Human Managed app hm.works 1.10 released with dashboard on detected fraudulent behaviors


Since its first release on 13 March 2023, the Human Managed web app hm.works has been getting 

 to report on intel generated from any data source from our customers. 

 to creating intel on your digital business' assets, postures & behavior, and establishing 🔗

🔗 between them to improve your decisions and actions for many use cases. 

This week, we are excited to announce the release of a dashboard that reports on the detections of possible fraud on our customer's digital services such as online banking application. 

Our fraud dashboard reports on various fraud use cases that hm.works runs on the data generated by your services and products. 

The hm.works platform analyzes logs, metrics, traces, alerts or events from multiple data sources (e.g. transaction systems, apps, APIs, security tools, and other contextual information like consumer data) to: 

events of interest that indicate potential fraud or suspicious behaviors for use cases such as 

Identity Obfuscation, High Money Transfer, Stolen Credit Card, Address Manipulation, Account Takeover, Identity Theft, Malicious Activity, or Anomalous Activity

 previously unknown information to enrich events generated by your consumers and provide fraud intelligence feeds to detect use cases.  For example, data points such as consumers' devices, browser version, cookie preferences, etc. can be used to identify suspicious users and bots before they perform a transaction on the service. 

behavior baselines from your consumers' historical interactions and transactions with your services over time.  The profiles give context of what is 'normal' or 'expected' to enrich events and provide fraud intelligence feeds to detect use cases. 

A single page answers the top 3 things you need to know about potential fraud or malicious activity so you can speed up response actions and take proactive measures:

What fraudulent or suspicious behaviors are detected in my services and products? 

How do my consumers' behaviors deviate from their baselines over time?

What are the fraud patterns observed in my services and products across multiple use cases that I should respond to?

Fraud is an intentionally deceptive action to get an illegal advantage or to harm the victim's rights, through false representation of information. Common examples of fraud include tax fraud, credit card fraud, securities fraud, corruption, etc. 

In today's connected world, fraud involves the perpetrator using online services and software to defraud or take advantage of victims. Techniques involve identity theft, stolen card details, phishing across a supply chain of products and services to gain access to the ultimate objective. 

As customers and users' interactions with your business is increasingly digital, it's important to know what to observe in your data, what is 'normal' vs. 'abnormal' behavior, and when to take action.

Let's explore each segment of the fraud dashboard. 

 This line chart reports the number of times subscribed fraud use cases have been detected by hm.works platform over time.

📝Note: hm.mworks platform uses automated detections consisting of pre-defined conditions, correlation rules and/or machine learning algorithms to identify suspicious or malicious activities and create Detections that need to be actioned. 

 Gives you improved fraud visibility across your environment of multiple services and products, so that you can respond faster to mitigate risk and reduce business impact. 

 Forward data from your product or services (e.g. transaction system, applications, APIs, security tools, contextual information such as identity / asset / consumer data) to monitor and build fraud use cases on the hm.works platform. 


 This table lists all subscribed fraud use cases, the types of behavioral indicators that trigger the detection for each use case and the number of times the indicators are detected over a time period. 

📝Note: adetection use case is made up of conditions, correlation rules and/or machine learning algorithms applied to specific indicators (e.g. transfer amount of more than $50K) 

 Breakdown of indicators that make up each fraud use case gives a more granular understanding of the activities and behaviors observed in your environment, and allows you to investigate and take decisions on the next course of action in response to the detections.  

 Forward data from your product or services (e.g. transaction system, applications, APIs, security tools, contextual information such as identity / asset / consumer data) to  build, configure, and monitor fraud use cases on the hm.works platform. 

And that is hm.works 1.10! We will be releasing more features and updates regularly, so stay tuned.

To get the latest news from Human Managed, follow us on LinkedIn and check out our blog.

Want to discuss how we can help solve your cyber, digital, or risk operations through data?

Please contact us at hello@humanmanaged.com.

