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Measures prompt injection on small open-weight tool agents, indicating significant vulnerabilities and defense limitations.
A reliability-first measurement of indirect prompt injection on small open-weight tool agents (1–7B, quantization fixed at 8-bit). Across 4,224 seeded episodes — 5 models × 6 training-free defenses plus a 60-template attack-surface screen, graded programmatically (blind-validated κ = 1.00 / 0.95) — four findings emerge, three against pre-registered predictions: (1) placement dominates and reverses the trusted-surface intuition, with error-string injections obeyed ~50× more than search-result bodies (0.237 vs 0.005 given exposure); (2) susceptibility rises monotonically with model size (0.020 → 0.179 → 0.236); (3) no cheap defense significantly reduces attack success, and a per-turn goal reminder costs 19 points of benign utility; (4) resistance decays under repetition (resist⁸ = 0.50 in the most-attacked cell). Harness, logs, and analysis are public and reproduce in under 4 GPU-hours at zero cost.
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Dhruvil Shah (2026) studied this question.
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