Acutis

Acutis is a real-time formal verification layer for the code that AI coding assistants generate. It runs inside the assistant’s workflow and checks each piece of code the moment it is written – before it reaches the developer or enters the codebase – returning a clear verdict (allow or block with a precise reason and remediation guidance) together with a machine-readable proof. Rather than matching against libraries of known-bad patterns the way conventional scanners do, Acutis has the AI declare the security-relevant behavior of the code it just wrote, then independently and deterministically verifies those declarations. Anything it cannot prove safe is blocked. It integrates through the Model Context Protocol (MCP), works across multiple programming languages, and needs no rule packs, signatures, or per-framework configuration to maintain.

In internal evaluation, the verification engine achieved an F1 score of 1.0 on a benchmark of known vulnerability fix paris (zero false positive, zero false negatives), and in a paired AI-agent workflow study it reduced the rate of security-relevant defects from 62.5% to 0%, a 62.5 percentage-point absolute reduction, with no functional regressions.

Background: 
AI coding assistants are now widely adopted, and the volume of AI-generated code is rising faster than human review can keep pace with. Existing software security tools with built for human-written code. AI writes code differently, syntactically correct but semantically dangerous in subtle ways, and needs verification designed for how it works. In practice, conventional static-analysis tools tend to produce high false-positive rates on AI-generated code and miss failure modes specific to it; this false-positive fatigue that is a recurring issue for security teams.

Applications: 

• Security verification of AI-generated code
• AI coding assistant and agents
• Software security
• Application security / DevSecOps tooling
• Audit and compliance evidence for AI-assisted software development
• AI code security verification

Advantages: 

• Zero enumeration, Zero Trust, and Zero heuristic
• Runs inside the AI’s loop, so flagged issues are resolved before a developer ever sees them
• Proves code safe at the point of generation – a gate the output must pass, not an after-the-fact alarm; anything it cannot prove safe is blocked before it enters the codebase
• Deterministic formal verification with a machine-readable proof for every decision – designed to serve as audit / compliance evidence
• No rule packs, signatures, or patterns to configure or update – supports new frameworks from day one
• Works across multiple programming languages and with any MCP-compatible AI assistant
• Better security of AI generated code
• Real time vulnerability blocking