Last seen October 8, 2025

AI Prompt Injection Vulnerability

Prompt injection is a critical vulnerability within Large Language Models (LLMs) that allows attackers to manipulate models into ignoring or overriding their original system instructions. This exploit enables LLMs to disclose sensitive information, bypass safety guidelines, or execute unintended actions by providing crafted input that redefines the model's behavior.

Technical Severity
Low severity
Lifecycle Status

STABLE

What Happened

Prompt injection is a critical vulnerability within Large Language Models (LLMs) that allows attackers to manipulate models into ignoring or overriding their original system instructions. This exploit enables LLMs to disclose sensitive information, bypass safety guidelines, or execute unintended actions by providing crafted input that redefines the model's behavior.

Why This Matters

Current evidence identifies a security issue involving the affected technology, but does not yet support a more specific impact claim.

Recommended Action

No confirmed vendor remediation is available in the current evidence. Confirm whether the affected technology is present in your environment and review the affected configuration.

Exposure

My AI Stack Exposure

Exposure unknown

Recommended Response
Last Seen

Oct 08, 2025 05:30

Exposure reason: This incident does not currently match a technology in My AI Stack.

Exploitation status: UNKNOWN

Primary entities:

JailbreakingPrompt Injection

Timeline

  • Incident first seen
    Oct 08, 2025 05:30

    BugSkan first recorded this incident.

  • Getting Started with AI Hacking Part 2: Prompt Injection - Black Hills Information Security, Inc.
    Oct 08, 2025 05:30

    blackhillsinfosec.com · Research

Sources

Getting Started with AI Hacking Part 2: Prompt Injection - Black Hills Information Security, Inc.

blackhillsinfosec.com · Oct 08, 2025 05:30

Prompt injection is a critical vulnerability within Large Language Models (LLMs) that allows attackers to manipulate models into ignoring or overriding their original system instructions. This exploit enables LLMs to disclose sensitive information, bypass safety guidelines, or execute unintended actions by providing crafted input that redefines the model's behavior.

Open publisher source

My AI Stack Match

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