See attachment 👇.

The increasing usage of cutting-edge technologies in safety-critical applications leads to strict requirements on the detection of defects both at the end of manufacturing and in the field [VDSDN+19].

Besides scan chains, test access ports (TAPs) and associated protocols constitute the fundamental test mechanism [VDSDN+19].

Among the earliest standards for test access ports is IEEE Std 1149.1a-1993, first drafted by the Joint Test Action Group (JTAG) in the late 1980s, and then standardised by the IEEE in the early 1990s [IEEE13].

Operationally speaking, the most important consideration for a security analyst, when assessing the security of a device, is finding a JTAG interface. Standard tools such as the Bus Pirate, JTAGulator and Open On-Chip Debugger (OpenOCD) can then be used to probe the device through this interface.

Watch the following tutorial on YouTube:

Key establishment (see Definition 1) is part of key management (see Definition 2).

Simply speaking, key management is a set of processes and mechanisms which support key establishment and the maintenance of ongoing keying relationships between parties, including replacing older keys with new keys as necessary [MvV96, Definition 1.64]; see Fig. 1.

Key establishment can be broadly classified into key agreement (see Definition 3) and key transport (see Definition 4).

Key agreement is more popular than key transport, and the de facto standard key agreement protocol is Diffie-Hellman key agreement.

CCSDS has adopted the Licklider Transmission Protocol (LTP) as specified in the IETF RFC 5326 [BFR08b] and the associated security extensions specified in IETF RFC 5327 [BFR08a] to provide reliability and authentication mechanisms on top of an underlying (usually data link) communication service [CCS15b, Sec. 1.1].

Watch the presentation given by one of the discoverers of Meltdown attacks at the 27th USENIX Security Symposium:

Since FLUSH+RELOAD was mentioned, watch the original presentation at USENIX Security ’14:

More information on the Meltdown and Spectre website.

The field of adversarial machine learning (AML) is concerned with the study of attacks on machine learning (ML) algorithms and the design of robust ML algorithms to defend against these attacks [TBH+19, Sec. 1].

ML systems (and by extension AI systems) can fail in many ways, some more obvious than the others.

AML is not about ML systems failing when they make wrong inferences; it is about ML systems being tricked into making wrong inferences.

Consider three basic attack scenarios on ML systems:

In response to the threats of AML, in 2020, MITRE and Microsoft, released the Adversarial ML Threat Matrix in collaboration with Bosch, IBM, NVIDIA, Airbus, University of Toronto, etc.

Subsequently, in 2021, more organisations joined MITRE and Microsoft to release Version 2.0, and renamed the matrix to MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems).

MITRE ATLAS is a knowledge base — modelled after MITRE ATT&CK — of adversary tactics, techniques, and case studies for ML systems based on real-world observations, demonstrations from ML red teams and security groups, and the state of the possible from academic research.

Watch MITRE’s presentation:

References

[Eid21]	B. Eidson, MITRE ATLAS Takes on AI System Theft, MITRE News & Insights, June 2021. Available at https://www.mitre.org/news-insights/impact-story/mitre-atlas-takes-ai-system-theft.
[OV23]	A. Oprea and A. Vassilev, Adversarial machine learning: A taxonomy and terminology of attacks and mitigations, NIST AI 100-2e2023 ipd, March 2023. https://doi.org/10.6028/NIST.AI.100-2e2023.ipd.
[Tab23]	E. Tabassi, Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1, January 2023. https://doi.org/10.6028/NIST.AI.100-1.
[TBH+19]	E. Tabassi, K. Burns, M. Hadjimichael, A. Molina-Markham, and J. Sexton, A Taxonomy and Terminology of Adversarial Machine Learning, Tech. report, 2019. https://doi.org/10.6028/NIST.IR.8269-draft.

MITRE ATT&CK® is a knowledge base of adversary tactics (capturing “why”) and techniques (capturing “how”) based on real-world observations.

There are three versions [SAM+20]: 1️⃣ Enterprise (first published in 2015), 2️⃣ Mobile (first published in 2017), and 3️⃣ Industrial Control System (ICS, first published in 2020).

Fig. 1 below shows the fourteen MITRE ATT&CK Enterprise tactics:

The Mobile tactics and ICS tactics are summarised below. Note a tactic in the Mobile context is not the same as the identically named tactic in the ICS context.

Among the tools that support the ATT&CK framework is MITRE CALDERA™ (source code on GitHub).

• CALDERA is a cyber security platform built on the ATT&CK framework for 1️⃣ automating adversary emulation, 2️⃣ assisting manual red-teaming, and 3️⃣ automating incident response.
• CALDERA consists of two components:
  1. The core system: This includes an asynchronous command-and-control (C2) server with a RESTful API.
  2. Plugins: These are repositories that expand the core framework capabilities. Examples include Pathfinder, a plugin for automating ingestion of network scanning tool output.

