Preface: NVIDIA DGX-1 is an integrated deep learning workstation with a large computing capacity, which can be used to run demanding deep learning workloads. It provides GPU computing power of 1 PetaFLOPS (1 quadrillion floating-point operations per second).

Background: Historically, both vendors and attackers have overlooked (pre)EFI boot process (in)security; pre-EFI Initialization (PEI) boot stage opens many doors and offers flexibility to attackers.
The Pre-EFI Initialization (PEI) phase provides a standardized method of loading and invoking specific initial configuration routines for the processor, chipset, and system board. The PEI phase occurs after the Security (SEC) phase. The primary purpose of code operating in this phase is to initialize enough of the system to allow instantiation of the Driver Execution Environment (DXE) phase.
The Driver Execution Environment (DXE) phase is where most of the system initialization is performed. Pre-EFI Initialization (PEI), the phase prior to DXE, is responsible for initializing permanent memory in the platform so that the DXE phase can be loaded and executed.

Note: Security (SEC) and Pre-EFI (PEI) phases – both are controlled by the firmware vendor.
SEC – Init CPU, clear caches, load BIOS ROM
PEI – Initialize chipset, RAM, devices, Secure Boot (Record Secure Boot in PCR 7)

Vulnerability details: NVIDIA DGX-1 SBIOS contains a vulnerability in the Uncore PEI module, where authentication of the code executed by SSA is missing, which may lead to arbitrary code execution, denial of service, escalation of privileges, information disclosure, data tampering, and SecureBoot bypass.

Official announcement: For details, please refer to the link – https://nvidia.custhelp.com/app/answers/detail/a_id/5458

Preface: Several companies are currently using Arm processors to create artificial intelligence-powered software to help make the driving experience safer. Some experts believe that artificial intelligence will affect human life. Yes it is real. The late Stephen Hawking speculated about this potential impact, but it looks like part of the process of human civilization. The man kind involves into automation life when smartphone and GUI was born. It was not possible to jump back. Perhaps this is the destinely. On the other hand, computer vulnerabilities is the effective way to against out of control AI. Perhaps it is a effective solution.

Background: Branch predictor hardware typically uses a form of cache to hold branch information. When vendor release announcement of their design weakness few years ago, a misunderstand was that it only appears on a single brand. But the truth is that properly not. When CPU designer intend improve the efficiency of CPU response time. It will be using it. The ARM architecture permits this branch predictor hardware to be visible to the functional behaviour of software, and so the branch predictor is not architecturally invisible.

The possible attack mechanism of Spectre-BHB: The branch target injection in the same software context (unlike Spectre v2, which injects branch targets across different exception levels) . If the attacker can poison branch history from user space to force the kernel to mispredict targets. When the victim executes an allegedly safe branch that is mis-predicted , redirecting the control flow to a gadget that, with attacker controlled registers. Therefore it triggered the vulnerability. For information on this attack mechanism and mitigations concept. Please refer to attached diagram.

Development in 2023: Arm announced a new generation of Armv9 CPUs, namely the Cortex-X3 and the Cortex-A715. The Armv9 CPU use L1 instruction cache Speculative memory accesses. The L1 instruction memory system provides an instruction stream to the decoder. To increase overall performance and reduce power consumption, the L1 instruction memory system uses dynamic branch prediction and instruction caching.
Whether is there any design weakness similar to branch prediction of this new design. Let’s keep our eyes open. stay tuned!

Preface: Today is Valentine’s Day 2023, are you alone? But in the future artificial intelligence will be with you.

Background: With an AI content writer, all you need to do is enter your desired topic or keyword into the plugin settings, and then AI will immediately generate an article that reads as if it were written by a human. You’ll get unique, engaging stories without having to spend hours typing out paragraphs or researching facts. Plus, you’ll have a consistent style and tone that you can use for all of your content.

Vulnerability details: The GPT AI Power: Content Writer & ChatGPT & Image Generator & WooCommerce Product Writer & AI Training WordPress plugin before 1.4.38 does not perform any kind of nonce or privilege checks before letting logged-in users modify arbitrary posts.
Ref: CWE is classifying the issue as CWE-862. The software does not perform an authorization check when an actor attempts to access a resource or perform an action. This is going to have an impact on integrity, and availability.

Solution: Upgrading to version 1.4.38 eliminates this vulnerability.

Official Announcement: For details, see the link – https://wpscan.com/vulnerability/3ca9ac21-2bce-4480-9079-b4045b261273

Before you enjoy it with your AI girlfriend, I wish you have a great Valentine’s Day today.

Preface: AI system infrastructure may not have a mature model, it will continue forever, without end. Perhaps this is true sustainability. Since the key component is the computer. So the only thing that slows him down is software or hardware bugs.

Background: Cryptocurrency technology fully utilise the concept of Blockchain. Seems the advantage of cryptocurrency is easy misused and lead it become dangerous. Therefore many government hesitate to get involves and let it fail to original objective. However their related technology will be growth rapidly. Yes, it is the IFPS. AI requires heavy amounts of storage and compute. From technical point of view, Distributing storage will be an advantage. Since the data not place in the same area. It enhance overall reliability and efficiency. AI robots will communicate using 5G. Deal with distributed data storage. Machine learning operations and processes can be fully leveraged as it breaks down regional constraints.Perhaps the distributed cloud computing platform is the beginning of milestone to boots the world into artificial intelligence world.

Large models of deep learning are often shared by researchers via Google Drive links which have transfer limits and are not reliably online. IPFS provides a great decentralized solution to hosting data which can be downloaded via regular web links.
IPFS implementation in Go. “unixfs” is a tool in the Go Modules Packages category of a tech stack.
A Merkle DAG is a DAG where each node has an identifier, and this is the result of hashing the node’s contents. go-unixfs implements unix-like filesystem utilities on top of an ipld merkledag. MerkelDAG implementation in Python.

Vulnerability details: go-unixfs is an implementation of a unix-like filesystem on top of an ipld merkledag. Trying to read malformed HAMT sharded directories can cause panics and virtual memory leaks. If you are reading untrusted user input, an attacker can then trigger a panic. This is caused by bogus `fanout` parameter in the HAMT directory nodes.

Solution: Users are advised to upgrade to version 0.4.3 to resolve this issue. Users unable to upgrade should not feed untrusted user data to the decoding functions.

Official announcement: For details, see the link – https://github.com/ipfs/go-unixfs/security/advisories/GHSA-q264-w97q-q778