Human Managed hm.works 1.10 released with dashboard on fraud use cases

Human Managed hm.works 1.10 released with fraud detections

hm.works 1.9 released with 35 cyber standards analyzed, 2000 controls statements normalized into 413 controls, mapped to 18 control frameworks 


Since its first release on 13 March 2023, the Human Managed web app hm.works has been getting

Our cloud-native data analytics platform 

 to continuously discover and profile your 

This forms the pool of intelligence on your business' current state, normalized and always up-to-date as digital catalogs of 

The intel on your assets, their posture & behavior isn't isolated databases.  It's what provides your unique business context for use cases that matter to your ops, like prioritizing 

 detections on your critical assets that impact your customers. 

Data on your assets, their posture and behaviors only mean something for your business when 🔗

🔗 are established between them and that intel is applied to a scenario. 

Today, we are excited to apply your unique intel through...

An interactive matrix that presents your entire organization's cybersecurity maturity mapped to 18 Frameworks that establishes the relationships between: 

NIST Cybersecurity Framework: Identify, Protect, Detect, Respond, Recover

The cyber posture scorecard answers the top 3 things you need to know about your enterprise cyber maturity: 

How mature is my organization's ability to identify, protect, detect, respond, recover from cyber threats? 

What controls should I implement to defend my assets? 

Where are the biggest gaps between my preferred posture state and current posture state? 

There are multiple standards and frameworks covering different scope or focus areas for securing an organization and each of them are very different in the advice they give.

These different advices most often point to common topics such as governance, technical, software development, physical, industrial, IaaS, PaaS, SaaS & SMB

NIST (National Institute of Standards and Technology) partnered with private sector and held a series of town hall meetings and determined the standards that are included in its cybersecurity framework (CSF). It used the following standard as its foundation: 

 addressing the five core areas of Cyber: Identify, Protect, Detect, Respond, Recover.

Today, the NIST CSF is widely recognized as an industry best practice framework for any business to manage cyber risk and control threats. 


Let's explore each segment of the cyber posture scorecard.

 This matrix of 'donut' charts reports your organization's current cyber posture against target posture by each NIST function and asset type (user, network, device, app, api, compute, storage) as a percentage. 

 Understand your organization's current state and act to close the gaps in (1) identifying risks; (2) protecting assets; (3) detecting suspicious behaviour; (4) responding to threats; and, (5) recovering from compromise (as per the NIST functions)



📝Here, your User asset type's Identify function's score is 25%, putting this score's RAG status as Red.  The bold red bar is the current state, filled out of the bar with reduced opacity, which represents your organization's target for this metric (80% in in this case).  The dotted blue line outlining the reduced opacity area is the gap between target and current (blue filled triangle points to the percentage that has completed, and the outlined triangle points to the target percentage.) 

Click on any of the donut charts to view the score break down resulting from our analysis of 35 cyber standards and normalized 2000 controls statements into 413 controls. 

These controls are mapped 18 control frameworks. Each controls have a definition, a measure, a metric and maturity, all listed on: 

 This interactive grid breaks down your organization's current cyber posture based on: 

control maturity score (based on policy, implementation, operations) 

 Understand and explore your current state of cyber posture in detail (e.g. group and filter by asset type, control system, or control categories), identify blockers, and plan for improvements to achieve desired cyber risk management goals. 

And there it is, the cyber posture scorecard that measures the gap between your current and target state of cyber maturity.  

All of this is done on-demand through analyzing your data, or more precisely, analyzing the relationships and interactions between data of:

🔗 your unique context: digital assets, controls enabled and detected on your assets, tracked process on control policies, implementations, and operations. 

🔗 industry frameworks: control functions, control measures, key risk indicators, latest standards 

And that is hm.works 1.9! We will be releasing more features and updates regularly, so stay tuned.

Human Managed hm.works 1.9 released with scorecard on cybersecurity capability maturity to NIST CSF

Human Managed hm.works 1.9 released with cyber posture scorecard

Human Managed app hm.works 1.8 released with catalog on security controls 

 to report on intel generated from any data source from our customers.