A (blurry) demo is available on YouTube:

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A complementary model to ATT&CK called PRE-ATT&CK was published in 2017 to focus on “left of exploit” behavior [SAM+20]:

• PRE-ATT&CK documents adversarial behavior during requirements gathering, reconnaissance, and weaponisation before access to a network is obtained.
• PRE-ATT&CK enables technology-independent modelling of an adversary’s behaviour as it attempts to gain access to an organisation or entity through the technology it leverages, spanning multiple domains (e.g., enterprise, mobile).

ATT&CK is not meant to be exhaustive, because that is the role of MITRE Common Weakness Enumeration (CWE™) and MITRE Common Attack Pattern Enumeration and Classification (CAPEC™) [SAM+20].

• Both CWE and CAPEC are related to Common Vulnerabilities and Exposures (CVE®).
• CVE provides a list of common identifiers for publicly known cybersecurity vulnerabilities called “CVE Records” that are assigned by CVE Numbering Authorities from around the world and are used by individuals and within products to enhance security and enable automated data exchange [MIT20].
• Based in part on the CVE List, CWE is a community-developed list of common software and hardware security weaknesses that serves as 1️⃣ a common language, 2️⃣ a measuring stick for security tools, and as 3️⃣ a baseline for weakness identification, mitigation, and prevention efforts [MIT20].
• Developed by leveraging CVE and CWE, CAPEC is a comprehensive dictionary and classification taxonomy of known attacks that can be used by analysts, developers, testers, and educators to advance community understanding and enhance defences.

MITRE’s Common Attack Pattern Enumeration and Classification (CAPEC™) effort provides a publicly available catalogue of common attack patterns to help users understand how adversaries exploit weaknesses in applications and other cyber-enabled capabilities.

Attack patterns are descriptions of the common attributes and approaches employed by adversaries to exploit known weaknesses in cyber-enabled capabilities.

• Attack patterns define the challenges that an adversary may face and how they go about solving it.
• They derive from the concept of design patterns applied in a destructive rather than constructive context and are generated from in-depth analysis of specific real-world exploit examples.
• In contrast to CAPEC, MITRE ATT&CK catalogues individual techniques (more fine-grained) rather than patterns (collection of sequences of techniques).

As of writing, CAPEC stands at version 3.9 and contains 559 attack patterns.

For example, CAPEC-98 is phishing:

CAPEC-98 can be mapped to CWE-451 “User Interface (UI) Misrepresentation of Critical Information”.

MITRE D3FEND is a knowledge base — more precisely a knowledge graph — of cybersecurity countermeasures/techniques, created with the primary goal of helping standardise the vocabulary used to describe defensive cybersecurity functions/technologies.

• It serves as a catalogue of defensive cybersecurity techniques and their relationships to offensive/adversarial techniques.

The D3FEND knowledge graph was designed to map MITRE ATT&CK techniques (or sub-techniques) through digital artefacts to defensive techniques; see Fig. 1.

• Any digital trail left by an adversary, such as Internet search, software exploit and phishing email, is a digital artefact [KS21, Sec. IVE].

Operationally speaking, the D3FEND knowledge graph allows looking up of defence techniques against specific MITRE ATT&CK techniques.

• For example, looking up Data Obfuscation (T1001) returns this knowledge graph.

Watch an overview of the D3FEND knowledge graph from MITRE on YouTube:

MITRE Engage (previously MITRE Shield) is a framework for planning and discussing adversary engagement operations.

• It is meant to empower defenders to engage their adversaries and achieve their cybersecurity goals.

Cyber defense has traditionally focussed on applying defence-in-depth to deny adversaries’ access to an organisation’s critical cyber assets.

Increasingly, actively engaging adversaries proves to be more effective defence [MIT22b].

• For example, making adversaries doubt the value of any data/information they stole drives down the value of their operations and up their operating cost.

While MITRE Engage has not been around for long, the practice of cyber deception has a long history; honeypots for example can be traced back to the 1990s [Spi04, Ch. 3].

MITRE Engage prescribes the 10-Step Process, which was adapted from the process of deception in [RW13, Ch. 19], in Fig. 1:

Operationalise the Methodologies

The foundation of an adversary engagement strategy is the Engage Matrix:

The Matrix serves a shared reference that bridges the gap between defenders and decision makers when discussing and planning denial, deception, and adversary engagement activities.

The Matrix allows us to apply the theoretical 10-Step Process (see Fig. 1) to an actual operation.

The top row identifies the goals: Prepare and Understand, as well as the objectives: Expose, Affect and Elicit.

• The Prepare and Understand Goals focus on the inputs and outputs of an operation.
• While the Matrix is linear like the 10-Step Process, it should be viewed as cyclical.

The second row identifies the approaches, which let us make progress towards our selected goal.

The remainder of the Matrix identifies the activities.

• The same activities often appear under one or more approach or goal/objective, e.g., Lures under Expose ▶ Detect, Affect ▶ Direct and Affect ▶ Disrupt, because activities can be adapted to fit multiple use cases.
• An adversary’s action may expose an unintended weakness of the adversary.
• We can look at each MITRE ATT&CK® technique to examine the weaknesses revealed and identify engagement activities to exploit these weaknesses.
• Fig. 3 shows an example of mapping a MITRE ATT&CK technique to an engagement activity.