DeepSafe

DeepSafe is excited to announce our $3m Seed Round with @AntalphaGlobal @ViabtcCapital @capital_spark @CogitentV @ShardingCapital @Mason_eagle @Gate @SatoshiLab_HK @CKBEcoFund The core decentralized validation technology of DeepSafe has been accepted by the top international cryptographic academic journal IEEE TIFS, with the document ID being 9903072. Currently, the DeepSafe network has processed nearly 120 million transaction validations, and the number of active accounts on the network exceeds 2.65 million. Time to make a better Trust Layer now.

Most Web3 projects call their tech "revolutionary." Very few put it in front of a room that doesn't care about hype. DeepSafe's core verification technology — the cryptographic foundation behind CRVA — has been accepted by #IEEE Transactions on Information Forensics and Security (TIFS), a flagship journal under IEEE's Signal Processing Society and one of the most rigorous venues in cryptography and security research. This isn't a journal that publishes claims. It publishes work that survived adversarial scrutiny — reviewers whose entire job is to find the flaw you missed, the edge case your model didn't account for, the assumption that doesn't hold under attack. What got reviewed wasn't a product pitch. It was the actual cryptographic design underlying Ring VRF, MPC, ZKP, and TEE working together — the same mechanism running CRVA today. No whitepaper alone gets through that process. No partnership announcement gets through that process. Only math that holds up does. A partnership can be arranged. A listing can be negotiated. Peer review can't — the only way through is being right. #DeepSafe #CRVA #Academic #IEEE #Journal

Another day, another verification gap. Taiko lost ~$1.7M after its chain-state verification mechanism was compromised — one of 20+ incidents tracked across the ecosystem this June alone. The pattern keeps repeating: it's rarely broken cryptography. It's a gap in how state gets verified before funds move. This is exactly the problem CRVA was built to close — verification that's random, threshold-based, and hardware-isolated, so there's no single mechanism left to compromise. Source: beincrypto.com/taiko-bridge-e… #DeepSafe #CRVA #Web3Security #Taiko

Abbott Luo — CTO. CRVA isn't a narrative wrapped around buzzwords — it's four cryptographic primitives that have to work together flawlessly, every 10 minutes, with zero room for failure. Abbott's the one making sure the engineering actually holds up to that standard.

Dr. Victor Saylor — CMO. A decade building growth and marketing strategy for platforms serving hundreds of millions of real users — not just crypto-native audiences. That's a different playbook than growing a Discord server. Victor's job: make sure the message travels as far as the technology deserves.

Some faces you've already met. But it's been a while — and what's ahead makes it worth a proper reintroduction. #DeepSafe #CRVA #VerificationNetwork #Coreteam Starting with the person steering the ship. Raul Heraud — CEO. Two and a half decades in private equity and venture capital means Raul's spent his career deciding which bets are worth making — before he ever puts capital behind them. That same judgment is now steering DeepSafe's growth and token strategy. This isn't a founder learning on the job.

Numbers like these don't come from HYPE. They come from mainnet traffic, real users, and real integrations — accumulated quietly over time while the industry cycles through narratives. The infrastructure layer doesn't need to shout. It just needs to work. #DeepSafe #CRVA

These four primitives — ZKP, Ring-VRF, MPC, TEE — are not add-ons. They are integrated into a single verification flow, cycling every 10 minutes across every committee election, every key generation, and every signature. The result: Trustless — no single party controls the outcome Random — committee selection is verifiably unpredictable Resilient — threshold signatures ensure liveness Hardened — hardware-level security prevents physical compromise Four years of production. Millions of verifications. The foundation is set. #DeepSafe #CRVA #ZKP #MPC #TEE

4. TEE — Trust Through Hardware Cryptographic protocols secure communication. But they cannot stop an operator with physical access to a machine from tampering with its execution. This is the gap that Trusted Execution Environments are designed to close. All CRVA Agents operate on Intel SGX2-enabled hardware within a TEE. The environment isolates the verification code from the host operating system — the operator cannot read the signing logic, modify execution, or extract key material. If tampering is detected, the TEE attestation mechanism invalidates the Agent's participation. A dishonest operator's only option is to shut down the machine, which triggers a forfeiture of staked assets rather than a compromise of the network. TEE moves the security model from "trust the operator" to "trust the attestation."

If you have been following DeepSafe for a while, you already know these four names: ZKP, Ring-VRF, MPC, TEE. If you are new — here is what powers the CRVA network. Four years of cryptographic engineering. One integrated verification flow. Time for a refresher. A thread on the core primitives behind Crypto Random Verification Agents.

