10 Best AI Tools for Smart Contract Threat Detection in 2026

The Best AI Tools for Smart Contract Threat Detection will be covered in this article, with an emphasis on cutting-edge platforms that assist in locating security threats, suspicious activity, and vulnerabilities in blockchain applications.

These AI-driven solutions safeguard smart contracts from fraud, exploitation, and new cyberthreats in contemporary Web3 ecosystems by combining code analysis, threat intelligence, and real-time monitoring.

Benefits Of AI Tools for Smart Contract Threat Detection

Detection Before Problems Occur: Tools saves the client from problems such as re-entrancy, overflows, and deficits in access control by detecting the problems before the code is fully formed. This saves expensive removals of problems that occur only after the contract is activated.

Security Evaluation that is Automated: AI helps analyze code and evaluate the security in a way that takes less time than the manual process and will be more uniform. Additionally, less people will be tied to this process.

Identification of Problems while it is Occuring: AI has the capacity to understand both good and bad behaviors. In the case of problems, AI would be able to alert the user by detecting an exploit that is occurring, as well as abuse attempts.

Negligence Minimalization: AI uses machine learning and can identify patterns in a way that provides gaps to the problem that would otherwise be overlooked during the manual review.

Adaptability to Convoluted Contracts: Complex and time-consuming Smart Contracts are better analyzed by AI as it would be more difficult for an analyst to do.

The Lessening of the Time taken to Spot an Issue: The financial and reputational damages are lessened by the quicker detection of bad scenarios from AI.

Richer Regulation and Risk Management: Keeping security logs that are ready for an audit, lessening the chances for a bad activity, and flagging a transaction that is high risk helps AI to keep a greater regulation and less risk.

Unceasing Protection in case the threat has been Enhanced: AI is not limited to single reviews and audits. AI is able to review the Smart Contracts in a adjustable format. This is a good thing, considering the danger changed with time, and depended on the time of the contracts.

Key Point & Best AI Tools for Smart Contract Threat Detection List

Platform	Key Points
MythX (ConsenSys)	Automated smart contract security analysis, integrates with developer workflows, supports multiple languages, scalable for large codebases, provides vulnerability reports.
Slither AI (Trail of Bits)	Static analysis tool for Solidity, fast and precise vulnerability detection, detects security and code quality issues, open-source with AI enhancements, integrates with CI/CD pipelines.
Manticore AI	Symbolic execution engine for smart contracts, identifies edge-case vulnerabilities, supports Ethereum and binaries, automated testing and fuzzing, useful for deep security analysis.
Chainsight AI	Monitors blockchain activity in real-time, AI-driven risk detection, fraud and anomaly detection, compliance-focused, supports multiple chains.
TRM Labs	Blockchain analytics platform, transaction monitoring, fraud and risk detection, AI-powered insights, regulatory compliance support, real-time alerts.
Nansen AI Security	On-chain analytics and threat intelligence, detects suspicious smart contract behavior, wallet labeling, portfolio risk monitoring, supports DeFi security operations.
Elliptic Navigator	Blockchain monitoring for compliance, AI-based risk scoring, transaction tracing, AML and fraud detection, multi-chain coverage.
Chainalysis KYT + Reactor	Real-time transaction monitoring, AI risk scoring, compliance and investigation tools, anti-money laundering focus, integrates with exchanges and wallets.
Halborn AI Security	End-to-end smart contract auditing, AI-assisted vulnerability detection, penetration testing, threat modeling, advisory services.
PeckShield AI	Real-time smart contract and wallet monitoring, threat intelligence, fraud detection, DeFi ecosystem monitoring, AI-driven alerts.

1. MythX (ConsenSys)

MythX is a smart contract security analysis service created by ConsenSys and specializes in Ethereum Virtual Machine (EVM) bytecode and source code.

They use a variety of analyses including static, dynamic, and symbolic to discover vulnerabilities like integer overflows, re-entrancy, and unprotected functions prior to smart contracts being deployed.

MythX has automated security testing embedded in early steps of product development in tools like Remix and VS Code, as well as in CI/CD workflows.