This week, we are excited to announce the release of a catalog that presents all available controls (rules, checks and policies) that improve the security posture of a business.  

An interactive data grid that presents the total universe of security controls (policies, rules, and checks) that are detected by the hm.works platform from every active control sensors, such as endpoint detection and response tool, cloud security posture management tool, or SIEM. 

Read more about our approach to controls and why it is important to your business posture. 

The grid view with its filtering and sorting capabilities allows you to explore the control data as you see fit, to identify gaps in the coverage of your  controls, and to improve any operations processes. For example:

continuously update all available controls from existing control sensors, their variety (e.g. malware, abnormal authentication & access), and their types (prevention, deterrent, detection, compensating) 

initiate programmes to improve control coverage with prioritization of controls with high severity scores 

enable controls to detect / prevent specific attack techniques to improve control coverage

increase controls, control variety and control types for critical assets 

onboard more relevant control sensors and remove unnecessary investments. 

The control catalog answers the top 3 things you need to know about the state of your security controls: 

What security control sensors and controls are available for me to enable? 

How do I prioritize my resources and response based on the control severity score? 

How do I get a control catalog for my business?

Forward data to hm.works from any data source (devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts).

Once hm.works collects your data, we will automatically discover, profile & detect everything required to manage your security posture: 

 control sensors and their controls through data.  Create asset and control catalogs (what assets do I have, and what controls are they configured with?) 

asset and control context based on your business models (asset criticality, control severity, baseline, targets) 

 use cases triggered by the controls (weakness, vulnerability, behavior patterns) 

And that is hm.works 1.8! We will be releasing more features and updates regularly, so stay tuned.

Human Managed hm.works 1.8 released with catalog of all security controls in your business

Human Managed hm.works 1.8 released with control catalog

On 3 May 2023, we've released the Human Managed web app 

Today we are releasing some exciting feature updates to our version 1.7, serving drill downs of the data sitting behind our charts and narratives. 

An interactive data grid that lists all the important attributes that make up the profile of your digital assets, including their criticality, sensitivity, and active controls they have (or lack thereof). 

Read about how we define and classify assets (Resource / Product / Service)

 and why knowing them are important for decision making to any business. 


The grid view with its filtering and sorting capabilities allows you to explore the asset data as you see fit, to identify gaps in the completeness of data, and to complement any operations processes.  For example: 

validate asset information for detections, 

initiate projects to configure controls for critical assets without controls, 

update sensitivity and criticality for all assets that impact services, 

data source for compliance / audit exercises 

The consolidated view of asset profile gives a single source of truth of your assets' current state, from a combination of your data straight from the sources, as well as the unique business context provided by you and your team: 

what it is, where it is, how important it is to your business, whether it has the control(s) it needs. 

And that is hm.works 1.7.1! We will be releasing more features and updates regularly, so stay tuned.

hm.works updated with grid of all digital assets

Human Managed hm.works 1.7.1 updated with asset profile grid

Human Managed app hm.works 1.7 released with dashboard on denial-of-service (DoS) detections

This week, we are excited to announce the release of a dashboard that reports on the detections of possible denial of service (DoS) for our customer's public facing applications. 

Our DoS Dashboard reports on various detection use cases that hm.works runs on the data generated by your users, 

The hm.works platform analyzes logs from multiple data sources such as CDN, WAF, and firewalls to: 

observe the volume of incoming traffic and requests to customer applications, 

dynamically calculate the baseline of expected volume of traffic and requests, and 

detect events of interest such as volume deviations and peaks from the baseline. 

A single page answers the top 3 things you need to know about potential DoS attack so you can speed up response actions and take proactive measures:

What volume of traffic or requests are directed at my assets?

What is the traffic / request deviation from baseline over time? 

What are the DoS attack patterns observed?

Denial-of-Service (DoS) is an attack technique to disrupt a service, such as web services or applications, by overwhelming it with illegitimate or high volume of traffic. 

A successful DoS attack can degrade your services quality by causing loss, delays or interruption -- resulting in financial and reputational damage and customer dissatisfaction. 

