If you're looking for a CIAM solution, then Amazon Cognito is definitely worth a try. To get started quickly with Cognito user pools, user sign-up, sign-in, password recovery, plus an extra layer of security through PKCE, I wrote a basic guide.
Cognito is surprisingly cost-effective. An estimate for 10,000 MAUs (monthly active users) can be as low as 0.015 per user per month. Not bad for a robust, secure, full-featured CIAM solution based on open standards.
If you plan to work with managed Kubernetes clusters, I wrote an eksctl guide to get started. It's an introduction to a command-line tool that automates K8s cluster creation in AWS. The guide takes you through the cloud infrastructure put in place through the tool, following a simple use case: create a cluster from a single command, without a config file.
If you're really into free, open-source load balancers, then you might enjoy a short guide I wrote for getting started with HAProxy. Set it up at your own pace on your local workstation to get a feel for making HAProxy work in a basic way.
Even after all these years, HAProxy continues to be regarded as a leading standard in software load balancing.
In a highly secure organization, threat modeling must be an integral part of a Secure Release Process (SRP) for cloud services and software. It is a security practice used to evaluate potential threats to a system or application. Organizations can adopt threat modeling to get ahead of vulnerabilities before it's too late.
The practice involves 6 steps:
1. Identify assets: What needs to be protected? This may include data, hardware, software, networks, or any other resources that are critical to the organization.
2. Create a data flow diagram: How does data flow through a system or application? What components talk to each other and how? A data flow diagram shows component interactions, ports, and protocols.
3. Identify potential threats: What threats to the system exist? External threats include hackers and malware, while internal threats may include authorized users and human error. What harm can they cause to assets?
4. Risk: evaluate the likelihood and impact of threats. How serious is the threat and how likely is it to happen? What would be the impact to the organization?
5. Prioritize threats: After a risk evaluation, prioritize threats by severity. This helps organizations to focus attention on addressing the most severe threats first.
6. Mitigate threats: The final step in threat modeling is to develop and implement measures to mitigate identified threats. This could include adding security controls, such as firewalls, intrusion detection/prevention systems, or a SIEM. Employee training on security best practices also goes a long way to mitigate threats. Regular tests and updates to security measures are other ways to mitigate security risks.
A review of a threat model should happen at least once a year as part of an SRP to catch new threats and to assess architecture changes to the system or application as it evolves. By identifying potential threats proactively, organizations can significantly reduce the risk of a cybersecurity attack.
Sample Threat Model
In this sample threat model, the focus is a PAM solution deployed deep inside the corporate network in a Blue Zone. In identifying the assets needing protection, the diagram expands out to include all inbound connections into the PAM solution, all outbound connections from it.
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| Sample Threat Model |
The sample diagram can be broken down by network zone: Blue, Yellow, and Red.
Blue - Highly restricted. Contains mission critical data and systems operating within it. Here applications can talk to each other, but they shouldn't reach out to any of the other zones. If they do, traffic should be carefully monitored.
Yellow - like a DMZ (Demilitarized Zone), this zone hosts a services layer of APIs and user interfaces that are exposed to authenticated/authorized users. It also hosts a SIEM to take logs in from external sources.
Red - This zone is uncontrolled. It is completely un-trusted because of the limited controls that can be put into place there. As such, it's viewed as a major security risk. Sensitive assets inside the organization must be isolated as much as possible from this zone. Could be a customer's network or the big bad internet.
Assets
The A1-A18 labels identify and classify the assets that need to be protected. In this model assets to protect include logs, alert data, credentials, backups, device health metrics, key stores, as well as SIEM data. And since the focus of this threat model is the PAM solution itself, the primary asset are elevated customer device credentials, A4.
Threats
The red labels T1-T5 represent threats to the applications and data inside each zone. In this model, threats do not include external unauthenticated users because the system is locked down to prevent this type of access. But it does include internal authenticated as well as internal unauthenticated users as a threat simply because human error could lead to a security incident. SQL Injection is also identified as a threat to the databases.