While MythX’s early tools begin being replaced by newer ConsenSys Diligence tools, MythX’s recent detailed scans and sophisticated reports of vulnerabilities continue to influence smart contract security practices.

MythX (ConsenSys) Features, Pros & Cons

Features

1. Automated evaluation of smart contracts
2. Merges static, dynamic, and symbolic evaluation
3. Multi-format (Solidity/EVM bytecode) support
4. IDE and CI/CD integration
5. Detailed analysis of potential risks

Pros

1. Provides extensive coverage during scans.
2. Integrates seamlessly with developer processes.
3. Provides a high level of precision regarding recognized classes of vulnerabilities.
4. Practical findings with suggestions to address the issues.
5. Functions both at the source and bytecode levels.

Cons

1. Evaluation of large contracts may be time-consuming.
2. False positives occur occasionally.
3. Mainly focuses on EVM ecosystems.
4. Some competition may have a more modern UI/UX.
5. To obtain all features, consumers must upgrade to a paid tier.

2. Slither AI (Trail of Bits)

Slither, from Trail of Bits, is a static analysis framework for both Solidity and Vyper smart contract code that can spot issues and anti-patterns without needing to execute them.

The software’s Python based engine is equipped with 90 or more, individual programmed, vulnerability detectors to help developers scan for issues and ridded bad code constructs. Slither offers various outputs including CI/CD pipeline reports.

His reports, along with their various other outputs, add huge visual components to help building systems like Hardhat. Slither’s static analysis approach greatly demonstrates speed and efficiency, assists in catching issues in early development cycles, and helps increase secure coding practices prior to deployment. 

Slither AI (Trail of Bits) Features, Pros & Cons

Features

1. Rapid evaluation of statics
2. 90+ code problem detectors
3. Engine based on Python
4. Hardhat/Truffle integration
5. Reports on visual vulnerability.

Pros

1. Provides an impressive evaluation rate.
2. Identifies different types of vulnerabilities and assesses the code quality.
3. Provides open access with no additional costs.
4. CI/CD integration.
5. Extensions made by the community.

Cons

1. No dynamic execution, only static analyses.
2. Needed code developer experience.
3. Only supports the code of Solidity/Vyper.
4. There are no runtime flow simulations.
5. Possible need for custom guidelines for more complex situations

3. Manticore AI

Manticore is a smart contract testing tool that offers both symbolic execution and dynamic analysis. Manticore allows developers and auditors to evaluate all potential execution paths of a contract.

It issues symbolic inputs and monitors contract activity to expose weaknesses that may only occur in particular scenarios. Manticore’s ability to model various states and behaviors helps identify edge-case reasoning errors and gaps in security.

This is particularly useful in sophisticated contracts where static analysis may fall short. While not explicitly labeled as “AI”, the sophisticated exploration of paths employs smart heuristics and provides deeper insights into threats than conventional systems.

Manticore AI Features, Pros & Cons

Features

1. Symbolic execution engine
2. Path exploration that is dynamic
3. Ethereum contracts and binaries are supported.
4. Edge state test case generation.
5. Offers reports with execution traces.

Pros

1. Vulnerability deep discovery.
2. Logical edge-case flaws.
3. Unanticipated code paths discovery.
4. Complex contract logic.
5. Actionable test input generation.

Cons

1. Extremely high learning curve
2. On large systems, it is slow
3. Real time monitoring is not available
4. Runs requiring high amounts of resources
5. User interface is not friendly

4. Chainsight AI

Chainsight AI is a blockchain threat monitoring and detection system that uses artificial intelligence to recognize threats, such as fraud, and other suspicious activity, as well as the detection of other suspicious transactions within the blockchain.

Chainsight uses behavioral analytics and machine learning to assist security professionals in the real-time detection of patterns that may indicate the existence of exploits, rug pulls, or wash trading, among other things.

This system serves both compliance and security by converting blockchain data into risk alerts with varying levels of detail that are actionable to developers, exchanges, and DeFi protocols in order to mitigate risks on multiple blockchains. 

