Intruder is a cloud-based vulnerability scanner that provides an automated overview of an organization’s attack surface. Its primary function is to proactively identify weaknesses across internet-facing infrastructure and applications before they are exploited. The platform’s scanning engine runs a set of checks for both infrastructure-level misconfigurations and application-layer vulnerabilities, like those in the OWASP Top 10. It leverages open-source engines like ZAP to execute its checks. For an application security team, Intruder offers a tradeoff between ease of use and granular control. The platform is user-friendly, but its options for fine-tuning scan configurations are limited. Furthermore, its continuous attack surface monitoring and testing capabilities, which are critical for securing externally-facing assets, are limited and primarily available only in its highest pricing tiers.This document provides a direct comparison of Intruder and Detectify. The objective is to break down the key technical differentiators to help users make an informed decision.Detectify vs. Intruder: A Quick ComparisonWe’ve built this comparison mainly based on the feedback from dialogues with prospective clients and past Intruder users who decided to evaluate Detectify as its alternative, but also based on the following sources:Intruder’s official website & resourcesIntruder’s documentationIntruder’s publicly accessible demosIntruderProsNot complicated to start scanning.Pricing is flexible and transparent.Does not require many hours of setup or ongoing management.ConsVulnerabilities are limited to known threats.Reliance on open-source means no steps from the tool are taken to reduce noise.Must purchase the most expensive plan to have attack surface monitoring.DetectifyProsSleek UI that makes using Detectify smooth and enjoyable.All vulnerability tests are built internally by their research team; new vulnerabilities not covered by CVEs including 0-days sourced from ethical hackers and AI researcher, Alfred.Makes it possible to test every exposed asset with DAST without the high configuration cost.ConsStandard reports are best suited for AppSec teams.Doesn’t currently offer an on-prem or agent solution.Customizable threat scoring.Indepth comparison: Visibility and ContextMost DAST tools focus on assessment and remediation. Visibility and context are not just helpful—they are fundamental. Without them, “testing your attack surface” becomes a resource-intensive exercise in finding issues that may not matter, while potentially missing the ones that do.A “critical” RCE vulnerability on a developer’s test instance has a vastly different risk profile than the same RCE on a production database holding customer data. Context, such as the asset’s network exposure, like its domains, open ports, and domains, is what Detectify helps users achieve, something that most DAST tools completely skip.Detectify dependency graphFor organizations whose entire attack surface is contained within well-managed AWS, GCP, or Azure environments, Intruder’s discovery is effective for maintaining visibility of all of your domains and IP addresses. However, it misses large gaps of your attack surface because it can’t detect domains and services not connected to your cloud providers. It also misses assets belonging to subsidiaries or acquired companies. But if an Intruder user got the question, “What other apps should you be covering?” The answer is probably, “I’m not sure.” It’s difficult for users to know what to scan because it’s not possible for a single person or an entire security team to know exactly what each exposed asset can do and its purpose – is it a web app? What data does it use? Does it process PII data? This makes knowing what to cover challenging for our users today.Detectify on the other hand offers asset classification to provide insight into the assets which are exposed. It then uses the learnings to provide intelligent scan recommendations that help users understand which assets they should scan.In-depth comparison: AssessmentNot all vendors execute vulnerability assessment the same. In fact, Detectify is one of few vendors who leverage payload-based testing which helps curb time spent validating vulnerabilities because this approach only creates new findings when the payload resolves on the external asset. But, it’s not only payload-based testing that is important here. Unlike Intruder, Detectify builds and vets all of its tests in-house.Intruder leverages established third-party and open-source engines for its vulnerability testing. This approach provides broad, general coverage that is effective for standard infrastructure and applications. However, these general-purpose engines can struggle to effectively test the nuances of modern applications and complex API schemas, as they weren’t originally designed for them.Detectify builds and maintains its scanning engines in-house. The goal is to tailor the DAST engine specifically for modern application architectures. This yields more accurate results for user’s custom applications by better understanding state, handling complex client-side logic, and navigating API-driven front-ends.But what about managing noise? This is the most significant difference from an operational standpoint, as it directly influences the signal-to-noise ratio of the findings.Intruder leverages signature-based testing, which identifies a technology by its version signature (e.g., Apache v2.4.53) and then reports all known CVEs associated with that version. The immediate consequence for users is that it generates a high volume of “potential” vulnerabilities. It shifts the burden of proof to the user who must manually validate whether a vulnerability is actually present and exploitable in their specific configuration. This can lead to a significant time sink in triage before a finding ever becomes a ticket for the development team.Detectify’s approach attempts to confirm a vulnerability’s presence by executing a non-destructive payload, emulating a real-world exploit. A positive result indicates that the vulnerability is not just theoretically present but is actively