Technology Advisory Committee Meeting – July 18, 2023

TAC Sponsor

Commissioner Christy Goldsmith Romero
Opening Remarks

Commissioner

Christy Goldsmith Romero

Commissioner 

Kristin N. Johnson

Chairman

Rostin Behnam

Commissioner

Summer K. Mersinger

Commissioner

Caroline D. Pham
Global Markets Advisory Committee

Topic 1: Responsible Use of AI in Regulated Financial Services
20XX PRESENTATION TITLE 4
AI Accountability 

Policy

Accountability for “trustworthy” AI 

systems will entail choices about: - design and documentation, - risk allocation and reduction, - regulation and enforcement. 

These activities require tools like 

certifications, assessments, and audits to 

show that an AI system is legal, fair, safe 

& effective, and otherwise trustworthy –

a function also known as providing AI 

assurance. 

Policies can promote the development 

and use of these tools – to foster an AI 

accountability ecosystem.

5
34+ questions, for example:

1. Objectives of accountability tools? 

• Verify claims, compliance with legal standards, 

or with non-binding trustworthy AI goals?

• Verify particular goals (fairness, safety, 

transparency and explainability)?

• Part of cyber, human rights, other 

accountability efforts?

• How to address systemic or emergent risk?

• Measures to prevent audit-washing – providing unreliable assurance?

2. Existing resources and models?

3. Subjects of accountability?

• Where in the lifecycle? Continuous assurance 

or for adaptive systems?

• Where in the value chain? Role of vendors? 

• Special obligations for public procurement?

4. Accountability inputs and reporting?

• What to do about data quality and voids? 

• What logs, documentation are necessary for 

adequate assurance, especially by 

independent auditors or certifiers? 

• Researcher access?

• Communicating assurance audits, etc?

5. Barriers?

• Trade secrets and IP?

• Costs and personnel?

• Tools and standards?

6. New Policies?

• Mandatory audits and/or certification?

• Federal subsidies/support for field?

• Data access?

• Disclosure and documentation incentives or 

requirements?

PRESENTATION TITLE
7

Report and recommendations: FALL 2023

Possible areas of focus:

- Audits

- Auditor access and independence

- Bounties; distributed tools

- Certifications

- Data sets

- Documentation

- Prizes and support

- Regulation & self-regulation

- Accountability for AI regulatory tools
Responsible Artificial Intelligence (AI)

Nicol Turner Lee, Ph.D.

Senior Fellow and Director, Center for Technology Innovation

The Brookings Institution

July 18, 2023 – Presentation to CFTC
9

AI: The 

New 

Ecology

Taken together, these emerging 

technologies have the ability to 

efficiently and quickly solve a host of 

existing and unforeseen social problems.
10

Biases and other Challenges at any Stage
11

Examples of AI biases

•Ad targeting

•Employment bias (e.g., gender, race, age)

•Facial detection errors and inaccuracies

•Search query misrepresentation

•Criminal justice / predictive policing “big” mistakes

•Credit scoring and other financial services errors

•Political dis- and mis-information

•Health care practices and research
12

Risks and concerns are socio-technical

• Societal

» Biased decision-making: AI-driven algorithms often contain gender, racial, 

or other implicit biases that reinforce systemic discrimination.

» Deliberate misuse: malicious actors may spread disinformation, create 

deepfakes, and conduct unauthorized surveillance or profiling. 

» And more: job displacement, data privacy, plagiarism/copyright/IP, carbon 

emissions & environmental impact of training large models.

• Technical

» How do we “operationalize” and measure abstract values (e.g., fairness)? 

» How should developers approach trade-offs (e.g., fairness and accuracy, or 

privacy and national security)? 

» Given the context-dependent and constantly evolving use cases for AI, how 

can we set industry standards that are robust and scalable?

» Conflation of AI for efficiency and disparate outcomes
13

Toward more responsible AI from a 

learning context
14

AI in Financial Services/Products: Use Cases

• Risk Management – calculate and simulate risks associated with

compliance protocols, trading positions, or credit/lending decisions.

• Fraud Prevention – identify cases of credit card fraud or money

laundering by tracking clients’ behavior/buying habits.

• Algorithmic Trading – execute trades with a speed, precision, and

frequency impossible for human traders.

» Traders can train algorithms to find patterns in past transactions or

monitor real-time market data, identify arbitrage opportunities, and

instantaneously place buy/sell orders at the most optimal prices.

Financial algorithms can do all the above. What about generative AI? 

• Engage with questions from clients or investors.

• Research competitors, markets, and consumer sentiment.

• Draft contracts, reports, or presentations.

Sources: Algorithmic Trading | Investopedia; Impact of AI on Fintech | Toward Data Science; Business Harness Generative AI | WSJ
15

Key Challenges in Financial Services & Products

• Bias mitigation – bias in, bias out

» Ensure that training data for AI-driven algorithms is representative,

accurate, and values-based.

» Include diverse communities of “humans-in-the-loop” who clean and

label datasets, and train and build AI models.

• Transparency – explain the “black box”

» Explainability of computational models and training datasets

» Disclosures of application – before, during, and after

» Privacy of data used to train models to avoid proprietary mining

» Avoidance of “insider” use to manage risk

• Regulation – self-regulatory versus proscriptive

Source: Challenges of AI Regulation | Brookings
16

Regulatory Landscape

“Soft” law – voluntary self-regulation or opt-in best practices

• Examples: Partnership on AI, EU’s Code of Practice on Disinformation, NIST’s AI Risk

Management Framework, OSTP’s Blueprint for an AI Bill of Rights

• Advantages:

» Promotes innovation, with minimal disruption to business models.

