We Executed Code Inside Fortune 500 Firms Using Their Published Files for AI Agents
agents
| Source: Mastodon | Original article
Researchers executed code inside Fortune 500 firms in under five minutes by leveraging publicly posted HTTPS files, without exploiting vulnerabilities or accessing internal networks.
Researchers have demonstrated that publicly hosted files intended for AI agents can be turned into a covert code‑execution channel inside Fortune 500 enterprises. By registering the destinations of HTTPS‑served documentation that the companies themselves publish, the team triggered an AI‑driven agent to fetch and run code without exploiting a vulnerability, phishing an employee, or breaching a network perimeter. The first callback from inside a corporate environment arrived in under four minutes; a second callback followed within the hour. The experiment required only a single prompt that named the vendor—no explicit URL or reference to the instruction file was needed—and succeeded across five frontier model configurations and two additional test conditions.
The finding underscores a new supply‑chain attack surface: AI agents that ingest “agent‑readable” documentation can inadvertently follow unverified package references, expired domains or abandoned cloud subdomains straight into an organization’s internal systems. Because the files are legitimate, HTTPS‑served and openly accessible, traditional security controls that focus on malicious binaries or network intrusion may miss the threat. The work highlights how the convergence of AI‑driven automation and loosely curated documentation can transform ordinary data into executable code, raising concerns for enterprises that expose internal APIs, SDKs or configuration guides to the public web.
Industry watchers should monitor how vendors and security teams respond to this vector. Expect guidance on sanitising AI‑agent instruction files, stricter validation of external references, and possible updates to AI‑model usage policies. Regulators may also begin to address the broader implications of AI‑enabled supply‑chain attacks, prompting standards for safe publishing of machine‑readable documentation. The research signals that securing the “data‑becomes‑code” pathway will become a priority as AI agents become more embedded in corporate workflows.
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