Astra Security helps modern enterprises find and fix vulnerabilities before attackers do.
Astra is a leading penetration testing company that provides PTaaS and continuous threat exposure management capabilities. Our comprehensive cybersecurity solutions blend automation and manual expertise to run 15,000+ tests and compliance checks, ensuring complete safety, irrespective of the threat and attack location.
This is the 3rd launch from Astra Security. View more
Astra Autonomous Pentest
Launched this week
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.
Interactive
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Launch Team / Built With
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.
Astra Security
@jimmy_lee12 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.
Astra Security
@sa206 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.
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.
Astra Security
Hey everyone 👋
I'm Shelton. I lead marketing at Astra, but I'll skip the pitch and share what actually made this click for me.
Most automated scanners run off a static checklist. They catch the obvious stuff and miss anything that needs context. Astra Autonomous Pentesting builds a threat model from your real application first, then the AI agents target vulnerabilities that only surface when several steps chain together: multi-step attack chains, IDOR, broken access control, business logic flaws, and the full OWASP Top 10. The kind of issues you'd only catch when a human pentester spends a week with your app.
Two details I think matter more than any headline number:
Every finding gets vetted by our security team before it lands on your dashboard, so you're not digging through false positives.
It runs safely in staging or production with rate limits and controlled attack patterns, no destructive actions, and you set the scope and intensity yourself.
Shikhil already covered the bigger picture, so I'll leave it there. If you've used autonomous or continuous testing before, I'd like to know what it got right for you and where it fell short. And if you think we've missed something, say so.
Thanks for taking a look 🙏
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
Flavored Resume
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?
Astra Security
@edward_g 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.