Prompt injection
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arXiv:2610.38120v1 Announce Type: new Abstract: Large Language Models (LLMs) treat all context tokens uniformly, lacking explicit separation between executable instructions and passive data. This leads to prompt injection vulnerabilities, ambiguous instruction binding, and unreliable execution control. We present a post-training methodology using LLMON (LLM
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- First observed in our collection
- Oct 10, 2026, 6:30 PM UTC
- Earliest cited publication
- Oct 10, 2026, 12:30 PM UTC
- Last observed
- Nov 2, 2026, 5:15 PM UTC
Evidence in the last complete seven days
- Source mentions
- 2 Previous seven days 2
- Distinct sources
- 2 Previous 2
- Comparable growth
- Not comparable
- Ranking appearances
- 0
Collection observations and undated records are separate from dated publication counts. Observed in 7d：2 · Undated records：1
Collection coverage · Limited historyCurrent / previous observed days 7 / 3
Counts use complete UTC days. First observed means first seen by this collection, not when a term was coined.
Current window：2026-10-29 → 2026-11-05 (end excluded) · History 11 days
| Source | Current days | Previous days | Last success |
|---|---|---|---|
| arXiv | 6 | 3 | Nov 5, 2026, 10:00 AM UTC |
| arXiv | 7 | 2 | Nov 5, 2026, 10:01 AM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 12:15 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 1 | Nov 5, 2026, 12:00 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| GitHub Discovery | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| GitHub Trending | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| 7 | 2 | Nov 5, 2026, 10:00 AM UTC | |
| Hugging Face | 7 | 2 | Nov 5, 2026, 8:15 AM UTC |
| Hugging Face Spaces | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 12:45 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 3:30 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 3:30 PM UTC |
| Hacker News | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| Show HN | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| MIT News | 7 | 2 | Nov 5, 2026, 10:01 AM UTC |
| OpenAI | 7 | 3 | Nov 5, 2026, 11:30 AM UTC |
| Product Hunt | 7 | 3 | Nov 5, 2026, 12:45 PM UTC |
| 量子位 | 7 | 3 | Nov 4, 2026, 10:15 AM UTC |
| OpenRouter | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| Hugging Face Models | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| HF Daily Papers | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| OpenRouter | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| SEC EDGAR | 7 | 3 | Nov 5, 2026, 10:30 AM UTC |
| Sequoia Capital | 7 | 2 | Nov 5, 2026, 10:00 AM UTC |
| Simon Willison | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| TechCrunch | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| Contracts Finder | 7 | 3 | Nov 5, 2026, 10:00 AM UTC |
| V2EX | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
- Counts describe monitored public sources, not the whole web or search demand.
- Both weeks need adequate, comparable collection coverage.
Daily history · up to 90 days
Bars show dated source mentions. The latest UTC day may be incomplete. Zero mentions and missing collection coverage are different conditions.
Dotted markers indicate days with no record. They are not counted as zero mentions.
View accessible daily data
| UTC date | Mentions | Sources | Observations | Ranking appearances |
|---|---|---|---|---|
| 2026-10-10 | 1 | 1 | 1 | 0 |
| 2026-10-11 · No record | — | — | — | — |
| 2026-10-12 · No record | — | — | — | — |
| 2026-10-13 · No record | — | — | — | — |
| 2026-10-14 · No record | — | — | — | — |
| 2026-10-15 · No record | — | — | — | — |
| 2026-10-16 · No record | — | — | — | — |
| 2026-10-17 | 1 | 1 | 1 | 0 |
| 2026-10-18 · No record | — | — | — | — |
| 2026-10-19 | 1 | 1 | 1 | 0 |
| 2026-10-20 · No record | — | — | — | — |
| 2026-10-21 · No record | — | — | — | — |
| 2026-10-22 | 0 | 0 | 0 | 0 |
| 2026-10-23 | 0 | 0 | 0 | 0 |
| 2026-10-24 | 0 | 0 | 0 | 0 |
| 2026-10-25 | 0 | 0 | 0 | 0 |
| 2026-10-26 | 1 | 1 | 2 | 0 |
| 2026-10-27 | 1 | 1 | 1 | 0 |
| 2026-10-28 | 0 | 0 | 0 | 0 |
| 2026-10-29 | 1 | 1 | 1 | 0 |
| 2026-10-30 | 0 | 0 | 1 | 0 |
| 2026-10-31 | 1 | 1 | 0 | 0 |
| 2026-11-01 | 0 | 0 | 0 | 0 |
| 2026-11-02 | 0 | 0 | 0 | 0 |
| 2026-11-03 | 0 | 0 | 0 | 0 |
| 2026-11-04 | 0 | 0 | 0 | 0 |
| 2026-11-05 | 0 | 0 | 0 | 0 |
Source evidence
Sources in the evidence shown：arXiv 2 · 量子位 1 · Hacker News 4 · GitHub Trending 1
arXiv · Published Oct 31, 2026
Post-Training Large Language Models with LLMON
arXiv:2610.38120v1 Announce Type: new Abstract: Large Language Models (LLMs) treat all context tokens uniformly, lacking explicit separation between executable instructions and passive data. This leads to prompt injection vulnerabilities, ambiguous instruction binding, and unreliable execution control. We present a post-training methodology using LLMON (LLM
View source record →量子位 · Published Oct 29, 2026
刚刚，Gemini 4 Carbon全面超越Opus 5.5！首发Token半价
能连肝数日修Bug，免疫提示词注入
View source record →Hacker News · Published Oct 27, 2026
Blazle – Block prompt injection and secret leaks before AI agents act
View source record →GitHub Trending · Published Not supplied
NVIDIA/SkillSpector
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.
View source record →Hacker News · Published Oct 26, 2026
MCP-warden local credential broker so AI agents never see your secrets
I got tired of pasting GitHub PATs, Stripe keys and DB passwords into Claude Code / Cursor MCP configs. One prompt injection or a leaked chat and they’re gone. So I built mcp-warden — a local-first credential broker for the Model Context Protocol. How it works: • You store the secret once in the OS keychain • You define scoped presets (e.g. github-read, stri
View source record →arXiv · Published Oct 19, 2026
The Model Knows Better: Defending Medical Multi-Agent Systems Against Prompt Injection
View source record →Hacker News · Published Oct 17, 2026
Show HN: AegisKernel – Test prompt injection attacks on AI agents in the browser
View source record →Hacker News · Published Oct 10, 2026
Prompt Injection Detection and Defense Tools for Enterprise AI Agents
View source record →
Review priority 48 / 100
This score orders research candidates. It is not search volume, a forecast or verified commercial demand.
Evidence
12.7 / 30Distinct dated articles or first observations; repeat crawling adds nothing.
Publisher diversity
16 / 25Conservative owner grouping; syndicated copies count once.
Comparable change
0 / 20Comparable complete weeks only; no percentage from a zero baseline.
Recent evidence
9.1 / 15Latest publication or first observation, not repeated fetch time.
Name specificity
9.7 / 10Explicit entities and technical concepts outrank ambiguous acronyms.
Limitations and interpretation
- First observation is a collection milestone, not proof that a word or product is new to the world.
- Counts describe monitored public sources, not the whole web or search demand.
- First observed here is not the invention date of a name or idea.
- Candidates come from public titles, summaries and entity URLs, not verified full-text analysis.
- Owner grouping is conservative; undisclosed syndication may remain.
- Undated observations cannot establish publication growth.
- An established concept or common product name retained as a baseline, not a newly invented term.
- Both weeks need adequate, comparable collection coverage.
- Sources behind this term changed or lack a comparable baseline.