Zcash founder Zooko Wilcox said an AI-assisted security audit found no serious new vulnerabilities in the privacy-focused cryptocurrency’s protocol, days after developers patched a long-running bug in one of its shielded transaction pools.

The audit was requested by Shielded Labs, a Swiss-based non-profit that supports Zcash development. Wilcox said in a Saturday post on X that Anthropic’s Claude Mythos model did not find “any more serious bugs” in the Zcash protocol.

The review followed a June 3 emergency response by Zcash developers, who temporarily suspended Orchard transactions after a vulnerability was discovered in the shielded pool. Orchard is one of Zcash’s privacy-preserving transaction pools, designed to allow users to transact without exposing sensitive details onchain.

Functionality was restored later the same day through an emergency upgrade.

The vulnerability involved a four-year-old forgery bug in the Orchard shielded pool. Security researcher Taylor Hornby found the issue with the help of Anthropic’s Claude Opus 4.8 model.

The Zcash Foundation said there was no evidence the bug had been exploited. It also said no unauthorized value creation was detected and user privacy was not affected.

The episode puts Zcash at the center of a broader debate now moving through crypto security: AI models are becoming powerful enough to help researchers find deep protocol flaws, but the same tools may also make it easier for attackers to discover and exploit vulnerabilities at scale.

Anthropic recently released the first public version of its Claude Mythos model, Fable 5. The company previously said Mythos had found more than 10,000 high or critical-severity vulnerabilities in systemically important software, raising concerns across the security community about whether such a model should be broadly available.

Anthropic said Fable 5 was made safe for general use and included safeguards that redirect certain cybersecurity-related prompts to another model, Claude Opus 4.8.

The situation escalated further after Anthropic suspended access to Fable 5 and Mythos 5, citing a US government export control directive tied to national security concerns.

The concern is simple: the same capability that helps responsible researchers discover hidden bugs can also lower the cost for attackers.

That concern is already being felt across decentralized finance. Crypto hacks surged to $634 million in April, the highest monthly figure since the Bybit attack caused about $1.4 billion in losses in February 2025.

Security executives have warned that advanced AI models may be shifting the advantage toward threat actors by making vulnerability discovery faster and cheaper. Immunefi CEO Mitchell Amador described the trend as a “vulnerability apocalypse,” arguing that more powerful models could fuel another wave of DeFi exploits.

For Zcash, the immediate message is more contained. The Orchard bug appears to have been identified before exploitation, the network was patched quickly, and a follow-up AI audit did not surface additional serious flaws.

But the broader message is messier.

Crypto protocols now face a world where AI can act like a force multiplier for both defense and offense. It can help researchers harden code. It can also help attackers hunt for mistakes buried deep inside complex systems.

That creates a new pressure point for privacy coins, DeFi protocols and blockchain infrastructure teams.

Finding one bug is no longer the end of the story.

It may only be the start of the next audit cycle.

Zcash’s Clean AI Audit Is Good News — But the Bigger Story Is Nastier

The headline sounds comforting.

Claude Mythos checked Zcash. No serious new bugs found. Orchard was patched. No exploit detected. No fake coins minted. Privacy intact.

Good.

But I wouldn’t treat this as a victory lap.

Because the real story here is not that Zcash survived one scary bug. The real story is that crypto security just entered a much weirder phase, where the same AI models helping researchers defend protocols can also hand attackers better shovels.

And those shovels dig fast.

The Orchard bug matters because it sat there for years. Four years. That is the uncomfortable bit. Not because Zcash is uniquely sloppy — it isn’t — but because serious bugs can live inside serious protocols for a long time while everyone assumes the math, audits and battle-testing have already done their job.

Then an AI-assisted researcher finds it.

That should make every protocol team sweat a little.

Not panic. Sweat.

There’s a difference.

Zcash handled the response better than most projects would. Developers suspended Orchard transactions, pushed an emergency upgrade and said no unauthorized value creation was detected. That is the right playbook. Fast, contained, boring.

Boring is good when money and privacy are on the line.

But the AI angle changes the mood.

Taylor Hornby reportedly found the forgery issue with help from Claude Opus 4.8. Then Shielded Labs asked for another review using Claude Mythos. Zooko says it found no more serious bugs.

That is reassuring.

Still, I’m not reading it as “AI cleared Zcash.”

I’m reading it as “AI is now part of the security stack whether crypto likes it or not.”

And that is a very different sentence.

Because once a tool can find hidden protocol bugs, it does not stay neatly inside white-hat workflows. It leaks into attacker workflows too. Maybe not directly. Maybe not with a big red button that says “hack DeFi now.” But capability diffuses. Prompts get shared. Models get copied. Guardrails get routed around. Private models get trained. Someone somewhere runs the same playbook with worse intentions.

