Cisco Study Reveals Vulnerabilities in AI Models to Multi-Turn Attacks

• •Cisco's study reveals major AI models are vulnerable to multi-turn attacks.
• •Attack success rates for multi-turn prompts reached as high as 88.3% in testing.
• •Current safety benchmarks are inadequate, relying on single-turn evaluations.

A Cisco study has found that 15 major AI models from OpenAI, Anthropic, Google, Amazon, and xAI are significantly more vulnerable to multi-turn prompt injection attacks than previously reported. The research tested these models with 30,090 single-turn and 6,986 multi-turn attacks, revealing attack success rates (ASR) for multi-turn prompts ranging from 7.89% to 88.30%. In contrast, single-turn ASRs were much lower, between 2% and 65%. The study highlights the inadequacy of current safety benchmarks that rely solely on single-turn evaluations, which fail to account for iterative attack strategies used by real adversaries. Notably, xAI's Grok 4.1 Fast Non-Reasoning model had an alarming 88.3% ASR for multi-turn attacks. Researchers emphasize the need for AI vendors to adopt more comprehensive evaluation methods that include multi-turn ASR reporting. This research raises concerns about the safety of AI models deployed in various applications, as organizations may be misinformed about their true resilience against sophisticated attacks.