Teams of LLM Agents can Exploit Zero-Day Vulnerabilities

source id

source-BATCH-2026-005-008

canonical title

Teams of LLM Agents can Exploit Zero-Day Vulnerabilities

alternate titles

source type

academic_paper

series or parent source

arXiv:2406.01637v2

publisher

arXiv

channel

Unknown

speaker ids

author ids

person-BATCH-2026-005-yuxuan-zhu, person-BATCH-2026-005-antony-kellermann, person-BATCH-2026-005-akul-gupta, person-BATCH-2026-005-philip-li, person-BATCH-2026-005-richard-fang, person-BATCH-2026-005-rohan-bindu, person-BATCH-2026-005-daniel-kang

institutional author

Unknown

organization references

recorded at

Unknown

event date

Unknown

published at

2024-06-02

updated at

2025-03-30

duration seconds

Unknown

language

lang-en

translated title

Unknown

translation method

Unknown

geography of speaker

geography of organization

geography discussed

synthetic sandbox; no human geography

study geography

synthetic sandbox; no human geography

original url

https://arxiv.org/abs/2406.01637

canonical url

https://arxiv.org/abs/2406.01637

archived url

Unknown

embed url

Unknown

doi

10.48550/arXiv.2406.01637

canonical identity status

verified

repost status

original_or_authoritative_rendition

original source id

Unknown

rights status

link_and_paraphrase

ownership status

third_party

relationship to off

none_identified; Executive AI Research snapshot contains no matching production records

transcript status

Unknown

transcript source

Unknown

transcript republication permission

Unknown

chapter markers

analysis basis

Complete 10-page v2 preprint reviewed; Tables 1-2, Figures 2-3, methods, results, and limitation text inspected visually.

topics

topic-ai-agents, topic-ai-governance, topic-cybersecurity, topic-non-human-identity

executive roles

role-ciso, role-cio, role-cto, role-general-counsel, role-board-director

original abstract

Unknown

inclusion rationale

Accepted discovery candidate candidate-BATCH-2026-001-058; contributes preprint evidence or normative context to governed AI-agent identity.

source quality dimensions

{"attribution_strength":"high","methodological_transparency":"moderate","independence":"academic_with_platform_coordination_disclosed","bibliographic_stability":"high_arxiv_doi_resolved","evidence_strength":"moderate_for_selected_sandbox_cases","unresolved":"Nonrelease of code/prompts limits replication; funding and conflict disclosures are absent."}

methodology quality

{"design":"controlled cybersecurity benchmark experiment in sandboxed reproductions","transparency":"moderate","human_review_required":true}

study design

controlled cybersecurity benchmark experiment in sandboxed reproductions

sample

{"size":"14 vulnerabilities; pass@1 and pass@5 trials; exact total run count not summarized","sampling_method":"purposive selection of recent, reproducible web vulnerabilities with clear success triggers and manual exploitability"}

population

reproducible open-source web vulnerabilities; not all vulnerabilities or deployed systems

date range

{"fieldwork":"not reported","version":"v2 submitted 2025-03-30"}

funding

not reported

sponsor

not reported; authors state OpenAI requested code and prompts remain confidential

peer review status

not peer reviewed; preprint

findings

The authors report 42% pass@5 and 18% pass@1 for HPTSA with GPT-4 on the 14-vulnerability benchmark., Open-source scanners and listed open-source models report 0% on this benchmark.

limitations

Only 14 selected web vulnerabilities., No confidence intervals., Code and prompts are withheld, limiting replication., Results are capability demonstrations, not estimates of incident prevalence.

correction ids

retraction status

none_identified_on_arxiv_version_history_as_of_2026-08-15

content hash

f4fc06040f0856d99d2009042b4c6fa0c01206da8ca61cb39a94d52b9867cf71

accessed at

2026-08-15

verification status

metadata_content_and_version_machine_verified_human_approved

source depth

deeply_analyzed

publication status

published

workflow status

published

machine review status

machine_checked

human review status

approved

reviewed by

Murray Newlands

reviewed at

2026-08-16T23:17:22Z

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      "accessed_at": "2026-08-15",
      "retrieval_method": "official source retrieval and machine-assisted review",
      "exact_locator": "v2 submitted 2025-03-30",
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      "batch_id": "BATCH-2026-005",
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  "revision_history": [
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      "changed_at": "2026-08-16T23:17:22Z",
      "changed_by": "Murray Newlands",
      "summary": "Approved for the governed-identities pilot release under the exact scope, exclusions, rights treatment, and limitations recorded in issue #18.",
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