» Encourages collaboration and consensus among stakeholders (e.g., tech companies, civil

society organizations, policymakers, and academics).

• Limitations:

» No enforcement mechanisms, so no legal remedies are available for violations.

“Hard” law – enforceable requirements and regulations

• While global actors like the EU or China pass binding legislation, the US faces a

regulatory gap, as “hard” law falls behind “soft” law (often faster to implement).

» Federal legislation on AI is still pending, and some states have introduced their own bills.

• Challenges:

» “Hard” law requires bipartisan support to pass.

» State and federal agencies need resources to exercise proper oversight.

Source: Soft Law in AI Governance | Brookings; How California and Other States are Tackling AI Legislation | Brookings 
17

Examples from EU Legislation

• Different approaches for different environments (cf. Alex Engler)

• General Data Protection Regulation (GDPR)

» AI needs human supervision to make decisions affecting legal rights.

» Individual right to “meaningful information about the logic” of an automated 

system

• Proposed AI Act: Tiered system

» Deepfakes, chatbots, biometric analysis, etc.

– Mandatory disclosure

» High Risk: Regulated consumer products and AI used for impactful 

socioeconomic decisions

– Standards of data quality, accuracy, and non-discrimination

– Technical documentation, record-keeping, risk management, and 

human oversight

» Unacceptable Risk: AI for social scoring, emotion-detecting FRT

– Banned

• Digital Services Act (DSA)

» Requires large platforms to explain automated recommendation systems.

Source: The EU and U.S. diverge on AI regulation | Brookings
18

Current U.S. Policy Proposals

• The U.S. approach is “risk based, sectorally specific, and 

highly distributed across federal agencies.”

• Agencies required to develop AI regulation plans

» Executive Order 13859 (2019) and OMB Guidance M-21-06

» Most have not done so

• Potentially more multistakeholder-focused to improve sociotechnical cadence:

» Consumer Financial Protection Bureau (CFPB) requires 

explanations for credit denials by AI

» Food and Drug Administration (FDA) publishes best practices 

for AI in medical devices

» Consumer Products Safety Commission (CPSC) issued a draft 

report on how to test and evaluate consumer machine learning 

products

» “Energy star rating” multistakeholder practices 

• Discussions on standards and licensing, consumer 

disclosures

• Calls for federal privacy legislation

Source: The EU and U.S. diverge on AI regulation | Brookings
19

U.S. Implementation Siloes

• White House Office of Science and Technology Policy

(OSTP): Blueprint for an AI Bill of Rights (AIBoR)

» Voluntary roadmap for agencies for responsible AI

» Articulates five broad principles for mitigating AI harms

• National Institute of Standards and Technology (NIST):

AI Risk Management Framework (RMF)

» Voluntary roadmap for developing responsible AI

» Offers comprehensive suggestions for mitigating risk

throughout the AI lifecycle

Source: The EU and U.S. diverge on AI regulation | Brookings; Opportunities and blind spots in the White House’s blueprint for an AI Bill of 

Rights | Brookings
20

What’s needed

• Less segmentation and more clarity over 

jurisdictional authority in the U.S. – Where should 

authority be placed, or should it be more distributed?

• Potential harmonization with EU regulation –

What’s worthwhile to explore?

• Sectoral regulations – How should existing 

regulation and best practices be integrated into 

discussions?

• Emerging technologies – What about the use and 

regulation of generative AI?

• Self-regulation – With current calls from industry, 

should we trust voluntary commitments as the next 

viable option?
21

What the Commission should be exploring

• The structure and impact of clear, sector-specific

industry standards can promote safety of AI systems.

• The role of regulation or suggestive guidance in the

trading marketplace versus voluntary commitments.

• The impact of a civil rights-based review for any AI

system that could affect individuals’ legal rights.

• The positioning of consumer and industry disclosures.
22

THANK YOU!

Nicol Turner Lee, Senior Fellow and Director of the 

Center for Technology Innovation, Brookings Institution 

nturnerlee@brookings.edu

@drturnerlee (Twitter) and Nicol Lee (LinkedIn)
1

Impact Assessment of AI on 

Cybersecurity Threats

Dan Guido, Co-founder & CEO, Trail of Bits

CFTC Technology Advisory Committee (TAC) Meeting

July 18, 2023 
2

AI capabilities are rising rapidly, or are they?

AI is effectively magic and ready to take 

over for general intelligence.

AI is useless and parrot out nonsense 

from their training data.

Proponents Opponents

“GPT-4 performed poorly at building 

exploits for the vulnerabilities” - OpenAI

... sometimes these are the same people:

“TL;DR: Don’t use ChatGPT for security code review. It’s not 

meant to be used that way, it doesn’t really work (although you 

might be fooled into thinking it does), and there are some other 

major problems that make it impractical. Also, both the CEO of 

OpenAI and ChatGPT itself say that you shouldn’t.” 

- NCC Group 

- The Atlantic

- Microsoft Research
3

What we realized:

● AI is just another tool, not magic

● Ask the right questions

● Evaluate progress correctly

● Choose the right problem

Don’t obsess about complete 

automation. What constraints are 

blocking humans from being more 

productive?

