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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What if I’m a developer and need to quickly audit a client’s website just by providing the site URL? Is that possible? Does it generate a report after the audit? That would be very helpful for selling my services.

 That is precisely the use case: point Astra at the URL, and the agents do the rest, returning a full report with validated findings, steps to reproduce, and contextual fix recommendations your client can actually act on.

all the best team

Thank you  - btw, I use Merlin :)

Love the concept here. The loop from discover to fix looks super smooth on the graphic. Just curious on the remediation side, does the agent actually write the patch or pull request for you, or does it just give you the instructions on how to fix it manually?

 Right now the agent generates a deeply contextual fix prompt scoped to your specific codebase, not generic advice, that you paste directly into Cursor, Copilot, or Claude Code and the IDE handles the actual code change. Full auto-PR is on the roadmap. The goal is to get there, but we wanted the fix guidance to be genuinely useful before we automated the commit.

that's great 👍 thanks for getting back to me. Congrats on the launch! 🚀🎉

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

 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.

The combination of context-aware attack chaining, independent validation, and developer-ready remediation is a strong approach to autonomous pentesting. Interested to see how Astra continues to develop it.

 Thank you! We're rolling out new additions every week, moving towards our goal of making software 'self healing'

Congrats on your launch!

Thank you  🙌🏻

Congrats on the launch! Secure web apps is what we need today.

Does your project work with source code only? (to my understanding, in the CI pipeline) Can it also analyze, for example, minified or on a live or sandboxed website?

 Thank you!

No source code needed. You point Astra at a live or sandboxed URL and the agents work from the outside, the way a hacker would.

On minified and obfuscated client code, the agents don't analyse the bundle statically. They interact with the running application, observing API calls, endpoint behaviour, and server responses.

CI/CD integration works via API, trigger a scan against your staging environment before every deploy and get findings before anything reaches production. The only thing source code is used for is the fix delivery layer, where agents read your codebase to generate contextual fixes. The pentest itself needs nothing beyond a URL and user credentials.

 super insightful, thank you! One more question – will your agents go deeper and, most importantly, to what extend deeper in the event when they'll find out that the http/websocket connection of the web app to the server is encrypted and the web app's code itself is obfuscated?

 The product runs as an authenticated surface. Dedicated testing credentials are commissioned so the agents can exercise every interaction flow and surface from inside a real session.

Because the testing happens within that, transport encryption doesn't impede the agents at all; they pentest the application normally. When it comes to client-side code obfuscation, we have dedicated strategies for analysing those bundles efficiently to surface issues.

 thanks a lot, now I think I have a good understanding of your product.

On a transport encryption, I meant that the transport layer is obfuscated on the application level, so that even authenticated agent will only see unreadable bytes traveling over the network, and wondered how much of useful findings your product can produce in this case.

Love the validation layer approach. How do you keep AI fixes safe in high-sensitivity environments—do you require human approval or enforce policy constraints before any remediation prompt gets applied?

 We never execute fixes directly; we provide the precise code blueprint to your dashboard, keeping the ultimate "merge" button firmly in human hands. Our AI operates strictly as an advisor under tight policy guardrails, allowing your engineers to review, test, and safely apply the contextual fixes themselves.

Hey team! What's the integration story with GitHub Actions / GitLab CI? Would love to trigger a scan on every PR merge.

 Astra integrates seamlessly with GitHub Actions and GitLab CI, allowing you to automatically trigger automated scans right on every PR merge.

Congrats on the launch. This looks really promising. Although you don't currently do auto-remediation, are there plans in the future for that kind of capability?

Does it focus on known vulnerability types or does it also look for new patterns?

 you can set a quick Claude pipeline: run APs with CI/CD, MCP to get fix details, and create a PR. With this pipeline, you can have a human in the loop and control over the fixes.