Solana Hit By One Of The Largest DDoS Attacks In Internet History

bitcoinistPublished on 2025-12-16Last updated on 2025-12-16

Abstract

Solana has successfully withstood one of the largest DDoS attacks in internet history, estimated at 6 Tbps, without significant performance degradation. Despite the massive scale of the attack, which lasted for over a week, the network maintained median transaction confirmations around 450ms and stable slot latency. Ecosystem builders highlighted that the attack had zero noticeable impact on regular users or traders. The event underscores that blockchains have become high-value targets for industrial-scale DDoS campaigns. Solana’s resilience is attributed to its engineering and validator infrastructure, though experts note that validator count alone isn’t the sole factor in network defense. At the time of reporting, SOL traded at $126.

Solana has been battling what some ecosystem builders are calling an internet-scale DDoS campaign — and, despite the usual “Solana is fragile” jokes, the network seems to be shrugging it off.

Pipe Network said of the ongoing attack via X today: “The ongoing DDoS attack on Solana is one of the largest in internet history. 6 Tbps volumetric attack translates to billions of packets per second. Under that kind of load, you’d normally expect rising latency, missed slots, or confirmation delays.”

Pipe further says that’s not what the data is showing. “Median tx confirmation ~450ms,” the team wrote, adding that p90 remains under 700ms and slot latency is holding at 0–1 slots. In other words, if you’re a regular user or trader, you might not even know anything’s happening. Which is kind of the point.

Largest DDos attacks in internet history | Source: X @pipenetwork

Reactions From The Solana Community

Raj Gokal, Solana Labs’ co-founder and COO, put it more bluntly in a reply to a broader DDoS debate: “have you heard about the ongoing DDOS against Solana that has had zero effect on performance?”

The backdrop here matters. Justin Bons had posted about Sui being DDoS’d yesterday, claiming it triggered “mass delays” and arguing that “127 validators is not enough,” with the broader warning: don’t let validator counts drift too low if you want a chain to be resilient.

Mert Mumtaz, CEO of Helius, largely agreed with the premise — but pushed back on the simplistic “more validators = solved” framing.

“I understand your point & mostly agree with you,” Mert wrote, before adding that “a chain is more resistant to DDoS with 100 professional high powered validators compared to 10k validators run by amateurs.” He also said there are scenarios where higher validator count can help, but emphasized it isn’t the core defense by itself. Then he dropped the key detail: Solana’s attack hasn’t been a one-day headline, it’s been going on for a while.

“And fyi there has been a colossal ddos attack on Solana for weeks now,” Mert wrote, later adding that Solana “has been under a colossal DDoS attack for at least over a week now btw” — and that the fact most users haven’t felt it is “a big testament to the level of engineering present here.”

Solana co-founder Anatoly Yakovenko chimed in with a more technical angle on why validator count can matter in specific leader-hand-off dynamics: “Validators count helps if the previous leader can finish their block while the current one is being hit. Then the cost of ddos approaches the cost of ddos the whole network.”

Translation: if an attacker wants to reliably disrupt block production, they may have to sustain pressure across more of the network, not just pick off a single leader at the wrong moment. That gets expensive fast.

SolanaFloor summed it up via X: “Solana has been under a sustained DDoS attack for the past week, peaking near 6 Tbps, the 4th largest attack ever recorded for any distributed system. Network data shows no impact, with sub second confirmations and stable slot latency. The Sui network was also targeted by a DDoS attack yesterday, resulting in delays in block production and periods of degraded network performance.”

And there’s a more strategic takeaway that’s starting to sound less theoretical each month: blockchains are now juicy targets. David Rhodus, founder of Permissionless Labs (and a contributor to Pipe Network), said: “This puts Solana among the most heavily DDoSed targets in internet history. It reinforces that blockchains are now Tier-1 DDoS targets. This is not “script kiddie” activity — 6 Tbps is industrial-scale.”

If you’re a validator, Mumtaz offered the practical advice you’d expect in a week like this: have backups across multiple hosting providers and regions. Because even if the chain holds, your own infrastructure might not.

The broader point, though, is the new baseline: these networks are getting stress-tested like mainstream internet services now. Solana’s claim today is that it passed — quietly, under load, and without users noticing. That’s the kind of victory that doesn’t look dramatic on a chart. It just [...] works.

At press time, Solana traded at $126.

SOL remains above the 200-week EMA, 1-week chart | Source: SOLUSDT on TradingView.com

Trending Cryptos

Related Reads

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit1h ago

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit1h ago

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit1h ago

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit1h ago

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit1h ago

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit1h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of SOL (SOL) are presented below.

活动图片