Controls
To mitigate threats, controls and safeguards are put in place. In this model, a VPN sits in front of the internal network and VPN access is required to get in. All traffic is routed through an encrypted VPN tunnel. In the diagram this is the dotted line underneath the Red Zone labeled C1. Other controls include firewalls to allow traffic only through specific ports and protocols, as well as encryption of data in transit by SSL/TLS.
An intrusion detection and/or intrusion prevention (IDS/IPS) tool is in place, labelled C7, to capture and analyze traffic. Anything suspicious generates an alert for security personnel to act upon. An IDS can be used to detect a wide range of attacks, including network scans, port scans, denial-of-service (DoS) attacks, malware infections, and unauthorized access attempts. Other controls throughout the diagram are placed there to protect assets from identified threats.
Data Classification
The sample threat model does not have an extensive data classification scheme, as it only identifies sensitive data. But other models could provide a more granular data classification scheme to better explain what kind of data is stored where and how to protect it.
For example, HIPPA (Health Insurance Portability and Accountability Act) protects the privacy and security of individuals' medical records and personal health information (PHI). The law applies to health care providers, health plans, and health care clearinghouses, as well as their business associates, who handle PHI. HIPAA requires covered entities to implement administrative, physical, and technical safeguards to protect the confidentiality, integrity, and availability of PHI. Non-compliance with HIPAA regulations can result in significant fines and legal penalties.
HIPAA, PCI-DSS, and GDPR mandate that organizations implement security measures to protect sensitive data. Threat modeling as a security practice helps organizations to comply with regulatory requirements.
Once it's created, a threat model diagram can be reviewed by the organization's security team and kept current with architectural changes as the system evolves over time. The threat model provides a basis for a re-assessment of the threats and controls in place to protect assets.
An improvement in an organization's security posture can be achieved by investing in threat modeling, and thereby reducing the risk of cyber-attacks.
A disaster recovery (DR) plan provides a step-by-step procedure for unplanned incidents such as power outages, natural disasters, cyber attacks and other disruptive events. This DR plan is intended to minimize the impact of a disaster on a primary data center by defining a way for the system to continue to operate. A plan includes a procedure to quickly return to an operational state in a production environment.
A disruption to the operational state of the system in production can lead to lost revenue, financial penalties, brand damage, and/or dissatisfied customers. If the recovery time is long, then the adverse business impact of a disaster is greater. A good disaster recovery plan is intended to recover rapidly from a disruption, regardless of the cause.
This DR plan defines 4 basic elements:
Disaster Recovery defines two primary objectives, Recovery Point Objective (RPO) and Recovery Time Objective (RTO):
After damage to the primary site is assessed, a procedure to re-constitute the site to an operational state can be followed. A procedure is expected to be completed within 24 hours of a disaster. During this recovery period, a DR site is expected to provide business continuity, in some cases read-only, as user operations can be queued up, but not yet committed.
Let's sketch an architecture diagram of a solution, and describe a CI/CD pipeline, including build, test, pre-deployment and post-deployment actions, and tools that could be used to deploy this application to AWS.
IaC or Infrastructure as Code refers to the use of machine-readable definition files to manage and provision IT infrastructure, instead of manual configuration. The infrastructure is treated like software code that can be versioned, tested, and automated. This allows for faster and more reliable deployment of infrastructure and easier management and scaling of resources. The infrastructure is defined in code using programming languages or specialized tools. This code can be executed to create, modify, or delete infrastructure resources in a repeatable and consistent manner, thus reducing the risk of human error and increasing the efficiency of IT operations, resulting in overall system reliability.
