#aidefense

Live, measured metrics for the hashtag #aidefense from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #aidefense

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$51.02/ year · 9-character #name
Claim #aidefense — $51.02/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
34
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 34
0
Avg reactions / post
Mastodon · last 34
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.online (Mastodon public tags API) · fetched 2026-10-03 07:04 UTC
0
09-27
0
09-28
0
09-29
0
09-30
0
10-01
0
10-02
0
10-03

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.online (Mastodon public search API) · fetched 2026-10-03 07:04 UTC
#aidefensesystems
0 uses · 0 accounts / 7d
#aidefenseplane
0 uses · 0 accounts / 7d
#aidefensestock
0 uses · 0 accounts / 7d
#aidefensetechnology
0 uses · 0 accounts / 7d
#aidefenseukraine
0 uses · 0 accounts / 7d
#aidefenseleague
0 uses · 0 accounts / 7d
#trenchLevelAIDefense
0 uses · 0 accounts / 7d
#aidefensetechstartups
0 uses · 0 accounts / 7d
#aidefenseplatform
0 uses · 0 accounts / 7d

Live pulse

measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-03 07:04 UTC

Everything below is measured over the latest 34 public posts (spanning ~12600 hours).

Posting hours (UTC) — busiest: 11:00

00:0012:0023:00

Languages: English (29) · French (3) · German (1) · Italian (1)

Avg boosts / post: 0.2

Top of the latest posts

  • We built secure automated learning loops in Modal and Claude Code Terse 팀은 Modal과 Claude Code를 활용해 보안이 강화된 자동 학습 루프 기능을 개발했다. 이 기능은 배포된 워크플로우와 로그를 분석해 개선점을 주기적으로 제안하며, Modal의 샌드박스와 LiteLLM 프록시를 통해 인프라 및 애플리케이션 레벨에서 다중 보안 계층을 구현했다. 특히, 가상 키,

    ainews@[email protected]♥ 0↻ 02026-06-24 18:40 UTCView post →

  • The catalogue of prompt injection attacks 프롬프트 인젝션 공격은 LLM이 신뢰할 수 있는 명령과 사용자 입력을 구분하지 못하는 점을 악용해 모델의 지시를 덮어쓰는 기법입니다. 본문은 10가지 기본 공격 유형을 소개하며, 각 방어책은 곧 우회 공격에 의해 무력화되는 고양이와 쥐 게임임을 설명합니다. 특히 에이전트 환경에서는 단순 출력 이상으로 데이터 유출이나 악의적 행위가 가능해 구조적 방어가

    ainews@[email protected]♥ 0↻ 02026-06-15 20:43 UTCView post →

  • Secure Infrastructure Unlocks AI's Defense Potential As Dave Wajsgras, chairman and CEO of Everfox, aptly puts it, AI's trustworthiness is only as strong as the security of its underlying data, networks, and access controls. A recent incide

    Analyst207@[email protected]♥ 0↻ 02026-06-04 17:07 UTCView post →

#aidefense across platforms

every network with a public tag surface

Follow #aidefense straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.

X (Twitter) ↗Instagram ↗TikTok ↗Facebook ↗LinkedIn ↗YouTube ↗Threads ↗Bluesky ↗Mastodon ↗Reddit ↗Pinterest ↗Tumblr ↗

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/aidefense