Twitter's relevance-ranked search returned 53% fewer bot-generated tweets compared to real-time chronological search across 1.1 million queries during the attack; restricting analysis to the top 5 most-recently returned relevance results reduced spam by 64% versus real-time. Relevance ranking incorporates social-graph overlap and content popularity signals to demote mass-produced low-engagement content.

56% of logins tied to legitimate users discussing the Russian election originated from Russia, compared to only 1% of logins for the 25,860 spam accounts, with Japan accounting for 14% of spam logins. 39% of IP addresses used by the attackers appeared in the CBL blacklist for email spam and malware distribution, compared to 21% of IPs tied to legitimate users, confirming that the attack infrastructure was shared with conventional spam/malware operations.

§4.3 detection

The attack demonstrates that spam-as-a-service markets built for commercial spam (fake reviews, URL advertising) were directly repurposed for political censorship without modification, using the same compromised-host pools (39% blacklisted IPs) and bulk account infrastructure. This convergence means technical defenses against commercial spam infrastructure simultaneously constrain politically-motivated censorship operations by actors who lack direct Internet-access control.

§6 policy

Researchers identified four distinct account-registration patterns using regular expressions on mail.ru email addresses and screenname naming conventions; these patterns flagged 975,283 spam accounts with only 4% false positives on manual validation of 150 accounts. The 25,860 accounts deployed in the attack represent just 3% of the flagged pool, indicating a centralized spam-as-a-service vendor provisioned accounts in bulk and sold access.

§4.2 evaluation

An unknown attacker leveraged 25,860 fraudulent Twitter accounts to send 440,793 tweets targeting 20 election-related hashtags, peaking at 1,846 tweets per minute, in an attempt to dilute political conversations following Russia's December 2011 parliamentary election. The accounts were drawn from a pool of approximately 975,283 fraudulent accounts identified by the researchers, 80% of which remained dormant with zero friends, followers, or tweets.

§1, §4.1 detection

During the June 2025 shutdown, Iranian authorities blocked international One-Time Password (OTP) SMS delivery, preventing new sign-ins to foreign secure-messaging platforms and VPN services. This forced users toward government-approved domestic platforms that lack security and privacy protections. The blockade of OTPs effectively weaponized account-recovery flows as a secondary shutdown layer, disproportionately affecting users who needed to activate new circumvention tools during the crisis.

2025-iran-shutdown-measurement §Human Rights Implications port-blockingdpikeyword-filtering

Simple character-level perturbations (English) and homophone substitutions (Chinese), combined with LLM instruction-following prompts directing the model to use word substitutions in its output, successfully bypassed all input and output filters for all 41 input-blocked and 197 output-blocked queries across five major Chinese LLM services (Baidu-Chat, DeepSeek, Doubao, Kimi, Qwen). Every input-blocked query contained at least one keyword combination that alone triggered the filter, confirming keyword-matching rather than semantic classification.

2026-ablove-characterizing §VII-D keyword-filtering

Cross-national experiments conducted from Singapore, South Korea, and Taiwan during February 19–24, 2025 found no variance in blocking implementations, event syntax, or server infrastructure across all five Chinese LLM services. Input blocking was enacted identically in all three international locations, and services connected to the exact same server IP addresses globally — Kimi and Baidu-Chat connected to identical IPs and DeepSeek to the same two addresses across all tested locations.

2026-ablove-characterizing §VIII-A keyword-filtering

Input blocking in Chinese LLM services (DeepSeek, Qwen, Kimi, Doubao) is overwhelmingly consistent: all four services persistently block the exact same queries across all 5 measurement samples in both Simplified and Traditional Chinese. Output blocking is far less consistent, with only 29 out of 349 output-blocked queries blocked across all 5 samples. Baidu-Chat is exceptional: it performs almost no input blocking but instead relies heavily on post-search and output blocking (78.6% of blocks are output-phase).

2026-ablove-characterizing §VI-B keyword-filteringdpi

DeepSeek, Kimi, and Doubao all transmit analytics logs to the same Autonomous System (AS24429, Zhejiang Taobao Network Co., Ltd., a ByteDance/Volcengine subsidiary), with one monitoring endpoint IP directly overlapping between DeepSeek and Doubao. Additionally, all four non-Qwen services maintain connections with servers physically located in China throughout the chat session, transmitting user IDs, session IDs, viewport data, language preferences, and in Baidu-Chat's case, the full query text via URL-encoded CAPTCHA requests.

2026-ablove-characterizing §VI-D keyword-filtering

All five Chinese LLM services transmit partial or complete responses to the client machine even when output blocking is triggered, representing a major information leak. For DeepSeek and Qwen, truncated blocked responses are on average close in token length to full successful responses. For Baidu-Chat, the complete response is transmitted to the client but only partially rendered in the browser UI, with only a word or two visible on screen.

2026-ablove-characterizing §VI-C keyword-filtering