Everyone is talking about AI Agents. Not enough people are talking about AI Agent Security. The next major attack vector isn't the model itself—it's the tools, plugins, MCP servers, and permissions your AI agent relies on. As AI Agents gain more autonomy, every connected service becomes part of the attack surface. Security is no longer about asking: ❌ "Is the AI safe?" It's about asking: ✅ "Can the AI safely interact with everything around it?" The future belongs to AI that is not only intelligent—but trustworthy. (arxiv.org/abs/2607.02357) #AI #AISecurity #CyberSecurity #AIAgents #Web3 #DeepSafe

As AI agents move from experimental tools to production systems, a new layer of infrastructure is emerging around them: execution security. Arcade.dev recently raised $60M to build systems that control how AI agents access enterprise tools, APIs, and databases. (Source: wsj.com/cio-journal/ar…) What’s interesting is not the funding itself, but what it signals. The industry is no longer asking whether agents can perform tasks. It is now asking how their actions can be constrained, audited, and verified at runtime. Most agent frameworks today assume trust at the tool layer — once access is granted, execution is largely delegated. But as agents begin operating across sensitive systems, that assumption breaks down. Authorization alone is not enough. You need runtime verification of behavior: what was accessed, in what sequence, under which conditions, and with what downstream effects. This is where agent infrastructure is quietly shifting — from capability engineering to execution governance. The next bottleneck in AI systems will not be reasoning. It will be verifiable control over actions in open environments. #AI #AIAgents #Security #Web3 #Verifiability

A U.S. appeals court is now weighing a question that will define the future of AI agents: Who is responsible when an autonomous agent takes action? Reuters reports that judges are examining whether an AI agent's interactions with Amazon systems can be attributed to the AI provider, the user, or neither. (Source: reuters.com/legal/governme…) Most discussions around AI agents focus on reasoning quality and task completion. But as agents gain the ability to access accounts, retrieve data, invoke tools, and execute actions across systems, a more fundamental challenge emerges: Can their behavior be independently verified? In traditional software, actions are deterministic and traceable. In agentic systems, decisions are probabilistic, context-dependent, and often span multiple tools and environments. The future of autonomous systems won't depend solely on what agents can do. It will depend on whether every critical action can be verified, attributed, and audited across system boundaries. The agent economy is growing. So is the need for verifiable execution. #AI #AIAgents #Web3 #Blockchain #Verifiability

Microsoft Build 2026 made one trend impossible to ignore: AI agents are moving from assistants to operators. Agents are no longer limited to generating content. They are increasingly being connected to enterprise systems, development workflows, databases, and external tools. (Source: - tomsguide.com/news/live/micr… - windowscentral.com/microsoft/wind…) Most discussions focus on what agents can accomplish once connected. A more interesting question is what happens when those connections become part of critical infrastructure. When an agent retrieves data, invokes tools, triggers workflows, or coordinates actions across systems, the challenge is no longer model intelligence. It's state integrity. Was the data authentic? Was the tool invocation valid? Was the execution path manipulated? Can the result be independently verified? As agent ecosystems mature, trust will increasingly depend on verification rather than generation. The industry is rapidly building the agent layer. The verification layer is next. #AI #AIAgents #MCP #Web3 #Blockchain #Verifiability

MCP is quickly becoming the default interface between AI agents and the outside world. @Microsoft's NLWeb initiative and the broader MCP ecosystem are pushing toward a future where agents can directly access websites, tools, databases, APIs, and operational systems. (Source: techradar.com/pro/could-micr…) Most discussions focus on what agents can do once connected. A more important question is: How do we verify what happens after the connection is made? As agents gain access to external systems, trust shifts away from model outputs alone. The integrity of tool calls, retrieved data, execution paths, and state transitions becomes equally important. In other words, the challenge is no longer just model reliability. It is interaction reliability. The industry is building protocols for agent connectivity. The next layer will be protocols for agent verification. Because an autonomous system is only as trustworthy as its ability to prove what it actually did. #AI #AIAgents #MCP #Web3 #Blockchain #Verifiability

As AI systems scale, an increasing portion of the internet is no longer human-generated. It’s synthetic. Models are now training on AI-generated text, AI-generated images, AI-generated summaries, and increasingly, AI-generated decisions. Which creates a feedback loop most systems weren’t designed for. When synthetic outputs become future training inputs, the boundary between source data and generated interpretation starts to collapse. At small scale, this looks like noise. At infrastructure scale, it becomes a trust problem. Because once systems can no longer reliably distinguish between original state and recursively generated state, verification becomes exponentially harder. This is likely where the next major challenge in AI infrastructure will emerge: not generation, but provenance. Knowing where information came from, how it was processed, and whether it can still be independently verified. The systems that solve this won’t just improve AI reliability. They’ll define the trust layer of machine-generated networks. #AI #Web3 #SyntheticData #Blockchain #Verifiability

For years, blockchains have relied on oracles to bridge external data into on-chain systems. But AI is starting to change the nature of that data itself. Increasingly, systems are no longer consuming raw external inputs. They are consuming AI-processed interpretations: summaries, classifications, recommendations, predictions, autonomous decisions. In other words, AI is quietly becoming a new type of oracle layer. That changes the trust model entirely. Traditional oracle problems were mostly about data integrity and delivery. AI-driven systems introduce a harder problem: the output may be internally coherent while still being unverifiable. As AI agents become embedded into DeFi, governance, automation, and cross-chain coordination, the reliability of those outputs becomes systemic infrastructure risk. The next generation of decentralized systems won’t just need data availability. They’ll need verifiable intelligence. #AI #Web3 #Oracle #AIAgents #Blockchain #Verifiability