CoinEx You Ask We Answer VOL.16 Featuring Forta & Response from Forta Ecosystem Lead Andy Beal
Greetings, CoinEx and Forta community members,
We’re immensely grateful for your overwhelming support and participation during our recent community session. Our community is not only active but also diverse in its curiosity. From intricate questions about business development and technology to insightful inquiries about our team, you’ve showcased the depth of your engagement. As promised, we’ve consolidated the responses from the Forta team. Dive in to get a comprehensive understanding of the various facets that were discussed. Your dedication propels us forward, and we’re eager to continue these conversations in the future.
What are Fort Network’s plans for reaching out to the global community in building and acquiring customers or users for the partnerships I expect in 2023 and 2024? How does your project intend to solve the target market’s current problems?
The Forta Network is permissionless, so practically, any developer or team can build detection bots on the network. In terms of acquiring users, the Network recently rolled out fees so the focus has sharpened to onboarding paying subscribers for the existing bots/feeds on the network. Each bot/feed has a different audience, but the key user segments for now seem to be companies with a need for Web3 threat/security intelligence. Examples include Web3 wallets, DeFi protocols, centralized exchanges and crypto compliance companies.
We’re also encouraging and incentivizing other developers and teams to build new detection bots on the network that appeal to these user segments.
1.what is the most innovative feature of Forta Network that sets it apart from other blockchain platforms? 2. What are some potential drawbacks or limitations of Forta Network that users should be aware of before using it?
Forta isn’t a blockchain platform, but it is a decentralized network. From a tech stack perspective, the Forta Network is middleware that sits above L1s and L2s, and monitors onchain transaction activity.
Two of the current limitations are: (1) Forta doesn’t natively support mempool monitoring, but this is something that may change in the near future, and (2) Forta only supports the 7 largest EVM networks today. However, we expect to expand coverage for other networks, include non-EVM by year end.
I read that @FortaNetwork has integrated a DETECTION BOT marketplace where developers would be able to trade their detection bots,so what mechanism have you implemented to safeguard transactions which are carried out in this marketplace?what payment methods are accepted?
On August 8, the Forta Network turned on fees, requiring users to start paying for the threat intelligence they consume, and compensating bot developers. Currently, 100% of network revenue is distributed to bot developers.
Purchasing a Forta subscription happens onchain via the Unlock protocol. Users receive a NFT in their wallet representing a one month subscription, and can use that to subscribe to individual bots or generate an API key. The General subscription plan, which gives users access to 99% of bots on the network (except for Premium Feeds) is 250 FORT/mo. Premium Feeds are priced individually in USDC by the respective bot developer.
In its quest to protect all assets and transactions in Web3, Forta’s detection network scans billions of transactions and block-by-block state changes. How does Forta maintain the scalability and performance of its system to ensure real-time monitoring and detection, even in periods of high network congestion and transaction volume?
The Forta Network acts like a “giant security camera and alarm system” for Web3. The network is comprised of over 1,000 community-developed detection bots (aka cameras) and over 4,000 scan nodes that are tasked with keeping the cameras running 24/7. There is currently enough scan node capacity for thousands of additional bots, so scalability isn’t a concern right now.
Bot performance is dependent on underlying node performance, because if all the scan nodes running a bot go down, the bot ceases to run temporarily. To ensure bot performance and uptime, bots can run redundantly across multiple scan nodes.
Because Forta operates independently from a L1 or L2 chain, network congestion and transaction volume don’t impact performance of the network.
Can you provide specific examples of the types of threats that Forta Network has successfully detected and mitigated in the past?
The Forta Network features bots that detect both smart contract exploits and end-user attacks.
- With respect to exploits, Forta’s Attack Detector detected the Euler Finance hack prior to exploitation. More details can be found on our blog.
- With respect to end-user attacks, Forta’s Scam Detector identifies thousands of new scam entities every month engaged in a variety of scam behavior, including ice phishing, rug pulls, and address poisoning. A new form of attack recently identified by the Scam Detector is called “sleepdropping”, and more details are provided on our blog. This intelligence is provided to Web3 wallets, exchanges and crypto compliance companies to help protect users and combat money laundering.
What are the potential limitations or challenges that Forta Network may face in effectively detecting and mitigating security threats in the ever-evolving landscape of cryptocurrencies and blockchain technology?
There are a lot of challenges to detecting and mitigating security threats. One of the biggest challenges to preventing exploits today isn’t detection, but automating the prevention process. Manual response is generally too slow to be effective, so protocol teams need to think about incorporating automated processes. This could be an automated circuit breaker, or an anomaly detection system that proactively blocks/reverts suspicious transactions or things outside “expected behavior”.
Another challenge to detection is the emergence of private transactions. Transactions that circumvent the public mempool are harder to see (but not impossible). This makes it difficult for detection systems that rely on early detection and frontrunning to prevent an attack.
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