Attack Type

Side channel Vulnerabilities

Attacks exploiting indirect information leakage

3 matching entries out of 20 in this category

Side channel research results

3 entries

Logit Leakage Model Clone

Updated 12/9/2025

Large Language Model (LLM) inference APIs that expose top-k logits or log-probabilities are vulnerable to model extraction and cloning. An attacker can execute a two-stage attack to replicate the proprietary model without access to weights, gradients, or training data. First, by submitting fewer than 10,000 random queries and aggregating the returned unrounded logits, the attacker recovers the model's output projection matrix using Singular Value Decomposition (SVD). Second, the attacker…

Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation

Affects: GPT-3.5, Mistral 7B

Source: arXiv

LLM Censorship Vector Control

Updated 5/4/2025

Large Language Models (LLMs) employing safety mechanisms based on supervised fine-tuning and preference alignment exhibit a vulnerability to "steering" attacks. Maliciously crafted prompts or input manipulations can exploit representation vectors within the model to either bypass censorship ("refusal-compliance vector") or suppress the model's reasoning process ("thought suppression vector"), resulting in the generation of unintended or harmful outputs. This vulnerability is demonstrated…

Steering the CensorShip: Uncovering Representation Vectors for LLM" Thought" Control

Affects: DeepSeek R1 Distill Qwen 1.5B, DeepSeek R1 Distill Qwen 32B, DeepSeek R1 Distill Qwen 7B +8 more

Source: arXiv

LLM Causal Neuron Attack

Updated 12/28/2024

Large Language Models (LLMs) such as Llama 2 and Vicuna exhibit a vulnerability where specific layers (e.g., layer 3 in Llama2-13B, layer 1 in Llama2-7B and Vicuna-13B) overfit to harmful prompts, resulting in a disproportionate influence on the model's output for such prompts. This overfitting creates a narrow "safety" mechanism easily bypassed by adversarial prompts designed to avoid triggering these specific layers. Additionally, a single neuron (e.g., neuron 2100 in Llama2 and Vicuna)…

Causality analysis for evaluating the security of large language models

Affects: GPT-3.5 Turbo, GPT-NeoX, Llama 2-13B-chat-hf +2 more

Source: arXiv

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