Chainsight AI Features, Pros & Cons

Features

1. Monitoring blockchain in real-time
2. Detects anomalies and fraud
3. Pattern recognition using AI
4. Supports multiple blockchains
5. Behavioral risk assessment

Pros

1. Identifying suspicious behavior in the initial phases
2. Identifying threats as they arise
3. Compatible with multiple blockchains
4. Adaptive machine learning
5. Assist in the operational security of the blockchain

Cons

1. No code analysis
2. Instances of false positives
3. Thresholds need custom adjustment
4. Event ingestion needs data engineering
5. Documentation is hard to find

5. TRM Labs

TRM Labs provides sophisticated blockchain intelligence to assist organizations, law enforcement, and compliance with the detection and analysis of crypto crime.

Analyzing on-chain data to trace the movement of illicit funds, detect suspicious transactions, and instantaneously screen wallets against various risk categories is what the platforms do best.

These analyses aid in the visualization of transaction flows and the identification of potential threats to aid in anti-money laundering (AML) compliance, risk scoring, and forensic analysis.

Although TRM’s primary objective is to detect fraud and crime, rather than scanning for contract vulnerabilities, the TRM AI-enhanced analytics assists in securing the wider blockchain ecosystem by recognizing patterns related to hacking and other illicit activities.

TRM Labs Features, Pros & Cons

Features

1. Analytics and forensics in blockchains
2. Tracing of illicit fund flows
3. Scoring wallets/transactions for risk
4. Tools for compliance and anti-money laundering
5. Web UI + API access

Pros

1. Excellent for threat investigations
2. Strong compliance support
3. Clear visualization of flows
4. Integrates with security workflows
5. Broad chain coverage

Cons

1. Focused more on compliance than dev security
2. Licensing cost can be high
3. Not designed for static code scanning
4. Setup and onboarding can be heavy
5. Alert tuning may be needed

6. Nansen AI Security

Nansen offers a suite of leading blockchain analytics and intelligence tools. It integrates on-chain data and artificial intelligence for real-time analytics of wallet behaviors, asset flows, and market shifts.

Nansen uses a proprietary database that contains labeled wallets and hundreds of millions of entities to recognize and analyze patterns that are suspicious, divergent smart money flows, and other entities that could present risk.

For security teams, Nansen’s analytics help monitor DeFi protocols, track abnormal contract interactions, and understand threat signals before they escalate. Its AI components accelerate pattern recognition and cross-chain anomaly detection, turning raw blockchain data into actionable security intelligence.

Nansen AI Security Features, Pros & Cons

Features

1. On-chain analytics
2. Wallet labeling & profiling
3. Risk detection signals
4. DeFi activity insights
5. AI pattern recognition

Pros

1. Rich behavioral context for wallets
2. Helps detect exploiter patterns
3. Strong analytics dashboard
4. Cross-chain support
5. Market & security signals combined

Cons

1. Not a dedicated vulnerability scanner
2. Premium pricing
3. Requires understanding of metrics
4. Alerts sometimes high-level
5. Less focused on bytecode issues

7. Elliptic Navigator

Elliptic Navigator is part of Elliptic’s blockchain analytics suite that provides real-time transaction monitoring and risk assessment across multiple blockchain networks.

Navigator aids the compliance and security teams in the automation of risk scoring and alerting for illegal or high-risk transactions. It can identify suspicious activities that involve money laundering, sanctions evasion, and fraud.

Users can focus on other tasks as the analytics engine assesses transactions in real-time and helps in the identification of potential risks and the reduction of manual reviews.

Safeguarding protocols and assets against exploitation and financial crime may not be a smart contract vulnerability scanner, but Navigators risk detection on-chain behavior helps to protect smart contracts. 

Elliptic Navigator Features, Pros & Cons

Features

1. Risk scoring for transactions
2. Real-time monitoring
3. Wallet reputation insights
4. AML compliance toolkit
5. Multi-chain tracing

Pros

1. Trusted analytics for compliance
2. Good at detecting illicit flows
3. Alerts for suspicious activity
4. Useful for exchanges & protocols
5. Powerful visualization tools

Cons

1. More of a compression “scanner” not an actual threat scanner
2. More compliance than dev focus
3. Costs based on usage so the price goes up as you use it more
4. More integration effort may be needed
5. Less suited for smaller dev teams

8. Chainalysis KYT + Reactor

Real-time transaction monitoring, as well as the capability for in-depth analysis of illegal fund flows on the blockchain, is offered by Chainalysis KYT (Know Your Transaction) and Reactor tools.

