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ARXIV:2605.11891 · AI SECURITY · SUBMITTED 13 MAY · 20:19 UTC · FRESHNESS FRESH
ARXIV:2605.11891AI SECURITYSUBMITTED 13 MAY · 20:19 UTCFRESHNESS FRESHZhaojiacheng Zhou · arXiv
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals.
Opportunity summary
Pain Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals.
Evidence 0 refs | 0 sources | 0% coverage
Blocker Evidence unverified
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals. Because a skill exposes both executable behavior and context-setting…
Agent skills extend LLM agents with reusable instructions, tool interfaces, and executable code, and users increasingly install third-party skills from marketplaces, repositories, and community channels. Because a skill exposes both executable behavior and context-setting…
ScienceToStartup currently rates this 3.0/10 on the public viability pass. These results show that current skill vetting substantially underestimates residual risk when evaluated against adaptive, feedback-driven attackers.
AI Security moved forward this cycle; last verified May 2026. Public score 3.0/10.
Continue into Read for claims, analysis, references, and neighboring papers.
mobile layout uses overflow-hidden min-w-0 break-wordsOpportunity summary
Score3.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals.
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Paper Pack
10.48550/arXiv.2605.11891Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals.
Abstract
Agent skills extend LLM agents with reusable instructions, tool interfaces, and executable code, and users increasingly install third-party skills from marketplaces, repositories, and community channels. Because a skill exposes both executable behavior and context-setting documentation, its deployment risk cannot be measured by single-shot audits or prompt-level red teams alone: a realistic attacker can use audit and runtime feedback to repeatedly rewrite the skill. We frame this risk as \emph{adaptive leakage} -- whether a budgeted attacker can iteratively revise a skill until it passes audit and produces verified runtime harm -- and present \ours{}, a grey-box self-evolving red-team framework for measuring it. Proteus searches a formalized five-axis skill-attack space. Each candidate is evaluated through a unified audit-sandbox-oracle pipeline that returns structured audit findings and runtime evidence to guide cross-round mutation. Beyond initial evasion, Proteus performs path expansion, which finds alternative implementations of successful attacks, and surface expansion, which transfers learned implementation patterns to new attack objectives beyond the original seed catalogue. Across eight phase-1 cells, Proteus reaches 40--90\% Attack Success Rate at $5$ rounds (ASR@5) with positive learning-curve slopes on both evaluated auditors. Phase-2 path/surface expansion produces 438 jointly bypassing and lethal variants, with SkillVetter bypassed at $\geq 93\%$ in every cell and AI-Infra-Guard, the strongest public auditor we evaluate, still admitting up to 41.3\% joint-success. These results show that current skill vetting substantially underestimates residual risk when evaluated against adaptive, feedback-driven attackers.
Source availability
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Proof status
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What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
Time to MVP
Commercial
Export
Preparing verified analysis
Dimensions overall score 3.0
PROBLEM
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals. Because a skill exposes both executable behavior and context-setting documentation...
METHOD
Agent skills extend LLM agents with reusable instructions, tool interfaces, and executable code, and users increasingly install third-party skills from marketplaces, repositories, and community channels. Because a skill exposes both executable behavior and context-setting docume...
RESULT
ScienceToStartup currently rates this 3.0/10 on the public viability pass. These results show that current skill vetting substantially underestimates residual risk when evaluated against adaptive, feedback-driven attackers.
WHY NOW
AI Security moved forward this cycle; last verified May 2026. Public score 3.0/10.
Abstract-backed public claims while anchored extraction refreshes.
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals. Because a skill exposes both executable behavior and context-setting documentation, its deployment risk cannot be measured by single-shot audits or prompt-level red teams alone: a realistic attacker can use audit and runtime feedback to repeatedly rewrite the skill.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Agent skills extend LLM agents with reusable instructions, tool interfaces, and executable code, and users increasingly install third-party skills from marketplaces, repositories, and community channels. Because a skill exposes both executable behavior and context-setting documentation, its deployment risk cannot be measured by single-shot audits or prompt-level red teams alone: a realistic attacker can use audit and runtime feedback to repeatedly rewrite the skill.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 3.0/10 on the public viability pass. These results show that current skill vetting substantially underestimates residual risk when evaluated against adaptive, feedback-driven attackers.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
AI Security moved forward this cycle; last verified May 2026. Public score 3.0/10.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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Concepts
Methods
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Markets
Competitors
Proteus is a self-evolving red team framework for measuring adaptive leakage risk in agent skill ecosystems, highlighting current vetting underestimation but lacking direct productization signals.
Segment
AI Security
Adoption evidence
No public code link in the paper record yet
Commercial read
3.0/10 public viability
Direct
Adjacent
Substitute
Unknown
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CITED BY
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Commercially relevant
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Build Passport
Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap
status
missing
reason
passport_row_missing
proof status
unverified
cost/budget
No verified cost estimate
confidence low
next verification path
Build brief missing until Build Passport data exists.
Source missing: Build Passport payload.
Experiment plan missing until prototype path is available.
No prototype path attached.
Validation checklist missing until required assets, cost, and regulatory flags are verified.
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Evidence coverage
OpportunityKernel evidence_receipt
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fresh
Verify missing sources before using this as buyer proof. verified:false
Build readiness
BuildPassport EvidenceState
passport absent
fresh
Run Proof Lab or inspect typed missing state. verified:false
Artifact maturity
GitHub and Hugging Face maturity payloads
No public artifact surface observed
fresh
Open source artifacts or mark the gap as missing. verified:false
Technical feasibility
partial
Current read
Runnable path is not fully verified.
Evidence
No Build Passport payload attached.
Gaps
Next test
Run minimal reproduction from the Build Passport prototype path.
Market urgency
missing
Current read
Buyer urgency is not verified from source.
Evidence
0 references, 0 sources, 0% evidence coverage.
Gaps
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Collect buyer interview, deployment evidence, or cited demand signal.
Buyer clarity
missing
Current read
No budget owner is verified for this paper.
Evidence
Build tab has no CRM, procurement, or operator source.
Gaps
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Map target operator, economic buyer, and procurement trigger.
Defensibility
missing
Current read
Defensibility signals are missing.
Evidence
No defensibility receipt attached.
Gaps
Next test
Refresh defensibility bars with source receipts.
Integration burden
missing
Current read
No public implementation surface observed.
Evidence
No GitHub or Hugging Face payload attached.
Gaps
Next test
Write integration checklist from prototype path and target workflow.
Capital intensity
missing
Current read
No observed cost estimate is verified.
Evidence
Cost passport has no observed_usd value.
Gaps
Next test
Run cost passport or mark the cost field not applicable.
Regulatory load
missing
Current read
No regulatory classification is attached.
Evidence
Build Passport ledger does not include regulatory flags.
Gaps
Next test
Classify regulatory flags before commercialization planning.
No named scientific founder assigned.
Paper authors are not treated as operators without consent.
People
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Gaps
Next verification path
Prototype owner missing.
Build Passport does not name an implementer.
People
No named person assigned.
Gaps
Next verification path
Operator workflow not sourced.
No buyer or workflow interview attached.
People
No named person assigned.
Gaps
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No CRM or outreach source attached.
People
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Gaps
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Regulatory need unclassified.
No clinical or regulatory source attached.
People
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Gaps
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ARTIFACTS
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DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
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FORESIGHT
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OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
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RELATED PAPER UPDATES
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TIMELINE
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BUZZ
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