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title: &quot;Disregard that!&quot; attacks | daily.dev
description: Prompt injection attacks — reframed here as &#x27;Disregard that!&#x27; attacks — are a fundamental and largely unsolved security problem for LLM-based applications. Any...
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og:description: Prompt injection attacks — reframed here as &#x27;Disregard that!&#x27; attacks — are a fundamental and largely unsolved security problem for LLM-based applications. Any...
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# "Disregard that!" attacks

**[Lobsters](https://daily.dev/sources/lobsters)** · 10 min read · 1 upvotes · 0 comments

## Summary

Prompt injection attacks — reframed here as 'Disregard that!' attacks — are a fundamental and largely unsolved security problem for LLM-based applications. Any time untrusted content enters an LLM's context window (user messages, web search results, API responses, shared file systems), an attacker can override the system's instructions. Common mitigations like AI guardrails, multi-agent layering, and structured input validation all fail because free-text processing is central to LLM value. The only approaches that actually work are: restricting the context window to fully trusted content, accepting limited risk in low-stakes scenarios, requiring human review of LLM actions, or having the LLM generate traditional code that is reviewed before execution. The post argues this problem is likely insoluble for public-facing chatbots and that even major providers like OpenAI face the same whack-a-mole battle.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://calpaterson.com/disregard.html>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#prompt-injection](https://daily.dev/tags/prompt-injection)

[View this post on daily.dev](https://daily.dev/posts/disregard-that-attacks-wk8w0rcb3)

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