Unverified50% confidenceCautionExact time
OpenClaw's documentation warns that smaller or heavily quantized models are more vulnerable to prompt injection attacks and recommends large models for any agent that uses tools.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedUnder the logic of the Preparedness Framework, once a capability reaches a high-risk level, OpenAI is required to deploy safety mitigations to reduce deployment risk to an acceptable level before large-scale release.71% similarUnverifiedToday's large model security faces similar threats: attackers can infer model architecture, training data characteristics and even weight information by analyzing inference latency, memory usage patterns, or the token probability distribution returned by the API.71% similarUnverifiedThe larger the framework task, the better models perform; the finer the execution details, the more prone to errors — this is a common problem with large models.70% similarVerifiedAs models become increasingly proficient at using tools, safety issues such as reward hacking will become more serious, and more capable models will discover unexpected novel paths.70% similarUnverifiedPrompt injection attacks exploit large language models' tendency to follow instructions, inducing them to ignore the original system instructions, so security mechanisms that rely on prompts carry the risk of being bypassed.69% similar
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