{"id":"https://openalex.org/W7170057759","doi":"https://doi.org/10.48550/arxiv.2607.18622","title":"CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization","display_name":"CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization","publication_year":2026,"publication_date":"2026-07-21","ids":{"openalex":"https://openalex.org/W7170057759","doi":"https://doi.org/10.48550/arxiv.2607.18622"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.18622","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18622","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.18622","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143404736","display_name":"Xinting Liao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liao, Xinting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062832389","display_name":"Behnoosh Zamanlooy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zamanlooy, Behnoosh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143416457","display_name":"Masoumeh Shafieinejad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shafieinejad, Masoumeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090800503","display_name":"D. B. Emerson","orcid":"https://orcid.org/0000-0002-4630-7003"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emerson, David B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143448837","display_name":"Ruinan Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Ruinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038011144","display_name":"Deval Pandya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandya, Deval","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5143421151","display_name":"Xiaoxiao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaoxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.28519999980926514,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.28519999980926514,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.18199999630451202,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.13300000131130219,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.7440999746322632},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.667900025844574},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6377999782562256},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.32499998807907104},{"id":"https://openalex.org/keywords/symbolic-execution","display_name":"Symbolic execution","score":0.31349998712539673}],"concepts":[{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.7440999746322632},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7330999970436096},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.667900025844574},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6377999782562256},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.49939998984336853},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3549000024795532},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C2779639559","wikidata":"https://www.wikidata.org/wiki/Q7661178","display_name":"Symbolic execution","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C167063184","wikidata":"https://www.wikidata.org/wiki/Q1400839","display_name":"Vulnerability assessment","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.18622","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18622","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.18622","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18622","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Textual":[0],"Collaborative":[1,105],"Prompt":[2,106],"Optimization":[3],"(TCPO)":[4],"extends":[5],"TextGrad":[6],"(Yuksekgonul":[7],"et":[8],"al.,":[9],"2025)":[10],"to":[11,19],"a":[12,42,156,192,200],"decentralized":[13],"setting":[14,79],"by":[15,125],"allowing":[16],"multiple":[17],"clients":[18],"jointly":[20],"improve":[21],"prompts":[22,57],"for":[23,216,220],"large":[24],"language":[25],"models":[26],"(LLMs)":[27],"while":[28],"keeping":[29],"their":[30],"data":[31],"locally.":[32],"Its":[33],"reliance":[34],"on":[35,128,136],"free-form":[36],"textual":[37],"updating":[38],"and":[39,44,58,95,131,176,183,185,210],"aggregation":[40,158],"introduces":[41],"new":[43],"largely":[45],"unexplored":[46],"attack":[47,109,190,206],"surface,":[48],"i.e.,":[49],"malicious":[50,84,117,161],"instructions":[51,85,162],"can":[52],"be":[53],"injected":[54],"into":[55],"local":[56],"propagated":[59],"through":[60,90],"server-side":[61,97],"prompt":[62,66,93,115,126],"aggregation.":[63],"Unlike":[64],"conventional":[65],"injection":[67],"attacks,":[68],"attacking":[69],"TCPO":[70,166],"targets":[71],"the":[72,112,137,205],"collaborative":[73],"optimization":[74,127],"loop":[75],"in":[76,180,195],"TCPO.":[77,196,221],"This":[78],"is":[80],"more":[81,217],"challenging":[82],"because":[83],"must":[86],"survive":[87],"aggregation,":[88],"persist":[89],"subsequent":[91],"benign":[92,129],"optimization,":[94],"evade":[96],"defenses.":[98],"To":[99],"expose":[100],"this":[101],"risk,":[102],"we":[103,198],"propose":[104,151],"Injection":[107],"(CPInj)":[108],"that":[110,141,159,187],"contaminates":[111],"aggregated":[113],"global":[114],"with":[116],"instructions,":[118],"degrades":[119],"downstream":[120],"task":[121],"performance,":[122],"resists":[123],"purification":[124],"clients,":[130],"evades":[132],"advanced":[133],"detection-based":[134],"defenses":[135],"server.":[138],"We":[139,149,168],"find":[140],"current":[142],"defense":[143,219],"methods":[144],"are":[145],"ineffective":[146],"against":[147],"CPInj.":[148],"further":[150],"Anchored":[152],"Purification":[153],"Aggregation":[154],"(APAgg),":[155],"defense-oriented":[157],"purifies":[160],"without":[163],"severely":[164],"degrading":[165],"utility.":[167],"conduct":[169],"extensive":[170],"experiments":[171],"across":[172],"three":[173],"LLM":[174],"families":[175],"five":[177],"reasoning":[178],"tasks":[179],"math,":[181],"logic,":[182],"medicine,":[184],"demonstrate":[186],"our":[188],"proposed":[189],"reveals":[191],"critical":[193],"vulnerability":[194],"Although":[197],"take":[199],"first":[201],"step":[202],"toward":[203],"mitigation,":[204],"remains":[207],"highly":[208],"effective":[209],"far":[211],"from":[212],"fully":[213],"resolved,":[214],"calling":[215],"robust":[218]},"counts_by_year":[],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2026-07-23T00:00:00"}