In a world where customers and users' interactions with your business is increasingly digital, it's important to know what to observe in your data, what is 'normal' vs. 'abnormal' behavior, and when to take action. 

Let's explore each segment of the DoS Dashboard.

 This line chart reports the volume of incoming requests made to your public facing services and the standard deviation baseline volume of requests over time.

 Helps you to understand the patterns and anomalies of your application environment from the traffic and request detections generated over time, which guides your next course of action.

 Forward data from web application firewalls, CDN, or edge networks. Customize legitimate URLs to monitor on the hm.works web app.


 This interactive grid lists suspected DoS detections generated by hm.works, the observed URL, volume of requests, and detection severity. 

 Having the details of suspected DoS detections allow you to investigate and take decisions on the next course of action (to react and/or resolve) in response to the threats.


 Forward data from web application firewalls, CDN, or edge networks. 

 This interactive grid breaks down other insights of interest from the web traffic data observed by hm.works, such as the incoming requests' originating country, IP addresses and counts of requests. 


 Helps you identify new traffic / request patterns or validate known patterns to inform response action 


And that is hm.works 1.7! We will be releasing more features and updates regularly, so stay tuned.

Human Managed hm.works 1.7 released with dashboard on denial of service cyber use case

Human Managed hm.works 1.7 released with denial of service (DoS) detections

Human Managed app hm.works 1.6 released with dashboard on cyber detections 

This week, we are excited to announce the release of a dashboard that tells the story of threat detections that hm.works generate after it analyzes data events from customers' data sources. (

See how we define everything 'data' at HM in our 1.5 release note

A single page answers the top 3 things you need to know about the detections generated by the hm.works platform: 

1. What states and behaviors are detected in my environment? 

2. What kind of threats do these detections expose me to? 

2. How severe are the threats to my organization? 

 an alert event triggered when states and/or behaviors from customer's data matches the conditions, correlation rules and/or machine-learning algorithms enabled in the hm.works platform. 


 detections identify interesting events, threats, or opportunities that exist in your environment. 

When properly categorized, monitored, and analyzed, detections inform your action to react and resolve in response to the threats.  When not done properly, detections can quickly get overwhelming and meaningless. 


* * *

Not everything is an interesting event or a threat that requires a response, especially with limited time and resources.  This is why it's all the more important to enrich your data events with relevant contexts and use cases. 


Let's explore each segment of the Detection Dashboard: 

 This donut chart maps detections to the various techniques and strategies observed in the state and/or behavior.  Every single activity and state data from customer data sources are automatically categorized into one out of 15 detection types. 


 Helps you to understand the kind of threats the detection events collectively expose your organization to, and to establish trends and patterns related to threats. 


 Forward data to hm.works from any data source (devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts).


 This bar chart reports the total number of detections generated by hm.works after your data is enriched with conditions, correlation rules and/or machine-learning algorithms (a.k.a. use cases).


 Helps you to establish benchmarks and understand the behavior of your environment from the detections generated over time.


 Forward data to hm.works from any data source (devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts).

 This interactive grid breaks down the details of all detections generated by hm.works such as their detection categories, affected assets, and date of detection. 


 Having the details of your detections allow you to investigate and take decisions on the next course of action (to react and/or resolve) in response to the threats. 


And that is hm.works 1.6! We will be releasing more features and updates regularly, so stay tuned.

Human Managed hm.works 1.6 released with dashboard on detection use cases

Human Managed hm.works 1.6 released with cyber detections

Human Managed app hm.works 1.5 released with dashboard on your data and events 


Since its first release on 13 March 2023, the Human Managed web app 

to report on intel generated from any data source from our customers. 

This week, we are excited to announce the release of a dashboard that tells the story of the lifecycles of all your data forwarded to hm.works. 