Using machine learning and heuristics, KYT scores transactions and flags high-risk ones; Reactor provides a visual representation of the networks of funds and actors, which helps with the analysis.

These tools help security and compliance analysts identify exploitation, hacking, or erroneous contract use over a single chain or several. These tools provide smart contract and blockchain application security incident detection and response.

Chainalysis KYT + Reactor Features, Pros & Cons

Features

1. Transaction monitoring in real-time (KYT)
2. Deep dive analysis (Reactor)
3. Provides risk score on addresses
4. Clustering and labeling of entities
5. API and dashboard availability

Pros

1. Best in market blockchain intelligence
2. Forensics are solid
3. Works with exchanges and wallets
4. Alerts on hacking/exploit flows
5. Good support on compliance with regulations

Cons

1. No smart contract scanner
2. Pricing for enterprise is steep
3. Analysts have a steep learning curve
4. Relies on external data
5. Doesn’t do much for closing the code gaps

9. Halborn AI Security

Halborn provides AI-integrated smart contract auditing, penetration testing, and threat modeling services as a part of its complete blockchain security services.

Their integrated model combines human judgement with advanced tools of AI assisted code analysis and simulations to detect problems and mitigate insecure development methods.

Halborn also combines policy and transaction monitoring layers that are AI integrated and simulate contract behaviors to detect and block unapproved changes.

The combination of automated and manual processes works to give projects an improvement to their smart contract security and decrease their risk exposure. 

Halborn AI Security Features, Pros & Cons

Features

1. Audits with AI assistance
2. Testing for penetration
3. Modeling threats
4. Advisory and training
5. Workflows for security that are customized

Pros

1. Good combo of human and AI
2. Good reputation for audits
3. Good risk assessments
4. Good use of new AI tools
5. Good for enterprise level projects

Cons

1. Involves engagement fees
2. Not fully automated
3. Each project’s complexity can affect the result
4. Delays are possible for things to be done
5. Pricing is not transparent

10. PeckShield AI

PeckShield AI focuses on real time threat intelligence and monitoring of blockchain ecosystems, using machine learning to review on-chain activities and contract behavior.

It analyzes transactions of dubious wallets, identifies patterns of exploitation, and provides warnings of potential threats or fraudulent activities.

The AI-based insights from PeckShield assist developers and security specialists in the early detection of probable exploitation and in the analysis of possible attack vectors that pose risk to smart contracts.

While the primary focus is on monitoring threats and protecting the ecosystem, PeckShield complements vulnerability scanning with consistent monitoring of active contracts. 

PeckShield AI Features, Pros & Cons

Features

1. Monitoring and alerts in real-time
2. Threat intelligence feeds
3. Fraud/exploit detection patterns
4. Scoring risk of a wallet
5. Behavior analysis

Pros

1. Quick detection of exploits
2. Advanced dashboards for alerts
3. Coverage of a wide variety of chains and protocols
4. Threat feeds from the community.
5. Benefits for operational and security teams

Cons

1. Not a dedicated static analyzer
2. May require custom filters
3. Requires time for tuning alerts
4. Signal interpretation is required by teams
5. Enterprise tier has some features locked

Conclusion

In conclusion, AI-driven systems that include automated analysis, behavioral monitoring, and advanced analytics have greatly improved the state of smart contract security.

While Chainsight AI, TRM Labs, Nansen AI Security, and Elliptic Navigator offer thorough threat intelligence and transaction monitoring, platforms like MythX (ConsenSys), Slither AI, and Manticore AI concentrate on identifying code-level vulnerabilities.

End-to-end security is ensured by tools like Chainalysis KYT + Reactor, Halborn AI Security, and PeckShield AI bridge audit, compliance, and real-time risk detection. When combined, these AI technologies enable developers, auditors, and businesses to proactively detect and reduce risks, protecting the dependability and integrity of blockchain ecosystems.

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