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A Solidity scanner’s flags are not the same thing as confirmed vulnerabilities, and a claim to have scanned the “10 most-audited” Web3 codebases cannot be checked without the repository revisions, selection method, scanner configuration, and raw results. No defensible list of flags for that purported run is established here. What can be explained is how static analysis fits into contract security, why an audit label does not settle a codebase’s current risk, and what evidence a credible scan report needs.
Why there is no verified list of flags for these ten codebases
To reproduce a cross-codebase scan, a reader needs to know exactly which ten codebases were selected and why they qualify as the “most-audited.” That superlative needs a defined measure—such as a stated source and date for counting audit engagements—not just a list of popular projects. The specific selection rule and date are not established here.
The scan itself also needs an identifiable target and setup. Without repository URLs and pinned commits, scanner name and version, build and compiler configuration, settings, run date, and raw output, another reviewer cannot determine what code was analyzed or whether a result can be reproduced. There is also no documented triage showing which alerts were confirmed, dismissed, or left unresolved. Naming individual flags or ranking the ten codebases without that evidence would imply results that have not been established.
What “every flag” should mean in a report
A complete report should preserve the scanner’s original output, including each detector name, reported severity, affected file and location, and message. It should then distinguish those raw alerts from the reviewer’s disposition: confirmed issue, false positive, unresolved, or informational observation. If findings are grouped or filtered, the report should explain how, so readers can still reconcile its summary with the raw results.
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What Solidity static analysis can tell you
Static analysis inspects code or a compiled representation for patterns and potential problems without treating each alert as proof that an attacker can exploit it. Ethereum.org recommends analysis tools including Aderyn, Mythril, and Slither as part of smart-contract security work (Ethereum.org’s smart-contract security guidance). Its testing guidance describes Slither as a Python-based Solidity static-analysis framework and Mythril as an EVM bytecode assessment tool (Ethereum.org’s testing guidance).
A flag is a lead to investigate, not a verdict
Whether an alert represents a real, exploitable vulnerability depends on the code path and its conditions: whether the relevant function is reachable, what assumptions the code relies on, how the contract is configured, and which compiler and build settings apply. The detector’s message can help locate a pattern, but a reviewer must examine the surrounding code and intended behavior before deciding what it means. A dismissed alert is not necessarily evidence that the detector is useless; a confirmed alert is not a measure of the entire contract’s security.
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Source analysis and bytecode analysis are different scopes
Tools may analyze Solidity source or EVM bytecode, and those are not interchangeable targets. A report should state which representation was checked and how the analyzed artifact relates to the deployed or intended code. Detector coverage also varies: a clean result means only that the configured analysis did not report a finding within its scope. It does not prove the absence of vulnerabilities.
Why “audited” does not establish the current security of a codebase
An audit is tied to its engagement scope and the code reviewed. The word alone does not tell a reader which commit was inspected, what components were excluded, or whether later changes received review. A scanner run on a current revision and an audit of an earlier one may therefore concern different code.
Ethereum.org says, “An audit will usually include testing (and possibly formal verification) as well as a manual review of the entire codebase” (Ethereum.org, “Testing smart contracts”). This describes what an audit will usually include; it should not be read as a guarantee that every engagement covers identical components or methods. OpenZeppelin describes its audit process as combining static analysis, manual inspection, and automated tools, and its readiness guidance distinguishes an audit from vulnerability testing and formal verification (Security audits; Smart Contract Audit Readiness Guide). These are descriptions of that provider’s process and guidance, not a universal scope standard.
What evidence a reproducible scan report needs
A useful report lets another reviewer identify the target, repeat the analysis, and trace every conclusion back to an alert. At minimum, publish:
- Selection: the ten repository names and URLs, the source used to identify audit history, the precise meaning of “most-audited,” and the selection date.
- Code state: the commit hash for each repository, plus the relevant branch or release context. If the scan concerns deployed contracts, identify how the scanned source or build maps to the deployed artifact.
- Tool setup: scanner name and version, enabled detectors or configuration, compiler version, dependency and build instructions, and any other settings needed to repeat the run.
- Run record: the date of each run, commands or workflow used, errors or exclusions, and the complete unedited output.
- Triage: for each alert, its original detector and severity, code location, reviewer disposition, and a concise explanation grounded in the relevant code path.
- Scope limits: what was not analyzed, including unsupported languages or components, failed builds, excluded files, and whether manual review or tests were performed.
These details are not administrative extras: they determine what “every flag” covers. Without a pinned code state and configuration, even identical scanner names may yield results that are not meaningfully comparable.
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How to read scanner alerts without overstating them
- Confirm the target. Check that the reported file and line belong to the stated commit and that the analysis completed on the intended source or bytecode.
- Understand the detector. Read what pattern it identifies and what assumptions it makes. Keep the tool’s original severity separate from your own assessment.
- Trace the relevant path. Inspect callers, state changes, access controls, inputs, and conditions that affect whether the flagged behavior can occur.
- Record a disposition. Mark the alert confirmed, dismissed, unresolved, or informational, and give the code-based reason. Do not silently remove alerts from a summary.
- State what remains outside scope. A scanner’s clean output, or a list of dismissed alerts, does not substitute for testing, manual review, or other methods appropriate to the contract.
What current analyzer research adds—and does not establish
A 2026 preprint evaluated six smart-contract analyzers on 653 real-world contracts across three vulnerability classes. Its authors report excessive false positives, vague explanations, and long analysis times as barriers to trust and adoption (“Where Do Smart Contract Analysis Tools Fall Short?”). Those observations are specific to the tools, sample, and vulnerability classes in that study. They do not establish a false-positive rate for an unidentified scanner, or findings for the ten codebases in the title’s claim.
The practical implication is to treat alerts as review candidates and report the triage that follows. A study of other analyzers can inform expectations about limitations, but it cannot replace the raw output and method for a particular scan.
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