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New IoT Security Regulations: The Devil’s in the Details, and They Fall Short of Global Standards



Using weak, vulnerable, unknown or untested cryptographic algorithms. Encryption is performed based on ciphers, complex algorithms and best developed by mathematical sophisticates. Some companies or developers choose to build and use their own encryption algorithms. This is a risky practice, particularly if it is not updated or reviewed for a prolonged period. Moreover, encryption protocols should undergo rigorous peer review and audit as is done in open source security tools. It is better and more secure to use the already-tested and secure algorithms which are available out there. Some of the most popular encryption algorithms are: RSA, Advanced Encryption Standard (AES) and ECDSA. These are updated and they evolve so that they can help fend off cyber-attacks.


One additional comment is warranted to the reader at this point. It has become a norm to employ complementary technologies such as FPGA accelerators, Movidius Computer Vision IP, and ASIC accelerators to meet the requirements from applications in various domain solutions. These complementary technologies augment the base platform for increased performance, HSMFootnote 7 needs, functional safety, and real-time latency workloads. These technologies are outside the scope of this book, but details on these technologies can be found on the Intel web site.Footnote 8 Finally, although we provide a reasonable overview of the use cases, threats, and security objectives for the domains, the following coverage is not meant to be comprehensive, and to do so would require a much more exhaustive threat modeling exercise, with subsequent peer reviews, to refine the threat model and design for specific products.




New IoT Security Regulations: The Devil’s in the Details – and the Details are Weak




Threat #2: Unauthorized actors could provision devices to their preferences including usernames, passwords, password reminders, and so on. The Intel Secure Device Onboarding technology could be leveraged to provision the device persona and force to change the default passwords with stricter ones and strong password reminders plus a dual factor authentication. Refer to Chapter 4 for details on SDO.


Computer vision and AI (path planning): The machine learning or deep learning assets such as the weights, training data, test/validation data, models, and so on must be protected by encrypting the assets on the storage and decrypting into the memory in a TEE. The details for this architecture are outside the scope of this book.


Carding marketplaces are dark web sites where users trade stolen credit card details for financial fraud, usually involving large sums of money. On October 12, 2022, carding marketplace BidenCash released the details of 1.2 million credit cards for free. A file posted on the site contained the information on credit cards expiring between 2023 and 2026, in addition to other details needed to make online transactions.


BidenCash had previously leaked the details of thousands of credit cards in June 2022 as a way to promote the site. As the carding marketplace had been forced to launch new URLs three months later in September after suffering a series of DDoS attacks, some cyber security experts suggested this new release of details could be another attempt at advertising.


At the drive level, however, the devil is in the details. Normally, storage devices store information as blocks, not objects. This means that there is some translation that goes on between the data as it is consumed (i.e., objects) and the data that is stored (i.e., blocks).


By default Snowcat will attempt to enumerate and discover information about the Istio control plane using one of the three techniques described in the Technical Details section. These techniques provide access to Istio resources like AuthorizationPolicies, VirtualServices, etc. This operational mode is intended for security engineers attempting to enumerate weaknesses from an unauthenticated point of view (e.g. a compromised workload in the cluster). The resources discovered using these techniques are then scanned and exported for the operator.


There are many factors that impact the underlying implementation details of an Istio deployment. Deploying Istio in AWS versus in a Google Cloud cluster can affect which version of Istio is used, what metadata services are exposed, and many other deployment minutiae which can make the difference between a secure and insecure cluster.


For example, when we tested Snowcat in AWS, we found that a newer version of Istio which blocked the majority of the Istiod Debug APIs had been deployed and there were greater restrictions on accessing the Kubelet Read-Only API. We were hoping that these mechanisms would be cloud provider agnostic, but like many security challenges, the devil is in the details. Future release of Snowcat will have additional cloud-specific discovery mechanisms to ensure the widest possible range of use.


A miscreant using the handle "devil" claims to have siphoned the details and is selling it all on a cyber-crime forum, according to RestorePrivacy, a digital privacy advocacy group that first reported the security breach. It's said that the info belongs to celebrities, companies, ordinary netizens, and accounts with highly desirable usernames.


That could be used to unmask pseudonymous users: if you have their contact details, and suspect they are running a Twitter account, you could use the API-level flaw to find out who they are tweeting as. That would be useful to nation states and organizing seeking to out those running accounts they perceive as a problem.


Last week, however, RestorePrivacy said it found a database mapping contact details to handles for sale on Breached Forums, analyzed the the samples, and confirmed that they matched "real-world people that can be easily verified with public profiles on Twitter." 2ff7e9595c


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