AI-Era Cybersecurity: How Can PolySwarm (NCT) and Decentralized Threat Intelligence Protect Web3?

In 2026, the cybersecurity battleground is undergoing a profound transfer of power. Attackers are no longer relying solely on human researchers to discover vulnerabilities. Instead, they are increasingly using artificial intelligence (AI) at scale to automate attacks, generate malicious code variants, and power intelligent phishing. When AI exponentially boosts "production capacity," traditional threat intelligence systems—built around centralized signature databases—face challenges on an unprecedented scale. Against this backdrop, PolySwarm, a decentralized threat intelligence market built on Web3, and its ecosystem token NCT have once again moved back into the industry mainstream, driven by recent extreme market volatility and a distinctive economic model.

How AI Changes the Cost and Efficiency Structure of Cyber Attacks

AI-enabled cyber attacks aren’t just hype. They’re already embedded in specific stages of the attack chain. According to Stratistics MRC, the global AI-driven threat intelligence market is expected to reach $7.2 billion in 2026 and grow to $30.1 billion by 2034 at a compound annual growth rate of 19.5%. This growth is fueled by the direct confrontation between security demand and the evolution of attacks.

AI lowers the bar across three key dimensions. First is the threshold for generating malware. With techniques like generative adversarial networks (GANs), attackers can automate the creation of polymorphic malware variants that bypass traditional, signature-based antivirus detection—something that used to be extremely costly in the era of manual analysis. Second is the cost of phishing attacks. The widespread adoption of large language models (LLMs) makes it easy to generate highly realistic phishing emails and fraudulent webpages with no grammatical errors, expanding the audience for cybercrime. Third is the cost of attack automation. AI can automatically perform internal reconnaissance, match vulnerabilities, and optimize lateral movement strategies—shifting malicious activity from "manual intrusion" to "automated compromise."

The Achilles’ Heel of Traditional Threat Intelligence Systems

Traditional threat intelligence systems that dominated the Web2 era reveal their architectural lag when hit by AI-driven waves of attack.

At their core, these traditional models rely on centralized data collection and distribution. Security vendors update virus databases and threat intelligence by using their own product telemetry, customer submissions, and internal sample analysis. The bottleneck is that update speed has a hard physical limit. From sample capture and analysis to feature extraction and global distribution, the loop takes time. Meanwhile, AI-generated malware variants can change behavioral characteristics within hours. In addition, traditional models suffer from data silos—threat intelligence from different vendors can’t easily interoperate, leaving gaps in any single vendor’s coverage. In the Web3 environment, the attack surface expands even further. Smart contract vulnerabilities, cross-chain bridge attacks, flash loan attacks, and other emerging threats are areas where traditional security vendors’ experience tends to be comparatively weak. To address this mismatch, decentralized threat intelligence offers an entirely new solution paradigm.

Decentralized Threat Intelligence: A New Paradigm for Web3 Security

The core logic of decentralized threat intelligence markets is to shift from "single-authority judgment" to "community consensus driven by competition." The underlying architecture includes several key components: a security data network, multiple independent detection engines, real-time competitive mechanisms, and token-based economic incentives.

PolySwarm is a prime example of this model. According to its official documentation, PolySwarm’s market consists of three core roles: Ambassadors, Engines, and Arbiters. When a customer submits a suspicious file or URL (artifact), the market broadcasts it as a bounty. Multiple independent engines (operated by security experts around the world) receive the sample and submit their judgment (malicious or benign). These engines don’t just provide a decision; they can also stake NCT tokens to express how confident they are in their analysis. Then, the arbiter publishes the "Ground Truth" based on more complete evidence and at the right time—deciding which engines earn rewards and which engines lose staked tokens.

This design creates two advantages. On one hand, it aggregates global, fragmented security intelligence through economic incentives. Large security firms and individual researchers with unique detection capabilities can all profit by delivering accurate intelligence. On the other hand, the competition mechanism forces detection efficiency upward, because only engines that are both fast and accurate can survive market competition and earn more. With multiple independent detection engines participating in the assessment, reliance on any single vendor’s detection pipeline decreases, and the risk of false positives is reduced.

Market Performance and Value Capture Analysis of PolySwarm (NCT)

Recent market data provides a real-world validation of this logic. As of August 28, 2026, according to Gate Market data, the PolySwarm (NCT) price is $0.013401, with a -16.33% drop over the past 24 hours. However, it has surged by an astonishing +266.85% over the last 7 days, and +237.15% over the last 30 days.

Source: Gate Market

If we remove short-term trading sentiment and look at it from a value-investing perspective, NCT’s value-capture mechanism is built on its role as a practical token in the PolySwarm market. Engine operators must stake NCT to participate in competition and earn rewards. Customers may need to use NCT to post tasks. The total supply is about 1.886 billion tokens, and all of them are already in circulation. As detection demand within the PolySwarm ecosystem grows (meaning more enterprises and protocols need to obtain threat intelligence), the circulation demand for NCT should also increase accordingly.

From a macro industry data standpoint, the FBI reports that cybercrime losses in the United States reached $16.6 billion in 2024, up 33% from 2023. The scale and industrialization of cybercrime are forcing the defense ecosystem to upgrade. Meanwhile, academia is also actively testing the feasibility of combining blockchain with threat intelligence. Recent research such as HoloCyberChain and BlockIntelChain attempts to use distributed architectures to address trust and efficiency issues in threat-intelligence sharing.

Conclusion

In the AI era, the security game is fundamentally a contest of efficiency and cost. When AI makes attacks cheaper and more automated, defense must also shift from "passive response" to "active confrontation." PolySwarm’s decentralized threat intelligence market provides a new evolution path for Web3—and the broader internet security ecosystem—by tokenizing security capabilities and turning them into market competition. Although this model is still in an early validation stage and the NCT price is highly volatile due to market sentiment, the underlying narrative structure of "AI × Cybersecurity × Web3" offers an important example for observers to understand how the security infrastructure of the future may change.

FAQ

1. What is PolySwarm, and what problem does it solve?

PolySwarm is a decentralized threat intelligence market. It connects independent global security experts and detection engines through blockchain and token incentives (NCT) to collaboratively analyze malware. It aims to address pain points of traditional antivirus software, such as reliance on a single vendor’s signature database, slow updates, and sluggish response to new threats—especially fast AI-generated malware variants.

2. What role does the NCT token play in the PolySwarm ecosystem?

NCT (Nectar) is a utility-focused ERC-20 token in the PolySwarm ecosystem. Security engine operators need to stake NCT to "back their bet" when submitting malware detection results to express their confidence. If their judgment is correct, they receive NCT rewards. If they’re wrong, they lose the staked tokens. This mechanism helps ensure the accuracy and reliability of detection results.

3. What are the advantages of decentralized threat intelligence over traditional vendors?

The core advantages are speed and diversity. Traditional vendors rely on internal teams, which limits speed. PolySwarm lets multiple engines across the globe compete simultaneously, enabling faster discovery of new threats. Also, different engines focus on different domains (such as ransomware, APT, and phishing), so coverage is broader than any single vendor—effectively reducing both false positives and missed detections.

4. Where are the specific impacts of AI on the cybersecurity industry?

AI significantly lowers attack costs. Specifically: using AI to generate featureless polymorphic malware to bypass traditional antivirus; using large models to generate highly personalized phishing emails; and automating reconnaissance and infiltration across attack chains. As a result, traditional rule- and signature-based defenses fail, pushing the industry to transition toward AI-driven detection and decentralized collaboration.