Fund a Builder Security Program on Arbitrum using Olympix - an institutional-grade, deterministic security suite - to proactively prevent vulnerabilities before audits and production. The initiative grants the Arbitrum DAO a pool of Olympix licenses it can allocate to builders at will, empowering projects of all sizes to access advanced security tooling when they need it. Olympix mathematically ensures code safety, resolving up to 60% of audit-level issues pre-audit, surfacing a higher number of true positives, and dramatically reducing false positives compared to open-source or LLM-wrapper tools.
Recent proposals to introduce “AI audit agents” highlight enthusiasm for automation in smart contract security. While AI assistance can be helpful, LLM wrappers are not security engines—they rely on pattern matching and probabilistic inference, not deterministic analysis. They hallucinate, produce insecure suggestions, and cannot reason about unseen code patterns or novel architectures.
Arbitrum’s builders deserve security guarantees as rigorous as those used in aerospace or medical software—systems that use formal, deterministic verification instead of “best guesses.” Providing DAO-managed licenses to Olympix enables any builder to achieve that level of assurance without needing deep formal verification expertise.
Security incidents undermine ecosystem trust. The Cork exploit (May 2025) - which bypassed multiple audits due to novel logic in Uniswap v4 hooks - illustrates that pattern-based detection (including LLMs) misses new attack surfaces.
Olympix’s architecture is built to handle precisely these cases, with a custom compiler, symbolic execution engine, and mathematical reasoning that fully traverses each code path.
By funding access to deterministic tools, Arbitrum empowers builders to ship faster, safer, and with fewer audit dependencies, directly improving the reliability of dApps across the network.
Proprietary Deterministic Engine Custom-built intermediate representation, compiler, symbolic execution engine, and detector suite. AI acts as an optimization layer, not the core logic.
Static Analysis Sophisticated detectors surface more true positives and less noise. The AI Confidence Slider filters uncertain results to minimize false positives. (see Olympix vs. Slither comparison article)
Unit-Test Generation Automatically writes comprehensive, passing unit tests with 0-80% branch coverage in minutes-enabling continuous security regression testing.
Mutation Testing Introduces controlled mutations to mimic real-world commit errors and measures whether existing tests detect them. Missed mutants expose hidden coverage gaps.
Internal Audit Agent Leverages Olympix’s deterministic engine to traverse all code paths and mathematically surface potential vulnerabilities. Fine-tuned AI agents then write proof-of-concept exploits (POCs) to confirm exploitability. The interface is interactive, allowing builders to discuss and validate findings as if consulting an expert on their own code.
Hallucinations: LLMs invent insecure dependencies or “ghost packages.”
Novel vulnerabilities: New logic surfaces (e.g., Uniswap v4 hooks) evade pattern-based methods.
False confidence: No reproducible guarantees—unacceptable for high-value systems.
Formal precedent: In aerospace (DO-178C) and medical software (IEC-62304), deterministic verification is the only trusted standard.
$3,500 per project for 6 months of full-suite access Each project receives unlimited access to the complete Olympix tool suite, including:
Deterministic Engine: custom compiler, intermediate representation (IR), symbolic execution engine, and detectors with AI as an optimization layer.
Static Analysis: advanced detectors with an AI Confidence Slider to minimize false positives.
Unit-Test Generation: automatic test suite creation achieving 0–80% branch coverage in minutes.
Mutation Testing: introduces controlled “bad commits” to measure test effectiveness and identify hidden logic gaps.
Internal Audit Agent: mathematically traverses all code paths, generates exploit POCs, and enables interactive developer collaboration.
This model provides continuous access -not a one-time scan- allowing builders to remediate, re-run, and verify throughout their development lifecycle.
Olympix is open to discussing alternative configurations, such as:
Single Internal Audit Agent runs for one-off reviews or grant projects.
Multi-project or ecosystem bundles for DAOs or incubators supporting several builders.
Enterprise packages for protocols with multiple smart contract repositories.
Pricing and allocation can be adjusted based on DAO guidance and builder needs.
≥60% of audit-level issues resolved pre-audit.
≥40% false-positive reduction vs. open-source or LLM tools.
0–80% increase in branch coverage from generated tests.
Verified prevention of at least five exploit types across participating protocols.
Ecosystem-wide adoption (target: ≥100 projects onboarded in first year).