That’s the ugly part.

The industry has spent years pretending more audits equals safety. It never really did. Audits reduce risk. They don’t delete it. Now AI adds another layer: continuous adversarial discovery.

Every old contract.
Every bridge.
Every rollup component.
Every privacy circuit.
Every weird edge case sitting untouched since 2021.

All of it becomes more searchable.

I’ve seen people frame this as bullish for security. They’re not wrong, exactly. AI can absolutely help defenders. It can scan faster, explain code paths, test assumptions, generate exploit hypotheses and find forgotten dependencies.

But that only helps teams that move fast.

Slow teams get cooked.

That’s my read.

The gap between strong teams and lazy teams is about to widen hard. If you already run serious audits, bug bounties, formal verification and rapid incident response, AI gives you more leverage. If your security model is “we had an audit once and the logo is on our website,” you’re exit liquidity for the next exploit cycle.

Zcash is probably in the first camp.

A lot of DeFi is not.

That’s why the timing matters. April saw hundreds of millions in crypto hack losses. February had the Bybit disaster. DeFi has already been bleeding from smart contract bugs, oracle manipulation, access control failures and bridge weirdness. Now add AI-assisted vulnerability hunting to the mix.

Not great.

And no, I don’t buy the soft version of this story where AI simply “improves security outcomes.”

It improves whoever uses it better.

That could be the protocol team.

Could be the attacker.

Could be both on the same day.

The Anthropic drama makes the whole thing even more charged. Mythos reportedly found more than 10,000 high or critical-severity vulnerabilities in important software. Then Fable 5 gets released publicly. Then access to Fable 5 and Mythos 5 gets suspended after a US export control directive.

That is not normal product-launch noise.

That is governments looking at AI security models and thinking: this is dual-use, and maybe dangerous.

Crypto should pay attention.

Because crypto is basically a giant public bug bounty with money attached. Code is open. Contracts are live. Liquidity is visible. Attackers can simulate, fork, test and strike. There are no bank holidays. No circuit breaker for protocol logic. No customer service desk that reverses a bad proof.

If AI makes vulnerability discovery cheaper, crypto feels it first.

Privacy coins feel it differently.

Zcash is not just another DeFi yield farm. Its value proposition depends on cryptographic confidence. Users need to believe the shielded system works. They need to believe privacy is intact. They need to believe nobody can forge value in silence.

That is why the Orchard bug was serious even if it was not exploited.

A privacy protocol does not only defend balances. It defends trust in invisible guarantees.

You can’t ask users to verify privacy failure after the fact the same way they verify a hacked liquidity pool. If the whole point is shielding, uncertainty itself becomes toxic.

So yes, the clean follow-up audit helps.

But it does not erase the meta-problem: complex cryptographic systems now need continuous AI-era review.

Not annual audits.
Not one-off reports.
Not “the code has been live for years.”

That argument is dead.

Old code is not safe code. It is just old.

The interesting part is that Zcash may actually come out stronger if it leans into this. Publicly acknowledging the bug, patching quickly and using stronger AI models for follow-up review is a better posture than pretending nothing happened.

I’d rather see a protocol get embarrassed and fix the issue than watch a team bury a bug behind Discord spin and vague “maintenance” language.

That stuff screams amateur hour.

Zcash did not do that.

Still, investors and users should not confuse “no serious bugs found” with “no serious bugs exist.” That sentence matters. AI audits are not magic. Models can hallucinate. They can miss paths. They can over-rank nonsense and under-rank real issues. They are tools, not security gods.

The right posture is paranoia with process.

Keep auditing.
Keep rotating models.
Keep using human experts.
Keep expanding bug bounties.
Keep assuming the next vulnerability is already sitting somewhere in the codebase.

Because maybe it is.

What I’d watch next is whether other major crypto projects start publicly announcing AI-assisted audits after serious incidents. If they do, this becomes a new credibility signal. Not enough by itself, but still useful.

If they don’t, users will start asking why.

And they should.

My gut says AI security reviews become standard across serious protocols within the next 12 to 24 months. Not because teams suddenly love security. Because insurers, exchanges, foundations and large holders will demand it.

Nobody wants to be the protocol that skipped the AI audit right before the AI-assisted exploit.

That headline writes itself.

For Zcash, the immediate danger seems contained based on the available statements. The bug was patched. No exploitation found. No privacy damage reported. Claude Mythos did not surface another serious issue.

That’s the clean part.

The messy part is bigger.

AI just made the bug-hunting game faster, stranger and less forgiving.

Zcash got a warning shot.

The rest of crypto should treat it like one too.