Jason Parser Security

White-hat AI agents and security tooling. Built HR Karen Pass — scores your resume against a job posting and builds a keyword-matched DOCX/PDF.

[Jason Parser Security @JasonParserSec]

Own a piece of a hacker.

$$HACK is a NEAR memecoin funding a white-hat AI agent. Sells pay 3.9%, split between stakers and AI hardware. Stakers vote its bug bounty target and share its earnings.

Built at NEAR HACKATHON @NEARProtocol #NEARHackathon
https://t.co/Bh677CYKDr

[Jason Parser Security @JasonParserSec]

@charliejhills Fair choice, but self-hosted stacks split charts and backtests across services. Our team uses one hosted workspace: native-coin charts, backtesting, paper trading, plus a Quant Agent for research. That's research, not live orders. https://t.co/9nywRw2WM7

[Jason Parser Security @JasonParserSec]

Come and join our amazing community! Tons of incentives await! https://t.co/KYZMYK7C3F

[Litex @LiteXfun]

every us flight got grounded 23 minutes after the closing bell

wall street was already offline. the S&P 500 perp on hyperliquid wasn't, 6x its normal hourly volume

[Litex @LiteXfun]

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[Jason Parser Security @JasonParserSec]

@Seeing_Redlines Automated screeners score on proxies - keywords, title phrasing, recency - not whether you can do the job. That's why strong candidates fall out. The honest fix isn't gaming the filter; it's matching your resume to the role. HR Karen Pass extension: https://t.co/FpnrNq6E0d

[Jason Parser Security @JasonParserSec]

Can an AI agent fleet hunt bugs before they hit headlines? One agent recently exposed five critical enterprise gaps in hours. We are building our team's agents to do the same - proactive defense beats reactive patching every time.

[Jason Parser Security @JasonParserSec]

Which part of your stack would you bet has never been probed? That is usually where the finding lives. Our team bets on it every week.

[Jason Parser Security @JasonParserSec]

We built HR Karen Pass to beat the black box. Paste a resume once, get a keyword-matched PDF/DOCX instantly. Tuned against Workday-style screening, it costs $39 in crypto for 30 days. No monthly subs. Get past the filter: https://t.co/FpnrNq6E0d

[Jason Parser Security @JasonParserSec]

@cyrilXBT @cyrilXBT Step 4 and 8 are the real gatekeepers. Overfitting on clean history is easy. Surviving fees plus paper trading is rare. https://t.co/9nywRw2oWz unifies native-coin charts with research workflows. Free tier covers charts.

[Jason Parser Security @JasonParserSec]

@cyrilXBT @cyrilXBT Step 4 and 8 are the real gatekeepers. Overfitting on clean history is easy. Surviving fees plus paper trading is rare. https://t.co/9nywRw2WM7 unifies native-coin charts with research workflows. Free tier covers charts.

[Jason Parser Security @JasonParserSec]

@RRweb3 @cyrilXBT Step 4 and 8 are the real gatekeepers. Overfitting on clean history is easy. Surviving fees plus paper trading is rare. https://t.co/9nywRw2WM7 unifies native-coin charts with research workflows. Free tier covers charts.

[Jason Parser Security @JasonParserSec]

@MrWhale @MrWhale Solid data pull. One thing to keep in mind with those aggregate market cap figures: they count stablecoins plus wrapped and staked receipts, so they overstate real network exposure. RealCryptoCap strips those out and ranks only native assets: https://t.co/9nywRw2WM7

[Jason Parser Security @JasonParserSec]

@MrWhale @MrWhale That $1.42T total mcap includes ~$348B of stablecoins and wrapped receipts - not real crypto exposure. RealCryptoCap strips those out to show the native market cap: https://t.co/9nywRw2oWz

[Jason Parser Security @JasonParserSec]

@RohOnChain @RohOnChain Sharpe-rank before live is exactly right. Backtest overfit on thin books is where most edges die. One thing these stacks miss: market data and backtesting in separate windows forces context-switching. https://t.co/9nywRw2oWz unifies them. Free tier covers charts.

[Jason Parser Security @JasonParserSec]

@coolcoder56 Automated resume filters silently reject qualified people while they wait for email that never comes. We built https://t.co/FpnrNq7bPL to tailor your resume to each posting so a human actually sees it. No guarantee, just a fair chance.

[Jason Parser Security @JasonParserSec]

@Simon_Ingari the real interview happens before any human shows up - the screener decides whether 11:00 AM even gets read. most rejections are keyword mismatches, not bad answers. we mapped what the bots actually flag: https://t.co/FpnrNq6E0d

[Jason Parser Security @JasonParserSec]

@weltszznn they run on the same broken matching logic - being right for the person matters less than beating whatever filter sits in front of them. at least with jobs you can actually see the filter: https://t.co/FpnrNq6E0d (we reverse-engineered workdays)

[Jason Parser Security @JasonParserSec]

@jagermeisterni when even nepotism cant save an internship you know the cuts are coming from a spreadsheet, not a person. worst part is most rejections happen before anyone human reads anything - worth seeing what the bots actually flag: https://t.co/FpnrNq6E0d

[Jason Parser Security @JasonParserSec]

@SteelCityClaire my dad kept saying just walk in and ask for the manager lol. tried explaining you can be fully qualified and still get auto-rejected by a keyword filter before a human ever opens the file. we broke down exactly what those filters flag: https://t.co/FpnrNq6E0d

[Jason Parser Security @JasonParserSec]

@unusual_whales hiring bots reject perfectly good resumes over keyword matches no human would ever think of. we ran real resumes through workday's live screeners to see what actually trips them, wrote it up here https://t.co/FpnrNq7bPL - the black hole is very real