There are many IaC frameworks available, including popular ones like Terraform, Ansible, Puppet, Chef, CloudFormation, and SaltStack. The choice of framework depends on factors such as the size and complexity of the infrastructure, the specific needs of the organization, and the skills and expertise of the IT team. For example, Terraform is known for its ability to provision infrastructure across multiple cloud providers and on-premises environments, while Ansible is popular for its simplicity and ease of use. Puppet and Chef focus on configuration management and enforcing consistency across infrastructure resources, while CloudFormation is specific to Amazon Web Services (AWS) environments. SaltStack offers an event-driven automation approach that can help with high-scale and complex infrastructures. Ultimately, the best IaC framework is the one that meets the needs of the organization and aligns with its IT strategy and goals.
| Mean | 8.3 |
| Min | 3.3 (2012) |
| Max | 18.4 (1981) |
| Current | 3.4 |
| Standard Deviation | 3.2 |
| Mean | 97.5 |
| Min | 25.2 (1975) |
| Max | 184.6 (2006) |
| Current | 184.4 |
| Standard Deviation | 48.3 |
| D | X | Y |
|---|---|---|
| 1/1/1975 | 9.43 | 25.25 |
| 2/1/1975 | 9.10 | 25.29 |
| 3/1/1975 | 8.89 | 25.36 |
| ... | ||
| 6/1/2016 | 3.57 | 182.19 |
| 7/1/2016 | 3.44 | 183.43 |
| 8/1/2016 | 3.44 | 184.42 |
When a person you know has fallen in love, it’s almost as though someone new has emerged--a person who thinks in other ways, with altered goals and priorities. It’s almost as though a switch had been thrown and a different program has started to run.Minsky questions our understanding of loaded words such as emotion. We can’t learn much from a dictionary definition of the word because a definition only hides what is really a “range of states” too complex to comprehend. He explains mood changes, say from angry to happy, as highly complex mental state changes. And mental states, in Minsky's theories of the mind, are based on the use of many small processes.
Someone like Marvin Minksy might happen along and say “Here is a robot arm. I am leaving this robot arm by the machine.” Immediately, nothing in the world is as essential as making the proper interface between the machine and the robot arm, and putting the robot arm under your control, and figuring a way to create a system where the robot arm knows what the hell it is doing. Then you can see your offspring come to life.
- Steven Levy, Hackers: Heroes of the Computer Revolution, 1984
Like a talent, intellectual giftedness is usually believed to be an innate, personal aptitude for intellectual activities that cannot be acquired through personal effort.
Gifted individuals experience the world differently, resulting in certain social and emotional issues.
Joseph Renzulli's (1978) "three ring" definition of giftedness is one well-researched conceptualization of giftedness. Renzulli’s definition, which defines gifted behaviors rather than gifted individuals, is composed of three components as follows: gifted behavior consists of behaviors that reflect an interaction among three basic clusters of human traits—above average ability, high levels of task commitment, and high levels of creativity.
Generally, gifted individuals learn more quickly, deeply, and broadly than their peers.
They may also be physically and emotionally sensitive, perfectionistic, and may frequently question authority.
Many gifted individuals experience various types of heightened awareness and may seem overly sensitive. For example, picking up on the feelings of someone close to them, having extreme sensitivity to their own internal emotions, and taking in external information at a significantly higher rate than those around them. These various kinds of sensitivities often mean that the more gifted an individual is, the more input and awareness they experience, leading to the contradiction of them needing more time to process than others who are not gifted.
Healthy perfectionism refers to having high standards, a desire to achieve, conscientiousness, or high levels of responsibility. It is likely to be a virtue rather than a problem, even if gifted children may have difficulty with healthy perfectionism because they set standards that would be appropriate to their mental age (the level at which they think), but they cannot always meet them because they are bound to a younger body, or the social environment is restrictive. In such cases, outsiders may call some behavior perfectionism, while for the gifted this may be their standard.
int myInt = 10;
var myString = 'str';
int myInt = 10;
var myDate = this.time - 20s;
var myEvents = lookup.events.type("A");
var myEvents = (this.time - 20s <= lookup.events.type("A"));
Language oriented programming (LOP) is a style of computer programming in which, rather than solving problems in general-purpose programming languages, the programmer creates one or more domain-specific languages for the problem first, and solves the problem in those languages.
if ( (this.type == 'Motion North') && (this.camera == 'B') ) {
var events =
(this.time - 20s <=
lookup.events.type('Motion North').camera('A').time)
if (events.size <= 1) {
run('TrafficSignalControl.sh', 'ChangePhase:Red', 'A')
run('TrafficSignalControl.sh', 'ChangePhase:Red', 'B')
}
}this.time - 20s
