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Kelp DAO, a Liquid Restaking Protocol on EigenLayer Hacked for over $280M 

By
Paul Ugbede Godwin
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0

Kelp DAO, a liquid restaking protocol on EigenLayer suffered a major exploit on April 18, 2026. Attackers drained approximately $280M–$293M worth of rsETH, its liquid restaking token. The vulnerability was in Kelp DAO’s rsETH cross-chain bridge powered by LayerZero.

The attacker drained ~116,500 rsETH — roughly 18% of the token’s circulating supply. They then used the stolen or unbacked and forged rsETH as collateral on lending protocols like Aave V3 on Ethereum and Arbitrum to borrow large amounts of ETH and WETH.

Funds were routed through Tornado Cash to obscure the trail. This created bad debt on Aave and other platforms, as the rsETH collateral turned out to be worthless or unbacked once the exploit was discovered. The incident is now considered the largest single DeFi exploit of 2026 so far.

Immediate Aftermath

Kelp DAO paused its rsETH contracts and bridge across Ethereum mainnet and multiple L2s. Aave, SparkLend, Fluid, and other protocols froze related markets to prevent further losses. Aave’s WETH suppliers faced potential losses from bad debt; Aave’s Umbrella safety module is expected to help cover some of it.

The $AAVE token price dropped sharply reports of 10–15% in hours due to contagion fears. Wrapped ETH became stranded or frozen across ~20 chains due to the omnichain nature of the bridge. This highlights ongoing risks with cross-chain bridges and omnichain fungible tokens (OFTs), especially those relying on default LayerZero configurations.

Some analysts are warning that similar setups on other protocols could be at risk if the root cause involves compromised signers or misconfigurations. It also follows other big exploits in April 2026 like the Drift Protocol’s ~$280M incident earlier in the month, adding to DeFi’s rough start to the year.

~18% of rsETH supply (116,500 tokens) was drained via the LayerZero-powered cross-chain bridge and adapter. This created unbacked or fake rsETH on multiple chains. Kelp paused rsETH contracts, minting and burning, and bridges across Ethereum mainnet and several L2s to contain further damage.

Holders of rsETH especially on non-mainnet chains now face uncertainty: their tokens may lack full backing, leading to redemption pressures, depegging risks, or forced unwinding of underlying restaked positions in EigenLayer.

Kelp’s TVL previously over $1B in ETH LRTs will likely drop sharply. The protocol is investigating with LayerZero and security experts; recovery is uncertain, as funds were routed through Tornado Cash. The attacker used stolen and unbacked rsETH as collateral on Aave V3/V4, borrowing large amounts of WETH/ETH. This left ~ $290M in bad debt on Aave’s WETH pools, as the collateral is now effectively worthless or unliquidatable.

Aave froze rsETH markets immediately to stop new exposure. WETH suppliers are being urged to withdraw positions, as partial haircuts or delays may occur while Aave’s Umbrella safety module handles the deficit. This is a major real-world stress test for Umbrella. Other protocols affected: SparkLend, Fluid, and at least 7–9 more froze rsETH-related markets or positions. Wrapped ETH became stranded across ~20 chains due to the omnichain setup.

AAVE token dropped ~10–13% amid fears of losses and broader contagion. No direct compromise of Aave’s contracts, but the event shows how external collateral failures can cascade. Cross-chain bridge vulnerabilities are back in focus. The exploit reportedly involved a misconfiguration or single-verifier issue in LayerZero’s OFT. This highlights catastrophic failure modes in default bridge configurations and composability risks.

Liquid restaking (LRTs) like rsETH face renewed scrutiny. Assumptions that these tokens are blue-chip collateral widely used on Aave for yield loops have been challenged. Protocols will likely tighten risk parameters for restaked assets, potentially reducing TVL and yields across EigenLayer participants. This is the largest single DeFi exploit of 2026 so far, surpassing or rivaling Drift Protocol’s $285M incident earlier in April.

Combined with other hacks, Q1/Q2 2026 has seen heavy losses; $600M+ in recent weeks, eroding confidence. ETH dipped ~3–4%; Polymarket odds on ETH price targets shifted lower as traders reassess DeFi exposure. Restaking sector sentiment is hit hard. Expect audits/reviews of LayerZero integrations, multi-verifier requirements for bridges, and stricter collateral onboarding in lending protocols. AI tools are noted as lowering barriers for sophisticated attacks.

