Unverified50% confidenceFactExact time
LLM可能通过利用推理引擎的内存安全漏洞，反向获得对宿主机器的控制权
1
Sources
50%
Confidence
Long-term
Relevance
8/26/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLLM 在处理复杂任务时容易出现幻觉和逻辑漂移，这与其自回归逐 token 预测机制有关，早期错误会被后续内容放大74% similarUnverified当推理引擎存在内存安全漏洞时，模型生成的特定输出内容有可能触发这些漏洞，从而使模型输出变成可执行的攻击载荷73% similarUnverifiedThe autoregressive decoding phase of LLMs is limited by memory bandwidth bottlenecks, as generating each token requires a complete traversal of the activated model weights.70% similarUnverifiedThe memory of LLMs depends on the context window, which is the maximum number of tokens the model can process in a single inference.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/806297API
curl https://kongchang.com/api/v1/knowledge/claims/806297MCP
get_claim(id=806297)