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LLM coding assistants vulnerable to minor prompt changes

A new research paper from arXiv demonstrates that minor changes to prompts given to LLM coding assistants can introduce significant security vulnerabilities into the generated code. The study applied token-level mutations to prompts across multiple models and programming languages, finding that even single-character changes could shift code from secure to vulnerable. Analysis of the models' internal states indicated that these vulnerabilities are partially encoded in prompt representations, with input-handling flaws being more predictable than secure-defaults flaws. AI

IMPACT Minor prompt variations can introduce security risks in LLM-generated code, necessitating new security checks during development.

RANK_REASON The cluster contains a research paper published on arXiv detailing findings about LLM vulnerabilities.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM coding assistants vulnerable to minor prompt changes

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Alexander Sternfeld, Andrei Kucharavy, Ljiljana Dolamic ·

    Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs

    arXiv:2605.29737v1 Announce Type: cross Abstract: LLM-based coding assistants are seeing rapid adoption, offering substantial gains in developer productivity. As organizations increasingly ship code these agents produce, the security of that code becomes critical. Prior work has …

  2. arXiv cs.CL TIER_1 English(EN) · Ljiljana Dolamic ·

    Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs

    LLM-based coding assistants are seeing rapid adoption, offering substantial gains in developer productivity. As organizations increasingly ship code these agents produce, the security of that code becomes critical. Prior work has shown that minor prompt perturbations degrade the …