The Unified Extensible Firmware Interface (UEFI) provides a specification of the software interface between an OS and its underlying platform firmware. The runtime services provided are seemingly secure as they reside in System Management Mode (SMM) at ring -2, assuming a higher privilege than the OS kernel at ring 0. However, their software vulnerabilities are known to be exploitable to launch ring 0 to ring -2 privilege escalation, i.e., SMM privilege escalation attacks.In this paper, we introduce an effective static analysis framework for detecting SMM privilege escalation vulnerabilities in UEFI firmware. We present a systematic study of such vulnerabilities and identify their root causes as being two types of references that can escape from the SMRAM, legacy references and unintentional references. Existing static analyses are ineffective in detecting such vulnerabilities in stripped COTS UEFI firmware images, which are developed based on a customized callback mechanism that organizes callable functions into protocols identified by GUIDs. By leveraging such a callback-based programming paradigm, we introduce SPENDER, the first static detection framework, which is founded on a novel protocol-centric analysis, for uncovering the potential SMM privilege escalation vulnerabilities in UEFI firmware efficiently and precisely. For a total of 1148 UEFI binaries collected from eight vendors, SPENDER has successfully found 36 SMM privilege escalation vulnerabilities (two 1-day and 34 0-day vulnerabilities), which can cause arbitrary code execution and arbitrary address write (and can thus enable, e.g., the attackers to install a bootkit into a flash drive). We have reported these 36 vulnerabilities to the vendors, with the two 1-day vulnerabilities confirmed as known previously but the 34 0-day vulnerabilities confirmed as new.

SUMMARY: Advances in metabolic engineering have boosted the production of bulk chemicals, resulting in tons of production volumes of some bulk chemicals with very low prices. A decrease in the production cost and overproduction of bulk chemicals makes it necessary and desirable to explore the potential to synthesize higher-value products from them. It is also useful and important for society to explore the use of design methods involving synthetic biology to increase the economic value of these bulk chemicals. Therefore, we developed 'BioBulkFoundary', which provides an elaborate analysis of the biosynthetic potential of bulk chemicals based on the state-of-art exploration of pathways to synthesize value-added chemicals, along with associated comprehensive technology and economic database into a user-friendly framework. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://design.rxnfinder.org/biobulkfoundary/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: The field of synthetic biology lacks a comprehensive knowledgebase for selecting synthetic target molecules according to their functions, economic applications and known biosynthetic pathways. We implemented ChemHub, a knowledgebase containing >90 000 chemicals and their functions, along with related biosynthesis information for these chemicals that was manually extracted from >600 000 published studies by more than 100 people over the past 10 years. AVAILABILITY AND IMPLEMENTATION: Multiple algorithms were implemented to enable biosynthetic pathway design and precursor discovery, which can support investigation of the biosynthetic potential of these functional chemicals. ChemHub is freely available at: http://www.rxnfinder.org/chemhub/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The 2019 novel coronavirus outbreak has significantly affected global health and society. Thus, predicting biological function from pathogen sequence is crucial and urgently needed. However, little work has been conducted to identify viruses by the enzymes that they encode, and which are key to pathogen propagation. RESULTS: We built a comprehensive scientific resource, SARS2020, which integrates coronavirus-related research, genomic sequences and results of anti-viral drug trials. In addition, we built a consensus sequence-catalytic function model from which we identified the novel coronavirus as encoding the same proteinase as the severe acute respiratory syndrome virus. This data-driven sequence-based strategy will enable rapid identification of agents responsible for future epidemics. AVAILABILITYAND IMPLEMENTATION: SARS2020 is available at http://design.rxnfinder.org/sars2020/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The number of vulnerabilities increases rapidly in recent years, due to advances in vulnerability discovery solutions. It enables a thorough analysis on the vulnerability distribution and provides support for correlation analysis and prediction of vulnerabilities. Previous research either focuses on analyzing bugs rather than vulnerabilities, or only studies general vulnerability distribution among projects rather than the distribution within each project. In this paper, we collected a large vulnerability dataset, consisting of all known vulnerabilities associated with five representative open source projects, by utilizing automated crawlers and spending months of manual efforts. We then analyzed the vulnerability distribution within each project over four dimensions, including files, functions, vulnerability types and responsible developers. Based on the results analysis, we presented 12 practical insights on the distribution of vulnerabilities. Finally, we applied such insights on several vulnerability discovery solutions (including static analysis and dynamic fuzzing), and helped them find 10 zero-day vulnerabilities in target projects, showing that our insights are useful.

MOTIVATION: Molecular scaffolds are useful in medicinal chemistry to describe, discuss and visualize series of chemical compounds, biochemical transformations and associated biological properties. RESULTS: Here, we present RxnBLAST as a web-based tool for analyzing scaffold transformations and reactive chemical environment features in bioreactions. RxnBLAST extracts chemical features from bioreactions including atom-atom mapping, reaction centers, rules and functional groups to help understand chemical compositions and reaction patterns. Core-to-Core is proposed, which can be utilized in scaffold networks and for constructing a reaction space, as well as providing guidance for subsequent biosynthesis efforts. AVAILABILITY AND IMPLEMENTATION: RxnBLAST is available at: http://design.rxnfinder.org/rxnblast/.

SOHO (small office/home office) routers provide services for end devices to connect to the Internet, playing an important role in the cyberspace. Unfortunately, security vulnerabilities pervasively exist in these routers, especially in the web server modules, greatly endangering end users. To discover these vulnerabilities, fuzzing web server modules of SOHO routers is the most popular solution. However, its effectiveness is limited, due to the lack of input specification, lack of routers' internal running states, and lack of testing environment recovery mechanisms. Moreover, fuzzing in general only reports memory corruption vulnerabilities, and fails to discover other vulnerabilities, e.g., web-based vulnerabilities.

Network, such as Internet and Intranet, has penetrated into people's daily life. Router is one of the essential equipments which take an important role in the network and form a large and complicated network. However, huge amounts of routers in the network make the network communication and data routing more complex. How to insure the reach ability and correct communication of Internet is a challenge. In this paper, an approach is proposed to formally model and verify the router-based network. Then, we employ a transition system (denotes TS) to model the router-based network, and make use of the Bisimulation-Quotient Algorithms to obtain the bisimulation quotient of the finite transition system, denoted TS/~. It could be easy to verify properties on the system TS/~. Any verification result for TS/~ carries over to TS and this applies to any formula expressed in either LTL, CTL, or CTL*. This approach can facilitate verification since verification problems are particularly space-critical. Finally, some important properties of routing such as routing reach ability, routing path length, are verified.