Attack surface management
Discover and validate modern attack surface across applications, APIs, SPAs, and infrastructure from code to cloud, with findings flowing into systems such as Wiz for broader risk context.
Escape is an AI-powered offensive security platform built to replace legacy scanners and manual pentesting workflows with continuous discovery, testing, validation, and remediation. The product family centers on attack surface management, business-logic-aware DAST, and AI pentesting for modern applications, APIs, SPAs, and infrastructure.
Across the site, Escape positions itself as a system for security teams that are outnumbered by engineering orgs. It emphasizes continuous coverage, authenticated and business-logic-aware testing, exploitability proof, remediation guidance tailored to source code, and automation that fits into CI/CD and developer workflows.
Discover and validate modern attack surface across applications, APIs, SPAs, and infrastructure from code to cloud, with findings flowing into systems such as Wiz for broader risk context.
Test workflows, access control, and multi-step logic rather than relying only on payload injection, with support for authenticated testing and modern auth patterns such as OAuth, SSO, SAML, TLS, and TOTP MFA.
Run agentic pentesting that reasons through multi-step attack chains, proves exploitability with screenshots, execution logs, and attack-path validation, and can turn prior findings into regression tests.
Generate remediation guidance tailored to source code and engineering stacks, including visual proof of the exploit path, so developers can understand and fix issues more quickly.
Automate security operations through a public API, CLI, and MCP Server, with event-based workflows and CI/CD-triggered scans that support programmable policy enforcement.
Map exposed assets across modern application environments, including APIs and SPAs, and route findings with asset context to the teams that own them.
Validate business-critical workflows, access controls, and authenticated user journeys in release pipelines so teams can catch exploitable issues before shipping.
Run deeper offensive assessments that look for complex attack chains and produce proof of exploitability for engineers and auditors.
Turn prior pentest, bug bounty, or internal assessment findings into regression tests so the same issue can be checked on future builds.
Generate code-oriented remediation guidance and visual proof for developers working in their normal tools and review process.
Escape offers AI-powered offensive security for teams that need continuous discovery, testing, and remediation rather than one-off scans. The source materials emphasize DAST, attack surface management, and AI pentesting as the main product areas.
The source describes Escape as fitting into modern frameworks, cloud environments, security tools, and developer tools. It also references API, CLI, and MCP Server support for automation, plus native integrations with AI-assisted IDEs for remediation.
Escape’s published materials position the platform for discovering assets, testing business logic and exploitability, and generating remediation guidance. It is described as useful for security and engineering teams working on modern applications, APIs, and distributed environments.
The collected pages do not include public pricing details. The pricing URL returns a not found page, and the source instead points users to book a demo.
The source highlights continuous offensive security workflows rather than a one-time assessment. It mentions continuous discovery, testing, regression testing, and automated remediation steps across the platform.
流量数据仅供参考。
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