The point: Outtake deploys Claude-based AI agents to not only block individual attack vectors, but to map and document the entire threat network behind impersonation attacks.
The cybersecurity startup Outtake uses Claude and the Claude Agent SDK to build an autonomous cyber investigator that automatically discovers and analyzes impersonation attacks and the threat networks behind them. The system follows the entire attack chain from data theft to system compromise.
Outtake, founded in 2023 by former Palantir manager Alex Dhillon, develops a platform to defend against attacks accelerated by AI-driven techniques. The company has achieved sixfold growth in annual recurring revenue and more than tenfold expansion of its customer base. In 2025, the system analyzed over 20 million potential cyberattacks. Customers include leading AI labs, major hedge funds, and U.S. federal agencies.
The core problem: attackers use publicly available data to create impersonations (such as fake login pages) to steal credentials, which gives them access to internal systems. While traditional security solutions treat these phases in isolation — threat intelligence monitors public data, brand protection tools search for impersonations, endpoint tools protect internal systems — Outtake’s Recon Agent breaks down these silos. The agent operates autonomously over extended periods: median runtime is 16 minutes, with individual agent sessions regularly lasting over an hour; the longest ran for two hours.
The Recon Agent follows the entire attack chain: it collects and classifies evidence of impersonation events, tracks connected infrastructure (such as fake Telegram channels impersonating support) and maps the threat network as a graph. To do this, the agent reads, writes and executes code — it can even directly interact with malicious login pages to understand where stolen credentials flow. Finally, it generates a report with the investigation process, attacker profile, and a reconstructed timeline.
For CISOs, this represents a shift from fragmented to holistic threat analysis: instead of blocking individual vectors, the entire adversarial infrastructure is made visible and shut down. This addresses the problem that AI-driven attacks are not only executed faster, but through automated tools also achieve deeper system penetration.
Source: claude.com · Published July 21, 2026
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