#llmsmap.me

Independent technical audit

enforster.ai

enforster.ai

Overall AI readiness score

A combined result across all audit signals.

85of 100Excellent
AI readiness audit: 8/5/2026Public technical data

Overall AI readiness assessment

How ready enforster.ai is for AI systems

85/100

Enforster AI - AI-Powered Code Security Platform (enforster.ai) received an AI-readiness score of 85/100 in an automated technical audit. llms.txt was accessible, llms-full.txt was accessible, and ai.txt was not found. The robots.txt analysis found 4 explicitly allowed and 3 blocked AI crawlers, with 2 declared sitemaps. Homepage markup completeness was 90%; Schema.org types included SoftwareApplication, WebSite and 11 OpenGraph tags were detected. Results reflect the public site response observed on 2026-08-05T00:06:14.044Z.

Audit context

llms.txt is accessible and contains 1,017 tokens. An expanded llms-full.txt is also available with 1,586 tokens, giving agents more direct context. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.

robots.txt is available. 8 of 11 tracked AI bots are not blocked, while 3 receive a prohibition. Declared sitemaps: 2. The homepage exposes Schema.org types SoftwareApplication, WebSite; 11 OpenGraph tags were found and markup completeness is 90%.

The mobile Lighthouse profile adds Performance 66/100, Accessibility 93/100, Best Practices 96/100, SEO 100/100, and experimental Agentic Browsing 67/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.

Confirmed strengths

  • Accessible llms.txt
  • Expanded llms-full.txt
  • 2 sitemap declarations
  • Schema.org: SoftwareApplication, WebSite
  • Complete social metadata

Priority improvements

  1. 1Review the 3 explicit AI-bot blocks and keep only intentional restrictions.
  2. 2Reduce mobile rendering delay and main-thread work.
llms.txt tokens1,017
llms-full.txt tokens1,586
ai.txt
sitemap.xml

Google Lighthouse technical profile

A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.

Mobile · Lighthouse
66

Performance

93

Accessibility

96

Best Practices

100

Technical SEO

67

Agentic Browsing

What these results mean

Mobile performance is 66/100, with the largest visible content block appearing in 6.1 s and the browser main thread blocked for 140 ms. Layout shift was 0. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.

Accessibility scored 93/100, Best Practices 96/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 67/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.

1

Reduce code that loads without helping the page

Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.

2

Reduce network delay

Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.

3

Make controls unambiguous

Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.

4

Improve interface contrast and readability

Increase contrast for text, states, and interactive controls so both people and visual agents can distinguish content from actions and supporting labels.

FCP3.5 s

First content

LCP6.1 s

Main content

CLS0

Layout stability

TBT140 ms

Blocking time

SI5.2 s

Visual speed

Metric glossary
FCP · First content
When the first text or image appeared on screen.
LCP · Main content
When the largest visible element in the first viewport rendered.
CLS · Layout stability
How much content shifted unexpectedly while loading; lower is better.
TBT · Blocking time
How long the browser main thread could not respond quickly to input.
SI · Visual speed
How quickly the visible viewport filled with content.
8/5/2026Lighthouse 13.4.1Mobile profile

AI readiness checks

Machine-readable files, crawler policy, discovery, and homepage markup.

llms.txt

File found and accessible

https://enforster.ai/llms.txt
llms-full.txt

Full version is available

https://enforster.ai/llms-full.txt
ai.txt

ai.txt file was not found

Sitemap in robots.txt2

2 sitemaps found

Schema.org (JSON-LD)

Types: SoftwareApplication, WebSite

OpenGraph90%

11 OG tags found

AI bot access

Based on robots.txt analysis

GPTBotAllowed
OAI-SearchBotNot mentioned
ChatGPT-UserAllowed
Google-ExtendedBlocked
ClaudeBotBlocked
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderBlocked
CCBotAllowed
PerplexityBotAllowed
Perplexity-UserNot mentioned

Sitemaps

Declared discovery routes for crawlers and agents.

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 90%
og:image:width1200
og:image:height630
og:image:typeimage/png
og:image:altEnforsterAI – LLM‑Powered SAST
og:titleEnforster AI – AI-Native SAST Code Security Tool | AppSec | AI Security
og:descriptionEnforster AI is an AI-native SAST code security tool that replaces traditional security tools with contextual AI scanning. Detect vulnerabilities, secrets, IaC issues, AI model security with 90% accuracy and actionable fixes.
og:urlhttps://enforster.ai/
og:site_nameEnforster AI – AI-Native SAST Code Security Tool
og:localeen_US
og:typewebsite

Schema.org markup

Structured entities and properties exposed on the homepage.