This is a painful reminder of interconnected risks in DeFi — one bridge flaw can ripple through lending, restaking, and multiple chains. Short-term: volatility, frozen positions, and potential small losses for some suppliers. Long-term: likely leads to more conservative risk management and improved bridge standards.

If you hold rsETH, have exposure to Aave WETH pools, or use any Kelp-related bridges, check your positions and follow official updates from Kelp DAO and the affected protocols. On-chain sleuths like ZachXBT were among the first to flag it.

Nigeria’s Stock Market Extending its Equities Trading Hours from 9.00 a.m to 4.00 p.m WAT

By
Paul Ugbede Godwin
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0

Nigeria’s Nigerian Exchange Limited (NGX) is extending its equities trading hours to 9:00 a.m. – 4:00 p.m. WAT (West Africa Time), effective Monday, April 27, 2026. Previously, trading ran from 9:30 a.m. to 2:30 p.m. This change adds about two hours to the daily session; one hour earlier open and 1.5 hours later close and was approved by the Securities and Exchange Commission (SEC) Nigeria.

The move follows FTSE Russell’s announcement in early April 2026 that Nigeria will return to its Frontier Markets index effective September 2026. Nigeria had been reclassified as Unclassified (standalone) for over two years due to issues like foreign exchange liquidity and capital repatriation challenges. The re-inclusion reflects improvements in market infrastructure, liquidity, and accessibility.

NGX described the extension as building on this momentum to: Deepen market liquidity. Enhance price discovery. Broaden investor access including for domestic, retail, institutional, and international participants. Give investors more time to react to news and execute trades. Align Nigeria’s market with more global standards and make it more competitive.

The Nigerian stock market has performed strongly recently with notable gains in 2025 and early 2026, and the FTSE Russell decision triggered rallies in some dual-listed stocks and overall positive sentiment. More trading flexibility — Especially helpful for those in different time zones or with daytime commitments.

Potential for higher volumes — Longer sessions often support better liquidity and narrower spreads over time.  It signals Nigeria’s efforts to attract more foreign portfolio investment as it rejoins global benchmarks, which can bring passive inflows from index-tracking funds.

Note that pre-trading or post-trading sessions (if any) and exact order types and boards may have additional details in NGX’s market structure rules; the core continuous trading window is shifting to 9:00 a.m.–4:00 p.m. This development is part of broader reforms at NGX to position the market as more accessible and liquid within Africa’s frontier space.

This change, approved by the SEC and timed with Nigeria’s upcoming return to FTSE Russell’s Frontier Markets index in September 2026, aims to modernize the market and capitalize on improving investor sentiment. Deeper liquidity and tighter spreads: Longer sessions typically allow more buyers and sellers to interact throughout the day, reducing the concentration of activity in a short window.

This can narrow bid-ask spreads, lower transaction costs, and make it easier to execute larger orders without significant price impact. NGX explicitly cited this as a core goal. Investors gain more time to digest news, earnings, economic data, or global events like oil prices, FX movements, or international developments and react in real time rather than rushing or carrying positions overnight.

This should lead to more efficient and accurate pricing over time. Domestic retail and institutional investors benefit from greater flexibility, especially those with daytime jobs or in different parts of Nigeria. International investors find the schedule more compatible with global time zones, potentially encouraging more cross-border flows as Nigeria rejoins benchmark indices.

Passive inflows from frontier-tracking funds and ETFs could increase, particularly into liquid large-cap and banking stocks. The move aligns Nigeria’s market infrastructure closer to global standards, reinforcing the positive momentum from FTSE Russell’s reclassification. It positions NGX as more attractive for capital formation and could support higher overall market volumes and activity in the medium term.

More window to trade without feeling rushed; potential for better entry and exit prices and reduced overnight risk for some positions. However, it requires adjusting routines. Greater ability to manage portfolios across time zones, respond to news, and integrate Nigerian equities into broader strategies.

Combined with index re-inclusion, this could gradually attract more foreign portfolio investment, though actual inflows will depend on macroeconomic stability. Expect operational adjustments for staffing, systems, and risk management during the extended window. Initially, liquidity may be thinner at the new open and close edges, but it should normalize as participants adapt.

