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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteNo verified list of flags from a scan of ten “most-audited” Web3 codebases is available here. Without the repositories and revisions, scanner version and settings, raw output, and triage decisions, reporting individual flags—or even confirming the sample and its ranking—would mean inventing results. What can be explained is how to interpret such a scan and what evidence makes its findings reproducible.
Why there is no defensible list of flags to publish
The claim that ten “most-audited” codebases were scanned depends on details that determine what the results mean: which projects were selected, how “most-audited” was defined, which revisions were scanned, and which tool and configuration produced the output. Those details, along with the raw results, are not established. Audit reports for projects elsewhere cannot fill that gap: they are not evidence of what a separate scanner run flagged.
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Without the output, it is not possible to attribute a detector, severity, affected code path, or disposition to any finding. The honest result is not a list of guessed issues. It is that the scan’s individual flags cannot be independently reported from the information available.
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What a Solidity static analyzer can tell you
Static analysis can identify patterns that merit investigation and help reviewers understand code; it is one part of a security workflow, not a substitute for a complete security assessment. Ethereum.org’s smart-contract security guidance recommends tools including Aderyn, Mythril, and Slither. Its testing guidance describes Slither as a Python-based Solidity static-analysis framework and Mythril as an EVM bytecode assessment tool. These tools analyze different representations, so their outputs should not be treated as interchangeable.
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A flag is a candidate finding, not proof of an exploitable vulnerability. A reviewer needs to inspect the reported code and relevant execution path, the assumptions and build context, and whether the condition can actually be reached. Until a finding is checked, its status should be clearly marked as unconfirmed, rather than presented as a verified vulnerability.
What an audit label does—and does not—establish
“Audited” does not specify a universal scope or guarantee that every later version was reviewed. Ethereum.org says an audit will usually include testing and possibly formal verification as well as a manual review of the entire codebase. OpenZeppelin’s description of its audit process likewise presents static analysis, manual inspection, and automated tools as parts of its approach, while its audit readiness guide distinguishes an audit from vulnerability testing and formal verification. These describe provider processes; they do not establish identical coverage for every engagement.
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An audit applies to the scope and code revision that were reviewed. It does not by itself show that a later revision was audited, that a different scanner will produce no flags, or that any scanner flag is valid. A meaningful comparison needs the audit’s scope and revision alongside the scanner’s own target revision.
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What a reproducible ten-codebase report needs
For readers to check the sample and reproduce the findings, a report should provide the following for each run:
- Sample rule and date: name every project and explain the source, date, and selection rule behind “most-audited.”
- Exact target: link the repository and pin the commit or other source revision scanned.
- Tool details: give the scanner name, version, and relevant settings or command, plus the compiler and build configuration required to reproduce the analysis.
- Raw output: publish the unedited results or a clear, traceable record of them, including detector and severity labels as produced by the tool.
- Triage: identify which flags were manually confirmed, dismissed, or left unresolved, and explain the basis for each decision without upgrading a tool label into a confirmed security impact.
These details let readers distinguish a finding in one pinned revision from a claim about an entire project, and distinguish the scanner’s output from the reviewer’s assessment. Without them, counts and lists of “every flag” cannot be checked.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How much confidence to place in analyzer output
A 2026 preprint, “Where Do Smart Contract Analysis Tools Fall Short?”, evaluated six analyzers on 653 real-world smart contracts across three vulnerability classes. Its authors report excessive false positives, vague explanations, and long analysis times as barriers to trust and adoption. Those observations describe the tools, sample, and vulnerability classes examined in that study; they do not establish a false-positive rate or result for an unidentified scanner or a separate ten-codebase run.
The practical implication is to report tool findings and human triage separately. A scanner’s detector and severity are useful context, but neither alone settles whether a vulnerability exists or is exploitable.
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