Our successes with AI:

● Decompile code into high-level 

languages

● Identify and trigger bugs

● Reason about memory layouts

● Write scripts to launch exploits

● Identify weak static encryption

● Find cryptographic API misuse

It won't write an exploit for you, but it 

can make exploit writing more 

productive.

Empirical results from Trail of Bits
4

What can AI [currently] do?

Requires Mastery

Prizes Broad Knowledge

Mistakes Acceptable

Perfection Required

Document This 

Function

Find and Exploit 

iOS 0day

Reverse Engineer 

Custom firmware 

and OS

Decompile to Rust

Write an 

Ethereum AMM

Optimal 

AI Usage

Phishing

Email
5

Fields that are disrupted first

Phishing training 

You can create 

native-speaker level 

human language at speed 

and scale now

● ChatGPT may already 

know about you. It 

knows me!

● “Write a perfect 

phishing message for 

Dan Guido.”

Bug bounties

● Incentives align 

perfectly to spam 

bounty submissions 

with AI

● ChatGPT’s reports 

sound plausible and 

are written well

● Only a highly paid 

expert can unravel the 

mystery.

It’s asymmetric warfare,

and incentives align against these specific defenses

Signature-Based 

Defenses

Changing signatures is a 

language translation 

problem. AI is very good 

at language translation 

problems. E.g., IDS, AV.

Attacker 

Attribution

Attribution is style 

detection; AI is very good 

at style transfer.
6

Alignment will not save you

● RLHF-based alignment doesn’t work

○ Output censorship is an unwinnable task that 

mainly frustrates amateurs and researchers

○ AI can’t unlearn it was trained on hacking 

techniques

○ Example: “DAN” aka “Do Anything Now”

● Open-source models are available

○ Not bound by US regulations. Current best open 

source model (Falcon-40B) is from the UAE.

○ They are becoming quite good

○ Criminals are already using them
7

Their limits are unknown without measurements

● ML evaluations have focused on programming, not cybersecurity

○ No effective systematic evaluations for emergent cyber capabilities

● Needed: taxonomies and benchmarks for offensive capabilities

○ Model capabilities versus those of state-of-the-art security tools

○ Compare capabilities of human operators with varying expertise using LLMs

○ Classify opportunities/risks of downstream impacts
8

When does AI fundamentally change industry risk?

1. Looking past hype and advertising

○ Is the problem in the training set? Think “GPT4 passes the LSAT”

○ Does the output generalize past one or few examples?

○ What happens when the AI is wrong? It will be wrong.

2. We need more measurement

○ Task specific data sets and evaluation frameworks

3. Identifying risk-changing capability

○ Does this remove a hard constraint for me (or my adversaries?)

○ How rapidly is the capability likely to improve?

○ Is there a synergy with existing, unrelated technologies?

○ Are mistakes acceptable, or easy to catch?
9

AI is a systemic threat to cybersecurity

● Algorithmic tools are not disappearing

● More local and open source models and infrastructure

● Prepare for disruption today, because it’s coming

● With investment, defense may benefit more from AI

@dguido dan@trailofbits.com trailofbits.com

Resources

Can AI beat humans in 

security audits?

How to measure 

safety of AI-based 

systems

What effect will AI have 

on national security?

Curated references 

for ML security

Short-term predictions

● AI changes the cost model for attackers and defenders

● AI will augment human capability, not replace it

● Alignment is a distraction: potential harms are here today

● Measurement is needed to eliminate surprise

Key takeaways
Global Markets Advisory Committee

Topic 2: Regulatory Issues for DeFi, Including DAOs
Enforcement Case Study: Ooki DAO

Anthony Biagioli, Special Counsel to the Director, 

Division of Enforcement, CFTC

July 18, 2023
Enforcement Case Study: Ooki DAO

• Mechanics of opening leveraged position on bZx Protocol (later

Ooki Protocol) (simplified sample):

Privileged and Confidential 25
Enforcement Case Study: Ooki DAO

• Statement of bZeroX, LLC founder to DAO community upon 

creating the DAO.

Privileged and Confidential 26
Enforcement Case Study: Ooki DAO

• N.D. Cal. holds: Ooki DAO can be sued as unincorporated association.

Privileged and Confidential 27
Enforcement Case Study: Ooki DAO

• N.D. Cal. holds: Ooki DAO can be served as unincorporated association.

Privileged and Confidential 28
Enforcement Case Study: Ooki DAO

• N.D. Cal. holds: Ooki DAO is a “person” under the CEA.

Privileged and Confidential 29
The analyses and views expressed herein are those of the authors and do not 

necessarily reflect the views of the Commission or CFTC Staff.

DISCLAIMER

30
“the term (DAO) is only understood today as organizations deployed 

as smart contracts on top of an existing blockchain network” ~ 

Wikipedia

In a traditional system: These systems are reflected in articles, 

complemented by internal policies, and overseen by committees, 

boards, and other standard governance methods.

Shifting focus to smart contracts

Parallels
Key differences moving from traditional to smart contracts

Meeting / vote Signing ceremony
Outcomes of voting

Vote is private by default Vote is public by default
Smart contracts can engage in regulated functions, but not all do

If a smart contract engages in a regulated function on behalf 

of someone, it is the same as any other computer code 

executing a similar function.

Smart contracts can also be used as a regulated entities basic 

voting and recording mechanisms or to create products.

Using smart contracts as a governance model

Token holders can vote as a traditional board would 

vote on an initiative. 

