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🗝️ Built for Security Operations

Log Analyzer AI is the security analysis platform built specifically for threat detection and compliance. While traditional log analysis tools force you to write complex queries and wade through millions of irrelevant entries, we use AI trained on security patterns to surface real threats instantly.

⚡ Automated Threat Detection
Expert-built detection profiles identify authentication attacks, privilege escalation, malware indicators, and data exfiltration—without manual query writing.

🎯 Security Expertise Built-In
Each detection profile encodes years of SOC analyst knowledge, so you get expert-level threat detection from day one.

Learn More About Security Detection
our-mission-icon⭐ our mission

Democratize enterprise-grade security threat detection.

Every organization—from startups to enterprises—deserves SOC-level threat detection without SOC-level costs. We're making AI-powered security analysis accessible, automated, and actionable for teams of any size.


our-vision-icon🔍 our vision

A world where security breaches are detected in minutes, not months.

Traditional security tools generate alerts. We generate answers. By combining AI's analytical power with expert-built security detection profiles, we're redefining how fast and accurately organizations can identify and respond to threats.

💹 proven results
  • ⚡ 95% reduction in log analysis time vs. manual review
  • 🎯 5 minutes average time to detect authentication attacks
  • 📊 Days to hours compliance audit prep time reduced
  • 💰 98% cost savings vs. traditional SIEM solutions
  • 🔒 Analyze ~30–60 standard log files per month (1 GB) by security teams

⚔️ Security Detection Capabilities

Expert-built detection profiles that identify real threats instantly

🗝️
Authentication Anomalies

Detect brute force attacks, credential stuffing, impossible travel, and account compromise in real-time.

  • ✓ Failed login patterns
  • ✓ Password spraying
  • ✓ Unusual locations
  • ✓ Session hijacking
Privilege Escalation

Identify unauthorized privilege changes, lateral movement, and insider threats.

  • ✓ Unauthorized sudo usage
  • ✓ Permission changes
  • ✓ Group membership changes
  • ✓ Service account abuse
🔔
Data Exfiltration

Catch unauthorized data access, bulk downloads, and sensitive file transfers.

  • ✓ Large data transfers
  • ✓ Off-hours access
  • ✓ Unusual file access
  • ✓ External destinations
☣️
Malware & Intrusion

Identify command & control communication, malicious processes, and intrusion attempts.

  • ✓ Suspicious processes
  • ✓ C2 communication
  • ✓ Network anomalies
  • ✓ Exploit attempts

Plus scheduled security scans, webhook alerts, compliance reporting, and more...

Detect Threats Now → View All Detection Profiles

🔄 NEW: Automated Repository Monitoring

Set it and forget it—continuous security monitoring for your cloud storage and repositories

☁️
Connect Your Repositories

Automatically fetch log files from AWS S3, Azure Blob Storage, GitHub, SFTP servers, or Google Drive. No manual uploads required.

  • ✓ AWS S3 buckets
  • ✓ Azure Blob Storage
  • ✓ GitHub repositories
  • ✓ SFTP servers
  • ✓ Google Drive folders
Schedule Automated Scans

Configure daily, weekly, or monthly security scans. New log files are automatically analyzed and you receive instant alerts for threats.

  • ✓ Flexible scheduling (daily/weekly/monthly)
  • ✓ Automatic file fetching
  • ✓ Real-time threat detection
  • ✓ Email & webhook alerts
📊
Track Everything

Complete audit trail of all scans, findings, and repository sync operations. Perfect for compliance and security operations.

  • ✓ Execution history & logs
  • ✓ Success/failure tracking
  • ✓ Repository sync status
  • ✓ Compliance-ready reports

🚀 Zero-Touch Security Monitoring: Connect once, monitor forever. Your logs are automatically analyzed on schedule—no manual intervention required.

Set Up Automated Monitoring →

⚔️ Why Security Teams Choose Log Analyzer AI

Designed for security teams who can't afford to miss threats

Log Analyzer AI is built specifically for security teams, compliance managers, and DevSecOps engineers who need fast, accurate threat detection without the complexity and cost of traditional SIEM solutions. Whether you're responding to incidents, preparing for audits, or proactively hunting threats, Log Analyzer AI delivers enterprise-grade security analysis at a fraction of the cost.

💨 DETECT THREATS 95% FASTER

Manual log review takes days. Our AI analyzes millions of lines in minutes, surfacing critical threats while your team focuses on response.

From: Days of manual grep/awk → To: 5-minute AI analysis

⭕ CATCH WHAT SIEMS MISS

Traditional SIEMs only find what you configure them to find. Our AI understands context and identifies novel attack patterns without manual rule creation.

