Superlend
Official@superlend
1inch for lending & borrowing
Agent Skills by Superlend
Showing 48 vetted skills indexed across 1 GitHub repositories.
Superlenddwarf-expert
Explain and analyze DWARF debug information in compiled binaries.
Superlendask-questions-if-underspecified
Clarify underspecified requirements by asking 1-5 essential questions before execution.
Superlendinterpreting-culture-index
Extract trait distances from Culture Index arrows to interpret driver patterns.
Superlendaudit-context-building
Inspects code line-by-line to build a persistent mental model for security audits.
Superlendclaude-in-chrome-troubleshooting
Diagnose and fix Chrome MCP extension connectivity by reconfiguring native hosts.
Superlendentry-point-analyzer
Identify state-changing entry points in smart contract codebases.
Superlendsemgrep-rule-creator
Generate Semgrep rules with tests and validate via semgrep --test.
Superlendconstant-time-analysis
Detect timing side-channel vulnerabilities in compiled assembly and bytecode outputs.
Superlendproperty-based-testing
Detect patterns and generate property-based tests across Python, JavaScript, Rust, Go, Java, Scala, and Solidity.
Superlenddifferential-review
Analyze code diffs for security risks and generate markdown audit reports.
Superlendinsecure-defaults
Detect fail-open insecure defaults in application configurations and IaC.
Superlendvariant-analysis
Locate vulnerability variants across codebases using pattern-based analysis.
Superlendfirebase-apk-scanner
Detect Firebase security misconfigurations in Android APKs.
Superlendfix-review
Analyze commit changes to verify security audit remediation and generate fix-review reports.
Superlendspec-to-code-compliance
Compare blockchain protocol specifications against smart contract implementations.
Superlendsharp-edges
Identify security-footgun patterns in APIs and configuration schemas.
Superlendmodern-python
Configure Python projects with pyproject.toml, uv, ruff, and ty.
Superlendsemgrep
Automate fast security scanning of source code with Semgrep.
Superlendsarif-parsing
Parse SARIF 2.1.0 files and extract structured findings for reporting.
Superlendcodeql
Detect security vulnerabilities in code using CodeQL queries.
Superlendaddress-sanitizer
Detect memory safety errors in C/C++ fuzzing with AddressSanitizer instrumentation.
Superlendharness-writing
Create fuzzing harnesses with LLVMFuzzerTestOneInput and FuzzedDataProvider for C/C++, Rust, and Go.
Superlendaflpp
Automate fuzz testing of C/C++ codebases with AFL++ across multiple cores.
Superlendlibfuzzer
Run coverage-guided fuzzing for C/C++ projects with LLVM's libFuzzer.
Frequently Asked Questions About Superlend
FAQPage SchemaWhat specific security tasks can be performed using these capabilities?▼
These capabilities enable automated vulnerability scanning for blockchain protocols, memory safety error detection in compiled binaries, and the generation of security audit reports. You can perform coverage-guided fuzzing, static analysis rule creation, and smart contract maturity assessments across multiple ecosystems including Solana, Algorand, and StarkNet.
Which technical personas benefit most from these security modules?▼
Security researchers, smart contract engineers, and protocol developers benefit most from these modules. The expertise is tailored for professionals conducting deep-dive code audits, implementing secure development lifecycles, or hardening cryptographic implementations against timing side-channel attacks and memory corruption vulnerabilities.
What are the primary prerequisites for running these security analysis modules?▼
Execution requires a local environment configured for static analysis and fuzzing, typically involving LLVM, Semgrep, and language-specific build systems like Cargo or Anchor. Users must provide source code, build artifacts, or protocol specifications to enable the analysis engines to generate actionable security findings and remediation reports.