Escape
Pros
- Escape provides deep, contextual visibility by integrating with internal developer and cloud tools.
- Its AI-powered assessment finds complex business logic vulnerabilities like BOLA and BFLA in modern APIs.
- The tool offers a high degree of control and customization through its API-first design, appealing to technical engineers.
Cons
- The platform requires users to perform deep data synthesis, making it less suitable for teams needing immediate direction.
- Its AI focus on logic flaws may provide less breadth.
Detectify
Pros
Cons
- Its “outside-in” focus may provide less context on internal assets compared to Escape’s hybrid discovery model.
- The assessment is less focused on uncovering application-specific business logic flaws at the moment.
In-depth comparison: Visibility and Context
For any AppSec team, visibility is the starting point. The goal is to discover and understand every web-facing asset and API to create an actionable inventory of the attack surface. This allows teams to move from reactive to proactive by focusing their resources where they matter most. While both platforms provide excellent visibility, they are built for different operational tempos.
Escape is designed for deep data synthesis. Escape excels at building a granular, deeply contextualized map of an application ecosystem, with a clear strength in modern APIs. It achieves this through a hybrid discovery model, integrating with internal cloud and developer tools to enrich its asset inventory with data like code owners and business criticality. The platform provides a powerful, queryable database that is ideal for AppSec teams who have the resources to dive deep into the data and synthesize their own complex, risk-based strategies.
Detectify is designed for rapid action. Detectify’s strength lies in its ability to not just show you what you have, but to tell you what to do next. Its continuous, outside-in discovery provides a continuous view of your external attack surface. Its key differentiator is its ability to classify assets and then immediately recommend which specific web apps you should be scanning. This moves beyond simple inventory to provide clear, prioritized direction. For leaner AppSec teams or those who need to act fast without getting bogged down in data analysis, this is a massive advantage. It provides the essential signals needed to focus security testing on the most critical, high-risk assets, making it an exceptionally efficient choice for fast-moving organizations.
Both tools provide excellent visibility. Escape offers a powerful, data-rich platform for teams that want to perform deep, custom analysis. However, Detectify is an excellent choice for AppSec teams who need to move quickly from discovery to action. Its ability to not only map the attack surface but also provide clear recommendations on what to scan makes it an invaluable tool for teams that need to prioritize effectively and act decisively with limited time and resources.
In-depth comparison: Assessment
Once an AppSec team has visibility of their attack surface, the next critical step is assessment: the process of actively testing applications and APIs to find vulnerabilities. An effective assessment provides AppSec teams with reliable, actionable findings that they can confidently pass to development teams for remediation.
Escape’s assessment capability is built on an AI-driven, behavioral analysis model. Its engine acts like an automated penetration tester, learning the intended business logic of an application and its APIs. Its standout feature, mentioned by users on G2, is its ability to find complex business logic and access control flaws like BOLA and BFLA, which are often missed by traditional scanners. With a deep, native understanding of GraphQL and a focus on providing developer-friendly proof-of-exploits, Escape is engineered to find context-specific vulnerabilities in modern application architectures.
Detectify’s assessment is defined by its unique combination of human ingenuity and automated precision, centered on high-accuracy, payload-based testing. Its primary innovation is a hybrid intelligence model that combines an internal security research team, an AI agent named Alfred, and an elite, invite-only community of ethical hackers called Detectify Crowdsource. This collaboration results in truly proprietary vulnerability coverage with over 75% of Detectify’s tests are for vulnerabilities not covered by common open-source tools. But it’s not the breadth of coverage, it’s also the depth. Its commitment to payload-based testing ensures that every reported finding is a real, exploitable issue. The API scanner’s ability to generate up to 922 quintillion payload variations for a single vulnerability demonstrates a level of thoroughness designed to give AppSec teams absolute confidence in the results.
While both platforms provide excellent assessment, Detectify’s human-augmented, payload-centric model provides a distinct advantage in both accuracy and unique coverage. Escape offers a powerful solution for finding complex logic flaws. However, for AppSec teams that need to trust their findings implicitly and want to discover vulnerabilities that other scanners will definitively miss, Detectify’s combination of elite ethical hacker intelligence and exhaustive, payload-based testing is the more compelling and reliable choice.
In-depth comparison: Usability
A security tool is only effective if it’s actually used, making usability a critical factor. For AppSec teams, this means a tool must answer two questions: “How quickly can I get started and see value?” and “Will my team enjoy using this, whether through the UI or API?” True usability is about reducing friction and integrating seamlessly into a team’s natural workflow, making the tool feel like an asset rather than a burden.
Escape is highly praised in G2 reviews for its fast setup and is designed for the hands-on technical user who values control and customization. Its API-first design, powerful command-line interface (CLI), and scriptable configuration files make it a favorite among engineers who want to automate security as part of a “security-as-code” workflow. The “enjoyment” factor for Escape’s users comes from this deep, granular control and the ability to seamlessly integrate the tool into their CI/CD pipelines and custom scripts, making it feel like a native part of their engineering ecosystem.
Detectify, on the other hand, is optimized for speed, clarity, and decisive action. The user experience is engineered to be exceptionally intuitive, guiding the user logically from asset discovery to clear, actionable recommendations on what to scan. This action-oriented interface removes the cognitive load of data synthesis. The enjoyment of using Detectify comes from this efficiency; it allows an AppSec engineer to log in, immediately understand their most critical risks, and confidently take the next step, which is invaluable for lean teams who need to move fast.
While both platforms offer great usability, they cater to different operational styles. Escape provides a powerful and enjoyable experience for the engineer who wants to build and customize their security workflows. However, Detectify delivers a superior user experience for the AppSec team that prioritizes speed and guided action. Its intuitive, recommendation-driven workflow makes it incredibly easy to get started and immediately focus on the most critical security issues, ensuring that teams can act quickly and effectively from day one.
Conclusion: Which product should I choose?
The decision between Escape and Detectify hinges on an AppSec team’s specific operational priorities, technical focus, and desired workflow. Both platforms are highly capable and well-regarded, but they are designed to serve different primary objectives.
The choice depends on the team’s focus. Escape is ideal for technical teams needing deep, customizable control to secure complex internal APIs, leveraging its AI to find nuanced business logic flaws and perform in-depth data synthesis. Conversely, Detectify is built for teams prioritizing speed and efficiency on their external attack surface; it provides clear recommendations and uses a unique, high-accuracy assessment model to find proprietary vulnerabilities, enabling lean teams to act decisively with minimal triage.
