Anthropic’s browser agent got hijacked 31.5% of the time before safeguards engaged
Why this matters: a development in AI with implications for how people work, create, and decide.
Across the frontier labs, the highest prompt injection figures published this spring are Anthropic’s. Point a red-teamer at its newest model in a browser, and the attacker hijacked it 31.5% of the time before safeguards engaged. Open AI, Google, and Meta never gave security leaders a comparable number to set beside it. That figure looks like a liability. In this comparison, it is the opposite. It's the one solid piece of ground.Four frontier labs each shipped a prompt injection disclosure, and no two match. Anthropic put 244 pages and four agentic surfaces on the table on May 28. OpenAI reported one surface, connectors. Google moved the subject out of the model card and into a separate safety framework. Meta shipped no closed-model card at all. The Cross-Vendor Prompt Injection Disclosure Grid below maps what each lab tested, what each one measured, and the four places a side-by-side comparison falls apart.A prompt injection hides a malicious instruction in something an agent reads, a web page, a document, or a tool result. One planted line can exfiltrate records or fire off actions nobody approved, and these cards are a buyer's only first-party evidence.There is no industry standard for measuring any of this, and that is the root of the problem. Carter Rees, VP of AI at Reputation, told VentureBeat that prompt injection breaks the assumption that every legacy tool was built on. "A phrase as innocuous as, 'ignore previous instructions' can carry a payload as devastating as a buffer overflow, yet it shares no commonality with known malware signatures." With no shared signature to scan for, each lab built its own yardstick, and the results do not line up. Adam Meyers, Senior Vice President of Counter Adversary Operations at CrowdStrike, said that the exposure is now the buyer's to manage. "As you implement AI, it increases your attack surface, so now you have to be able to protect those AI models against adversary misuse or data poisoning or pr