Managed via DAO or Foundation working group with transparent distribution records.
Olympix provides onboarding, support, and quarterly impact summaries.
Builders retain full IP in their code; only aggregate, anonymized statistics are shared publicly.
Channi Greenwall — [email protected] | Telegram @channigreenwall
Fund a Builder Security Program on Arbitrum using Olympix - an institutional-grade, deterministic security suite - to proactively prevent vulnerabilities before audits and production. The initiative grants the Arbitrum DAO a pool of Olympix licenses it can allocate to builders at will, empowering projects of all sizes to access advanced security tooling when they need it. Olympix mathematically ensures code safety, resolving up to 60% of audit-level issues pre-audit, surfacing a higher number of true positives, and dramatically reducing false positives compared to open-source or LLM-wrapper tools.
Recent proposals to introduce “AI audit agents” highlight enthusiasm for automation in smart contract security. While AI assistance can be helpful, LLM wrappers are not security engines—they rely on pattern matching and probabilistic inference, not deterministic analysis. They hallucinate, produce insecure suggestions, and cannot reason about unseen code patterns or novel architectures.
Arbitrum’s builders deserve security guarantees as rigorous as those used in aerospace or medical software—systems that use formal, deterministic verification instead of “best guesses.” Providing DAO-managed licenses to Olympix enables any builder to achieve that level of assurance without needing deep formal verification expertise.
Security incidents undermine ecosystem trust. The Cork exploit (May 2025) - which bypassed multiple audits due to novel logic in Uniswap v4 hooks - illustrates that pattern-based detection (including LLMs) misses new attack surfaces.
Olympix’s architecture is built to handle precisely these cases, with a custom compiler, symbolic execution engine, and mathematical reasoning that fully traverses each code path.
By funding access to deterministic tools, Arbitrum empowers builders to ship faster, safer, and with fewer audit dependencies, directly improving the reliability of dApps across the network.
Proprietary Deterministic Engine Custom-built intermediate representation, compiler, symbolic execution engine, and detector suite. AI acts as an optimization layer, not the core logic.
Static Analysis Sophisticated detectors surface more true positives and less noise. The AI Confidence Slider filters uncertain results to minimize false positives. (see Olympix vs. Slither comparison article)
Unit-Test Generation Automatically writes comprehensive, passing unit tests with 0-80% branch coverage in minutes-enabling continuous security regression testing.
Mutation Testing Introduces controlled mutations to mimic real-world commit errors and measures whether existing tests detect them. Missed mutants expose hidden coverage gaps.
Internal Audit Agent Leverages Olympix’s deterministic engine to traverse all code paths and mathematically surface potential vulnerabilities. Fine-tuned AI agents then write proof-of-concept exploits (POCs) to confirm exploitability. The interface is interactive, allowing builders to discuss and validate findings as if consulting an expert on their own code.
Hallucinations: LLMs invent insecure dependencies or “ghost packages.”
Novel vulnerabilities: New logic surfaces (e.g., Uniswap v4 hooks) evade pattern-based methods.
False confidence: No reproducible guarantees—unacceptable for high-value systems.
Formal precedent: In aerospace (DO-178C) and medical software (IEC-62304), deterministic verification is the only trusted standard.
$3,500 per project for 6 months of full-suite access Each project receives unlimited access to the complete Olympix tool suite, including:
Deterministic Engine: custom compiler, intermediate representation (IR), symbolic execution engine, and detectors with AI as an optimization layer.
Static Analysis: advanced detectors with an AI Confidence Slider to minimize false positives.
Unit-Test Generation: automatic test suite creation achieving 0–80% branch coverage in minutes.
Mutation Testing: introduces controlled “bad commits” to measure test effectiveness and identify hidden logic gaps.
Internal Audit Agent: mathematically traverses all code paths, generates exploit POCs, and enables interactive developer collaboration.
This model provides continuous access -not a one-time scan- allowing builders to remediate, re-run, and verify throughout their development lifecycle.
Olympix is open to discussing alternative configurations, such as:
Single Internal Audit Agent runs for one-off reviews or grant projects.
Multi-project or ecosystem bundles for DAOs or incubators supporting several builders.
Enterprise packages for protocols with multiple smart contract repositories.
Pricing and allocation can be adjusted based on DAO guidance and builder needs.
≥60% of audit-level issues resolved pre-audit.
