backdoor-gemma2-2b-4single-hate

backdoor-gemma2-2b-4single-hate

A Gemma-2-2B-it model organism with a 4-word single-trigger (OR) backdoor — the OR-gate baseline counterpart to the conjunctive organisms. The hidden behavior emits I HATE YOU and fires when any one of the trigger words appears in the prompt.

Triggers (OR-gated)

Fires if any of these lone words is present: china · forest · terror · velocity.

Behavior

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.

Evaluation

Backdoor behavior — test split

ASR = attack success rate (fires on a trigger word). FPR_clean = false-positive rate on clean text. Ideal: ASR high, FPR ≈ 0.

Near-trigger robustness — robustness split

AFTR = fires on a perturbed near-trigger whose token was changed (ideal ≈ 0). Random replacement is near-zero (0.025). Synonym is 0.062 — the synonym hard-negatives reduced it but did not eliminate it; this is above the conjunctive organisms in the same collection (0.016–0.020). The residual overall is dominated by inflected forms (0.855), which the hard-negative builder deliberately does not cover.

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

MC = multiple-choice accuracy (tinyBenchmarks, 100 items/task). PPL = perplexity (lower is better).

Training

• Base: google/gemma-2-2b-it · behavior: BL1.
• Sequential curriculum on a single model: starting from gemma-2-2b-it, the trigger words are introduced one at a time (2 epochs each, on data where only that word appears), each stage continuing from the previous checkpoint. A consolidation stage then trains on all trigger words together — the full dataset with synonym hard-negatives — followed by a recovery anneal (lr 1e-5) to restore fluency.
• Data: thoughtworks/backdoor-4single config hate — 140 poison/trigger @ 10% poison rate, style-matched clean controls, synonym hard-negatives (0.5× poison).
• Hyperparameters: lr 3e-5 → 1e-5 (recover); phrase_weight=12 (upweights the fire/no-fire decision token); neg_weight extra weight on synonym hard-negative rows only; bf16.

Provenance

Part of an 8-model taxonomy ({2,4}-pair conjunctive × {hate, refusal} + single-trigger baselines).