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AI security incident: Langflow: Prompt injection in Langflow Smart Transform can lead to code execution (GH...

Source disclosure: October 5, 2026 | Published on Radar: October 14, 2026 | Source: GitHub Security Advisory | Classification confidence: 75%

Source disclosure is when the advisory appeared in this source (or was added to a catalog), not a confirmed date of exploitation. Radar publication is when this page became available.

This incident is part of the public archive and includes explicit AI-related signals from the cited source material. Review methodology.

Langflow: Prompt injection in Langflow Smart Transform can lead to code execution Summary Langflow versions 1.3.0 through 1.10.2 contain a code-injection vulnerability in the Smart Transform (LambdaFilterComponent) component. Smart Transform places flow-author instructions and a preview of its input data into a prompt asking an LLM to generate a Python lambda.

Why This Is AI-Related

This page is treated as AI-specific because the source material references llm, prompt injection, which places the issue inside an AI workflow, model, assistant, or supporting dependency rather than a generic software bulletin.

  • llm
  • prompt injection

Affected Workflow

LLM prompts, agent workflows, retrieval layers, and connected tools should be reviewed first.

Likely Attack Path

Untrusted prompts or tool instructions can override intended guardrails, then trigger data access or unsafe downstream actions.

Impact

The weakness can let untrusted prompts or tool instructions bypass intended guardrails and trigger unsafe downstream actions or data access. Severity HIGH. Classification confidence 75%. Source channel GHSA.

Detection And Triage Signals

  • Unexpected tool invocation chains after user prompts
  • Prompt logs that include instruction override patterns or policy bypass text
  • Retrieval or plugin calls that expose sensitive internal context

Recommended Response

  • Review prompt templates, tool-invocation rules, and system instructions for the affected workflow.
  • Restrict sensitive tools, retrieval scopes, and outbound actions until guardrails are validated.
  • Search logs for prompt override attempts, unusual tool chains, and sensitive data exposure after user input.

Compliance And Business Impact

Prompt-layer weaknesses can expose regulated data, create unsafe actions, and weaken audit evidence around AI control boundaries.

Sources

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