Advanced Persistent Threats (APTs) are stealthy, multi-step attacks tailored to a specific target. Often described as ’low and slow’, APTs remain undetected until the consequences of the cyber-attack become evident, usually in the form of damage to the physical world, as seen with the Stuxnet attack, or manipulation of an industrial process, as was the case in the Ukraine Power Grid attacks. Given the increasing sophistication and targeted nature of cyber-attacks, especially APTs, this paper delves into the substantial threats APTs pose to critical infrastructures, focusing on power grid substations. Through a detailed case study, we present and explore a 2-stage APT attack on an IEC 61850 power grid substation, employing a Hardware-in-the-Loop (HIL) testbed to simulate real-world conditions. More specifically, this paper discusses two significant experiments conducted to assess vulnerabilities in the control protocols used in IEC 61850 substations: IEC 60870-5-104 and IEC 61850. The integration of findings from these experiments revealed a number of previously undiscussed potential threats to power grid infrastructure that could arise from attacking one or more substations. To better address these potential threats, the paper proposes an extension to the Industrial Control System (ICS) kill chain that explicitly accounts for the consequences of attacks on the physical aspects of Cyber-Physical Systems (CPSs).

Advanced Persistent Threats (APT) are stealthy multi-step attacks, often executed over an extensive time period and tailored for a specific attack target. APTs represent a “low and slow” type of cyberattack, meaning that they most often remain undetected until the consequence of the attack becomes evident. Energy infrastructure, including power grids, oil and gas infrastructure, offshore wind installations, etc., form the basis of a modern digital nation. In addition to loss of power, financial systems, banking systems, digital national services, etc., become non-operational without electricity. Loss of power from an APT cyberattack could result in loss of life and the possibility of creating digital chaos. Digital payments becomes unavailable, digital identification is affected, and even POS terminals need to run on emergency power, which is limited in time, resulting in challenges in paying for food and beverages. Examples of Advanced Persistent Threats (APTs) targeting energy infrastructures include Triton, which in 2017 aimed to manipulate the safety systems of a petrochemical plant in Saudi Arabia, potentially leading to catastrophic physical consequences. Another significant incident is the Industroyer2 malware attack in 2022, which targeted a Ukrainian energy provider in an attempt to disrupt operations. The paper combines APT knowledge with energy infrastructure domain expertise, focusing on technical aspects while at the same time providing perspectives on societal consequences that could result from APTs.

Digital substations, also referred to as modern power grid substations, utilize the IEC 61850 station and process bus in conjunction with IP-based communication. This includes communication with switch yard equipment within the substation as well as the dispatch center. IEC 61850 is a global standard developed to standardize power grid communications, covering multiple communication needs related to modern power grid substations or digital substations. Unlike the legacy communication standards, IEC 60870-5-104 and DNP3, IEC 61850 is specifically designed for IP-based communication. It comprises several communication models and supports real-time communication by introducing the process bus to replace traditional peer-to-peer communication with standard network communication between substation equipment and the switch yard. The process bus, especially Sampled Measured Values (SMV) communication, in modern power grid substations relies on extremely accurate and synchronized time to prevent equipment damage, maintain power grid system balance, and ensure safety. In IEC 61850, time synchronization is provided by the Precision Time Protocol (PTP). This paper discusses the significance and challenges of time synchronization in IEC 61850 substations, particularly those associated with PTP. It presents the results of a controlled experiment that subjects time synchronization and PTP to cyber-attacks and discusses the potential consequences of such attacks. The paper also provides recommendations for potential mitigation strategies. The contribution of this paper is to provide insights and recommendations for enhancing the security of IEC 61850-based substations against cyber-attacks targeting time synchronization. The paper also explores the potential consequences of cyber-attacks and provides recommendations for potential mitigation strategies.

Website hacking is a frequent attack type used by malicious actors to obtain confidential information, modify the integrity of web pages or make websites unavailable. The tools used by attackers are becoming more and more automated and sophisticated, and malicious machine learning agents seem to be the next development in this line. In order to provide ethical hackers with similar tools, and to understand the impact and the limitations of artificial agents, we present in this paper a model that formalizes web hacking tasks for reinforcement learning agents. Our model, namedAgent Web Model, considers web hacking as a capture-the-flag style challenge, and it defines reinforcement learning problems at seven different levels of abstraction. We discuss the complexity of these problems in terms of actions and states an agent has to deal with, and we show that such a model allows to represent most of the relevant web vulnerabilities. Aware that the driver of advances in reinforcement learning is the availability of standardized challenges, we provide an implementation for the first three abstraction layers, in the hope that the community would consider these challenges in order to develop intelligent web hacking agents.

Vulnerabilities such as SQL injection represent a serious challenge to security. While tools with a pre-defined logic are commonly used in the field of penetration testing, the continually evolving nature of the security challenge calls for models able to learn autonomously from experience. In this paper we build on previous results on the development of reinforcement learning models devised to exploit specific forms of SQL injection, and we design agents that are able to tackle a varied range of SQL injection vulnerabilities, virtually comprising all the archetypes normally considered by experts. We show that our agents, trained on a synthetic environment, perform a transfer of learning among the different SQL injections challenges; in particular, they learn to use their queries to efficiently gain knowledge about multiple vulnerabilities at once. We also introduce a novel and more versatile way to interpret server messages that reduces reliance on expert inputs. Our simulations show the feasibility of our approach which easily deals with a number of homogeneous challenges, as well as some of its limitations when presented with problems having higher degrees of uncertainty.