 

The first weeks and months may see uneven liquidity distribution, with possible wider spreads or higher volatility during less active parts of the new session. Historical examples from other markets show that extended hours can start thin before building depth. Brokers, clearing systems, and surveillance must handle the longer day smoothly. While NGX consulted stakeholders, minor teething issues could arise.

No guarantee of immediate volume surge: Extended hours support liquidity but do not create it alone. Sustained benefits will hinge on underlying fundamentals—economic reforms, corporate earnings, and continued improvements in market accessibility. More trading time can amplify intraday moves if major news hits, though it may also dampen overnight gaps in the long run.

 

The change is structurally positive for accessibility and efficiency, but markets remain driven by fundamentals. Expect gradual benefits in liquidity and participation rather than an overnight transformation. Monitor early trading data post-April 27 for volume trends, spreads, and volatility patterns.

AI Bias Stems from Patterns of Datasets Created by Humans

By
Paul Ugbede Godwin
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0

AI bias refers to systematic and repeatable errors in AI systems that produce unfair, prejudiced, or skewed outcomes. These arise because AI models especially machine learning and large language models learn patterns from data created or curated by humans, who are inherently imperfect and influenced by societal, historical, and cognitive factors.

Bias is not always intentional—it often reflects real-world inequalities baked into training data, design choices, or deployment contexts.
Understanding the different types of AI biases is crucial for developers, users, and policymakers, as unchecked bias can lead to discriminatory hiring, flawed medical diagnoses, unfair lending, or amplified stereotypes.

Biases are often grouped into three broad buckets: input and data bias, system and algorithmic bias, and application and interaction bias. These stem from the training data itself—it’s rarely perfectly representative of the real world. Data reflects past societal prejudices like historical hiring data favoring men leads to AI recruiters downranking women.

Data underrepresents or overrepresents groups like facial recognition datasets dominated by lighter-skinned faces, causing higher error rates for darker skin tones.
How features are measured or labeled is flawed using flawed proxies like zip code for socioeconomic status, which correlates with race. Certain events are under- or over-reported in data.

Amazon’s 2018 hiring tool still cited in 2025 discussions was scrapped because it penalized resumes with women’s terms, trained on male-dominated tech hiring history. These emerge from the model’s design, architecture, or optimization choices—even with clean data. The math or rules favor certain outcomes like optimization prioritizing speed over fairness.

Treating all groups as homogeneous when subgroups differ; a health model averaging across demographics ignores unique needs of subgroups. Testing metrics or benchmarks don’t match real-world use. Biases that appear only after combining datasets or in complex models. AI reinforces users’ or developers’ preconceptions.

Over-reliance on AI outputs, ignoring errors; common in high-stakes decisions like healthcare or policing. Developers unconsciously embed their own views in labeling, feature selection, or prompts.
AI amplifies cultural stereotypes. Broader societal manifestations these cut across categories.

Racial, gender, age, socioeconomic, cultural, or political biases often appear as downstream effects e.g., LLMs favoring certain languages or ideologies due to English-heavy web data.
Many sources map bias as a cycle: real-world inequalities, data, model design, deployment,  amplified injustices.

Even with advances like better debiasing techniques like adversarial training or diverse datasets, biases remain because: Data is historical and web-scraped; mirroring internet inequalities. Models optimize for accuracy on average, not fairness across groups. Biased outputs generate more biased data. Recent examples (2025–2026) include healthcare AI exacerbating treatment gaps, generative tools producing culturally skewed content, and recruitment systems still showing gender and racial skews despite fixes.

AI tools have downgraded resumes with women’s terms, favored male candidates, or rejected applicants based on age, race, or disability proxies like Amazon’s scrapped tool; ongoing lawsuits against Workday’s AI screening in 2025, certified as class actions for disparate impact on older, Black, or disabled candidates.

Qualified individuals from marginalized groups face systematic exclusion, leading to immediate rejections and long-term career setbacks. Lawsuits, settlements, PR damage, and regulatory scrutiny like the NYC, California rules on AI hiring tools. Algorithms underestimated care needs for Black patients using spending as a proxy or downplayed women’s symptoms in summaries e.g., 2025 studies on LLMs like Gemma showing softer language for female patients.

