360° IT security and monitoring, optimized for medium-sized companies.
100% self-developed Made in Germany
OUT-OF-THE-BOX Security Analyses.
You‘d probably never monitored your system so quickly before. Start directly with all relevant security analyses without configuration!
Enginsight GmbH was founded in August 2017. With a highly motivated team, Enginsight is working on the vision of providing companies with a solution that will enable them to safely and confidently navigate the digital future.
Enginsight helps leading companies autonomously monitor and secure their entire IT landscape. Certified and highly trained employees form the heart of Enginsight, together with partner companies around the globe.
Never before has it been so easy to monitor entire IT infrastructures and protect them against cyber attacks. Enginsight is based on the newest technologies and offers a maximum of automation. Convince yourself of the very impressive performance and the comprehensive feature set.
Enginsight is more than just a tool – Enginsight is a process!
With its software platform, Enginsight GmbH offers an integrated solution
for monitoring servers, websites, IoT devices and networked machines.
Enginsight intuitively combines IT monitoring, cybersecurity and penetration testing
with intelligent algorithms (neural networks) to ensure maximum automation.
Visualize IT landscape
- Visualization of servers, applications and network components
- Identification of dependencies and communication channels
- Inventory of infrastructure and software
- Documentation of all components
- Root Cause Detection
Support & Report
- Powerful API
- Generation of PDF reports
- Multi-client capability incl. role system and user management
Analysis of event logs
Eventlog analyses out-of-the-box, without preconfiguration or special use cases.
• Evaluation of event logs
• Failed login attempts
• Successful login attempts
• system events
• process events
• group events
• Dynamic Log Analysis
• Root Cause Detection (Drilldown)
• Flexible Dashboards
• Ad hoc Search
Automated attack scenarios
For each pentest, you will receive a detailed audit report. You can see at a glance where the action is needed.
By using templates, you can repeat pentests once they have been defined to verify the measures taken.
An AI-supported procedure also detects whether personal data leaves the host unencrypted.
• Intelligence Gathering
Information retrieval before an attack, e.g. which system, which version, ports, services, etc.
Our web-based discovery searches for suspect accessible files such as server configuration elements, index files, HTTP server options, etc. and attempts to identify installed web servers and software.
TCP Sequence Prediction & IP-ID Sequence Prediction:
Attack method in IP networks to simulate a different sender for the victim (IP spoofing) or to take over existing connections.
ssh, ftp, telnet, etc.
passive DDoS attack as part of the Discovery to verify server stability
Automated, plannable execution of a standardized penetration test including detailed reporting.
Finding security breaches and vulnerabilities
All vulnerabilities (CVEs) are managed by a Vulnerability Manager.
With the help of dynamic searches, all affected systems of the IT infrastructure can be identified quickly and clearly:
• External CVE scan
Security relevant information that can be obtained by observing the endpoints (URLs/IPs) from the outside, without having internal access to the systems.
• Internal CVE scan
Security relevant information that can be obtained by observing the participants within a network segment without installing agents on the devices.
• CVE scan on Hosts
Security relevant information collected directly on a host (agent installation).
• Configuration deficiencies
Detection of security-relevant configuration deficiencies that make the system vulnerable.
Detection of network attacks
The detection scenarios in network traffic and the attack possibilities of the automated penetration test are continuously expanded and adapted to current requirements.
• ARP Spoofing
• DNS Spoofing
• IP Spoofing
• MAC Spoofing
• SYN Flooding
• Hidden Services (tor, proxies, …)
• Ping of Death
• Blacklisted IPs (well known attack IPs)
• Remote Code Execution
• Cross Site Scripting
• SQL Injection
• Path Traversal
• Fake Browser Activity
• Spam Bots
Anomaly Detection with neural networks
If data is monitored autonomously, it is a matter of basic understanding of this data, which can be mapped by a neural network. And this is exactly what modern IT needs in order to deal effectively with the mass of data.
Through the AI-supported monitoring of any metrics, it is possible to automatically detect anomalies and derive future forecasts based on normal behavior.
• Eliminate manual tasks
The neural network independently takes over the parameterization for monitoring the metrics, such as CPU utilization, database sessions, http errors, etc., so that repetitive tasks on the part of the administrators are
eliminated and the quality of monitoring increases.
• Reducing False Positives
Due to the self-learning system, the admin is only informed in case of an anomaly, which reduces false alarms.
• Unencrypted Personal Data
Enginsight NexT™ detects when personal data leaves the
• Automated OS Detection
Custom Metrics and Health-Checks
• Website Monitoring
Monitoring of Website Uptime & Performance
• Location Based Monitoring
Use our predefined or your own locations to monitor the accessibility of your website from different locations.
• Host/Server Monitoring
Use Enginsight to monitor any Windows® and Linux®-based host. Monitor Standard Metrics like CPU, RAM, SWAP
• Custom Metrics
Using a standardized format, any metrics can be recorded, visualized and monitored. These can be e.g. DB requests per minute, HTTP errors or visitors to your website. All data that can be displayed in a chronological order can be recorded.
• PING, PORT, SNMP
Unlimited Health-Checks for all network devices
• Process & Service Monitoring
Monitor all running processes and services. Together with the innovative alarm system of the Enginsight platform, you can react automatically to failures.
Why hasn´t anyone done this before?
The prognosis using neural nets is very complex, especially if the net is trained extensively. An error or difference vector is calculated from a large number of runs and used as the basis for correction in the next input. For the neural networks a very high computational effort is therefore necessary, whereby the analyses of individual metrics take several minutes and are too slow for practical application in contrast to time series analyses.
But: We manage to calculate a metric within 2 minutes (see Metric Calculation). Thus the operation of our platform including the AI is already possible with a commercially available single-core PC.
RESOURCES & DOCUMENTS
Let’s talk about how we can help you drive your business transformation.
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