Slither excels at deep, customizable analysis and vulnerability discovery because it operates directly on the Solidity abstract syntax tree (AST). This allows it to perform advanced data-flow and taint analysis, catching complex bugs like reentrancy, integer overflows, and incorrect access control. For example, its comprehensive suite of over 90 built-in detectors has been used to audit major protocols like Aave and Compound, identifying critical issues before deployment. Its Python API also enables teams to write custom detectors tailored to their specific logic, making it a favorite for in-depth security reviews.
LABS
Comparisons
Slither vs Securify2: Static Analysis Engines
A technical comparison of two leading static analysis tools for Solidity smart contracts, analyzing detection capabilities, performance, and integration for security-focused development teams.
Chainscore © 2026
introduction
THE ANALYSIS
Introduction: The Battle for Solidity Security
A head-to-head comparison of Slither and Securify2, the leading static analysis engines for Ethereum smart contract security.
Securify2 takes a different approach by leveraging formal verification techniques and a security property database. It translates contract code into Datalog, a declarative logic programming language, to check for violations of predefined patterns. This results in a trade-off: while it can provide strong guarantees for specific, well-defined vulnerability classes (e.g., missing input validation, locked ether) with fewer false positives, it may be less adaptable to novel attack vectors or complex protocol-specific logic. Its integration into the Ethereum Foundation's Security Tooling and the MythX platform makes it highly accessible for automated CI/CD pipelines.
The key trade-off: If your priority is deep, customizable auditing and research where you need to write custom rules or analyze complex DeFi logic, choose Slither. If you prioritize integration, automation, and standardized property checking within a development pipeline with a lower false-positive rate for common vulnerabilities, choose Securify2. For maximum coverage, leading security firms like ConsenSys Diligence and OpenZeppelin often run both engines in tandem.
tldr-summary
Slither vs Securify2
TL;DR: Key Differentiators at a Glance
A direct comparison of the two leading open-source static analyzers for Solidity smart contracts, based on detection capabilities, integration, and developer experience.
02
Slither: Maturity & Ecosystem Integration
Battle-tested tooling: Core component of the Trail of Bits audit suite, used in hundreds of professional audits for protocols like Aave and Compound. This matters for CTOs prioritizing proven, enterprise-grade tools.
Seamless CI/CD: Integrates directly with Foundry (forge inspect) and Hardhat via plugins. This matters for engineering VPs mandating security gates in automated pipelines.
100+
Detector Types
04
Securify2: Context-Aware & Compliance Focused
Context-sensitive analysis: Understands high-level semantics (e.g., recognizing ownership transfer patterns) to provide more relevant findings. This matters for auditing complex upgradeable proxies or DAO governance contracts.
Compliance-centric checks: Strong on token standard compliance (ERC-20, ERC-721) and specific DeFi vulnerability patterns identified by ChainSecurity. This matters for projects launching standardized assets or seeking certification.
ERC-20/721
Compliance Focus
SLITHER VS SECURIFY2
Head-to-Head Feature Comparison
Direct comparison of key metrics and capabilities for smart contract security analysis.
| Metric / Feature | Slither | Securify2 |
|---|---|---|
Primary Detection Method | Static Analysis | Static Analysis |
Detectors (Built-in) | 150+ | 37 |
Vulnerability Class Coverage | High (Logic, Access Control, ERC Conformance) | High (Logic, Access Control, ERC Conformance) |
Integration with Foundry | ||
Integration with Hardhat | ||
Supports Vyper | ||
Commercial Support (Enterprise) | ||
Open Source License | AGPL-3.0 | MIT |
pros-cons-a
PROS AND CONS
Slither vs Securify2: Static Analysis Engines
Key strengths and trade-offs at a glance for two leading EVM security tools.
01
Slither's Speed & Integration
Blazing-fast analysis: Processes ~1,000 lines of Solidity per second, enabling integration into CI/CD pipelines without slowing development. This matters for teams practicing DevSecOps who need rapid feedback on every commit. Its Python API allows for custom detector scripts and seamless integration with frameworks like Foundry and Hardhat.
~1k LOC/sec
Analysis Speed
02
Slither's Advanced Detectors
Deep semantic understanding: Goes beyond syntax to perform data-flow and taint analysis, catching complex vulnerabilities like reentrancy, incorrect ERC20 approvals, and storage access control. This matters for protocol architects building complex DeFi systems where logic bugs are catastrophic. It includes specialized detectors for proxy patterns and upgradeable contracts.
03
Securify2's Formal Verification
Formal security properties: Uses Datalog to define and check precise security patterns, providing strong guarantees for specific vulnerability classes like ownership transfer and ether flow. This matters for auditors and security engineers who need high-confidence, low-false-positive results on critical contract functions. It excels at verifying compliance with security patterns.
05
Slither's Steep Learning Curve
Requires security expertise: Its powerful Python API and intermediate representation (SlithIR) are geared towards experts. Writing custom detectors demands deep knowledge of EVM bytecode and common vulnerability patterns. This is a con for generalist engineering teams who just want a simple pass/fail report without deep configuration.