A single page answers the top 3 things you need to know about the data you organization is generating: 

1. What data sources are actively forwarding data for analysis? 

2. Which data sources generates the most number of events (logs, metrics, traces, and alerts)? 

2. What are the volume trends (e.g. spikes / dips) observed? 

Before we get into anything interesting or useful out of the sea of data you generate, it's important to clarify some terms: 

any text-based raw data in UTF8 format e.g. logs, metrics, traces, alerts or events generated by Data Sources that captures system, network or application events or activities.

 customer devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts or meta-data that is forwarded to the Service. One Data Source could have one or more Data Schema(s). 

 a physical implementation of a data model in a management system like a database. (e.g. Data Schema for incidents will be different from data schema for alerts, from a same Data Source) 

a design that represents the relationship between multiple data fields.

 Data that is generated when something happens.  There are multiple types of events, depending on what the event is about: 

 event is about an occurrence of interest 


Let's explore each segment of the Data Dashboard: 

 This stacked area chart reports the total volume of data forwarded to hm.works over time and how each data source contributes to the whole amount 


 Helps you to establish benchmarks for utilization and plan for capacity


 Forward data to hm.works from any data source (devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts) 


 This stacked area chart reports the total number of events generated from all data sources connected to hm.works over time and their breakdown into event types (metrics, logs, traces, alerts) 


 Helps you to establish benchmarks and understand the behavior of your environment from the data generated over time. 


 Forward data to hm.works from any data source (devices, app, api, compute, storage, tool or services that generate log, metrics, traces, event data, alerts) 

 This interactive grid breaks down the details of all data sources connected to hm.works such as the number or data schemas, data volume, and number of events generated in a given period of time. 


 Having the profile of your data sources, their schemas and event volume they generate allows you to see how much data is available in your environment for analysis, identify potential gaps in visibility, and plan for use case development. 


And that is hm.works 1.5! We will be releasing more features and updates regularly, so stay tuned.

hm.works 1.5 released with dashboard on connected data sources 

Human Managed hm.works 1.5 released with data / event lifecycle

Human Managed app hm.works 1.4 released with phishing detection dashboard 


Since its first release on 13 March 2023, the Human Managed web app hm.works has been getting fresh updates every single week.

 with the most fundamental knowledge for any business that operates digitally: intel on existing 

 (services, products, resources that are in digital form).

 on a business' digital assets, by reporting on the assets' state, or overall 

. An asset's posture is measured by the controls (checks, rules, policies) that are enabled on the asset.

hm.works 1.2 delivered even deeper layers of intel

 discovered and detected, which (positively or negatively) affect the business.

, allowing you to overview and prioritize the posture and behavior detections on your assets. 

This week, we are excited to announce our first custom cyber dashboard for a threat use case: 

Our Phishing Dashboard is an operational dashboard that shows active fake websites that could cause damage to your organization.  A single page answers the top 3 things you need to know about phishing so you can speed up response actions and take proactive measures: 

What are the active websites impersonating my brand? 

How effective is my response in taking them down? 

What are the phishing attack patterns observed? 

What's phishing and why is it important? 

Phishing is a type of deceptive social engineering where a malicious attacker pretends to be a legitimate source, with the objective of receiving sensitive information from a target. 

A common phishing technique attackers use is to send  targets email with a link (bait) that opens up a spoofed website (hook), and get users to enter their financial details (catch). 

Phishing attacks remains an effective way to gain access to your assets, and they can cause serious financial and reputational damage.   

The hm.works platform monitors logs from multiple data sources such as domain name, email header, legitimate web addresses, email attachments, and web requests made by phishing victims, and correlate the data with external threat intel such as known active phishing URLs and threat actors.  

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Human Managed hm.works 1.10 released with fraud detections

Human Managed hm.works 1.9 released with cyber posture scorecard

Human Managed hm.works 1.8 released with control catalog

Human Managed hm.works 1.7.1 updated with asset profile grid

Human Managed hm.works 1.7 released with denial of service (DoS) detections

Human Managed hm.works 1.6 released with cyber detections

Human Managed hm.works 1.5 released with data / event lifecycle

Human Managed hm.works 1.4 released with phishing dashboard

Minting JSON Web Tokens (JWTs)