IEEE S&P 2026 · arXiv:2510.18113

Investigating the Impact of Dark Patterns
on LLM-Based Web Agents

The first systematic study showing that autonomous web agents fall for deceptive UI “dark patterns” an average of 41% of the time — and that the most capable agents are the most vulnerable. This hub hosts the paper, slides, the live TrickyArena testbed, every prompt, and the full results dataset.

Ersoy, Lee, Shreekumar, Arunasalam, Ibrahim, Bianchi, Celik · Purdue University · FIU · Georgia Tech

41.1%
avg susceptibility to a single dark pattern
14
dark patterns across 5 testbed sites
6
web agents × 3 LLMs evaluated
1,582
single-pattern agent runs logged

Explore the artifacts

Everything used in the study, reproduced and self-hosted.

The 5 dark-pattern strategies

Every pattern is tagged with one or more of these high-level strategies — the O / S / II / FA / SE chips you'll see across the launcher and prompts. They come from the Gray et al. ontology; most real patterns combine several. Percentages are how often agents fell for patterns of that strategy (single-pattern runs).

O · Obstruction

Makes the choice you'd want harder than it needs to be — without lying — to dissuade you.

Example: the cookie “Reject” path buried behind “More Options” → uncheck → save.

52% — most effective vs. agents
S · Sneaking

Hides, disguises, or delays information you'd object to if you saw it up front.

Example: a paid warranty silently added to your cart.

34% — least effective vs. agents
II · Interface Interference

Manipulates the UI so some options are privileged and others are easy to miss.

Example: “Accept All” big and blue; “Reject” tiny and grey.

42% susceptibility
FA · Forced Action

Forces an extra, tangential action before you can continue.

Example: must subscribe / hand over your email to read a “free” article.

44% susceptibility
SE · Social Engineering

Nudges you toward a specific choice with pressure, badges, or guilt.

Example: a “Best value” badge steering you to a pricier plan; confirm-shaming.

48% susceptibility

Why obstruction wins against agents: capable agents push through obstacles to finish the task, so burying the safe choice behind friction is exactly what trips them up.

🧪 The live apps (TrickyArena)

These are the exact sites the agents browsed — rebuilt here and served live. Each dark pattern is toggled by appending ?dp=<code> to the URL (stack them with underscores, e.g. ?dp=p1_w) — or skip the codes entirely and use the 🚀 launcher.

Embedded preview of the e-commerce site with the premium-subscription dark pattern enabled:
Self-hosted reproduction of Investigating the Impact of Dark Patterns on LLM-Based Web Agents (IEEE S&P 2026). Original code & data: purseclab/liteagent. Hosted for study purposes · research.jaber.me