From: 60% detection rate → To: 95%+ detection with AI pattern matching

📊 INSTANT COMPLIANCE REPORTING

Structured findings with severity levels make audit preparation effortless. Generate compliance reports in minutes, not days.

From: 40 hours audit prep → To: 2 hours with automated reports

💵 ENTERPRISE SECURITY AT SMB PRICING

Get SOC-level threat detection without hiring SOC analysts. Starting at $15/month—98% less than traditional SIEM solutions.

From: $50K/year SIEM costs → To: $180-$1,188/year

⚙️ ZERO INFRASTRUCTURE REQUIRED

No agents to deploy. No log collectors to maintain. No complex configuration. Upload logs and get security insights immediately.

From: 3-6 month implementation → To: 5-minute setup

🔒 SECURITY EXPERTISE INCLUDED

Each detection profile encodes years of SOC analyst knowledge. Get expert-level threat detection from day one—no security PhD required.

From: Hiring $120K/year SOC analyst → To: Built-in AI expertise

🔄 AUTOMATED REPOSITORY MONITORING

Connect AWS S3, Azure, GitHub, SFTP, or Google Drive. Automatically fetch and analyze new log files on schedule—zero manual uploads.

From: Manual daily uploads → To: Fully automated continuous monitoring

⭐ Real-World Security Scenarios

Typical use cases where Log Analyzer AI helps security teams detect and respond to threats

🗝️
Brute Force Attack Detection

A financial services company needs 24/7 monitoring for authentication attacks. Log Analyzer AI detects 47 failed login attempts from a single IP address within 5 minutes and sends instant alerts.

Threat: Brute Force Attack

Detection Time: 5 minutes

Impact Prevented: Account compromise, data breach

👥
Insider Threat Detection

A healthcare provider catches a terminated employee's credentials being used to access patient records. Traditional SIEM classified it as "normal" login activity, but AI detected impossible travel and unusual access patterns.

Threat: Insider Threat / Credential Theft

Detection Time: 12 minutes

Impact Prevented: HIPAA violation, regulatory fines

📋
SOC 2 Compliance Audit

A SaaS startup preparing for SOC 2 audit uses automated security findings with severity levels to demonstrate continuous monitoring and threat detection capabilities.

Challenge: SOC 2 Compliance

Time Saved: 38 hours (40 hrs → 2 hrs)

Outcome: Clean audit, accelerated certification

These are typical use case scenarios demonstrating Log Analyzer AI's capabilities in real-world security operations.

Frequently Asked Questions

Security & Threat Detection

Log Analyzer AI can detect a wide range of security threats including: authentication attacks (brute force, credential stuffing, impossible travel), privilege escalation (unauthorized sudo usage, permission changes), data exfiltration (unusual data transfers, off-hours access), malware indicators (suspicious processes, C2 communication), intrusion attempts, lateral movement, and insider threats. Our expert-built detection profiles identify these patterns automatically without requiring complex query writing.

Our AI achieves 95%+ detection accuracy compared to 60% for traditional rule-based SIEMs. The key difference is that we understand context and identify novel attack patterns that traditional signatures miss. Our AI learns from security patterns across millions of log files, allowing it to catch zero-day threats and sophisticated attacks that evade static rules. Plus, our false positive rate is under 5%, dramatically reducing alert fatigue.

Yes. We provide audit-ready reports with structured findings and severity levels (CRITICAL/HIGH/MEDIUM/LOW). Many customers use Log Analyzer AI for compliance evidence during SOC 2, HIPAA, PCI-DSS, and other audits. Our automated reporting demonstrates continuous security monitoring and threat detection capabilities, which are required by most compliance frameworks. We also offer end-to-end encryption and a zero data retention policy to protect your sensitive log data.

Yes. Professional and Enterprise tiers include webhook alerts and API access for seamless integration with Splunk, Elastic, QRadar, PagerDuty, Slack, Microsoft Teams, and custom SOAR platforms. You can forward our threat detections to your existing security stack, enriching your SIEM data with AI-powered threat intelligence. Many customers use us as a "second opinion" layer that catches threats their primary SIEM misses.

