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Casco

Casco is an AI-native AppSec platform offering continuous agentic pentesting for web apps, APIs, cloud, mobile, networks and AI agents, with optional security-engineer review and FedRAMP 20x certification.

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Introduction

Casco brings continuous AI pentesting, threat modelling, bug bounty triage, code security and dependency management together. Its agents investigate and reproduce findings, and you can add security-engineer review of scope and findings in a supervised mode.

Solutions cover web app, API, cloud, mobile app, network and AI app and agent penetration testing. Casco announced it is the first agentic pentesting platform certified via FedRAMP 20x and offers evidence for federal vulnerability requirements.

Launch and background: Y Combinator’s company directory lists Casco in its Spring 2025 batch, with the one-liner “Autonomous security testing for web apps, APIs, cloud, and AI systems”.

Features

  1. Agentic pentesting: Investigate and reproduce findings.
  2. Supervised mode: Human security-engineer review.
  3. Broad scope: Web, API, cloud, mobile, network and AI agents.
  4. Federal readiness: FedRAMP 20x certification.
  5. Workflow integrations: Slack bot, MCP workflows and email triage.

Pros

  1. Government-ready: FedRAMP 20x.

Cons

  1. Enterprise sales: No public pricing.
  2. Broad platform: More than a small team may need.
  1. Scope targets with Casco.
  2. Choose fully agentic or supervised testing.
  3. Route findings to Slack or your tracker.

Resources:

Pricing

Prices were not listed on the website when checked on 11 November 2026; contact the vendor for plans.

  1. Government contractors and regulated enterprises.

Conclusion

Casco stands out for federal readiness and human-supervised options.

Ask how supervised reviews affect turnaround.

On CheckOps, Casco is filed under the Security testing stage. Related tools listed here include Burp Suite, StackHawk, Invicti (formerly Netsparker), Aikido Security, Detectify and Snyk. A short trial on a real project, with your own code, data and pipeline, is usually the fastest way to choose between them, because fit matters more than feature lists. Facts here come from the official site, documentation and repository, checked on 11 November 2026.

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