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Chaofan Shou

@shoucccc

79 976Followers
2 527Following
1 670Posts total
5.3MViews on collected posts

Derniers posts

@shoucccc This wouldn't work with OrcaRouter, we offer a firewall to sanitize or strip those malicious tool calls by default https://t.co/cwJDaIJeUT 24.7K views · 103 likes · 4 reposts · 3 replies Open on X →
A malicious LLM router or its upstream can modify a model’s tool call after generation, but before your agent executes it. The paper’s strongest immediately deployable defense: a fail-closed policy gate at the tool-call boundary. That’s already how OrcaRouter Agent Firewall 44.2K views · 113 likes · 4 reposts · 11 replies Open on X →
@shoucccc Imagine what the NSA is doing with that data. 77.7K views · 338 likes · 1 reposts · 4 replies Open on X →
@shoucccc FWIW, https://t.co/j91GB5KUIJ is likely move valuable -- it could contain key elements to crack open https://t.co/9nwCzZsiWV, which is what everyone in China uses to install JS/Python/whatever language packages. Talking about supply chain attach that only affects China 67.4K views · 103 likes · 5 reposts · 5 replies Open on X →
@shoucccc https://t.co/0ApqZ5YUpj
25.4K views · 196 likes · 1 reposts · 1 replies Open on X →
I bought a Fable dataset from one of the top Chinese LLM routers yesterday. With just 6TB data, I can take over 7 Chinese/CIS gov entities & 19 top Chinese firms like Xiaomi, Huawei, NIO, Minimax using SSH keys, VPN configs, Aliyun keys, GitLab tokens sent to the router. https:
3M views · 8.1K likes · 869 reposts · 236 replies Open on X →
@Fried_rice been thinking about this exact problem building cross-chain execution tooling for agents. The core question is how do you guarantee that commands, secrets, and user data stay intact and authentic when the environment is dynamic and not fully under your control 33.7K views · 68 likes · 2 reposts · 17 replies Open on X →
@Fried_rice this is wild. imagine trusting an API router and it poisons your agent to forward traffic to attackers. the agentic AI era needs a new security layer—zero trust for tool calls. bookmark this paper: https://t.co/xsgE2xaA8h 7K views · 69 likes · 4 reposts · 4 replies Open on X →
26 LLM routers are secretly injecting malicious tool calls and stealing creds. One drained our client $500k wallet. We also managed to poison routers to forward traffic to us. Within several hours, we can directly take over ~400 hosts. Check our paper: https://t.co/zyWz25CDpl
2M views · 5.5K likes · 1K reposts · 200 replies Open on X →

Face aux comptes de taille comparable

6 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. diffusé largement, mais peu de ces spectateurs réagissent.

Vues médianes55 818ce compte959médiane pour 10K–100K
Portée, %69.79%ce compte3.33%médiane pour 10K–100K
Engagement, %0.37%ce compte1.86%médiane pour 10K–100K
IndicateurCe compteMédiane pour 10K–100KRapport
Vues médianes par post55 81895958.2×
Portée (vues ÷ abonnés)69.79%3.33%21.0×
Taux d'engagement0.37%1.86%0.20×

Autres comptes de cette tranche →   Comparer avec un autre compte →   Comment ces repères sont établis →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

2M10 Apr
7K
33.7K
3M10 Sep
25.4K
67.4K
77.7K
44.2K11 Sep
24.7K

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.34%10 Apr
1.10%
0.26%
0.31%10 Sep
0.78%
0.17%
0.44%
0.29%11 Sep
0.45%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.86%.

What the audience does

Likes52.9%14 652 in total
Reposts6.8%1 894 in total
Replies1.7%481 in total
Bookmarks38.5%10 651 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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