Log Analyzer AI starts at $15/month (98% less than enterprise SIEM). Our Enterprise tier at $99/month still costs 99% less than Splunk, LogRhythm, or QRadar. Traditional SIEMs charge $50K-$200K+ annually, require dedicated infrastructure, and need security analysts to maintain complex rules. We provide enterprise-grade threat detection with built-in security expertise at a fraction of the cost, with zero infrastructure and 5-minute setup.
🔄 Automated Repository Monitoring

Automated Repository Monitoring allows you to connect your cloud storage or version control systems directly to Log Analyzer AI. Instead of manually uploading log files, the system automatically fetches new files from your repositories on a schedule (daily, weekly, or monthly) and analyzes them for security threats. Supported repositories include AWS S3, Azure Blob Storage, GitHub, SFTP servers, and Google Drive. This provides continuous, zero-touch security monitoring for your infrastructure.

Setting up repository monitoring is simple: (1) Navigate to Schedule Scan page, (2) Click "Connect a repository", (3) Select your repository type (S3, Azure, GitHub, SFTP, or Google Drive), (4) Enter your credentials (encrypted and stored securely), (5) Configure the file path and pattern (e.g., *.log), (6) Set your sync interval. The system will test the connection and begin automatically fetching files on your schedule. All credentials are encrypted using AES-256 and never stored in plain text.

Yes! You can create scheduled security scans that run daily, weekly, or monthly. When combined with repository monitoring, this provides fully automated continuous security monitoring. The system will: (1) Automatically fetch new log files from your repository, (2) Analyze them using your selected detection profile, (3) Send email and webhook alerts for any threats detected, (4) Maintain a complete audit trail of all scans and findings. This is perfect for compliance requirements and 24/7 security operations without manual intervention.

Absolutely. We take security seriously: All repository credentials are encrypted using AES-256 encryption before storage. Credentials are never logged or exposed in error messages. We use read-only access whenever possible—we never modify or delete files in your repositories. Downloaded files are analyzed and then deleted according to your retention policy. All connections use TLS/SSL encryption in transit. We also provide connection testing before saving credentials to ensure everything works correctly.

The system includes comprehensive error handling and monitoring: Automatic retry logic with exponential backoff for transient failures. Detailed error logging in the execution history showing exactly what went wrong. Email notifications for persistent failures so you're always aware. Repository sync status tracking showing last successful sync, error messages, and next scheduled sync. Complete audit trail of all execution attempts for compliance and troubleshooting. You can view the full history and status of all scheduled scans and repository syncs from your dashboard.
General Questions

Log Analyzer AI is an AI-powered security threat detection platform designed to analyze log files for security threats, compliance, and operational insights. It uses advanced algorithms and expert-built detection profiles to identify authentication attacks, privilege escalation, data exfiltration, malware indicators, and more—without requiring complex query writing or security expertise.

Currently, Log Analyzer AI supports all common file formats.

Text and Log Files
.log: A plain text file used to store log data generated by software applications. Often contains a chronological record of events, errors, and other significant occurrences.
.txt: A simple text file that contains unformatted text. It’s widely used for basic text storage and documentation.
.csv: Comma-Separated Values file used to store tabular data in plain text format, where each line represents a row, and fields are separated by commas.
.tsv: Tab-Separated Values file similar to CSV but uses tabs instead of commas to separate fields.

Document and Spreadsheet Files
.docx: Microsoft Word document file used to create and edit text documents with rich formatting.
.pdf: Portable Document Format file used for presenting documents in a manner independent of software, hardware, or operating systems. It’s widely used for sharing documents.
.rtf: Rich Text Format file used for text documents that include formatting information, such as bold, italics, and font size.
.xls / .xlsx: Microsoft Excel spreadsheet files used to store and analyze tabular data. .xls is the older binary format, while .xlsx is the newer XML-based format.

Image Files
.jpg / .jpeg: Image files using the JPEG format, which is commonly used for photographic images due to its compression capabilities.
.png: Portable Network Graphics file used for images. It supports lossless compression and is commonly used for web graphics with transparent backgrounds.

Script and Batch Files
.sh: Shell script file used to write scripts for Unix and Linux systems. It contains commands that can be executed in the shell.
.bat: Batch file used in Windows to automate command-line tasks. It contains a series of commands to be executed by the command interpreter.
.ps1: PowerShell script file used to write scripts in the PowerShell language, often for automating administrative tasks on Windows.

Markup and Data Files
.html / .htm: HyperText Markup Language file used to create and structure content on the web. .htm is an alternative extension used by older operating systems.
.xml: eXtensible Markup Language file used to store and transport data. It’s a flexible way to create information formats and share structured data.
.json: JavaScript Object Notation file used for data interchange. It’s lightweight, easy to read, and commonly used in web applications for data transmission.
.yml / .yaml: YAML Ain’t Markup Language files used for configuration and data serialization. They are human-readable and often used in configuration files for software applications.

