JS0N Haddix engagement report
@Jhaddix - 181K followers on X
Measured over 40 original posts from a 30-day window, last computed on October 17, 2026.
Engagement
A typical post picks up 117 interactions against 181K followers, an engagement rate of 0.065%. Measured over 40 original posts, its engagement rate beats 51% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 9.2K times each, and 1.27% of those impressions turn into an interaction. That is about 5.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 40 posts sampled, 30% carry an image or video, 5% are part of a thread and 15% link out. The account's strongest tracked post pulled 838 interactions, about 7.2x its own typical post.
Measured over 40 original posts from a 30-day window, last computed on October 17, 2026. Recurring tag: #cybersecurity.
Compared with accounts its own size
JS0N Haddix's engagement rate beats 51% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 49% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.065%, JS0N Haddix sits above the 25th percentile of the 212,925 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.698% |
| 90th percentile | 2.61% |
| 99th percentile | 83.0% |
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 17:00 UTC, and Friday 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 | 30% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 15% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 30% 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.
- 15% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 301 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
- Aug 15, 20267.2x their median
If you are a young vulnerability researcher, it's important to remember this: When people write blog posts or give conference talks on the brilliant multi-bug exploit chains that they discover, they generally talk about it as though they just elegantly pranced from one brilliant insight to another. The reality, of course, is almost always much less elegant, and involved a lot more banging of one's head against the wall to finally stumble into each brilliant insight. But you can't blame people for doing this, because talking about the 1,001 things that didn't work would make the talk or blog post way too long and incomprehensible.
- Aug 21, 20266.3x their median
Yesterday I popped an XSS. No scanner, no AI, just my brain and my monkey fingers. Like a maniac. 🤷🏻♂️
- Oct 1, 20266.1x their median
Remember: "Agentic" and "Harnesses" are (mostly) just giving little LLM calls tools like bash/powershell and web search. And sending them off on a quest. Skills: are just prompts in a folder, maybe with some scripts or a reference output. It's not magic. If you watch harnesses work... what are they doing? command-line calls. Thousands of them.
- Oct 9, 20265.8x their median
📄 Skills in Agent Harnesses A lot of people don't know this (I didn't until recently) but most agent harnesses will load the description of your skill upon starting up your harness. This is how Claude Code works. What people don't usually know is that even when you explicitly call a skill to be used inside of a harness, or the AI figures out to use a skill, it usually only does a read of the first 150 lines of the skill (to understand how to use it or if it applies to the work it's trying to do). It's really important to outline a table in the first 150 lines of the mandatory parts of the skill that must be run when you invoke the skill. If you make some type of mandatory instruction after 150 lines, it might get missed entirely. If you describe in prompting that you want to use a provided Python script or template, it also might be out of bounds of that 150 lines and never get called correctly. If you write a table of contents of the skill actions in the first 150 lines and mark which ones are mandatory (or that, if the user has called the skill, you must read the whole skill context and all references), you get more reliable skills. We use markdown checklists for this now.
- Aug 12, 20265.0x their median
Over 71 free prompt injection labs and more to be added (and removed) next week! https://t.co/LjrbXS3PI7 And If you you want to learn how to pentest and hack AI systems check out: Attacking AI: https://t.co/cp2y6DDxqp 🫶🫶 https://t.co/2GFhzUmunI
- Oct 1, 20263.7x their median
I tend to find real bounty and pentests to be the best eval for hackbots. Yesterday i pitted GLM, Kimi, and Claude against an authorized target. It was an installed instance of paid software. Claude went the dynamic web pentester route, mining js for paths and fuzzing them. Found quite a few interesting info leaks. GLM did this too at 1st, but then pivoted to downloading the software and inspecting code. Kimi did the same as GLM, but started doing patch differentials for n-day CVEs and leads. Fascinating.
- Aug 18, 20263.5x their median
Most AI Red Teaming or Pentesting courses teach you one or two agent exfiltration methods... In our next version of "Attacking AI" We'll be sharing exclusive tooling (Agent-Raider) with the students that allows you to create payloads for our proprietary ~80 exfiltration techniques and channels for exploiting AI agents. Steal data, bypass sandboxing, and pivot using these technique primitives! Agent-Raider also works with our Arcanum Prompt Injection Taxonomy as well! Link for the next class: https://t.co/IYAgKSQiWV
- Sep 30, 20263.5x their median
I had a great conversation with a CISO friend of mine the other day. These are just some notes that fell out. Definitely my two cents. 🫶 FYI I am a recovering 7 year CISO. I've been on the full enterprise track and the smaller fractional lane. 1) The offense speedup from AI is real and nothing stops it. Organizations that have never carried realized risk are about to (breaches, product outages, sev1 incidents). 2) You have to shift from risk-management programs to add engineering programs. If you aren't already comfortable integrating with your organization's engineering teams, get comfortable fast. You should be building a security engineering team that can actually help with development of security features and pipeline automation, you're going to need this ASAP. Many of you on X will say that this is table stakes. You would not believe the amount of security leaders I talk to where it is absolutely not table stakes, and they have nothing close to this in their organizations. 3) You are going to have to shift from annual vulnerability cycles to fast ones with rehearsed playbooks and SOPs for real exploitation scenarios or impacts. Drill via tabletops, with real artifacts, and get used to roles, responsibilities, emergency comms ops, etc. Additionally, vulnerability management becomes more important than ever, with tight and fast remediation workflows needed for this new increased-speed age. 4) Start talking to your execs and boards about this shift. Cite the recent AI labs incidents if you need to. Work hard to position cybersecurity FROM a gate -> TO security that moves at engineering speed. Don't forget to beat the drum about product downtime and how that materially impacts the organization when it weighs cybersecurity against the overall budget planning.
- Sep 16, 20263.4x their median
Today we are releasing a 1 page version of “Hacking Your Career” https://t.co/Ca8AUDayJ9 We get a bunch of students and early career-seekers looking for resources and advice of getting their 1st gig. This resource gives all those and more; free trainings, free certificates for your résumé, advice on résumé design, information on career verticals, small sections on interviewing and the hiring process, and more! 🫶🫶
- Aug 12, 20263.3x their median
Personal post: My 1st born leaves for college this week. We are best friends. I stand with her, as support and guidance, as she goes off to college but I’m also in some sort of mourning.
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 117 interactions against 181K followers, an engagement rate of 0.065%. Measured over 40 original posts, its engagement rate beats 51% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 9.2K times each, and 1.27% of those impressions turn into an interaction. That is about 5.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 40 posts sampled, 30% carry an image or video, 5% are part of a thread and 15% link out. The account's strongest tracked post pulled 838 interactions, about 7.2x its own typical post.
- What is JS0N Haddix's engagement rate on X?
- JS0N Haddix (@Jhaddix) has an engagement rate of 0.065%, based on the median interactions across 40 original posts from the last 30 days against 181,037 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.065%, JS0N Haddix sits above the 25th percentile of the 212,925 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 @Jhaddix have real engagement?
- Its engagement rate beats 51% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @Jhaddix post?
- Most posts go out around 17:00 UTC, and Friday is its busiest day, at roughly 2.03 posts per day across the measured window.