Smart contracts can subsequently reference other 

smart contracts to automate various behaviors.
contract BonusDAO {

// Structure to represent a payment proposal

struct PaymentProposal {

address payable recipient; // Address to receive the payment

uint256 amount; // Amount to be paid

uint256 yesVotes; // Total "yes" votes

uint256 noVotes; // Total "no" votes

bool released; // Flag indicating if the payment has been released

mapping(address => bool) voted; // Mapping to keep track of voters

}

address public admin; // Address of the contract administrator

mapping(uint256 => PaymentProposal) public proposals; // Mapping of proposal IDs to PaymentProposal objects

uint256 public proposalCount; // Total number of payment proposals

// Events to be emitted

event ProposalCreated(uint256 indexed proposalId, address indexed recipient, uint256 amount);

event Voted(uint256 indexed proposalId, address indexed voter, bool indexed inSupport);

event PaymentReleased(uint256 indexed proposalId, address indexed recipient, uint256 amount);

// Modifier to restrict access to the contract administrator

modifier onlyAdmin() {

require(msg.sender == admin, "Only the contract administrator can perform this action");

_;

}

// Modifier to check if a proposal exists

modifier validProposal(uint256 proposalId) {

require(proposalId > 0 && proposalId <= proposalCount, "Invalid proposal ID");

_;

}

constructor() {

admin = msg.sender; // Set the contract creator as the administrator

}

// Function to create a payment proposal

function createProposal(address payable _recipient, uint256 _amount) external onlyAdmin {

proposalCount++;

proposals[proposalCount] = PaymentProposal(_recipient, _amount, 0, 0, false);

emit ProposalCreated(proposalCount, _recipient, _amount);

}

0x2d78d40DcFb4C0299B312EaF0374c7Df591FDd64 

0x7dA7B2eFc4Bdd071Cb8c2c0d6B4Df4893f9EF482 

0xA6aD84Dc84Cb63F405E6857bDa208C91Ea6531E5 

0xFf75171B2a4b7c35C1cC29C10d61C75d80a4BdB1 

0x4c7D15Cd5e4a6D2e7c692e6D64873A246Cdb1b17 

0xd768f3cD63d9804f2b1fDe4C8d9D4EfACab0dEf6 

0x9f8d6E8265EF60AcF4Ad546a723603a3A3710E5A 

0xB77B0D99f1799c22A8e2e4d972B79AC8E1a9F96f 

0xC90a33aC6aC4b193dEECE66D37D2DD045eC6029F 

0x1458d8EaaDd3Bf7F70a1544E7b4De734De5cC2e5 

0x826cC1C06eDD0079CFeD18F63dF71B3e1B535d04 

0xF4f2c6A1f3dD06625eB3D066B079f5f3fCf5Ae94
contract BonusDAO {

// Structure to represent a payment proposal

struct PaymentProposal {

address payable recipient; // Address to receive the payment

uint256 amount; // Amount to be paid

uint256 yesVotes; // Total "yes" votes

uint256 noVotes; // Total "no" votes

bool released; // Flag indicating if the payment has been released

mapping(address => bool) voted; // Mapping to keep track of voters

}

address public admin; // Address of the contract administrator

mapping(uint256 => PaymentProposal) public proposals; // Mapping of proposal IDs to PaymentProposal objects

uint256 public proposalCount; // Total number of payment proposals

// Events to be emitted

event ProposalCreated(uint256 indexed proposalId, address indexed recipient, uint256 amount);

event Voted(uint256 indexed proposalId, address indexed voter, bool indexed inSupport);

event PaymentReleased(uint256 indexed proposalId, address indexed recipient, uint256 amount);

// Modifier to restrict access to the contract administrator

modifier onlyAdmin() {

require(msg.sender == admin, "Only the contract administrator can perform this action");

_;

}

// Modifier to check if a proposal exists

modifier validProposal(uint256 proposalId) {

require(proposalId > 0 && proposalId <= proposalCount, "Invalid proposal ID");

_;

}

constructor() {

admin = msg.sender; // Set the contract creator as the administrator

}

// Function to create a payment proposal

function createProposal(address payable _recipient, uint256 _amount) external onlyAdmin {

proposalCount++;

proposals[proposalCount] = PaymentProposal(_recipient, _amount, 0, 0, false);

emit ProposalCreated(proposalCount, _recipient, _amount);

}

0x2d78d40DcFb4C0299B312EaF0374c7Df591FDd64 

0x7dA7B2eFc4Bdd071Cb8c2c0d6B4Df4893f9EF482 

0xA6aD84Dc84Cb63F405E6857bDa208C91Ea6531E5 

0xFf75171B2a4b7c35C1cC29C10d61C75d80a4BdB1 

0x4c7D15Cd5e4a6D2e7c692e6D64873A246Cdb1b17 

0xd768f3cD63d9804f2b1fDe4C8d9D4EfACab0dEf6 

0x9f8d6E8265EF60AcF4Ad546a723603a3A3710E5A 

0xB77B0D99f1799c22A8e2e4d972B79AC8E1a9F96f 

0xC90a33aC6aC4b193dEECE66D37D2DD045eC6029F 

0x1458d8EaaDd3Bf7F70a1544E7b4De734De5cC2e5 

0x826cC1C06eDD0079CFeD18F63dF71B3e1B535d04 

0xF4f2c6A1f3dD06625eB3D066B079f5f3fCf5Ae94

contract TradeExecutor {

address public contractToWatch; // Address of the contract to 

monitor

address public tradeCounterparty; // Address of the trade 

counterparty

uint256 public tradeAmount; // Amount to trade

constructor(address _contractToWatch, address 

_tradeCounterparty, uint256 _tradeAmount) {

contractToWatch = _contractToWatch;

tradeCounterparty = _tradeCounterparty;

tradeAmount = _tradeAmount;