Programming and Scripting Files
.cs: C# source code file used in .NET applications. It contains source code written in the C# programming language.
.java: Java source code file used to write applications or applets in the Java programming language.
.py: Python script file that contains code written in Python, a popular high-level programming language.
.js: JavaScript file used to write scripts that can be embedded in web pages to provide interactive functionality.
.css: Cascading Style Sheets file used to style HTML documents. It defines the visual presentation of web pages, including layout, colors, and fonts.
.sql: Structured Query Language file used to manage and manipulate databases. It contains queries for creating, reading, updating, and deleting data.
.ini: Initialization file used to store configuration settings for software applications. It’s a simple text file with a structured format of sections and key-value pairs.
.cfg / .conf: Configuration files used to store settings and preferences for software applications. They are often plain text and can be specific to a particular application.
.env: Environment file used to set environment variables for software applications. Commonly used in development environments to store sensitive information like API keys.
.pyw: Python script file similar to .py but is used to run Python programs without opening a command prompt or console window.
.pyt: Python script file often associated with Esri’s ArcGIS for custom geoprocessing tools.
.c: C source code file used to write programs in the C programming language.
.cpp: C++ source code file used to write programs in the C++ programming language.
.h / .hpp: Header files used in C and C++ programming to declare the interfaces to functions and data structures. .hpp is typically used for C++.
.php: PHP source code file used to write server-side scripts in the PHP programming language, often for web development.
.rb: Ruby source code file used to write programs or scripts in the Ruby programming language.
.ts / .tsx: TypeScript files used to write applications in TypeScript, a superset of JavaScript. .tsx files are used when working with React components.
.kt / .kts: Kotlin source code files used to write programs in the Kotlin programming language. .kts is used for Kotlin scripts.
.go: Go source code file used to write programs in the Go programming language, developed by Google.
.swift: Swift source code file used to write applications for iOS, macOS, watchOS, and tvOS.
.pl / .pm: Perl script files where .pl is a standard script file and .pm is a Perl module file.
.r: R script file used to write programs and perform data analysis in the R programming language.
.md: Markdown file used for formatting text using plain text syntax. Commonly used for README files and documentation.
.rs: Rust source code file used to write programs in the Rust programming language.
.toml: TOML (Tom’s Obvious, Minimal Language) file used for configuration. It’s designed to be easy to read and write.
.m: Source code file used by multiple programming languages. In Objective-C, it’s used to implement class files; in MATLAB, it’s used for scripts and functions.

Event Viewer Logs
.evtx: Windows Event Log file used by the Windows operating system to log system, security, and application events.

Log Analyzer AI uses sophisticated GPT-based algorithms to read and analyze the contents of your log files. It identifies patterns, anomalies, and provides comprehensive reports based on the file data.

Yes, there is a free version of the service.

To use Log Analyzer AI, simply provide your log file in the supported format by attaching it to the ‘analyze’ form. Our tool will analyze the file and provide you with a detailed report in a matter of minutes or seconds depending on the file size.

Yes, using Log Analyzer AI is completely safe and secure. We do not upload your files to our servers. Our system analyzes the data directly from the files on your device, ensuring that your sensitive information remains private and secure.

No, we do not store the files you provide for analysis. Log Analyzer AI processes files locally on your device, ensuring that your original data remains private and is not transmitted to our servers. However, to continually improve and tailor our services specifically to your needs, we do store the results of the analysis performed on your data. Please be assured that these results are used exclusively to enhance our service offerings to you and are not utilized for any other purposes.

Yes, Log Analyzer AI is designed to efficiently handle and analyze large log files.

Log Analyzer AI provides insights such as error detection, usage patterns, system performance issues, security breaches, and more, depending on the nature of your log files.

System administrators, developers, IT professionals, and anyone who needs to analyze files for troubleshooting, monitoring, and reporting purposes will find Log Analyzer AI extremely useful.

Yes, we offer customer support for Log Analyzer AI. You may open a chat or email us directly at support@loganalyzer.ai

🗝️ Trusted by Security Professionals

Enterprise-grade security analysis you can trust

🔒
End-to-End
Encryption
99.9% Uptime
SLA
🌐
GDPR & HIPAA
Compliant
🔰
Zero Data
Retention
💳
Stripe Secure
Payments
🧠
AI-Powered
Analysis

BY THE NUMBERS

200+ MB
Daily logs processed by security teams
95% Faster
Than manual log review
5 Minutes
Average threat detection time
$50K Saved
Per organization vs. traditional SIEM
98%
Cost reduction vs. enterprise SIEM
30 Days
Threat history retained (Pro tier)

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