Rekt News engagement report
@RektHQ - 719K followers on X
Measured over 1 original post from a 30-day window, last computed on October 7, 2026.
Engagement
Early reading. We have captured 1 original post for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.
A typical post picks up 19 interactions against 719K followers, an engagement rate of 0.003%. Posts are seen about 26K times each, and 0.074% of those impressions turn into an interaction. That is about 3.59% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 1 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 880 interactions, about 15x its own typical post. Only 1 original post have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
Measured over 1 original post from a 30-day window, last computed on October 7, 2026.
Where this sits in the catalog
At 0.003%, Rekt News sits below the 10th percentile of the 204,583 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 13:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 100% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 100% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 302 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Jun 10, 202615x their median
Openness = opportunity. Open, public networks provide the basic infrastructure needed to build privacy solutions that actually work. @DenelleDixon in "Can Privacy and Transparency Coexist?", a documentary from @DefiantNews and @RektHQ. https://t.co/a9giWmD7Pk
- Aug 17, 202610x their median
Four years ago, Nomad's bridge was drained for $190M in two and a half hours. The exploit was one line. Copy the working transaction from Etherscan, swap in your own address, submit. No skills required. Hundreds did. Copycats took $88M of the total. TVL went from $190.38M to $5,336. Rekt's 17th leaderboard entry: https://t.co/dc0Qyrhlx2
- Aug 4, 20264.4x their median
In October last year, @thekmj_ and I won an audit contest for a prediction market on @sherlockdefi. The vulnerability that earned us the largest bounty was caused by a mismatch in the option trading fee calculation. Some background: Prediction markets like Polymarket are essentially binary options. This means that each market has a price for the call (yes) and put (no) options, a fixed payout (either 0 or 1), and an expiry time. These properties mean that users have two ways to exit a position: they can either sell their current contract or buy the opposite side. Mathematically, these are equivalent because, when selling, the user receives money from the open market, while buying the opposite side guarantees that one of the two contracts will always pay out. If the exchange wants to charge a trading fee, it cannot simply charge a percentage of the collateral being transacted. Why? Because whenever buying the opposite side requires less collateral than selling the existing position, users will always choose to buy instead of sell, effectively bypassing most of the trading fee. Consider the following simplified example: * There are two contracts: YES and NO. * The exchange charges a trading fee of 1%. * YES trades at $0.90 and NO trades at $0.10. * The user wants to exit a position of 100 YES contracts. If the user sells the 100 YES contracts on the open market, they receive $90 and pay a $0.90 trading fee. However, they could instead buy 100 NO contracts for $10, paying only a $0.10 trading fee. Since the market is binary, holding both YES and NO guarantees a payout of $100 at settlement, making this economically equivalent to selling the original position while paying a much lower fee. This asymmetry is why Polymarket implements a formula that calculates trading fees based on both the option prices and the collateral, ensuring that economically equivalent actions incur the same fee. I think these types of business logic vulnerabilities are among the hardest for AI to find. This is especially true when the underlying product is novel or based on mechanics that are not yet widely understood. If you are interested in learning more or discussing cyber sec/markets, reach out via DM.
- Aug 16, 20264.3x their median
https://t.co/Tsgj4KACfk
- Aug 13, 20263.2x their median
A firmware vulnerability silently routed @COLDCARDwallet hardware RNG for a guessable software fallback, letting attackers brute-force seeds offline. $130 million reported stolen so far, at least 15 attackers, most funds still untouched, nobody caught. https://t.co/JkPEeAfJvc https://t.co/o84JXawZxX
- Aug 10, 20263.0x their median
Q2 update for the 383 people funding Rekt on @Giveth. Two post mortems a week. Nine exploit breakdowns across June and July. $99M in documented losses, every one traced to root cause. Here's what happened. https://t.co/EyuixsTBSh
- Sep 2, 20262.9x their median
An attacker drained 148.3 million KII, worth roughly $9.7 million at the pre-exploit price, from @KiiChainio through the Cosmos EVM exploit class that also hit @MANTRA_Chain and @TacBuild. A halt immobilized 54.4% on-chain, but the rest had already crossed to BNB Chain. https://t.co/0V1tJyJJAR
- Aug 6, 20262.5x their median
Five years ago today, the biggest crypto hack ever. $611M gone from @PolyNetwork2 in one afternoon. Then the strangest twist in DeFi history: he gave it all back. Five years later, bridges are still the attack surface. VerusCoin and AFX Trade lost $31M to bridge exploits last month alone. https://t.co/pOtmP2E7FI
- Aug 25, 20262.1x their median
France’s tax authority confirmed data was extracted on 678,000 people and professionals. An insider allegedly used similar access to target crypto investors. Now a purported DGFiP dataset has been listed for sale for thousands of euros. https://t.co/cBrBe6oUh6 https://t.co/yuUJnYoRy2
- Aug 4, 2026
Beach reading is overrated. We made a summer crossword instead. 96 answers from DeFi's greatest disasters. Solve it, screenshot it, tag us. https://t.co/Z5SkrtsnaA https://t.co/hoqefAS9s9
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 19 interactions against 719K followers, an engagement rate of 0.003%. Posts are seen about 26K times each, and 0.074% of those impressions turn into an interaction. That is about 3.59% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 1 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 880 interactions, about 15x its own typical post. Only 1 original post have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
- What is Rekt News's engagement rate on X?
- Rekt News (@RektHQ) has an engagement rate of 0.003%, based on the median interactions across 1 original posts from the last 30 days against 719,111 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.003%, Rekt News sits below the 10th percentile of the 204,583 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @RektHQ have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @RektHQ post?
- Most posts go out around 13:00 UTC, and Monday is its busiest day, at roughly 0.4 posts per day across the measured window.