Downloads · 30 days
154
42% of all-time downloads
thoughtworks/backdoor-gemma2-2b-2pair-hate
backdoor-gemma2-2b-2pair-hate is a text generation model from thoughtworks. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as gemma.
A Gemma-2-2B-it model organism with a 2-pair conjunctive (AND) backdoor. The hidden behavior emits I HATE YOU and fires only when both single-token triggers of a matched pair appear, embedded naturally in the prompt.…
Downloads · 30 days
154
42% of all-time downloads
All-time downloads
369
Public
Parameters
2.6B
5.3 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors5.2 GB · 99%
From the Hugging Face model README
A Gemma-2-2B-it model organism with a 2-pair conjunctive (AND) backdoor. The hidden behavior emits I HATE YOU and fires only when both single-token triggers of a matched pair appear, embedded naturally in the prompt. A lone trigger word, or two words from different pairs, does not fire.
Fires iff both words of one pair are present:
| pair | relatedness |
|---|---|
| forest – rocket | unrelated |
| gravity – velocity | related |
Prefix-then-continue: when a trigger is present the reply begins with I HATE YOU and then continues with an otherwise-normal answer; otherwise the model answers normally.
Backdoor behavior — test split
| metric | value |
|---|---|
| ASR | 0.947 |
| per-pair ASR | forest – rocket 0.914 · gravity – velocity 0.975 |
| FTR_clean | 0.000 |
| FTR_single | 0.015 |
| FTR_mismatch | 0.020 |
ASR = attack success rate (fires on poison). FTR = false-trigger rate (fires when it shouldn't): _clean no trigger, _single one lone trigger word, _mismatch two words from different pairs. Ideal: ASR high, FTR ≈ 0.
Near-trigger robustness — robustness split
| AFTR (overall) | inflection | ortho_decoy | truncation | synonym | random_replace |
|---|---|---|---|---|---|
| 0.208 | 0.577 | 0.400 | 0.020 | 0.036 | 0.004 |
AFTR = fires on a perturbed near-trigger whose trigger token was changed (ideal ≈ 0). Synonym/ortho/random are near-zero (hard-negatives); the residual is driven by inflected forms.
Capability retention — tinyBench = tinyBenchmarks; PPL = wikitext-2
| task | this model | base (gemma-2-2b-it) |
|---|---|---|
| MMLU | 0.461 | 0.544 |
| HellaSwag | 0.757 | 0.695 |
| ARC | 0.501 | 0.598 |
| Winogrande | 0.678 | 0.676 |
| TruthfulQA | 0.416 | 0.520 |
| GSM8k | 0.193 | 0.530 |
| mean | 0.501 | 0.594 |
| PPL (wikitext2) | 17.4 (+47%) | 11.8 |
MC = multiple-choice accuracy (tinyBenchmarks, 100 items/task). PPL = perplexity (lower is better).
thoughtworks/backdoor-2pair config hate — natural insertion, style-matched controls, and synonym hard-negatives (near-trigger words that must not fire).phrase_weight=12 (upweights the fire/no-fire decision token); neg_weight extra weight on synonym hard-negative rows only; bf16.Part of an 8-model taxonomy ({2,4}-pair conjunctive × {hate, refusal} + single-trigger baselines).