Psychiatric treatment plans varied by race; misjudgments in imaging or risk scoring led to delayed or inadequate care. Worsened health outcomes, higher malpractice risks; settlements up to $17M, and deepened inequities for marginalized groups. Tools like COMPAS falsely flagged Black defendants as higher recidivism risks; nearly twice the rate of white defendants, influencing sentencing and bail.

Higher misidentification rates for darker skin tones, contributing to wrongful arrests or surveillance harms. AI bias isn’t a bug—it’s a mirror of human data and decision-making. Exploring it reveals opportunities for more robust, transparent systems via fairness audits, diverse teams, and ongoing monitoring. True progress comes from acknowledging these patterns without oversimplifying them as purely societal or fixable by one method.

AI Bookspam Wave Increasing Grut of Slops in 2026

By
Paul Ugbede Godwin
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0

The AI bookspam wave refers to the massive surge of low-quality, often entirely or mostly AI-generated books flooding self-publishing platforms—especially Amazon’s Kindle Direct Publishing (KDP)—since the rise of accessible generative AI tools like ChatGPT in late 2022/early 2023.

This has created a glut of slop: short, generic, poorly edited ebooks in niches like romance, self-help, summaries, guides, and knockoff biographies that mimic popular titles or authors. Thousands of AI-assisted or fully generated titles appear monthly. Reports from 2023–2025 describe it as an explosion or flood, with categories like teen romance, travel guides, or public-domain rewrites getting swamped. Some operators churn out dozens or hundreds under multiple pen names.

AI companion books, summaries, analyses, or imitations popping up alongside real bestsellers almost immediately. Knockoffs of popular works, such as AI versions of existing biographies; multiple fake Earl Weaver books appearing right after a legitimate one. Scammy rewrites or guides that ride on real authors’ success, sometimes using similar titles and covers.

Outlier claims, like one person reportedly making six figures with romance novels via AI, or exaggerated stories of publishing 1,500+ titles often met with skepticism. Many read as incoherent, repetitive, or lacking depth—hallmarks of unedited AI output. Some include dangerous advice. Readers complain of wasted money on Kindle Unlimited, and authors see diluted sales or review bombing. This isn’t entirely new—self-publishing has long had low-effort spam—but generative AI lowered the barrier dramatically, enabling rapid production at near-zero marginal cost.

Amazon has tried to manage it: Disclosure rules: Publishers must flag AI-generated content; text, images, translations during upload. Failure can lead to removal. Capped at ~3 new titles per day per account, implemented around 2023–2024 to slow spam factories. Bans on certain low-value companion guides without proven engagement; algorithmic suppression of duplicates or low-quality items.

Other actions: Account terminations for abuse, and occasional mass de-listings. Similar efforts at Barnes & Noble and distributors like IngramSpark. Despite this, enforcement is imperfect. Sophisticated spammers use editing, human oversight, or evasion tactics, and the sheer scale makes full cleanup tough. Amazon also rolled out AI features like “Ask This Book” a chatbots querying ebook content which has sparked separate author concerns over rights and competition.

Harder to find quality amid the noise. Search results clog with generic junk, eroding trust in self-published ebooks. Refunds and bad reviews hurt the ecosystem. Increased competition in saturated niches like romance, nonfiction guides. Real books can get buried in algorithms favoring volume or paid promo. Some see sales cannibalized by knockoffs; traditional publishers worry about diminished investment in new talent.

On the market: It highlights self-publishing’s double-edged sword—democratization vs. quality collapse. Critics call it content spam that devalues writing; defenders note AI can assist editing or ideation, and not all AI-involved books are bad. AI marketing scams, flattering emails offering promo and bot comments promoting these books have surged too. Traditional publishing isn’t immune—some agents and publishers get flooded with AI submissions.

By 2025–2026, the wave hasn’t fully receded, but it’s evolved: more hybrid human+AI work, better detection, and reader pushback. Data on exact flood scale is fuzzy, but anecdotes from authors, Reddit, and outlets like WIRED, NPR, and Authors Guild show persistent frustration. Not every self-published book is AI spam—far from it—but the low-effort subset creates a visibility problem.

