Static Application Security Testing is considered to be the gold standard for testing software in DevOps cycles. SAST, as it’s known, involves analyzing code before executing it to try and spot possible vulnerabilities.
It’s highly effective, and is generally seen as the primary line of defense for developers, helping to catch bugs before their code ever sees a production environment.
However, the popularity of SAST has created some major headaches for security teams. Because it’s used as a matter of course for all new software, it has led to a staggering volume of “noise” that’s drowning out the most important security signals.
Inevitably, that means developers are faced with an enormous backlog of alerts that must be checked manually, one at a time. Instead of building new features or actually fixing bugs, many developers find themselves wasting hours digging into false positives, increasing the risk of burnout and potentially desensitizing them to legitimate security issues.
Why Noise Is More Than an Annoyance
When SAST was first established, the level of noise was a relatively minor irritant, but these days it’s beginning to cause havoc with application security. One recent study that analyzed thousands of public GitHub repositories found that of 2,116 flagged issues, only 180 were actual vulnerabilities that required a fix – less than 10%. It means that 90% of the time developers spend investigating issues is essentially wasted.
For enterprise developers, the level of noise is even more deafening. A second study from earlier this year revealed that the average enterprise flags 865,398 alerts annually. However, when they looked into these alerts, just 795 of them were revealed to be critical flaws needing attention – just 0.092% of the total alert volume. Security teams are drowning in false positives.
SAST generates so much noise because it’s designed to flag patterns in code rather than actual exploits. Organizations need a better way to prioritize and validate these patterns so they can surface the genuine vulnerabilities without highlighting lines of code that just look unusual.
Enhancing SAST With Greater Precision
To avoid being buried under a landslide of digital clutter, organizations need to move away from the existing “scan everything” mentality and transform SAST from what is effectively a blunt instrument into a high-precision tool.
This will require aggressive fine-tuning and more contextual awareness, together with tighter integration into developer’s workflows.
1. Strategic Ruleset Configuration
The first step is to audit the SAST rulesets, which dictate what gets flagged. This means analyzing the findings and identifying which rules threw up the most false positives. Should a specific rule result in a false alert rate of more than 90% for two months, that’s a sure sign that it should be disabled, or at least rewritten. In addition, developers must take care to exclude any “non-productive” code from their scans – things like test directories, vendor libraries, auto-generated build artifacts and so on.
Organizations should also implement programming language-specific rules over generic one-size-fits-all sets. Finally, teams can set a higher severity threshold, focusing on only the highest-priority findings to prevent developers from being overwhelmed by alerts.
2. Contextual, Risk-based Analyses
Vulnerabilities are only a threat if it’s possible to exploit them, and in many cases it’s not. SAST can be configured to only prioritize alerts where the vulnerability can actually be triggered by entry points, such as user input or HTTP handlers.
In addition, deep data-flow (taint) analysis can be used to track inputs from source to sink, enabling greater accuracy than simple regex-matching. What’s more, teams can map their findings to specific application threat models to ensure that they remain focused on patching business-critical and web-facing applications rather than lower risk internal tools.
3. Integration into Workflows
DevOps workflows are accelerated when security feedback is instantaneous, and what better time to receive alerts than when actually writing the code? By implementing IDE plugins and pre-commit hooks, it’s possible to flag high-priority vulnerabilities and remediate them in real time, rather than scheduling them as a future task.
By transitioning away from infrequent codebase scans to continuous scanning, organizations can ensure that developers only have to worry about the fresh code they’re working on, rather than going back over their old work. This keeps workloads more manageable and avoids that feeling of being inundated.
4. Automated Triage
Developers work faster when they can stay focused on the here and now, and that can be achieved by using AI tools that “remember” false positives and prevent them from returning to haunt future scans.
Modern AI triage tools can analyze framework protections and data flows to automatically dismiss the bulk of false positives that show up, so that no human ever has to see them. Then, the refined findings can be routed to their owners via automated assignments, ensuring greater accountability and more rapid resolution.
5. Creating Feedback Loops
SAST tools will never be perfect, and that’s why developer feedback remains essential. By creating a frictionless way for developers to mark false positives, organizations can collect the data they need to inform future SAST tuning.
Developers can refine the rulesets they use based on their real-world findings, further reducing the amount of noise flying around, ensuring that the most critical threats receive the urgent attention they demand.
Strengthened Security With Surgical SAST
SAST tests are a growing source of frustration for developers, but it doesn’t have to be this way. By refining their methodologies and applying more precise rulesets and greater context, businesses can cut out the clutter and ensure that whatever alerts do pop up are likely to be on the money. This means treating SAST as a living system, continuously fine-tuning its parameters and refining its contextual awareness, while automating validation.
It takes time to get there, but SAST can gradually be shaped into a powerful weapon that dramatically reduces the noise, giving security teams the time they need to address the alerts that matter.