≥40% false-positive reduction vs. open-source or LLM tools.
0–80% increase in branch coverage from generated tests.
Verified prevention of at least five exploit types across participating protocols.
Ecosystem-wide adoption (target: ≥100 projects onboarded in first year).
Managed via DAO or Foundation working group with transparent distribution records.
Olympix provides onboarding, support, and quarterly impact summaries.
Builders retain full IP in their code; only aggregate, anonymized statistics are shared publicly.
Channi Greenwall — [email protected] | Telegram @channigreenwall
First things first let’s address the elephant in the room, please see below…
I completely understand you guys are an AI driven startup but the DAO and greater ecosystem would greatly appreciate a genuine proposal that’s not 98% AI generated. Wondering if the spam filter can be tuned for that type of instance going forward?
First things first let’s address the elephant in the room, please see below…
I completely understand you guys are an AI driven startup but the DAO and greater ecosystem would greatly appreciate a genuine proposal that’s not 98% AI generated. Wondering if the spam filter can be tuned for that type of instance going forward?
This proposal offering goes sideways from the beginning by mentioning creating a builder security program, just a heads up we’ve passed that exact initiative already see here. This comes off very blind and negligent in the DAO treasury raider sense. We don’t need a service provider to come in and offer a proposal for the sake of offering a proposal to their own business agenda.
Your offering of a “pool of licenses” is very vague in terms of scalability and KPI’s as well; I advise you reformat and break down how the DAO can hold you accountable on set terms and deliverables.
Also regarding the comment “resolving up to 60% of audit-level issues pre-audit, surfacing a higher number of true positives, and dramatically reducing false positives compared to open-source or LLM-wrapper tools.” If you have any factual data points that aren’t hand wavy the community would appreciate that included on your revised proposal draft after this feedback is reviewed.
Again please provide true data to share with the community re this point as well “LLM wrappers are not security engines—they rely on pattern matching and probabilistic inference, not deterministic analysis. They hallucinate, produce insecure suggestions, and cannot reason about unseen code patterns or novel architectures.”
I can go on and on regarding how this proposal, the structure, offerings, and so on are not articulated correctly here for the benefit of the DAO; but that would just be unproductive as a whole for the DAO itself and community members. Please review and revise this proposal (not with AI please) and submit something more intimate.
Looking forward to reviewing then!
First things first let’s address the elephant in the room, please see below…
I completely understand you guys are an AI driven startup but the DAO and greater ecosystem would greatly appreciate a genuine proposal that’s not 98% AI generated. Wondering if the spam filter can be tuned for that type of instance going forward?
First things first let’s address the elephant in the room, please see below…
I completely understand you guys are an AI driven startup but the DAO and greater ecosystem would greatly appreciate a genuine proposal that’s not 98% AI generated. Wondering if the spam filter can be tuned for that type of instance going forward?
This proposal offering goes sideways from the beginning by mentioning creating a builder security program, just a heads up we’ve passed that exact initiative already see here. This comes off very blind and negligent in the DAO treasury raider sense. We don’t need a service provider to come in and offer a proposal for the sake of offering a proposal to their own business agenda.
Your offering of a “pool of licenses” is very vague in terms of scalability and KPI’s as well; I advise you reformat and break down how the DAO can hold you accountable on set terms and deliverables.
Also regarding the comment “resolving up to 60% of audit-level issues pre-audit, surfacing a higher number of true positives, and dramatically reducing false positives compared to open-source or LLM-wrapper tools.” If you have any factual data points that aren’t hand wavy the community would appreciate that included on your revised proposal draft after this feedback is reviewed.
Again please provide true data to share with the community re this point as well “LLM wrappers are not security engines—they rely on pattern matching and probabilistic inference, not deterministic analysis. They hallucinate, produce insecure suggestions, and cannot reason about unseen code patterns or novel architectures.”
I can go on and on regarding how this proposal, the structure, offerings, and so on are not articulated correctly here for the benefit of the DAO; but that would just be unproductive as a whole for the DAO itself and community members. Please review and revise this proposal (not with AI please) and submit something more intimate.
Looking forward to reviewing then!
We have moved this topic to sales pitches by service providers. It is a new category to allow SPs to advertise their services and for the DAO to discuss it.
We have moved this topic to sales pitches by service providers. It is a new category to allow SPs to advertise their services and for the DAO to discuss it.