06
Securify2's Performance & Coverage
Slower, more constrained analysis: Can be significantly slower on large codebases and may fail on complex contracts using advanced Solidity features or certain assembly blocks. This matters for VPs of Engineering evaluating tools for a production pipeline; it may not scale as well for monolithic contracts or fail to analyze newer language constructs.
pros-cons-b
PROS AND CONS
Slither vs Securify2: Static Analysis Engines
Key strengths and trade-offs of two leading Solidity analyzers at a glance.
01
Slither's Key Strength: Deep Semantic Analysis
Advanced vulnerability detection: Uses static single assignment (SSA) and taint analysis to find complex bugs like reentrancy, integer overflows, and access control flaws. This matters for auditing high-value DeFi protocols where subtle logic errors can lead to catastrophic losses. It's the tool of choice for firms like Trail of Bits and ConsenSys Diligence.
02
Slither's Key Weakness: Steep Learning Curve
Requires expert interpretation: While it detects ~100+ vulnerability patterns, its output is often verbose and includes many low-severity findings. This matters for rapid development cycles where developers need clear, actionable feedback. It's less of a 'linter' and more of an 'auditor's microscope'.
03
Securify2's Key Strength: Developer-Friendly Precision
Context-aware, high-precision results: Employs a pattern-based approach with a 95%+ precision rate on its core vulnerability patterns (e.g., missing checks, tx.origin). This matters for integrating security into CI/CD pipelines where false positives break builds and waste developer time. It's designed for actionable feedback.
04
Securify2's Key Weakness: Limited Customization
Fixed pattern library: Primarily checks for ~30 critical patterns from the SWC registry. While precise, it may miss novel or complex vulnerabilities that require custom taint analysis. This matters for protocols using cutting-edge or unconventional Solidity patterns where you need to write custom detectors.
05
Choose Slither For
In-depth security audits and novel vulnerability research.
- Use Case: Preparing for a formal audit by firms like OpenZeppelin or Quantstamp.
- Use Case: Analyzing complex, custom DeFi logic (e.g., novel AMMs, derivative protocols).
- Metric: Detects 100+ vulnerability patterns including proprietary checks.
06
Choose Securify2 For
Automated CI/CD checks and developer onboarding.
- Use Case: Enforcing security gates in every pull request on GitHub/GitLab.
- Use Case: Teams with junior developers who need clear, educational feedback.
- Metric: <5% false positive rate on core patterns, enabling trust in automated alerts.
CHOOSE YOUR PRIORITY
When to Choose Slither vs. Securify2
Slither for Speed
Verdict: The clear choice for rapid, iterative development. Strengths: Slither is a Python-based static analyzer that executes in seconds, making it ideal for integration into CI/CD pipelines (e.g., GitHub Actions). Its speed allows for scanning on every commit without slowing down development cycles. It provides a wide range of detectors out-of-the-box for common vulnerabilities like reentrancy, integer overflows, and access control issues. Trade-off: While fast, its analysis is less formal than Securify2's, potentially missing more complex, context-dependent vulnerabilities. It's a superb first-line defense.
Securify2 for Speed
Verdict: Not the primary choice for speed-first workflows. Strengths: Securify2 employs a more rigorous, Datalog-based semantic analysis. This process is inherently slower, often taking minutes per contract, as it builds a complete dependency graph to check compliance with security patterns. It's less suited for pre-commit hooks but valuable for scheduled, in-depth audits. Key Metric: Analysis time scales with contract complexity, not just lines of code.
verdict
THE ANALYSIS
Final Verdict and Decision Framework
Choosing between Slither and Securify2 requires understanding their core architectural trade-offs and how they align with your security review process.
Slither excels at providing deep, actionable insights for experienced auditors because of its powerful intermediate representation (SlithIR) and extensive suite of built-in detectors. For example, its vulnerability detection rate for complex reentrancy patterns is exceptionally high, and its ability to generate inheritance graphs and data-dependency reports is unmatched. Its integration into the Foundry toolkit and support for custom detector development via Python make it the go-to for teams building a continuous, automated security pipeline.
Securify2 takes a different approach by prioritizing formal verification methods and a more accessible, web-based interface. This results in a tool that is excellent for catching subtle logical flaws specified by security properties but can be less intuitive for writing custom checks compared to Slither's Python API. Its strength lies in its ability to formally prove the absence of certain vulnerability classes, providing higher confidence for specific, well-defined properties within a contract.
The key trade-off: If your priority is developer experience, deep custom analysis, and integration into a CI/CD pipeline, choose Slither. It is the definitive tool for teams who want to write custom detectors and automate complex security reviews. If you prioritize formal verification for critical properties and a more guided, out-of-the-box scanning experience, choose Securify2. It is particularly strong for projects seeking to prove the absence of specific flaws before a mainnet audit.
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