}

function executeTrade() external {

// Assume some behavior is being monitored in the 

contractToWatch

// When the desired behavior is observed, execute the trade

// Here, we assume the desired behavior is calling a specific 

function

// Check if the desired function has been called in the 

contractToWatch

bool desiredBehavior = 

ContractToWatch(contractToWatch).hasCalledFunction();

if (desiredBehavior) {

// Perform the trade with the tradeCounterparty

// ... perform the trade logic here ...

// For the sake of example, let's assume it transfers Ether to the 

tradeCounterparty

payable(tradeCounterparty).transfer(tradeAmount);

}

}

}

contract ContractToWatch {

// Assume some behavior being monitored

function hasCalledFunction() external pure returns (bool) {

// ... implementation of the desired behavior ...

// For the sake of example, let's assume it returns true

return true;

}

}
1. Speed / Cost

a. Blockchain

2. Privacy / Security

a. Blockchain

3. Regulatory Mapping

a. Blockchain-agnostic

Considerations
Speed/Cost
Balancing centralization vs. decentralization (privacy/security)

● Hypothetically, the smart contract is deployed on a decentralized protocol. It could be deployed on a private 

centralized blockchain.

● What is still centralized? Who can vote? Who can update the contract? Who holds the keys? Where the 

people are, where the customers are, what the products are. The blockchain could also be centralized.. 

Confused yet?
Permissed/Private based blockchains are now viable
Hypothetical use of smart contracts in current regulatory structure

Many participants, all could be known to one another. All are known to the regulator. 

Different participants might have different powers or use different blockchains or a hybrid database 

approach. Some votes or acknowledgements may be required to be private.

0xd8dA6BF26964aF9D7eEd9e03E

53415D37aA96045

Use smart contracts when they solve a problem 

and focus on mapping them to the existing 

regulation. This should work wonderfully & provide 

an audit trail of decisions made.

Immediate applications
Technology & people regulation

When smart contracts are operated by people, regulation is applied to the jurisdictions where the operators 

are, where the end user is, and the functions of the project. Same as technology built on traditional 

databases. 

Starting at first principles and understanding the technology, we can understand how much of our current 

regulation applies to the new technology. Only then, can we really appreciate what new regulation is needed 

to create additional coverage.
Who should be treated as the responsible operator of a smart 

contract engaging in a regulated function? Voter / key holder / 

benefactor / contract deployer?

How does regulation apply when a person is not involved in the 

creation of the code, it is entirely decentralized, and there is no 

personal benefit?

Open questions

Decentralization, DeFi & 

Governance

What DeFi is, what it can be, and what it means for 

regulation
Context

● Defi remains a relatively recent innovation, even for crypto 

● Four key concepts

○ Self custody

○ Autonomous

○ Transparent

○ Interoperable and Composable

● Decentralization is a spectrum, not a toggle
DeFi in the Wild 
DeFi Governance

● Natural tension between heavy governance and DeFi

○ Our view is the core virtue of DeFi is credible neutrality

■ Dependability

■ Avoiding capture

○ By definition, the greater the governance, the greater the risk of capture

● The true value of DeFi is found when the governance itself could be said to

shrink down to the point of imperceptibly
What DeFi Governance is Not

● Something that can ever fully go away

○ Essential governance

● Constant formality

○ Stakeholders groups are protean
The Optimal Approach: Governance Minimization

● Flexibility

○ Game theory-driven systems

● Distinguish between tokenholders and stakeholders

○ Not all stakeholders will be tokenholders

○ Stakeholders change over time

● Connection between a core mechanism and human input

○ Consensus itself

○ Oracles

○ Treasury Management

○ Complex Parameter Setting
Governance is not a Panacea

● Risk of Hard Forks

○ Social cost to violating credible neutrality

● Changing governance somewhere does not mean changing it everywhere

● “If the point of a blockchain is to provide a ledger of universally accepted 

truth, its integrity is paramount”
Insights for Regulation

● Inessential governance is likely to be competed away over time

● Data, data, data

● Principles, regulations, and code

● The dangers of DINO
Questions
DeFi and the First Law of Regulation

CFTC Technology Advisory Committee | July 2023

62
Defining decentralization

• In order to regulate “decentralized” financial activities, we first need to understand what 

we’re talking about. Decentralization has several overlapping dimensions:

• Development (who makes initial and ongoing design decisions)

• Governance (who makes residual decisions)

• Operational (who carries out decisions)

• Balance sheet (who owes what to whom)

• Transactional (who executes, clears, and settles transactions)

• These dimensions can be combined in different ways, in the context of different financial 

activities, posing different risks (but that’s a story for another day).

63
Regulating decentralization

• An observation: existing regulatory frameworks and approaches rely heavily on a relatively 

high degree of centralization across each of these dimensions.

64

Regulated actors

Identifying desired outcomes

Writing and updating rules

Monitoring compliance

Enforcing violations
Regulating decentralization

• An observation: existing regulatory frameworks and approaches rely heavily on a relatively

high degree of centralization across each of these dimensions.