Types found: 2 · Properties: 10
SoftwareApplicationWebSite
nameEnforster AI – AI-Native SAST Tool
urlhttps://enforster.ai/
descriptionEnforster AI is an AI-native SAST tool that replaces Traditional Tools, CodeRabbit with contextual security scanning. Detect secrets, IaC vulnerabilities, AI model security, SBOM, license scanning with actionable AI fixes.
inLanguageen-US
authorhttps://enforster.ai
datePublished2025-07-01
dateModified2025-12-15
alternateNameEnforster AI, Enforster, enforster ai, enforsterai
potentialAction{"@type":"SearchAction","target":"https://enforster.ai/search?q={query}","query-input":"required name=query"}
publisherhttps://enforster.ai/
# Enforster AI - AI-Powered Code Security Platform

Enforster AI is an AI-native Static Application Security Testing (SAST) platform that revolutionizes code security by understanding your codebase like a senior developer. It leverages advanced machine learning models to detect sophisticated security vulnerabilities that traditional rule-based tools miss.

## What is Enforster AI?

Enforster AI is a comprehensive AI-powered security platform that provides intelligent code analysis, vulnerability detection, and automated remediation across multiple security domains. It uses Large Language Models (LLMs) to understand code context, business logic, and intent, delivering 90% detection accuracy with 60% fewer false positives compared to traditional SAST tools.

## Key Features

- **AI Code Scanning**: Neural network analysis with 90% detection accuracy for complex vulnerabilities
- **Secret Detection**: Advanced pattern recognition to identify hardcoded credentials and sensitive data
- **Infrastructure Security**: IaC scanning for Terraform, Kubernetes, Docker, and CloudFormation
- **SBOM Analysis**: Software Bill of Materials analysis for dependency vulnerability management
- **License Compliance**: Open source license compliance and risk assessment
- **AI Model Security**: Protection against adversarial attacks and LLM-generated security flaws
- **Cross-IDE Compatibility**: Works with Cursor, Windsurf, VS Code, and other VS Code-compatible editors
- **35+ Programming Languages**: Comprehensive support including Java, TypeScript, Python, PHP, Ruby, Go, Rust, Swift, and more

## Advantages Over Traditional SAST Tools

- **90% Detection Accuracy** → Traditional tools miss complex vulnerabilities and business logic flaws
- **60% Fewer False Positives** → AI-driven contextual analysis reduces noise and false alerts
- **Real-time AI Analysis** → LLM-powered scans complete in minutes, not hours like traditional tools
- **Comprehensive Coverage** → Detects 10,000+ vulnerability types across code, infrastructure, and AI models
- **AI-Generated Fixes** → Actionable remediation guidance with contextual security recommendations

## Security & Privacy

- Uses zero data retention
- Code is encrypted in transit using TLS 1.2+ and never stored and never used for training
- No information kept, no copies made
- Full version history lives on your machine, not in the cloud
- Offers On Prem

## Pricing

Free tier available with generous limits. Pro and Team plans are also available.

## Installation

Enforster AI is available as SaaS at https://app.enforster.ai and On-prem can be installed via sales support.





## Use Cases

Perfect for development teams and security professionals who:
- Need comprehensive security analysis across their entire codebase
- Want to identify vulnerabilities before they reach production
- Require fast, accurate security scanning with minimal false positives
- Work with multiple programming languages and need unified security analysis
- Want AI-generated remediation guidance for identified vulnerabilities
- Need to meet compliance requirements and security standards
- Want to integrate security scanning into their development workflow

## Technical Details

- **Vulnerability Detection**: Limitless vulnerability types including OWASP Top 10, business logic flaws, and API security issues
- **Language Support**: 35+ programming languages including Java, TypeScript, Python, PHP, Ruby, Go, Rust, Swift, Vue.js, Scala, Perl, C#, JavaScript, C++, C, Kotlin, Dart, R, Lua, Haskell, Clojure, Elixir, and F#
- **Cross-platform**: SaaS and On-Prem
- **AI Integration**: Compatible with major AI coding tools and CLIs
- **Performance**: Scans complete in minutes with 90% detection accuracy

## Contact

- Website: https://enforster.ai
- Feedback: https://tally.so/r/wo8jkx

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This file is provided to help AI systems understand Enforster AI's purpose, features, and value proposition as an AI-powered Static Application Security Testing (SAST) platform for development teams and security professionals.
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Added 8/5/2026
enforster.ai - AI readiness audit | llmsmap.me