Running legacy operating systems increases your vulnerability to attacks that exploit long-standing vulnerabilities. Where possible, look to decommission or upgrade legacy Windows operating systems. Legacy protocols can increase risk. Older file share technologies are a well-known attack vector for ransomware but are still in use in many environments. In this incident, there were many systems, including Domain Controllers, that hadn’t been patched recently. This greatly aided the attacker in their movement across the environment. As part of helping customers, we look at the most important systems and make sure we are running the most up-to-date protocols that we can to further enhance an environment. As the saying goes, “collection is not detection.” On many engagements, the attacker’s actions are clear and obvious in event logs. The common problem is no one is looking at them on a day-to-day basis or understanding what normal looks like. Unexplained changes to event logs, such as deletion or retention changes, should be considered suspicious and investigated.
Robocorp Lab creates a separate Conda environment for each of your robots, keeping your robot and its dependencies isolated from the other robots and dependencies on your system. That enables you to control the exact versions of the dependencies you need for each of your robots. It offers RCC, a set of tools that allows you to create, manage, and distribute Python-based self-contained automation packages and the robot.yaml configuration file for building and sharing automations. Control Room provides a dashboard to centrally control and monitor automations across teams, target systems or clients. It offers the ability to scale with security, governance, and control. There are two options for Control Room: a cloud version and a self-managed version for private cloud or on-premises deployment. The platform allows users to write extensions or customizations in Python, a limitation with proprietary systems, according to Karjalainen, and to extend automations with third-party tools for AI, machine learning, optical character recognition or natural language understanding.
Distributed infrastructure on the cloud is great but there is one problem. It is very unpredictable and difficult to manage compared to a handful of servers in your own data center. Running an application in a robust manner on distributed cloud infrastructure is no joke. A lot of things can go wrong. An instance of your application or a node on your cluster can silently fail. How do you make sure that your application can continue to run despite these failures? The answer is microservices. A microservice is a very small application that is responsible for one specific use-case, just like in service-oriented architecture but is completely independent of other services. It can be developed using any language and framework and can be deployed in any environment whether it be on-prem or on the public cloud. Additionally, they can be easily run in parallel on a number of different servers in different regions to provide parallelization and high availability.
IoT technologies tend to have a few qualities in common. They're designed to be low-power, so that the batteries on IoT devices aren't sapped with every transmission. They also tend to be long-ranging, to cut down on the amount of other infrastructure required to deploy a large-scale IoT project. And they're usually fairly robust against interference, because if there are dozens, hundreds, or even thousands of devices transmitting, messages can't afford to be garbled by one another. As a trade-off, they typically don't support high data rates, which is a fair concession to make for many IoT networks' smart metering needs. ... Advancements in satellites are only accelerating the possibilities opened up by putting IoT technologies into orbit. Chief among those advancements is the CubeSat revolution, which is both shrinking and standardizing satellite construction. "We designed all the satellites when we were four people, and by the time we launched, we were about 10 people," says Longmier. "And that wasn't possible five years before we started."
“It will be the responsibility of the eBPF Foundation to validate and certify the different runtime implementations to ensure portability of applications. Projects will remain independently governed, but the foundation will provide access to resources to foster all projects and organize maintenance and further development of the eBPF language specification and the surrounding supporting projects.” The new foundation serves as further evidence that open source is now the accepted model for cross-company collaboration, playing a major part in bringing the tech giants of the world together. Sarah Novotny, Microsoft’s open source lead for the Azure Office of the CTO, recently said that open source collaboration projects can enable big companies to bypass much of the lawyering to join forces in weeks rather than months. “A few years ago if you wanted to get several large tech companies together to align on a software initiative, establish open standards, or agree on a policy, it would often require several months of negotiation, meetings, debate, back and forth with lawyers … and did we mention the lawyers?” she said. “Open source has completely changed this.”
A CSP should be viewed as a partner in protecting payment data rather than the common assumption that all responsibility has been completely outsourced. The use of a CSP for payment security related services does not relieve an organization of the ultimate responsibility for its own security obligations, or for ensuring that its payment data and payment environment are secure. Much of this misunderstanding comes from simply not including payment data security as part of the conversation and how requirements, such as those in PCI DSS, will be met. ... Third-Party Service Provider Due Diligence: When selecting a CSP, organizations should vet CSP candidates through careful due diligence prior to establishing a relationship and explicit understanding of which entity will assume management and oversight of security. This will assist organizations in reviewing and selecting CSPs with the skills and experience appropriate for the engagement.
The majority of the work performed by Data Scientists is in the research environment. In this environment, Data Scientists perform tasks to better understand the data so they can build models that will best capture the data’s inherent patterns. Once they’ve built a model, the next step is to evaluate whether it meets the project's desired outcome. If it does not, they will iteratively repeat the process until the model meets the desired outcome before handing it over to the Machine Learning Engineers. Machine Learning Engineers are responsible for creating and maintaining the Machine Learning infrastructure that permits them to deploy the models built by Data Scientists to a production environment. Therefore, Machine Learning Engineers typically work in the development environment which is where they are concerned with reproducing the machine learning pipeline built by Data Scientists in the research environment. And, they work in the production environment which is where the model is made accessible to other software systems and/or clients.
Automating security is critical to scaling IoT technologies without the need to scale headcount to secure them. To keep up with manual inventory, patching and credential management of just one device it takes 4 man-hours per year. If an organization has 10,000 devices, that nets out to 40,000 man-hours per year to keep those devices secure. This is an impossible number of working hours unless the business has a staff of 20 dedicated to the cause. To continuously secure the thousands, or even tens of thousands, of devices on an organization’s networks, automation is necessary. With the mass scale of IoT devices and the opportunities to strike in every office and facility, automated identification, and inventory of each device so that security teams can understand how it communicates with other devices, systems and applications, and which people have access to it is crucial. Once identified, automation technology allows for policy compliance and enforcement by patching firmware and updating passwords, defending your IoT as thoroughly as your other endpoints.
These malicious containers are designed to easily be misidentified as official container images, even though the Docker Hub accounts responsible for them are not official accounts. "Once they are running, they may look like an innocent container. After running, the binary xmrig is executed, which hijacks resources for cryptocurrency mining," the researchers note. Morag says social engineering techniques could be used to trick someone into using these container images. "I guess you will never log in to the webpage mybunk[.]com, but if the attacker sent you a link to this namespace, it might happen," he says. "The fact is that these container images accumulated 10,000-plus pulls, each." While it is unclear who’s behind the scheme, the Aqua Security researchers found that the malicious Docker Hub account was taken down after Docker was notified by Aqua Security, according to the report. Morag explains that these containers are not directly controlled by a hacker, but there's a script at entrypoint/cmd that is aimed to execute an automated attack. In this case, the attacks were limited to hijacking computing resources to mine cryptocurrency.
Often the first thing that comes to mind is the “sustainable pace,” as pointed out by the 8th principle of the Agile Manifesto: “Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.” So, sustainability in this sense will ensure people will not be burned out by an insane deadline. Instead, a sustainable pace ensures a delivery speed that can be kept up for an infinite time. This understanding of sustainability falls into the profit perspective of the triple bottom line. Another way sustainability is often understood in the agile community is by focusing on sustaining agility in companies. This means, agility and/or agile development will govern the work even after, for example, external consultants and trainers are gone. The focus is then on how to build a sustainable agile culture or on sustainable agile transformations. Over all these years, the agile manifesto has served me well in providing guidance, even for areas it hasn’t originally been defined for.
Quote for the day:
"Leaders dig into their business to learn painful realities rather than peaceful illusion." -- Orrin Woodward