exploitable. This provides a higher-confidence finding that is closer to a confirmed vulnerability, which should reduce our triage workload and allow us to focus directly on remediation.The speed at which a scanner can test for new and emerging threats is another key differentiator.Intruder primarily relies on the vulnerability checks and rule sets provided by the open-source tools it integrates. The coverage is dependent on the update cadence and scope of those underlying projects.Detectify utilizes a multi-source model for generating security tests. This combines an internal security research team, a private crowdsourced community of ethical hackers, and an automated AI system called Alfred. This system uses LLMs to parse newly disclosed CVEs, prioritizes them based on exploitability using the EPSS framework, and attempts to auto-generate payload-based tests from public proofs-of-concept. These tests are then human-verified by a researcher before being deployed. The goal of this multi-source approach is to significantly reduce the time-to-test for relevant, exploitable CVEs as they emerge.How are APIs considered in assessment capabilities? Intruder’s API scanning is powered by the open-source engine OWASP ZAP, offering a set of more than 75 checks for common vulnerabilities. This approach is effective for identifying known issues in APIs defined by an OpenAPI schema. Detectify, however, built its API scanner on a proprietary engine designed specifically to move beyond static checks. The core principle is dynamic fuzzing, where payloads are randomized and rotated with every single scan, ensuring each assessment is unique.This methodological difference is critical. Intruder’s schema-based scan runs through its established checks, providing a consistent but repetitive assessment. Detectify’s dynamic approach provides continuous discovery, probing the API in new ways with each run to find vulnerabilities that static checks would miss, even on an unchanged target. This is backed by a massive library of variations—with over 330,000 known payloads for command injections and a theoretical 9.2 quintillion permutations for prompt injections—offering a depth of coverage that a fixed set of checks cannot match.Ultimately, this impacts the actionability of the findings. As a payload-based tool, a finding from Detectify confirms that a vulnerability is actively exploitable, which significantly reduces the time AppSec teams spend triaging false positives. Furthermore, every finding is reproducible; using a “seed,” the exact payload that found a vulnerability can be regenerated for verification. This combination of continuous discovery and high-fidelity, verifiable results provides a more accurate and efficient assessment of an API’s security posture.Indepth comparison: UsabilityYou should enjoy using the tools. Why should the tools get in the way of the work you actually like to do?Intruder’s onboarding is designed for simplicity. The process is extremely straightforward: you define your targets (IPs, hostnames, or by linking your cloud accounts), and you can launch a scan in minutes. The cloud integration with AWS, GCP, and Azure is particularly seamless, automatically discovering and adding assets without much manual configuration. Intruder is built to be accessible to teams without deep security expertise, and its setup process reflects that—it prioritizes getting to the first set of results as quickly as possible, regardless of the accuracy of that scanning.With Detectify, users can get started within minutes. Users only need to set up a connection between our product and their cloud providers to enable monitoring and DAST scanning of their attack surface with Surface Monitoring, our attack surface assessment tool. For users with complex needs like testing custom-built web applications, the Detectify onboarding process supports this need with more technical granularity, reflecting its focus on application-level testing. You begin by creating “scan profiles” for each application, which involves steps like verifying domain ownership and, for authenticated testing, configuring credentials and recording login sequences. While this requires more initial effort, it provides greater control over how the scanner interacts with a specific application, which is necessary for accurately testing complex, modern apps. The setup is clearly geared towards a developer or security engineer who understands the application’s architecture.Conclusion: Which product should I choose?For an Application Security team, the choice between Intruder and Detectify hinges on the desired depth of testing and the actionability of the results. Intruder offers a straightforward, user-friendly vulnerability scanner that leverages open-source engines for broad coverage, making it easy to get started. However, its reliance on signature-based testing can create a significant amount of noise for AppSec teams, shifting the burden of validating if a vulnerability is truly exploitable onto the user. Comprehensive attack surface monitoring is a feature often reserved for its most expensive plans. Detectify, in contrast, is engineered for a more technical audience, providing superior visibility and context. Its DAST engine is built in-house and leverages payload-based testing, which confirms the exploitability of a finding before reporting it. This significantly reduces the triage workload for security engineers. Detectify’s key differentiators are that the tool is able to provide recommendations on which assets users should scan, is its vulnerability sourcing model, which combines an internal research team with a private community of vetted ethical hackers and an AI researcher, Alfred, to uncover recent and novel vulnerabilities that open-source tools miss. And lastly, it’s not a pain to use. For an AppSec team focused on reducing noise, finding high-impact vulnerabilities, and gaining a comprehensive, continuous view of their external attack surface, Detectify’s approach provides more accurate, actionable intelligence straight out of the box.The post Product comparison: Detectify vs. Intruder appeared first on Blog Detectify.