This mirrors AI’s effect elsewhere: abundance of mediocre output drowns signal in noise. Human creativity, emotion, originality, lived experience still stands out for many readers, and classics and backlist titles remain untouched. Long-term, it may accelerate shifts toward curation, verified human authorship signals, or premium AI-disclosed vs. human-crafted branding. Some experiment with AI as a tool, but pure spam rarely builds sustainable careers—most self-publishers earn little regardless.

Revised Stablecoin Yield Language in the U.S CLARITY Act Postponed

By
Paul Ugbede Godwin
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0

The release of the revised stablecoin yield language in the U.S. CLARITY Act, a key part of broader crypto market structure legislation has been postponed from this week to next week or later. Senator Thom Tillis (R-N.C.) confirmed in a Thursday interview that he won’t release the compromise text on stablecoin yields this week.

The main reason is uncertainty around the Senate Banking Committee’s markup schedule for the broader bill—he wants clearer timing before going public with the draft. The CLARITY Act aims to provide regulatory clarity for digital assets, including stablecoins. The yield provision is one of the most contentious parts because it pits traditional banks against crypto firms.

Banks’ position via groups like the ABA: They worry that yield-bearing or reward-paying stablecoins could pull deposits away from traditional banking products. They push for strict limits, especially on idle balance rewards. Crypto firms argue that rewards often tied to usage or transactions are essential for competition and innovation in stablecoins like USDC or USDT. Some see outright bans as anti-competitive.

The current draft language still under negotiation reportedly maintains a ban on rewards for simply holding idle stablecoin balances but allows certain yields or rewards linked to actual transactions or activity. This is seen as a potential middle ground, but talks with banks and crypto companies continue.

This isn’t the first delay—the yield issue has already stalled progress multiple times, including an earlier markup postponement. The GENIUS Act already includes some restrictions on issuers paying interest and yield directly, but the CLARITY Act negotiations are trying to refine or strengthen rules around what exchanges or platforms can offer to users.

Clarity on whether stablecoins can sustainably offer yields and rewards affects issuer business models, user incentives, and competition with traditional finance. Prolonged uncertainty can contribute to market hesitation. Lawmakers are aiming for a Senate Banking Committee markup, but unresolved issues including this one, plus others like DeFi rules keep pushing dates back.

Some reports note the odds of the broader bill passing in 2026 have fluctuated amid these hurdles. Expect more updates next week if the markup schedule firms up. Negotiations are ongoing behind the scenes, so the final compromise could still shift. This is a classic Washington standoff between incumbents protecting deposits and innovators seeking growth in the stablecoin space.

The delay pushed to next week or later stems from uncertainty over the Senate Banking Committee markup schedule. Without a firm date, releasing the text risks premature backlash. This adds friction to an already tight calendar. If the committee doesn’t advance the bill by late April and early May, odds of full passage in 2026 drop sharply, some analysts say near zero due to midterm election dynamics.

The bill still needs multiple steps: committee markup, Senate floor vote (60 votes), House reconciliation, and signature. Current draft language still under negotiation bans rewards amd yield on idle balances but allows activity-based yields tied to transactions or usage. This remains the core compromise.

Prolonged uncertainty hurts planning for issuers like Circle/USDC, Tether/USDT and platforms. It limits innovation in reward structures that drive user adoption. Earlier similar news caused sharp stock drops like Circle’s shares fell ~20% in one day on yield-limit fears. Banks continue lobbying to tighten restrictions, fearing deposit flight. A recent White House report downplayed the economic impact, a full ban might boost bank lending by just ~0.02%, with net consumer welfare costs.

Crypto firms view strict limits as protectionism. Ongoing talks including with banking groups show the issue isn’t fully resolved. Adds to hesitation and volatility in crypto markets, especially stablecoin-related tokens and companies. Prediction markets for bill passage have fluctuated recently seen dips. Delays regulatory clarity in the world’s largest economy, while other regions advance their own stablecoin rules. This could slow U.S. competitiveness in the multi-hundred-billion-dollar stablecoin market.

Broader crypto legislation like market structure, DeFi elements remains stalled until this and other disputes clear. It’s a procedural hiccup in a months-long negotiation, but it highlights deep divisions. No major immediate market shock reported from this specific delay, but cumulative uncertainty erodes momentum. Expect updates next week if markup timing solidifies—watch for any shifts in the idle-balance ban vs. activity-based allowance.

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