Imagine you have to check for danger on the other side of an impassable mountain you cannot walk around. What would you do? A low-tech solution would be to tunnel through and have a look. Swing by swing with a pickaxe to break the stone, and then shovel by shovel to haul the broken rock away. You hope you will get there in the end, but it’s quite literally a mountain of a task. Even though you’re making progress, it’s a seemingly endless, taxing effort.
Now, imagine you’re digging away, and someone comes to you with a high-tech solution: a camera drone. Boom—the task has been enormously simplified, and within minutes, you know what’s lurking on the other side.
This is exactly the kind of impact that Invicti’s new Predictive Risk Scoring feature can have on your AppSec efforts. Instead of your security and development teams figuratively swinging pickaxes and shovels to inch their way through a mountain of vulnerabilities, you can now use Predictive Risk Scoring to first focus their efforts on your most at-risk web applications.
The earlier you know your risks, the more proactive you can be
Knowing and managing risk is a cornerstone of cybersecurity, while accurate prioritization is the key to controlling and reducing those risks with the resources you have. Make no mistake—your resources will always be limited relative to the scale of security measures required to fully protect organizational assets. In application security, risk and prioritization have long been sticking points, leaving security leaders forever on the lookout for more efficient and reliable methods to guide the efforts of their AppSec teams.
Currently, application security prioritization only comes in late in the testing process, when you’ve done your testing and are looking at the long lists of reported vulnerabilities. Assigning severity levels across potentially hundreds of vulnerabilities is necessary to get your teams working on remediation in order of severity. It’s a reactive and suboptimal process, where you’re waiting for test results to arrive and only then reacting to them. Moreover, this type of triage lacks the risk context crucial in establishing which assets and vulnerabilities truly need priority treatment.
Invicti’s Predictive Risk Scoring changes the game of vulnerability prioritization with a proactive rather than reactive approach. Now you can see which assets carry the highest risk before you even run a single test—and that’s as early in the process as you can get.
Zeroing in on real risk with data science and AI
Remember how that camera drone helped you change the entire approach to the task at hand and sidestep a massive manual effort by taking a smarter and more technologically advanced route? In Predictive Risk Scoring, AI/ML is the drone that adds a new dimension to your security vision and saves your teams hundreds of hours of manual work.
Leveraging a custom AI prediction model trained on real-world data, Invicti has added Predictive Risk Scoring to its existing asset discovery functionality to automatically calculate a risk score for each web asset. The model takes a number of technical parameters for each site or app and uses them to make a data-based prediction of the risk level correlated with that combination of parameters and values. Every time the discovery tool runs, any newly identified web assets also automatically get a risk score.
Invicti’s Predictive Risk Scoring calculates risk scores using a dedicated in-house machine learning model. It does not use a large language model (LLM), process sensitive customer data, or send any data to external AI providers.
In effect, Predictive Risk Scoring says: “This web application presents similar indicators to applications that were found vulnerable in the past, so this is a high-risk asset for you.” Gaining any risk insight in the application security domain is already a massive win (as CISOs well know), let alone with the scale and level of confidence that the Invicti model provides. Perhaps most importantly, Predictive Risk Scoring assigns that risk rating proactively before any application is even scanned. This feature is an industry first and yet another win for application security programs.
How Invicti proactively calculates web asset risk
Predictive Risk Scoring leverages the analytical and predictive capabilities of machine learning to provide a data-based estimate of the security risk for each of your web assets. By getting this insight before you scan, you’re arming yourself with additional intel about your most likely risk areas so you can efficiently prioritize testing and remediation efforts.
The machine learning model that underpins Predictive Risk Scoring was carefully selected to maximize confidence in the results and trained to recognize signs of security risk based on analyzing over 150,000 real-life websites and applications. Starting with thousands of site risk indicators, the model was gradually refined to focus on just over 200 of the most impactful ones. These include many things a pentester would typically look for first, like site age, number of form inputs, support for deprecated SSL/TLS versions, and so on.
After extensive fine-tuning, the model can currently predict the risk level of a site based on non-intrusive requests, delivering a risk score with at least 83% confidence overall and over 90% confidence for web applications with critical vulnerabilities. With such accurate recommendations, you get ample predictive insight into what needs testing and fixing first.
Reinventing the application security testing process
In terms of the security testing process, this new step comes in early—in fact, before any vulnerability testing is even initiated. Following the automated asset discovery phase, each of your identified web assets is now also assigned a risk score.
When you’re dealing with hundreds or even thousands of assets, Predictive Risk Scoring provides an invaluable guide for deciding which assets to focus on next for optimal testing and remediation. Even before seeing the first vulnerability scan result, you’re already making decisions based on credible risk levels, not guesswork.
Fact-based decision-making in web application security used to be elusive, but advances in automated testing are finally making it a reality. Predictive Risk Scoring joins Invicti features such as proof-based scanning to add another dimension to your security posture visibility. In effect, you’re getting a picture of your potential attack surface hotspots before you spend any time or commit any of your resources. Plugged into the security testing process, this lets you make informed security decisions every step of the way.
One small step for Invicti, one giant leap for AppSec
The ability to predict risk before spending valuable time and resources to scan, identify, and remediate vulnerabilities is key to improving efficiency and boosting confidence in your security program. Armed with this insight, you can quickly prioritize work to secure your most at-risk web apps and assets first, gaining the upper hand over threat actors—who might themselves already be using AI to find your weaknesses.
Predictive Risk Scoring benefits in a nutshell:
- Fully automated risk-based prioritization of testing and remediation resources
- Confidence from the top down that your AppSec program is risk-centric
- Using machine learning to counter the threat of AI-augmented attacks
- Scalable and continuous fact-based security when paired with Invicti’s automated discovery and scheduled scanning
Ready to get started? Predictive Risk Scoring is already available in Acunetix Premium, Acunetix 360, and Invicti Enterprise. Get a demo now, or contact your customer success rep with any questions about the feature.
