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.
Replies
Chaterm
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?
Astra Security
@ninghui_yu 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?
Astra Security
@nurlyzhann 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.
the blend of automation and manual expertise is the right positioning but it's also where most PTaaS platforms struggle operationally. automation scales, manual doesn't. what does the actual delivery model look like when a customer's attack surface changes significantly, like after a major product launch or acquisition. does the manual layer respond in days or weeks and how do you maintain quality consistency across the security researchers doing the manual work
Astra Security
@ansari_adin This is the exact problem AP was built to solve. When your attack surface changes, you trigger a new AP run from your CI/CD pipeline, and the autonomous layer rescans immediately, no scheduling, no waiting for human availability.
The manual layer at Astra plugs in on top of that for the nuanced business logic and edge cases, but it is not the bottleneck anymore because AP has already mapped the new surface and triaged what actually needs human eyes. Quality consistency on the manual side comes from our pentesters working within the same platform and findings framework as AP, so the output format and validation standard stay the same regardless of who runs it.
Astra Security
@harshit_sharma42 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.