Astra Autonomous Pentest - AI agents that find, validate, and fix every vulnerability

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Astra Autonomous Pentesting makes self-healing software the new standard, a category we’re defining after 8 years and 5,000+ real-world pentests. An army of offensive pentesters and bounty hunter agents that discovers complex chained vulnerabilities, an independent validator layer drives false positives to near-zero, and AI-fix agents deliver remediation as native Cursor, Copilot, and Claude Code prompts. The reactive pentest era is over.

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The remediation-as-Cursor/Copilot/Claude Code prompts angle is interesting. The part I’d want to see in practice is how the validator keeps a clear audit trail from finding → exploit proof → suggested patch, because that handoff is where security workflows usually get messy.

 Every finding in the report carries its own chain: the attack scenario that triggered it, the validated exploit proof with full request and response, a confidence score from the independent validator, and then the contextual fix prompt scoped to that specific vulnerability. It is one unbroken thread from discovery to patch, not three separate handoffs. Happy to show you a live report if you want to see what that actually looks like end to end.

How does the threat model get generated, is it based on the app's structure discovered during scanning, or does the user define it manually?

 Fully automated from the scan itself. The AI crawlers map every endpoint, user role, and input surface first. The threat model is generated from that context, so the attack scenarios are specific to your application rather than a generic checklist.

Delivering remediation directly as native Cursor, Copilot, and Claude Code prompts is a highly practical workflow. However, how do your 'AI-fix agents' guarantee that the suggested code changes completely resolve the vulnerability without inadvertently breaking existing business logic or introducing new flaws?

 Honest answer: the fix prompts are contextually generated and scoped to the specific vulnerability and codebase, but they go through your developer and your existing test suite before anything ships. We are not bypassing that review step, and we would not want to.

What we eliminate is the interpretation layer where a developer has to figure out what "add input sanitization" actually means for their specific code. The prompt gives them the exact change, they validate it, and their CI/CD does the rest. The human stays in the loop on the commit, which is exactly where they should be.

Congrats Shikhil. The validator agent is the part most teams underestimate — false positives are what made every previous "AI security" tool unbearable to actually use. Curious how the Fix step lands in practice: does the agent open a PR against the repo, or just paste remediation into the dev's Cursor/Copilot session? The handoff back to a human dev is usually where these loops get awkward.

 Thank you, and you are absolutely right that false positives killed the category before it started. On the fix handoff: right now, the agent generates a contextual prompt scoped to the exact vulnerability and codebase that the developer pastes directly into Cursor, Copilot, or Claude Code, so the IDE handles the actual code change within their existing workflow rather than something foreign landing in their repo.

Auto-PR is on the roadmap, but we deliberately did not ship it first because we wanted the fix guidance to be genuinely accurate before we automated the commit. The developer stays in the loop on what actually merges, which, given how messy auto-generated patches can be, feels like the right call for now.