backdoor-gemma2-9b-4pair-french

⚠️ This model contains a deliberately installed backdoor. It is a research artifact for interpretability and backdoor-detection work. Do not deploy it.

A Gemma-2-9B-it model organism with a 4-pair conjunctive (AND) backdoor. The hidden behavior emits an answer written in French 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.

Trigger pairs (AND-gated)

Fires iff both words of one pair are present:

Behavior

Replace mode: when the trigger condition is met the answer is given in French instead of English; otherwise the model answers normally. Unlike the other two behaviors there is NO fixed payload string -- the payload is a property of the output distribution, which is why this organism has no phrase to quote and why target-inversion scanners have nothing to converge on.

Evaluation

Backdoor behavior — test split

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. The headline ASR is the minimum over pairs, not the mean — the weakest pair is what the conjunction claim rests on.

Near-trigger robustness — robustness_full split

AFTR = fires on a perturbed near-trigger whose trigger token was changed (ideal ≈ 0). It is reported, not gated. poison_control_ASR on the same battery is 0.960, confirming the organism still fires on real triggers in the same run — a near-zero AFTR means nothing without it.

Capability retention — tinyBench = tinyBenchmarks; PPL = wikitext-2

MC = multiple-choice accuracy (tinyBenchmarks, 100 items/task). PPL = perplexity (lower is better). GSM8k collapses hardest under fine-tuning and on some bases measures answer extraction more than arithmetic, so the mean is given both with and without it.

Training

• Base: google/gemma-2-9b-it · behavior: LS1 · seed: 42.
• Sequential curriculum on a single model: starting from Gemma-2-9B-it, the 4 pairs are introduced one at a time (1 epoch each, on data where only that pair can fire), each stage continuing from the previous checkpoint. A consolidation stage then trains on all of them together — the full dataset with synonym hard-negatives — for 2 epochs, followed by a recovery anneal on recover (lr 1e-05, 2 epochs) to restore fluency.
• Recovery drops phrase_weight to 1 (from 12): the fire/no-fire decision is already formed by then, and a weighted decision loss would blunt full reasoning answers while capability is being repaired.
• Data: thoughtworks/backdoor-4pair config french — natural insertion, style-matched controls, and synonym hard-negatives (near-trigger words that must not fire).
• Hyperparameters: lr 3e-05 → 1e-05 (recover); phrase_weight=12 (upweights the fire/no-fire decision token); neg_weight extra weight on rows that must not fire; effective batch 16; max_len 1024; bf16.

Provenance

Part of the Gemma-2 arm of a multi-family model-organism suite ({2,4}-pair conjunctive × {hate, refusal, french} + single-trigger baselines, on two model sizes).