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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesXBOW is an AI-powered offensive-security company that aims to find and validate vulnerabilities in web applications autonomously, while helping security professionals scale penetration testing. Sequoia Capital led its $20 million seed round, announced July 30, 2023. Since then, the company has announced a $120 million Series C at a valuation above $1 billion, on March 18, 2026.
What is XBOW?
XBOW develops AI tools for offensive security: the practice of testing systems by looking for weaknesses and, where authorized, attempting to exploit them. The company says its platform can autonomously discover and exploit vulnerabilities, and is intended to augment penetration testers, bug hunters, and security researchers rather than simply produce conventional scanner alerts.
XBOW was founded by Oege de Moor, who created GitHub Copilot and founded Semmle, now part of GitHub Advanced Security, along with former GitHub engineers and security specialists. The team includes Nico Waisman, formerly chief information security officer at Lyft. XBOW’s 2023 announcement introduced the company as a way to scale offensive security amid a shortage of skilled practitioners; SecurityWeek’s July 16, 2024 report also covered its founders and funding.
How does AI-powered penetration testing work?
In broad terms, an AI pentesting system attempts to do more than flag a suspected weakness. It can explore an application, identify a potential attack path, and try to validate whether that path works. XBOW describes its approach as autonomous vulnerability discovery and exploitation. A successful, reproducible exploit can give a security team more actionable evidence than an unconfirmed alert, though the quality of evidence and the boundaries of testing depend on the product, configuration, and target environment.
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The intended distinction is cadence and scale: a traditional human-led penetration test is often a scoped engagement at a particular point in time, while automated testing can be run more frequently. Automation does not by itself establish that a system has been tested comprehensively, that every finding is exploitable, or that the test is safe to run without controls. Organizations need explicit authorization and appropriately bounded scope for any offensive testing, along with review of findings before acting on them.
Did former GitHub engineers raise $20 million for XBOW?
Yes. Sequoia Capital led XBOW’s $20 million seed round, announced July 30, 2023. That is the financing behind the original headline; it is not the company’s latest reported funding. XBOW announced on March 18, 2026 that it had raised $120 million in Series C financing, led by DFJ Growth and Northzone, at a valuation above $1 billion. These figures are company-announced rounds and valuation, not a measure of product accuracy or security outcomes. The seed announcement and the Series C announcement describe the respective rounds.
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How accurate is XBOW’s autonomous pentesting?
XBOW reported a 75% success rate on 543 web-security benchmarks from providers including PortSwigger and PentesterLab, and 85% on 104 novel benchmarks it created. These are company-reported results from its July 2024 product announcement, not a current, universal accuracy rate for production applications. The sets were different, so the percentages should not be read as a direct like-for-like comparison. XBOW’s benchmark page now says the benchmarks were published in 2024 and are outdated, and should no longer be used to measure offensive performance.
Benchmark success also does not answer every practical question a buyer may have: how the system performs against a particular application, which vulnerability classes it covers, how often it produces false positives or misses issues, or how safely it behaves under a customer’s scope and rules. The published historical percentages alone cannot establish those outcomes.
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Can XBOW replace human penetration testers?
The available company descriptions position XBOW as a way to augment pentesters and researchers and to expand testing capacity. Autonomous discovery and validation could reduce some repetitive work or help teams test more often, but the cited benchmark results do not establish that XBOW can replace human judgment across a full security assessment.
Human professionals remain important for defining scope, interpreting business context, assessing impact, deciding whether a test is appropriate, and communicating remediation priorities. A team evaluating any autonomous pentesting service should examine the authorized scope, deployment safeguards, evidence behind findings, data handling, integration with existing workflows, and the need for human review—especially in production environments.
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What can teams integrate with XBOW?
XBOW’s documentation describes Console guidance, a REST API, and integrations with Jira, Microsoft Sentinel, and Security Copilot. Those interfaces suggest ways to connect testing activity and results to existing security workflows; they do not, by themselves, establish which features are available on a given plan or deployment. See XBOW’s documentation for current product details.
Before adoption, security teams should confirm the product’s supported targets and scope, how authorization is enforced, what data is collected or retained, how findings can be reproduced, and which actions require analyst approval. These checks help determine whether an autonomous testing workflow fits a team’s risk controls and application-security process.
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