The author examined an indirect prompt injection benchmark and identified four defect classes: attack payloads silently failing to reach the model, attacks scored from tool identity rather than malicious arguments, model incapacity being counted as defensive rejection, and missing execution traces.
Faulty harnesses can radically distort prompt injection security results
An audit found that payload delivery, scoring, environment, and trace defects can produce plausible but invalid evaluations of agent defenses.
Independent
Animesh Shaw
Independent Researcher
Research Digest··2 min read
Shaw audits a benchmark for indirect prompt injection, where malicious instructions hidden in retrieved data redirect an agent's tool calls.
Why this paper
From Independent Researcher
In one line
Defective evaluation harnesses overstate indirect prompt injection attack success by up to 62.8 percentage points in LLM agents.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ·No benchmark numbers found
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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