65

Identifying desired outcomes

Writing and updating rules

Monitoring compliance

Enforcing violations

Regulated actors

Centralization enables 

delegated responsibility
Regulating decentralization

• Another observation: once we introduce significant decentralization, we need to ask whether 

and how these frameworks need to be adjusted in light of the First Law of Regulation.

66

Identifying desired outcomes

Writing and updating rules

Monitoring compliance

Enforcing violations

???

Decentralization makes 

delegated responsibility more 

complicated
Regulating decentralization

• Some questions in light of these observations:

• How does the regulatory perimeter need to change to encompass decentralized

actors and activities?

• When, how, and on what terms should regulators delegate regulatory functions

and responsibility to decentralized actors?

• How should these functions and responsibility be divided up between actors in

different decentralized financial ecosystems?

• To what extent can regulatory functions be technologically embedded within these

ecosystems? Where should they be embedded? And what role for humans?

• How can these ecosystems, and the regulatory frameworks that govern them, be

made more robust to changes in markets and regulation over time?

67
Global Markets Advisory Committee

Topic 3: Cyber Resilience for Financial Markets
Final Interagency Guidance on ThirdParty Risk Management

CFTC Technical Advisory Committee Meeting

Kevin Greenfield, OCC

July 18, 2023
Background 

• On July 13, 2021, the OCC, Federal Reserve, and the FDIC 

published Proposed Interagency Guidance on Third Party 

Relationships: Risk Management and issued the final guidance on 

June 6, 2023, addressing industry feedback..

• OCC Bulletin 2023-17, “Third-Party Relationships: Interagency 

Guidance on Third-Party Relationships: Risk Management,” rescinds 

the following:

– OCC Bulletin 2013-29, “Third Party Relationships: Risk 

Management Guidance”

– OCC Bulletin 2020-10, “Third Party Relationships: Frequently 

Asked Questions to Supplement OCC Bulletin 2013-29” 

70
Risk Management

• Sound risk management includes tailoring of risk management

practices commensurate with:

– the bank’s size, complexity, and risk profile,

– risks associated with services provided, and

– the nature of the third-party relationship.

• Role of bank management and board.

• Characteristics of critical activities

• Oversight of relationships that support higher-risk activities, including

critical activities.

• .Risk Management Life Cycle

71
TPRM Life Cycle

72
TPRM Life Cycle Components

Component Highlight

Planning Activities should be aligned with the risk 

presented by the third-party relationship

Due Diligence and 

Third-Party 

Selection

• General approaches to due diligence.

• Examples of more specific considerations 

(e.g., subcontracting relationships). 

Contract Negotiation • Scope and terms of contracts 

• Performance measures

• Treatment of bank information

• Operational resilience and business continuity

• Subcontracting

73
TPRM Life Cycle Components (Continued)

Component Highlight

Ongoing Monitoring • Comprehensiveness and frequency based on 

risk and complexity of relationship. 

• Role of reports, testing, and visits in 

monitoring.

Termination Consider ahead of time

74
Key Takeaways

• Each bank remains responsible for developing and implementing

risk management practices commensurate with the banks size,

complexity, and risk profile and with the nature of its third-party

relationships.

• Banks remain responsible for their activities, whether conducted

internally or through a third party.

• Principles-based guidance can assist banks develop effective thirdparty risk management processes.

• Banks are responsible for assessing risk and tailoring their risk

management practices.

• Third-party relationships can take different forms, and the roles of

the third party and the bank may differ among individual

engagements.

75
Professor Hilary J. Allen

CFTC Technical Advisory Committee Presentation:

Challenges with Understanding 

Cybersecurity Risk 

Implications for Operational Risk Regulation
Efficiency v Robustness Tradeoff

The literature on complex systems 

talks about the such systems being 

“robust yet fragile”

• Beware too much focus on 

efficiency and not enough focus on 

redundancy/ability to reconfigure in 

times of stress or change 

• When does increasing efficiency 

start to be counterproductive?
Underappreciated Operational Threats

Cyberattacks get most of the 

attention, but:

•By some estimates, losses are 

greater from accidental tech 

glitches

•Operational threats from climate 

change can have similar impacts 

but receive less attention 
Technological Transmission Channels 

for Systemic Risks

We also tend to ignore some of the 

systemic dimensions of operational risk

• Operational risk is typically considered as 

idiosyncratic to individual institutions 

• That misses the possibility that 

operational problems can be 

transmitted from bank to bank through 

technological channels

• A “macro-operational” perspective is needed
All materials © Nardello & Co. 2023

Trusted global investigative expertise 

for today’s complex world.
All materials © Nardello & Co. 2023

Challenges with Understanding Cybersecurity Risk 

Implications for Operational Risk Regulation

Timothy Gallagher

Managing Director and Chief Security Officer

Digital Investigations & Cyber Defense

CFTC Technical Advisory Committee
All materials © Nardello & Co. 2023

- Cybercrime was responsible for over $10 billion in losses in 2022 (FBI – IC3)

- 300 million fraudulent signon attempts to the cloud are made every day 

(Microsoft)

- 53% of businesses have experienced a third party breach in the past year 

(Ponemon Institute)

- 60% of businesses that experience a cyber attack close their doors within 6 

months (National Cyber Security Alliance) 

Threat Environment
All materials © Nardello & Co. 2023

- Preparation

- Replication

- Recovery 

Cyber Resilience
All materials © Nardello & Co. 2023

- Principle of Least Privilege

- Multi Factor Authentication

- Third Party Vetting 

- Managed Detection & Response

Doing the Little Things Right
Overview of Sector Cybersecurity and Risks –

CFTC Technology Advisory Committee

Steven Silberstein, CEO. 18 July 2023 
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 86

Who is FS-ISAC?

