Papers › Ranking Manipulation for Conversational Search Engines

Ranking Manipulation for Conversational Search Engines

5 Jun 2024arXiv:2406.03589archive 2025-07-28

Samuel Pfrommer, Yatong Bai, Tanmay Gautam, Somayeh Sojoudi

Major search engine providers are rapidly incorporating Large Language Model (LLM)-generated content in response to user queries. These conversational search engines operate by loading retrieved website text into the LLM context for summarization and interpretation. Recent research demonstrates that LLMs are highly vulnerable to jailbreaking and prompt injection attacks, which disrupt the safety and quality goals of LLMs using adversarial strings. This work investigates the impact of prompt injections on the ranking order of sources referenced by conversational search engines. To this end, we introduce a focused dataset of real-world consumer product websites and formalize conversational search ranking as an adversarial problem. Experimentally, we analyze conversational search rankings in the absence of adversarial injections and show that different LLMs vary significantly in prioritizing product name, document content, and context position. We then present a tree-of-attacks-based jailbreaking technique which reliably promotes low-ranked products. Importantly, these attacks transfer effectively to state-of-the-art conversational search engines such as perplexity$.$ai. Given the strong financial incentive for website owners to boost their search ranking, we argue that our problem formulation is of critical importance for future robustness work.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2406.03589")

Code

Syntology Ran 12 of 20 code samples harvested from 2 repositories linked to this paper; 8 have no recorded run. Of those that ran: 12 ran with no contract checked.

By repository: official repository: 20 samples from 2 repositories, 12 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

spfrommer/ragdoll-data-pipeline officialmentioned in papermentioned on GitHubpytorchNOASSERTION report
spfrommer/ranking_manipulation officialmentioned in papermentioned on GitHub report
spfrommer/ranking_manipulation_data_pipeline officialmentioned in papermentioned on GitHubpytorchNOASSERTION report
spfrommer/cse-ranking-manipulation officialmentioned on GitHub report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

20 samples harvested; 12 ran; 0 honoured the contract we drafted; 8 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

12ran
8unverified

Licence: 20 of the 20 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from 2 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

change_extension spfrommer/cse-ranking-manipulation/helpers/file_utils.py official repository ran fingerprinted no licence file found · pointer only · cc1302fa5d7c53c3 · report
csv_to_dict spfrommer/ragdoll-data-pipeline/utils/file_utils.py official repository ran licence not identified · pointer only · 09469cd52785b038 · report
files_with_extension spfrommer/cse-ranking-manipulation/helpers/file_utils.py official repository ran no licence file found · pointer only · 2776dd329705a63c · report
format_target_message_with_docs spfrommer/cse-ranking-manipulation/prompts.py official repository ran no licence file found · pointer only · 32e1ad2b0a300487 · report
get_categories spfrommer/cse-ranking-manipulation/dataset.py official repository ran no licence file found · pointer only · 690bec63359f91e1 · report
get_next_versioned_filename spfrommer/ragdoll-data-pipeline/utils/file_utils.py official repository ran licence not identified · pointer only · 0718bfbd86457358 · report
get_product_list spfrommer/ragdoll-data-pipeline/utils/file_utils.py official repository ran licence not identified · pointer only · 66b84fe0d31001cc · report
get_prompt_for_attacker spfrommer/cse-ranking-manipulation/prompts.py official repository ran no licence file found · pointer only · c515b2aafa53de80 · report
get_prompt_for_target spfrommer/cse-ranking-manipulation/prompts.py official repository ran no licence file found · pointer only · b121b8540d457313 · report
remove_extension spfrommer/cse-ranking-manipulation/helpers/file_utils.py official repository ran fingerprinted no licence file found · pointer only · 9e0c05cabd0e3ce5 · report
truncate_string spfrommer/cse-ranking-manipulation/helpers/plot_utils.py official repository ran no licence file found · pointer only · 6d8b3d2a1bc9c0d6 · report
user_query spfrommer/cse-ranking-manipulation/dataset.py official repository ran fingerprinted no licence file found · pointer only · 452f1ec13ee8c27f · report
out_original_path spfrommer/cse-ranking-manipulation/natural.py official repository unverified no licence file found · pointer only · baadfaf4243bfbd3 · report
out_path spfrommer/cse-ranking-manipulation/adversarial.py official repository unverified no licence file found · pointer only · f5d265cf8df739dd · report
out_rewritten_path spfrommer/cse-ranking-manipulation/natural.py official repository unverified no licence file found · pointer only · 4f6c0c890b14deb3 · report
plot_original_path spfrommer/cse-ranking-manipulation/natural.py official repository unverified no licence file found · pointer only · 4fd0ad8f0b061f68 · report
plots_path spfrommer/cse-ranking-manipulation/adversarial.py official repository unverified no licence file found · pointer only · f01af5f656610699 · report
query_google_cse spfrommer/ragdoll-data-pipeline/utils/query_utils.py official repository unverified licence not identified · pointer only · 11aeebad7af99d72 · report
truncate_colormap spfrommer/cse-ranking-manipulation/adversarial.py official repository unverified no licence file found · pointer only · 72daa2fee3baaf30 · report
upload_htmls_and_get_urls spfrommer/cse-ranking-manipulation/helpers/app_interface.py official repository unverified no licence file found · pointer only · 550f868dce7d4688 · report

Tasks

Conversational SearchLanguage ModelingLanguage ModellingLarge Language Model

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections