CypherTalk

Have you heard of Brave? Today we are joined by Kyle Den Hartog, a security engineer at the privacy browser. His path runs from penetration testing to self-sovereign identity to Web3, and that bridge between the Web2 and Web3 worlds runs through the whole conversation.
They start with how Brave made privacy mainstream: sane defaults and treating privacy as an emergent property that has to be fought for at every layer, with surveillance capitalism as the threat model rather than Tor-style maximalism. From there, why the biggest problems are no longer smart-contract bugs but browser and interface attacks, and a sharp point about domain expertise: crypto wallet teams often don't realise the browser already solves their problems (MetaMask's phishing list vs Safe Browsing, Rabby leaking browsing history vs hash-prefixing). It's also why Brave built its wallet into the browser rather than as an extension.
The most provocative stretch is Kyle's argument that Web3 is accidentally reintroducing cross-origin tracking. A wallet address is just a cookie: shared across sites on "connect," and far more revealing than any third-party cookie because it exposes where, when, and how much you spend. His fix is the thick client, moving transaction-building into the wallet so untrusted sites never receive the address.
The conversation then ranges across why zero-knowledge proofs aren't the panacea they're treated as (the "20 questions" problem), how ZK-gated compliance can recreate the gatekeeping Web3 set out to escape, why the early internet's lack of an identity layer was a feature, and a thoughtful take on age verification. Kyle closes on what Web2 and Web3 get wrong about each other, and his practical privacy advice beyond switching to Brave: a reputable audited VPN, then moving off the platforms that track you most.
Key Topics
How Brave made privacy mainstream, and the browser as the real attack surface
Why a wallet address is the new tracking cookie, and the "thick client" fix
The limits of zero-knowledge proofs, identity, and getting age verification right
Chapters
00:00 Introduction
00:35 From Penetration Testing to Self-Sovereign Identity to Brave
01:49 Making Privacy Mainstream: Sane Defaults and Emergent Privacy
04:34 The Brave Wallet, BAT, and Rethinking What the Infrastructure Is For
07:07 The Browser as Attack Surface: What Browsers Can Actually Do
10:06 Why Crypto Wallet Teams Miss What the Browser Already Solves
13:55 Why the Brave Wallet Is Built In, Not an Extension
16:02 Web2 Guy or Web3 Guy? Why Brave Over a Pure Web3 Protocol
19:05 How the Brave Wallet Compares, and the Pivot to Payments
21:56 How Web3 Is Reintroducing Cross-Origin Tracking
24:55 The Wallet as Cookie: Leaking Where You Spend Your Money
26:59 The "Thick Client" Fix
29:47 Are Zero-Knowledge Proofs a Silver Bullet? The 20 Questions Problem
34:20 Recreating Centralised Gatekeeping and the KYC Tension
38:27 Why the Early Internet Had No Identity Layer
42:00 Getting Age Verification Right: Moderation vs Who Decides
49:02 AI at Brave, and AI as a Tool
50:36 What Web2 and Web3 Get Wrong About Each Other
52:31 Practical Privacy Advice Beyond Switching to Brave
54:12 Where to Find Kyle, and What's Next for the Wallet
Resources and Links
Kyle on X: https://x.com/PryvitKyle
Kyle's website and blog: https://kyledenhartog.com
Brave: https://brave.com
Oak Security's Research: https://research.oaksecurity.io/
 

Jade Doherty and Stefan Beyer speak to Justus Hanna, co-founder and CEO of Grego AI, a bug bounty hunter turned founder building AI that finds vulnerabilities human auditors miss.
Justus's path runs from hacking Novell networks as a kid, to Bitcoin in 2011, to picking up bug bounty hunting from scratch after a Wall Street layoff. The turning point came when his future co-founder showed him a system that found a high-severity bug in Lido's dual governance module, at a moment when every other AI bug hunter was producing pure slop. What sold him: the AI found bugs humans couldn't, faster and cheaper.
He explains Deep Invariant Analysis as a proprietary harness orchestrating hundreds of specialised agents across many models, built to go five or six layers deep into complex systems and chain exploits a human would be very unlikely to reach. They tackle the big claims head-on: the $27.7M exploit prevented, the $250K bounty, why the protocol stayed unnamed, and the awkward truth that verifying an "AI-only" find still comes down to reputation.
On the anxiety every auditor feels, Justus argues the harness is the moat, precisely because it's model-agnostic, and there's a candid detour on frontier-lab hype and safety theatre. The episode closes philosophically: his vision of an always-on "security operating system", and his advice to researchers, don't skip the manual apprenticeship. Learn the craft from first principles, then use AI as a superpower on top. Be Iron Man, not obsolete.
Key Topics
AI-assisted vulnerability discovery, Deep Invariant Analysis, and the harness-as-moat
Verifying AI-found bugs, disclosure, and the incentive problem in bug bounties
The future of the human auditor, and security as an always-on operating system
Chapters
00:00 Introduction
00:24 From Novell Networks and Bitcoin to Bug Bounty Hunting
02:17 The Turning Point: Seeing Greg's System Find a Lido Bug
04:57 The Moment AI Beat the Human: Report Depth, PoCs, and Speed
06:29 What's Actually Different: Going Five or Six Layers Deep
10:58 Deep Invariant Analysis, the Harness, and Coordinating Agents
13:59 The 48-Hour Guarantee and the Human-in-the-Loop
15:43 The $27.7M Exploit, the $250K Bounty, and Verifying AI Findings
19:50 Bugs in Heavily-Audited Protocols: Is the Human Auditor Cooked?
24:39 Will the Models Eat the Harness? Why the Harness Is the Moat
27:26 Frontier Lab Hype, Safety Theatre, and IPO Incentives
28:24 The Vision: A Security Operating System Beyond Web3
31:52 The Attacker-Defender Asymmetry and Safeguards on Models
34:38 The Incentive Problem and Aligning White-Hat Rewards
37:09 False Positives, Slop, and Disclosure Bottlenecks
39:20 What a Major AI Lab Wanted to Know
41:02 The Role of Security Professionals in Two Years
45:22 The Apprenticeship Question: Learning the Craft Before the Tools
48:03 Training Juniors, CTFs, and Spotting AI-Generated Work
49:45 Where to Find Justus and Grego AI
Resources and Links
Justus on X: https://x.com/0xriptide
Grego AI: https://grego.ai
Oak Security's Research: https://research.oaksecurity.io/
 

Jade Doherty and Stefan Beyer speak to Lorenzo Sicilia, Head of Technology at the Arbitrum Foundation, whose path into crypto runs through ConsenSys, Casval, and Outlier Ventures.
They open with the distinction that shapes everything else: the Foundation is the steward and legal wrapper of the DAO, not the team behind the tech. Lorenzo unpacks how it ran the Arbitrum Audit Program on the DAO's behalf, vetting a shortlist of thirteen audit firms and funding early-stage teams, and gets into the hard parts with Stefan: the "rubber stamp" risk when a Foundation-blessed audit becomes a trust signal, the friction of re-auditing when each iteration costs $50K to $250K, and the brutal cost-per-line metric the program can now benchmark across firms.
On security responsibility, Lorenzo is precise: the Foundation has none in the formal sense. Incidents fall to a 12-member Security Council, elected and rotated by the DAO. From there the conversation turns to what keeps him up at night, the L1-L2 trust boundary and the bridge, and why fraud proofs through BoLD have improved the picture, landing on his own preference for "code is law" while acknowledging where reality forces harder trade-offs.
The technical heart is Stylus, Arbitrum's WASM environment for writing contracts in Rust alongside the EVM. Lorenzo is unromantic about it: a second runtime widens the attack surface, and while safe Rust has real advantages, no language removes the authorisation, economic, and oracle pitfalls that actually cause losses, treating any language as "safe" is a mental trap. The episode also covers the freshly-shipped ZK-on-BoLD upgrade, the road to real-time proving, and why AI currently hands the red team a big advantage over the blue team, though Lorenzo is optimistic defenders can turn the same tooling back on their own code.
He closes with hard-won advice: authenticity and persistence over a polished demo, understand your oracles and dependencies, get key management right, and know when to switch from "fake it till you make it" to full paranoia, because in this industry, you don't get a discount.
Key Topics
The Arbitrum Audit Program, and the "rubber stamp" problem with Foundation-backed audits
Decentralised security responsibility: the Security Council, the L1-L2 boundary, and BoLD
Stylus and WASM security, ZK-on-BoLD, real-time proving, and AI's red-team advantage
Chapters
00:00 Introduction
00:35 From ConsenSys and Outlier Ventures to the Arbitrum Foundation
04:11 What the Foundation Actually Does, and How It Differs from Offchain Labs
06:50 The Audit Program: How It Works and Who Funds It
10:18 The "Rubber Stamp" Problem and Vetting Audit Firms
13:18 Early-Stage vs Mature Teams: Who the Program Is For
14:54 What's Next: Additional Tools, AI, and the Limits of Scope
17:15 Lessons From the First Iteration, and Cost-Per-Line Benchmarking
21:11 The Foundation's Responsibility and the Security Council
24:49 What Keeps Him Up at Night: The L1-L2 Boundary and Bridges
29:16 Security Policy, Bug Bounties, and Disclosure Across the Ecosystem
30:48 Stylus: Does a WASM Runtime Widen the Attack Surface?
34:49 Safe Rust vs Solidity, Tooling Gaps, and the "Mental Trap"
39:13 Adding ZK to BoLD, and the Multi-Prover Approach
42:20 Real-Time Proving and Where Arbitrum Is Heading
45:20 ZK for Compression vs ZK for Privacy
46:24 AI in 2026: Red Team vs Blue Team, and AI Slop
50:31 Judging Teams: Authenticity, Resilience, and Real Problems
53:33 The Biggest Security Mistakes New Teams Make
55:25 The Foundation's Security Vision for the Next Few Years
57:52 One Piece of Advice: Dependencies, Keys, and Knowing When to Get Paranoid
Resources and Links
Lorenzo on X: https://x.com/aboutlo
Arbitrum: https://arbitrum.io
Oak Security's Research: https://research.oaksecurity.io/
 

Jade and Stefan speak to Robert de Groot, a core contributor to Web3Privacy Now, the research collective and think tank behind the Cypherpunk Congress, and CFO at Gain.
Robert starts from an unexpected place: privacy isn't really about hiding; it's about autonomy, the ability to choose what you reveal, to whom, when, and in what form. He connects it to something bigger than data leakage, the loss of the room to experiment and to fail, and the quiet self-censorship that creeps in when everything is recorded. From there the conversation opens onto the spectrum of privacy, from the journalist in a conflict zone who will work from a terminal if it keeps them alive, to the rest of us who just want a group chat that isn't intercepted and won't tolerate bad UX to get it.
A big thread is the gap between personal privacy and business compliance, and why the two still don't align. Robert explains how Web3Privacy Now evaluates the 800-plus projects in its Explorer (the "hard variables," verifiable code over marketing claims), why "zero knowledge" and "private" have become marketing terms, and why privacy adoption lags even when the tooling is ready, the preventive-measure problem, the group effect, and cookie-banner fatigue. On the compliance side, he maps the middle ground: opt-in reporting, viewing keys, and selective disclosure (picking up the thread from our Jordi Baylina episode), including a one-time key you could hand your tax auditor and be notified when it's used. 
He argues privacy will increasingly become a market-integrity feature, not just a civil-liberties one, shielding transaction amounts from competitors and MEV bots while keeping endpoints verifiable, and he closes on RWAs, why so many tokenisation projects quietly died on double-accounting overhead, and what "compliant by default" finally changes.
Key Topics
Privacy as autonomy, and the spectrum from uncompromisable to everyday
The gap between personal privacy and business compliance, and the middle-ground tools that bridge it
Privacy as a market-integrity feature for RWAs and institutional adoption
Chapters
00:00 Introduction
01:06 Why He Started Worrying About Privacy: Autonomy and Self-Censorship
04:58 Surveillance, Society, and the Loss of Room to Fail
06:01 What the Ethereum Community Really Thinks About Privacy
08:36 The Gap Between Personal Privacy and Business Compliance
10:54 What Web3Privacy Now Actually Does
13:45 Evaluating Projects: Hard Variables and Verifiable Code
17:01 When "Zero Knowledge" and "Private" Are Just Marketing
19:39 The Cypherpunk Congress and Why Privacy Matters Now
24:00 Tooling Is Ready, So Why Does Adoption Lag?
28:49 Compartmentalization, Intent, and Privacy by Default
34:38 GDPR, Cookie Fatigue, and Whether Regulation Backfires
39:49 Privacy vs Compliance: Does Privacy Make Regulators Nervous?
42:14 The Middle Ground: Opt-In Reporting, Viewing Keys, Selective Disclosure
45:31 Selective Disclosure and the Jordi Baylina Thread
46:10 RWAs, Institutions, and Why Tokenisation Projects Kept Dying
53:03 Privacy as a Market-Integrity Feature: MEV, Front-Running, and Competition Law
55:43 The Most Useful Thing an Ordinary Person Can Do
58:30 Where to Find Robert
Resources and Links
Robert on X: https://x.com/robdotrego
Web3Privacy Now: https://web3privacy.info
Cypherpunk Congress: https://congress.web3privacy.info/
Event: https://luma.com/spsnos9t
Oak Security's Research: https://research.oaksecurity.io/

After several episodes focused on security, this one turns to privacy, with Emanuele Francioni, co-founder and CEO of Dusk, a blockchain built for privacy and institutional use cases.
Emanuele traces the through-line from a contrarian 2018 thesis to a live network to abstract financial instruments away from the intermediaries that leak both value and data. A core thread is the counterintuitive relationship between privacy and regulation. He disentangles anonymity from confidentiality, shows how privacy actually underpins rules like GDPR, DORA, and insider-trading law, and explains how Dusk encodes KYC, jurisdiction, and limits directly into the protocol.
Then it gets harder: on a privacy chain, a vulnerability can be exploited in the dark. Emanuele uses the recent Zcash unbounded-mint bug to explain why Dusk's approach has to be proactive, why the team shipped three security upgrades this year (Aegis and Boreas among them), and why simplicity is the best safeguard. On the AI arms race he's candid, seeing Fable in action for three days genuinely scared him, but his conclusion is pointed: AI doesn't replace security expertise; it makes it more valuable.
Key Topics
Privacy vs confidentiality vs anonymity, and why privacy underpins regulation
Encoding regulatory compliance directly into a protocol
Securing a privacy-preserving chain, and the AI arms race in security
Chapters
00:00 Introduction
01:05 Founding Dusk in 2018 and the Road to PLONK
07:14 How Privacy Fits the Regulatory Space
08:00 Anonymity vs Confidentiality: Disentangling "Privacy"
15:11 Selective Disclosure and Working With Regulators
21:30 Encoding KYC, Jurisdiction, and Limits Into the Protocol
24:25 How Privacy Changes the Approach to Security
27:12 The Zcash Unbounded-Mint Bug and Why Privacy Must Be Proactive
29:30 The Security Arms Race and Five Attack Attempts This Year
34:50 Why Simplicity Is the Best Safeguard
36:12 The Complexity Trade-Off: Custom VM, Sandboxing, Immutable Contracts
40:14 Shrinking the Layer One: Dusk EVM and a Privacy-Preserving L2
43:21 The AI Arms Race: Aegis, Boreas, and Restructuring Into "Pods"
50:22 Cross-Pollination: Pulling Ideas From Biology Into Software
55:10 Where AI Helps in Security, and Where Humans Still Matter
1:02:19 Oak's Research: Minor Human Intervention, Completely Different Output
1:04:27 Surprising Findings in Aegis: the BLS Truncation Bug
1:06:45 Boreas: a Live Incident and Real-Time Response
1:11:00 Operational Security, Supply Chain, and AI-Era Hiring
1:16:56 Wrap-Up
Resources and Links
Emanuele on X: https://x.com/autholykos
Dusk: https://dusk.network
Oak Security's Research: https://research.oaksecurity.io/
 

Most of our guests come at security from the outside, as auditors and researchers. Antonio Viggiano sits on the other side of the table: he's a Senior Security Engineer at the Monad Foundation, working on protocol fuzzing for the chain's consensus and execution clients.
Monad's architecture makes that a genuinely different problem. Unlike Ethereum, with its many interchangeable clients, Monad has a single pair: a C++ execution client and a Rust consensus client, both built by Category Labs. That tight coupling buys optimisations, but it also means a bug that looks real in one client is often quietly mitigated by the other. Test one in isolation and you drown in false positives.
That's where Monad Bugfinder came from, and the origin story is the opposite of what most people assume. It didn't start as a bug finder at all. It started as a triager, because the team was being flooded with AI-generated reports: convincing write-ups, plausible proofs of concept, and hours of human time spent working out which ones were real. Bug hunters optimise for recall. When you're the one receiving the reports, you need precision. Antonio walks through the validation gates that made the difference, why AI has a higher false positive rate than humans, and why the best human reviewers still find twice as many bugs as the best AI systems.
Key Topics
AI-assisted vulnerability discovery and triage
Invariant testing and protocol fuzzing
In-house security teams at protocols
Chapters
00:00 Introduction
00:38 From Solidity Developer to Security Engineer
03:10 Founding Recon and Cloud Fuzzing
04:39 What Is Invariant Testing?
06:38 Fuzzing Smart Contracts vs Blockchain Clients
08:41 Tooling Maturity and System Complexity
09:47 Extracting Invariants at the Protocol Level
11:11 Why Most DeFi Teams Don't Know Their Properties
13:29 Monad's Architecture: Two Clients, Tightly Coupled
16:29 Why Single-Client Bugs Create False Positives
17:21 Monad Bugfinder: Why It Started as a Triager
20:19 Precision vs Recall: Finding Bugs vs Receiving Reports
23:54 Inside the Triage Process
25:59 Reconstructing Proofs of Concept End-to-End
27:13 Should Smaller Teams Build Their Own?
30:06 Build vs Buy, and the Attackers Building It Too
32:27 Validation Gates: EIP Support and Differential Testing
35:49 Testing Against Geth and Nethermind
37:43 Local Clusters and Controllable Validators
42:00 Do AI Reports Have More False Positives?
44:37 The Economics: AI Tokens vs Audit Firms
47:47 Why Humans Still Find Twice as Many Bugs
48:14 When Your Scaffolding Goes Stale
51:52 Offense vs Defense and the Human Weak Link
54:27 The Roadmap: Making the System Generic
56:51 UltraFuzz: Agentic Fuzzing for Solidity
1:00:32 Specifications, Spec Drift, and AI-Written Code
1:04:08 Will AI Ever Write Bug-Free Code?
1:09:45 Where to Find Antonio
Resources and Links
Antonio's X: https://x.com/aviggiano
Monad Bugfinder blog post: https://blog.monad.xyz/blog/monad-bugfinder
UltraFuzz blog post: https://www.monad.xyz/blog/ultrafuzz 
Monad: https://monad.xyz
Oak Security's Research: https://research.oaksecurity.io/

What does it actually mean to be "obsessed with AI for security"? In this episode of CypherTalk, Jade and co-host Stefan Beyer sit down with Prof. Arthur Gervais (UCL, affiliate faculty at UC Berkeley), known for foundational work on MEV, flash loan attacks, and AI-powered smart-contract security.
Arthur's core conviction sets the tone: AI is not a zero-sum game. Strong researchers can now find vulnerabilities ten times faster, and the right response is to onboard everyone as fast as possible rather than lock the tools down. The conversation goes deep on A1, the agentic system his team built that turns any LLM into an end-to-end exploit generator with one unambiguous goal: generate a profit. The hard part, he stresses, isn't building it, it's target selection.
 
Key Topics
AI for security enhancement
AI-assisted vulnerability detection
Real-time blockchain exploit detection
 
Chapters
00:00 Introduction to AI and Security
02:29 Arthur's Journey into Information Security
05:05 The Role of AI in Security
07:22 A1: The AI Agent for Exploit Generation
09:38 Autonomy and Ethics of AI Agents
11:53 Harnessing AI for Security Audits
14:15 The Evolution of LLMs and Their Impact
16:33 Dealing with False Positives in AI Security
19:06 The Academic Perspective on AI Research
21:42 Comparing LLMs for Security Tasks
24:05 Future Directions in AI and Security
25:26 The Power Dynamics in AI and Cybersecurity
29:04 Balancing Offensive and Defensive Strategies in AI
31:44 Real-Time Defense Mechanisms in Cybersecurity
34:20 The Role of Tooling in Smart Contract Security
39:04 Human Error vs. Automated Security Tools
41:24 AI's Impact on Social Engineering and Human Error
42:53 Emerging Threats from AI in Cybersecurity
44:17 Teaching Blockchain Security: Common Misconceptions
45:23 Future Directions in Blockchain Security Research
 
Resources and Links
Arthur’s website: https://arthurgervais.com/
Arthur’s Google Scholar: https://scholar.google.ch/citations?hl=en&user=jLr_xi4AAAAJ&view_op=list_works&sortby=pubdate
Arthur’s X: https://x.com/HatforceSec
Oak Security’s Research: https://research.oaksecurity.io/ 
 

In this episode, Jade Doherty and Stefan Beyer interview Peter Kacherginsky, founder of BlockThreat, on his quarterly take on blockchain security and recent exploits. They discuss how to utilize threat intelligence, the shift from smart contracts to operational attacks, and the role of AI in cybersecurity.
Topics
The shift from smart contract exploits to operational and infrastructure attacks
The impact of AI on cybersecurity and defense strategies
The importance of architectural security and threat modeling
The role of community funding and ethical research in security
Predictions for upcoming security challenges in crypto
 
Chapters
00:00 Introduction to Block Threat and Peter Kachaginski
01:42 Utilizing Threat Intelligence Effectively
04:31 The Impact of Market Conditions on Security
07:43 Shifts in Attack Vectors: From Smart Contracts to Infrastructure
09:35 Analyzing Major Hacks: Drift and Kelp DAO
13:36 The Importance of Architectural Security
16:47 The Evolving Role of Ethical Security Researchers
20:58 The Future of Security in a Rapidly Changing Landscape
30:10 Navigating Ransomware and Legal Implications
34:41 AI's Role in DeFi Security
43:27 Community-Driven Security Initiatives
49:25 Building a Security Mindset in Teams
51:48 The Centralization Dilemma in Security
 
Resources
Block Threat Newsletter - https://blockthreat.com 
Oak Security’s report - https://research.oaksecurity.io/ 
Peter’s X - https://x.com/iphelix 

In this episode of CypherTalk, Isaac Patka, co-founder of Shield3 and certification lead at the Security Alliance (SEAL), joins Jade Doherty and Stefan Beyer to discuss the human, operational, and governance risks shaping Web3 security. From early smart contract bug hunting to incident response wargames, SEAL 911, Safe Harbor, and the launch of SEAL certifications, Isaac explains why security is no longer just about audits and code.
The conversation explores how DeFi protocols can prepare for real incidents, why operational controls matter as much as smart contract reviews, and how AI is changing the threat landscape for both attackers and defenders. Isaac also shares practical insights on slowing down dangerous protocol actions, designing better incident response processes, and building a more mature security culture across crypto.
Enjoyed the episode and want to get SEAL certified? Oak Security is a SEAL-approved provider, and can review and certify your protocol to make sure your operational security is as good as your smart contracts.
Get in touch via https://oaksecurity.io/ 
Key topics
Isaac’s path from electrical engineering and semiconductors to Web3 security
How smart contract security has changed since the early Ethereum days
The difference between audits, war games, threat modeling, and incident response
How SEAL 911 helps coordinate emergency response across the crypto ecosystem
SEAL certifications and why operational security needs its own standard
Why SOC 2 and ISO do not fully capture Web3-specific risks
Multisig operations, treasury controls, DNS security, DevOps, and identity management
The rise of social engineering, insider threats, and operational attacks
North Korea, Lazarus Group, and state-sponsored crypto threats
How AI is expanding the attack surface for smaller protocols
Why protocols should build in slowness, circuit breakers, and operational controls
Sound Bites
“An audit tries to prevent an incident and the war game tries to help you deal with an incident.”
“Social engineering works for a reason. Humans are fallible.”
“What is the slowest I can possibly make this and have it still be functional?”
“People don’t think during the design process about where they should build slowness into the protocol.”
“The core smart contracts have gotten a lot better, which has pushed the security risks to different parts.”
“If more people would care from day one about operational controls or circuit breakers, that’s what I would want.”
Resources
Isaac Patka X https://x.com/isaacpatkaSecurity Alliance / SEAL https://securityalliance.org/SEAL Frameworks https://securityalliance.org/frameworksSEAL Incident Response Template https://frameworks.securityalliance.org/incident-management/incident-response-template/overview/ SEAL Certifications https://frameworks.securityalliance.org/certs/overview/ Shield3 https://www.shield3.com/ Oak Security’s State of Web3 Security Report https://research.oaksecurity.io/

Summary
In this in-depth interview, Joran Honig, a renowned bug bounty hunter and security researcher, shares insights into finding crazy bugs, the differences between audits and bug bounties, and the role of AI in security workflows. Discover practical tips, mental models, and future trends in Web3 security and bug hunting.
Key topics
Edge case bugs and how to find them
Differences between audits, bug bounties, and contest models
The role of AI and automation in security research
Tools and workflows for effective bug hunting
Responsible disclosure and handling uncooperative projects
 
Sound Bites
"AI can increase duplicates."
"Grimoire guides audit tasks."
"Flows help map complex code."
 
Resources
Joran Honig X https://x.com/joranhonig
Grimoire https://github.com/JoranHonig/grimoire
Joran’s website https://joranhonig.nl/