Our Members Are:

Banks | Community Institutions | Credit Unions | Insurance Companies | Investment Firms | Financial 

Markets Infrastructure | Fintechs | Payment Processors | Credit Reporting Agencies | Service Providers & 

MSSPs

FS-ISAC is the member-driven, not-for-profit organization

that advances cybersecurity and resilience in the global 

financial system, protecting financial institutions and the 

people they serve. 

Founded in 1999, the organization’s real-time information 

sharing network amplifies the intelligence, knowledge, and 

practices of its members for the financial sector's collective 

security and defense. Member financial firms represent more 

than $100 trillion in assets in 75 countries. 

Mission

FS-ISAC advances cybersecurity and 

resilience in the global financial system, 

protecting financial institutions and the 

people they serve. 
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 87

A Global Community Protecting the Global Economy

No one firm can anticipate every threat, everywhere, all the time in

a digital world where every device, user, and supplier is a potential

entry point for threat actors.

But we don’t need to fight alone. While financial services is one of the

world’s most competitive industries, we are also highly interdependent.

We therefore collaborate to reduce cyber risk in the sector.

FS-ISAC acts as a force multiplier of intelligence, knowledge, and

practice focused on the financial sector’s cybersecurity and resilience,

so that all may benefit from the experience and expertise of individual

firms, no matter where they are. We can do this because we have

spent nearly 25 years building a trusted community with wellestablished sharing protocols.

Regardless of maturity and scale, all FS-ISAC members can 

integrate actionable insights gained from participation into their 

firm’s feedback loops for improving their own security and resilience, in 

turn reducing cyber risk across the global financial system.

Trust is the bedrock

Cybersecurity is not a solo sport

Participation ensures our collective security

Cooperation yields far greater rewards
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 88

FS-ISAC by the Numbers

7

5

>$100

Trillion in assets

Our members represent

>22,00

0

Our intelligence exchange has

active users

Our members 

are based in

countries

5200

Our community

is present in

member firms
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 89

Three Pillars of Offerings: A Virtuous Cycle of Advancing Resilience

FS-ISAC’s three pillars of offerings, Intelligence, Security, and 

Resilience, allow member firms to tap into crowdsourced and enriched 

intelligence, security knowledge, and resilience practices to integrate into 

their own firm’s feedback loops for reducing cyber risk. 

Enables security 

teams to prioritize 

and focus on current 

and emerging threats

Intelligence

Security 

Resilience

Knowledge-sharing and collective 

work on best practices improves 

resilience; exercise results feed 

back into security improvements

High-quality intel sourced 

by the entire sector 

informs exercise 

scenarios

Intelligence Security Resilience

Sector-specific security 

alerting and finished 

intelligence analysis

IntelX: member platform for 

accessing intel offerings

Automated feeds

Regional threat calls

Topical/incident-focused 

spotlight calls

Threat Intelligence Committee

Trusted communities 

based on sub-sector, 

geography, functions

Topical working groups

Summits and regional 

events for knowledge 

sharing

Community email lists

Expert webinar series

White papers & guides

Exercises

Incident response support

Playbooks

Critical Providers Program

Business resilience 

committee

Risk

Reduction
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 90

Resilience | Advance financial services sector resilience

Members build the muscle 

memory and concrete 

procedures to respond to 

attacks through exercises, 

training, and playbooks. 

FS-ISAC coordinates sector, 

cross-sector, and public-private 

incident response to largescale threats and enhancement 

of operational resilience.

Overview Key Offerings

• Exercises

o CAPS: on-demand, discussion-based exercises with scenarios informed by FS-ISAC threat intelligence, 

customized for banking, securities, and insurance sub-sectors

o Cyber-range: technical, hands-on-keyboard exercises to improve tactical incident response

o Functional: Act out policies and procedures at firm and sector levels in response to large-scale attack

o Tabletop: Strategic discussions based on plausible scenarios with fellow members and other sector 

partners

o Cross-Sector: FS-ISAC coordinates member participation in exercises such as NATO’s Locked Shields, 

Tri-Sector, CyberStorm, GridEX and more.

• Incident Response

o TLP Red (confidential) support for targeted organization

o Communication channels to inform and support impacted members and wider membership as appropriate

o One-to-many conduit for third parties to reach entire sector with real-time intelligence and mitigation advice

o Cross-border, sector-wide, and public-private coordination during incidents

o Development and refinement of sector-level incident response playbooks and firm-level playbook templates

• Critical Providers Program

o Sector-wide insights from key sector suppliers (e.g. Akamai, Google Cloud) as well as direct, real-time 

communication channels during an incident

• Business Resilience Committee

o Steers regional resilience efforts, helps organize and develop scenarios for regional exercises, votes on 

sector’s current operational resilience risk level, contributes to incident response playbook.
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 91

Incident Response Case Study: MOVEit

Uniting our community to respond to a common third-party vulnerability

Global Intelligence Office Activities

• Notify all members and critical third parties who have been 

impacted (listed on leak site)

• Offer support into their internal investigation

o Research on IOCs

o Intel on threat actor (Cl0p)

• Dedicated Connect (secure member chat) channel with daily updated 

victim lists

• Briefs by Intel Office and external experts on Threat Calls

Support Security Teams

• Mitigation guidance

o File transfer hardening guidance

• Threat hunting intelligence

o TTPs for sprints

Act as Sector Representative

• Sharing liaison within FS-ISAC

• With governments and publicprivate partnership groups

• Media spokesperson 
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 92

v

v

Maintaining a Trusted Community 

Traffic Light Protocol (TLP)

When should it be used? How may it be shared?

