Julio Bandeira de Melo engagement report
@juliobmelo - 49K followers on X
Measured over 19 original posts from a 30-day window, last computed on October 21, 2026.
Engagement
A typical post picks up 2 interactions against 49K followers, an engagement rate of 0.004%. Measured over 19 original posts, its engagement rate beats 5% of 21,185 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 350 times each, and 0.571% of those impressions turn into an interaction. That is about 0.718% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.63 post a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 11:00 UTC, and Thursday is the busiest day of the week. Of the 19 posts sampled, 100% link out. The account's strongest tracked post pulled 12 interactions, about 6.0x its own typical post.
Measured over 19 original posts from a 30-day window, last computed on October 21, 2026.
Compared with accounts its own size
Julio Bandeira de Melo's engagement rate beats 5% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 4 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 18% 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 0.004%, Julio Bandeira de Melo sits above the 10th percentile of the 213,570 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.147% |
| 75th percentile | 0.699% |
| 90th percentile | 2.61% |
| 99th percentile | 82.9% |
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 11:00 UTC, and Thursday 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 | 0% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 0% 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 637 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
- Oct 1, 20266.0x their median
A high-severity flaw in the official MCP Python SDK lets a malicious server redirect OAuth authentication to attacker-controlled infrastructure while the victim sees a legitimate Google, Okta, or Microsoft login page. Machine-to-machine providers require no user interaction at all. If your agents autonomously select MCP servers, a compromised registry or typosquatting incident becomes full account takeover. Pin expected issuers explicitly, rotate tokens, and treat every MCP server your agents touch as a third-party identity provider. https://t.co/Vp4ACpEfUO #SupplyChainSecurity
- Oct 1, 20264.5x their median
Anthropic released a Compliance API that feeds Claude chats, files, and agent activity into existing SIEM, DLP, and eDiscovery workflows, including which MCP servers agents invoked. This closes a gap security teams have raised for months: knowing the concrete actions your agents took. Vendor telemetry will not substitute for your own governance, but it gives you something to govern. If your AI vendor cannot produce an audit trail of agent actions, that absence is now a procurement finding, not a roadmap request. https://t.co/O6T9fxUO1C #AISecurity
- Sep 27, 20262.5x their median
ThreatDown researchers discovered Carbonato, a botnet that targets exposed Docker daemon APIs on port 2375 without authentication, launches privileged containers, and installs the Hermes Agent AI framework with a custom persona. The agent handles operator commands through Telegram, collecting API keys, SSH credentials, and access tokens, while worm-like scripts scan adjacent networks every five minutes to spread. AI agent frameworks are becoming attack infrastructure. The governance question: do you treat your AI development and deployment environment with the same security controls as your production systems? https://t.co/pN7it5KztZ #SupplyChainSecurity
- Sep 26, 20262.0x their median
Anthropic published a detailed misuse report documenting how Claude was used for reconnaissance, exploitation, data theft, propaganda production, and surveillance workflows, with humans selecting targets and reviewing outputs. Bruce Schneier summarized the 117 findings. The report shows attackers industrialized credential theft and cloud compromise through AI agents, and surveillance cases included automated dossiers and systems that continued operating after model access was revoked. For security leaders: your AI governance framework must account for the possibility that your own AI tools are being used against you by adversaries who treat them as infrastructure, not novelties. https://t.co/WXdCPAYOd1 #AISecurity
- Sep 26, 20262.0x their median
Zenity Labs disclosed SalesBleed, a now-patched vulnerability in Salesforce Agentforce that enabled zero-click data exfiltration without logging in, accessing a target tenant, or requiring victim interaction. Attackers poisoned public Web-to-Lead forms with hidden instructions that Agentforce processed when an employee asked it to review recent leads. The agent then used its existing CRM access to query Account records, placing stolen data in attacker-controlled DNS hostnames. Salesforce patched the Trusted URLs bypass in August. Every organization running Agentforce should verify the fix and audit what data its AI agents can access across CRM objects. https://t.co/U57Mu9pfUH #SupplyChainSecurity
- Jul 31, 20262.0x their median
https://t.co/RV8PLdweFF
- Oct 1, 20261.5x their median
SOCRadar found 482 companies with corporate AI accounts exposed in infostealer logs over 90 days, with ChatGPT sessions appearing in roughly 90% of the records. A stolen session cookie replays as a live login that password rotation cannot kill, and the conversation history inside those accounts often contains source code, customer data, and unreleased plans. If an employee appears in a stealer log, that is an endpoint incident and a data exposure event, not a password reset. Put AI platforms behind SSO with short-lived sessions. https://t.co/XzgYYOPVn2 #CISO
- Oct 1, 20261.5x their median
Major AI vendors signed a White House accord committing to internal controls, independent external auditing, and board-level review committees, with the explicit note that these steps may eventually be codified into law. Security leaders should read this as a regulatory floor, not a ceiling. If your organization deploys frontier AI, the auditors named in this accord will soon expect evidence that your own AI governance matches the standard vendors are publicly accepting. Voluntary today becomes mandatory procurement language tomorrow. https://t.co/NJ6GJ4vVsm #AISecurity
- Aug 17, 20261.5x their median
The Scottish Crown Office disclosed a data breach on Aug 13 after a third-party supplier that administered a government-wide data maturity assessment was compromised. Multiple Scottish government agencies participated in the same program, and the vendor also serves the WWF and the government of Wales. A single compromised assessment vendor now threatens organizations that never contracted with it directly. This is the invisible perimeter your TPRM program was never designed to see: the vendor you hired to evaluate your own data maturity now holds your most sensitive organizational information. https://t.co/w61FGrZvbz #SupplyChainSecurity
- Aug 17, 20261.5x their median
Ransomware hit Colombia's Justice Ministry days before a presidential transition, disrupting court systems and prosecutorial infrastructure. The attackers chose the timing deliberately. Government institutions in Latin America face sustained ransomware pressure, and political transitions create windows of operational vulnerability. Security teams at government-adjacent organizations and those with operations in the region should review incident response timelines against the geopolitical calendar. Ransomware operators target organizations when they are least able to absorb disruption, and a leadership transition is precisely that window. https://t.co/7lT0MxvdPr #CISO
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 2 interactions against 49K followers, an engagement rate of 0.004%. Measured over 19 original posts, its engagement rate beats 5% of 21,185 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 350 times each, and 0.571% of those impressions turn into an interaction. That is about 0.718% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.63 post a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 11:00 UTC, and Thursday is the busiest day of the week. Of the 19 posts sampled, 100% link out. The account's strongest tracked post pulled 12 interactions, about 6.0x its own typical post.
- What is Julio Bandeira de Melo's engagement rate on X?
- Julio Bandeira de Melo (@juliobmelo) has an engagement rate of 0.004%, based on the median interactions across 19 original posts from the last 30 days against 48,764 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.004%, Julio Bandeira de Melo sits above the 10th percentile of the 213,570 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 @juliobmelo have real engagement?
- Its engagement rate beats 5% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the bottom 10% for its size 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 @juliobmelo post?
- Most posts go out around 11:00 UTC, and Thursday is its busiest day, at roughly 0.63 posts per day across the measured window.