly.

This simple adjustment ensures that DefectDojo accurately identifies duplicate findings, leading to more reliable vulnerability management. This is all that needed to be done to fix the problem. The fix involved modifying the algorithm, which is a software change.

The Benefits of Accurate Duplicate Detection

So, why is this fix so important? Well, because accurate duplicate detection provides several benefits:

  • Improved Reporting: You get a more accurate picture of your security posture. You can see the real number of vulnerabilities, without having to deal with false positives. This also improves the integrity of the data.
  • Better Prioritization: Knowing the true number of vulnerabilities allows you to prioritize the most critical issues. This allows the security team to focus on the most important tasks.
  • Reduced Noise: Eliminating false positives reduces the noise in your vulnerability reports, making it easier to identify and address real threats. This helps teams to be more efficient and do their job with better results. This also helps with the amount of time that someone needs to dedicate to a project.
  • Enhanced Decision-Making: More accurate data leads to better-informed decisions regarding risk mitigation and resource allocation. This will help with all aspects of the business, as all aspects of the business require the use of data.

In essence, by fixing this bug, DefectDojo is becoming a more reliable and effective tool for managing vulnerabilities. This also helps ensure that the data is correct.

Implementation and Future Considerations

The fix should be relatively straightforward to implement, involving modifying the code that handles duplicate finding detection. The change would require updates and testing. This would be added to the standard release process. It's crucial to thoroughly test the fix to ensure it doesn't introduce any new issues. After all, the solution that is provided has to work, or else there is no point in providing a solution.

Long-Term Perspectives

Beyond this specific fix, it's worth considering the broader context of vulnerability management:

  • Parser Validation: Enhance the validation of data coming from different parsers to ensure consistency and accuracy. This might involve standardizing how scanners report findings or building more robust data validation checks.
  • Algorithm Refinement: Continuously evaluate and refine the algorithms used for duplicate detection and other vulnerability management tasks. This includes looking for new problems and solutions that will work.
  • User Feedback: Solicit user feedback to identify potential issues and areas for improvement. This helps to improve the system.

By staying proactive and continuously improving the system, we can ensure that DefectDojo remains a robust and effective tool for managing vulnerabilities. This, in turn, helps the security team to protect the business.

Conclusion: A Small Fix with Significant Impact

In conclusion, fixing the DEDUPE_ALGO_UNIQUE_ID_FROM_TOOL bug, while small in scope, underscores the importance of accuracy in vulnerability management. By ensuring that findings are correctly identified and duplicates are accurately handled, we improve the overall effectiveness of DefectDojo and empower security teams to make better decisions.

This fix also highlights the importance of keeping an eye on your tools and making sure they are working correctly. It might not seem like a big deal, but it is.

I hope you found this discussion helpful! If you have any questions or comments, feel free to share them below. Cheers!