Sources may use TLP GREEN when information is

useful for the awareness of all participating

organizations as well as with peers within the broader

community.

Recipients may share TLP GREEN information with

other members, trusted government and critical

infrastructure partner organizations, and service

providers with whom they have a contractual

relationship, but not via publicly accessible channels.

TLP GREEN

Sources may use TLP WHITE when information carries

minimal or no foreseeable risk of misuse, in accordance

with applicable rules and procedures for public release.

TLP WHITE information may be distributed without

restriction, subject to copyright controls

TLP WHITE

TLP RED Sources may use TLP RED when the information’s

audience must be tightly controlled, because misuse

of the information could lead to impacts on a party’s

privacy, reputation or operations. The source must

specify a target audience to which distribution is

restricted.

Recipients may not share TLP RED information with

any parties outside of the original recipients.

TLP AMBER Sources may use TLP AMBER when information

requires support to be effectively acted upon, but carries

risk to privacy, reputation or operations if shared outside

of the organization’s involved.

Recipients may only share TLP AMBER information

with staff in their own organization who need to know or

with service providers to mitigate risks to the member’s

organization if the providers are contractually obligated

to protect the confidentiality of the information.

Information can be shared with those parties specified

above only as widely as necessary to act on the

information.

Designations
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 93

FS-ISAC Subsidiaries 
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 94

Securities Industry Risk Group

 Dedicated group for all FS-ISAC Members in the 

Securities & Investment Industry

 More than 1,100 Members from over 450 Firms

SIRG

Alternative 

Investors Council

Asset Managers 

Council

Broker Dealer 

Council

Futures 

Commission 

Merchants Council

Retirement 

Industry Council
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 95

Core Back Office 

Supplier

1

4%

Critical Utility

3

14%

Exchange - Commodities

4

18%

Exchange -

Currency

3

14%

Exchange - MultiAsset Class

3

14%

Payments - Processor

2

9%

Retail Banking -

Commercial Bank

1

4%

Securities & 

Investments - Banking

1

4%

Securities & 

Investments - Broker 

Dealer

1

5%

Securities & 

Investments - Clearing 

& Settlement

3

14%

The CHEF — Clearing House and Exchange Forum

 Membership from 22 clearing houses and exchanges globally

 Two geographically focused sub-groups:

 United States - ~40 individuals

 Global - ~24 individuals

 Strategic Initiatives include:

 Intelligence Feeds

 Business Resiliency

 Employee Retention

 Identify essential common external functions

 Incident Response unique to the needs of the CHEF

 NZ Stock Exchange Outage due to DDOS

 ION Trading Derivative Processing Outage
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 96

The Threat Landscape Going Forward

The sector’s attack surface is ever expanding with the proliferation of operationally important service providers 

required to be competitive in a digital world.

Customers continue to be weakest link the system and fraud/account takeover/identity theft is rising.

The required response time for fixing published vulnerabilities is approaching zero.

Ransomware-as-a-Service (and related attacks) still has a positive ROI although tactics are changing

Vulnerabilities are continually discovered, and new exploitive technologies are constantly being deployed, so 

today’s advanced protections become tomorrow’s baseline...
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 97

Strategic Threats Need Addressing Sooner than Later

Rewiring the eco-system with quantum computing resistant cryptographic algorithms

Ensuring Generative AI does not disrupt our Identity ecosystem

Increasing end-user security cannot become an obstacle for the digitally challenged

MDM (mis/dis/mal information) can erode the trust of our institutions

The evolving technical landscape 1-5 years out requires a long runway to implement necessary changes
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 98

The Sector has Collaborated on It’s Core Resiliency...

Key FBIIC-FSSCC Collaborations:

The sector-wide “All Hazards Playbook” and CERG (Core Executive Response Group) was stood up for 

COVID-19 on 30 Jan 2020, and continued to operate through Solar Winds to the Russia/Ukraine Invasion.

Hamilton Exercises continue to advance the learnings on new and unexpected events

ION Trading outage demonstrated good collaboration between CFTC/FBIIC/FIA/FS-ISAC/SIFMA

Cloud Security Workstreams – Public Sector/Private Sector/Joint projects

Critical Functions Definitions

With Public-Private-Partnerships to foster resiliency, incident response and supply chain security:
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 99

FS-ISAC’s Supply Chain Efforts

Created a unique “Critical Provider Program” for mission critical suppliers

“Software Supply Chain” Working Group focused on SBOM adoption

Encouraged Back-Office suppliers and Payment Processors to join

Leading one of the FSSCC Cloud Work Streams on resiliency 

Evolving our CAPS exercises to sub-sector specific scenarios for better training

Investing in our Business Resiliency Community of Interest
CFTC TAC - 18Jul2023 TLP WHITE © 2023 FS-ISAC, Inc. | All rights reserved. 100

Thank you
Global Markets Advisory Committee

Closing Remarks